Published Manuscripts

Rugo HS, Campbell M, Yau C, et al. Pexidartinib and standard neoadjuvant therapy in the adaptively randomized I-SPY2 trial for early breast cancer. Breast Cancer Res Treat. 2024 Dec 3. doi: 10.1007/s10549-024-07555-9. PMID: 39625569

Albain KS, Yau C, Petricoin EF, et al. Neoadjuvant Trebananib plus Paclitaxel-based Chemotherapy for Stage II/III Breast Cancer in the Adaptively Randomized I-SPY2 Trial—Efficacy and Biomarker Discovery. Clin Cancer Res30:729-740, 2024. 

Kyalwazi B, Yau C, Campbell MJ, et al. Race, Gene Expression Signatures, and Clinical Outcomes of Patients With High-Risk Early Breast Cancer. JAMA Network Open6:e2349646, 2023.
Gallagher RI, Wulfkuhle J, Wolf DM, et al. Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial. Cell Rep MedPublished online 2023:101312:, 2023.
Perlmutter J, Brain S, Brown T, et al. Advocate involvement in Clinical Trials: Lessons from the Patient-centric I-SPY2 Breast Cancer Trial. Med Res Arch11 (7.2):, 2023.

Boughey JC, Yu H, Dugan CL, et al. Changes in Surgical Management of the Axilla Over 11 Years – Report on More Than 1500 Breast Cancer Patients Treated with Neoadjuvant Chemotherapy on the Prospective I-SPY2 Trial. Ann Surg Oncol(published online):1-10, 2023. 

Mukhtar RA, Chau H, Woriax H, et al. Breast Conservation Surgery and Mastectomy have Similar Locoregional Recurrence Following Neoadjuvant Chemotherapy: Results from 1,462 Patients on the Prospective, Randomized I-SPY2 Trial. Ann Surg(published ahead of print):, 2023.

Yu K, Basu A, Yau C, Wolf DM, Goodarzi H, Bandyopadhyay S, Korkola JE, Hirst GL, Asare S, DeMichele A, Hylton N, Yee D, Esserman L, van ‘t Veer L, Sirota M Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes. Frontiers in Oncol13:1192208, 2023.

Magbanua MGM, Brown-Swigart L, Ahmed Z, et al. Clinical significance and biology of circulating tumor DNA in high-risk early-stage HER2-negative breast cancer receiving neoadjuvant chemotherapy. Cancer Cell:, 2023.

Parker BA, Shatsky RA, Schwab RB, et al. Association of baseline ROR1 and ROR2 gene expression with clinical outcomes in the I-SPY2 neoadjuvant breast cancer trial. Breast Cancer Res Treat199:281–291, 2023.
Chitalia R, Miliotis M, Jahani N, et al. Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy. Communications Med3:46, 2023.
Magbanua MGM, van ‘t Veer L, Clark AS, et al. Outcomes and clinicopathologic characteristics associated with disseminated tumor cells in bone marrow after neoadjuvant chemotherapy in high-risk early stage breast cancer: the I-SPY SURMOUNT study. Breast Cancer Res Treat198:383–390, 2023.
Lang JE, Forero-Torres A, Yee D, et al Safety and efficacy of HSP90 inhibitor ganetespib for neoadjuvant treatment of stage II/III breast cancer. npj Breast Cancer8:128, 2022.
Li W, Le NN, Onishi N, et al Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy. Cancers14:4436-4448, 2022.
Osdoit M, Yau C, Symmans WF, et al. Association of Residual Ductal Carcinoma In Situ With Breast Cancer Recurrence in the Neoadjuvant I-SPY2 Trial. JAMA Surgery157:1034–1041, 2022.
Chitalia R, Pati S, Bhalerao M, et al. Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1. Scientific Data 9:440, 2022.
Wolf DM, Yau C, Wulfkuhle JD, et al. Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies. Cancer Cell40:P609-623.E6, 2022.
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Clark AS, Yau C, Wolf DM, et al. Neoadjuvant T-DM1/pertuzumab and paclitaxel/trastuzumab/pertuzumab for HER2+ breast cancer in the adaptively randomized I-SPY2 trial. Nature Comm 12: 6428, 2021.
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Symmans WF, Yau C, Chen YY, et al. Assessment of Residual Cancer Burden and Event-Free Survival in Neoadjuvant Treatment for High-risk Breast Cancer: An Analysis of Data From the I-SPY2 Randomized Clinical Trial. JAMA Onc 7: 1654-1663, 2021.
Onishi N, Li W, Newitt DC, et al. Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response. Radiology 301: 295–308, 2021.
Gonzalez-Ericsson PI, Wulfkhule JD, Gallagher RI, et al. Tumor-Specific Major Histocompatibility-II Expression Predicts Benefit to Anti–PD-1/L1 Therapy in Patients With HER2-Negative Primary Breast Cancer. Clin Cancer Res 27: 5299-5306, 2021.
Pusztai L, Yau C, Wolf DM, et al. Durvalumab with olaparib and paclitaxel for high-risk HER2-negative stage II/III breast cancer: Results from the adaptively randomized I-SPY2 trial. Cancer Cell 39: 989-998, 2021.
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Magbanua MJM, Li W, Wolf DM, et al. Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk. NPJ 7:, 2021.
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Tan ET, Wilmes LJ, Joe BN, et al. Denoising and Multiple Tissue Compartment Visualization of Multi‐b‐Valued Breast Diffusion MRI. J Mag Res Imaging 53:271–282, 2021.
Li W, Newitt DC, Gibbs J, et al. Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL. NPJ Breast Cancer 6:63, 2020.
Magbanua M, Brown-Swigart L, Wu H, et al. Circulating tumor DNA in neoadjuvant-treated breast cancer reflects response and survival. Ann Oncol 32:229-239, 2020.
Basu A, Philip EJ, Dewitt B, et al. The quality of life index: a pilot study integrating treatment efficacy and quality of life in oncology. NPJ Breast Cancer 6:52, 2020.
Wolf DM, Yau C, Wulfkuhle J, et al. Mechanism of action biomarkers predicting response to AKT inhibition in the I-SPY 2 breast cancer trial. NPJ Breast Cancer 6:48, 2020.
I-SPY Trial Consortium. Association of Event-Free and Distant Recurrence–Free Survival With Individual-Level Pathologic Complete Response in Neoadjuvant Treatment of Stages 2 and 3 Breast Cancer. JAMA Oncol 6:1355-1362, 2020.
Arasu VA, Kim P, Li W, et al. Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2− Patients. J Breast Imaging 2:352-360, 2020.
Jones EF, Hathi DK, Freimanis R, et al. Current Landscape of Breast Cancer Imaging and Potential Quantitative Imaging Markers of Response in ER-Positive Breast Cancers Treated with Neoadjuvant Therapy. Cancers 12:1511, 2020.
Li W, Newitt DC, Yun BL, et al. Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer. Tomogr 6:216-222, 2020.
Nguyen AA-T, Arasu VA, Strand F, et al. Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy. Tomography 6:101–110, 2020.
Onishi N, Li W, Gibbs J, et al. Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial. Tomography 6:77–85, 2020.
Malyarenko DI, Newitt DC, Amouzandeh G, et al. Retrospective Correction of ADC for Gradient Nonlinearity Errors in Multicenter Breast DWI Trials: ACRIN6698 Multiplatform Feasibility Study. Tomography 6:86-92, 2020.
Nanda R, Liu MC, Yau C, et al. Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women With Early-Stage Breast Cancer. JAMA Oncol 6:676-684, 2020.
Chien AJ, Tripathy D, Albain KS, et al. MK-2206 and Standard Neoadjuvant Chemotherapy Improves Response in Patients With Human Epidermal Growth Factor Receptor 2–Positive and/or Hormone Receptor–Negative Breast Cancers in the I-SPY 2 Trial. J Clin Oncol 38:1059-1069, 2020.
Jahani N, Cohen E, Hsieh M-K, et al. Prediction of Treatment Response to Neoadjuvant Chemotherapy for Breast Cancer via Early Changes in Tumor Heterogeneity Captured by DCE-MRI Registration. Scientific Reports 9:12114, 2019.
Piawah S, Hyland C, Umetsu SE, et al. A case report of vanishing bile duct syndrome after exposure to pexidartinib (PLX3397) and paclitaxel. NPJ Breast Cancer 5:17, 2019.
Li W, Newitt DC, Wilmes LJ, et al. Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL. J Magn Reson Imaging 50:1742-1753, 2019.
Partridge SC, Newitt DC, Chenevert TL, et al. Diffusion-weighted MRI in Multicenter Trials of Breast Cancer. Radiol 291:546–546, 2019.
Newitt DC, Zheng Z, Gibbs JE, et al. Test–retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial. J Mag Res Imag 49:1617-1628, 2019.
Esserman L, Hylton N, Asare S, et al. I-SPY2: Unlocking the Potential of the Platform Trial. In Z. Antonijevic & R. A. Beckman (Eds.), Platform Trial Designs in Drug Development: Umbrella Trials and Basket Trials (Chapman and Hall/CRC); pp. 3-22, 2018.
Partridge SC, Zhang Z, Newitt DC, et al. Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial. Radiol 289:618-627, 2018.
Boughey JC, Alvarado MD, Lancaster RB, et al. Surgical Standards for Management of the Axilla in Breast Cancer Clinical Trials with Pathological Complete Response Endpoint. NPJ Breast Cancer 4:26, 2018.
Wulfkuhle JD, Yau C, Wolf DM, et al. Evaluation of the HER/PI3K/AKT Family Signaling Network as a Predictive Biomarker of Pathologic Complete Response for Patients With Breast Cancer Treated With Neratinib in the I-SPY 2 TRIAL. JCO Precision Oncology 2:1-20, 2018.
Scheel JR, Kim E, Partridge SC, et al. MRI, Clinical Examination, and Mammography for Preoperative Assessment of Residual Disease and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: ACRIN 6657 Trial. Am J Roentgenol 210:1376-1385, 2018.
Drukker K, Li H, Antropova N, et al. Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival “early on” in neoadjuvant treatment of breast cancer. Cancer Imaging 18:12, 2018.
Olshen A, Wolf D, Jones EF, et al. Features of MRI stromal enhancement with neoadjuvant chemotherapy: a subgroup analysis of the ACRIN 6657/I-SPY TRIAL. J Med Imaging 5:11014, 2018.
Severson TM, Wolf DM, Yau C, et al. The BRCA1 ness signature is associated significantly with response to PARP inhibitor treatment versus control in the I-SPY 2 randomized neoadjuvant setting. Breast Cancer Res 19:99, 2017.
Wolf DM, Yau C, Sanil A, et al. DNA repair deficiency biomarkers and the 70-gene ultra-high risk signature as predictors of veliparib/carboplatin response in the I-SPY 2 breast cancer trial. NPJ Breast Cancer 3:, 2017.
Campbell JI, Yau C, Krass P, et al. Comparison of residual cancer burden, American Joint Committee on Cancer staging and pathologic complete response in breast cancer after neoadjuvant chemotherapy: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657). Breast Cancer Res Treat 165:181-191, 2017.
Vidula N, Yau C, Li J, et al. Receptor activator of nuclear factor kappa B (RANK) expression in primary breast cancer correlates with recurrence-free survival and development of bone metastases in I-SPY1 (CALGB 150007/150012; ACRIN 6657). Breast Cancer Res Treat 165:129-138, 2017.
Jones EF, Ray KM, Li W, et al. Dedicated Breast Positron Emission Tomography for the Evaluation of Early Response to Neoadjuvant Chemotherapy in Breast Cancer. Clin Breast Cancer 17:e155–e159, 2017.
Bolan PJ, Kim E, Herman BA, et al. MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial. J Mag Res Imaging 46:290-302, 2017.
Li W, Arasu V, Newitt DC, et al. Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL. Tomography 2:378-387, 2016.
Rugo HS, Olopade, OI, DeMichele A, et al. Adaptive randomization of veliparib-carboplatin treatment in breast cancer. New Engl J Med 375:23-34, 2016.
Park JW, Liu MC, Yee D, et al. Adaptive Randomization of Neratinib in Early Breast Cancer. N Engl J Med 375:11-22, 2016.
Hylton NM, Gatsonis CA, Rosen MA, et al. Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival—Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL. Radiol 279:44–55, 2016.
Magbanua MJM, Wolf DM, Yau C, et al. Serial expression analysis of breast tumors during neoadjuvant chemotherapy reveals changes in cell cycle and immune pathways associated with recurrence and response. Breast Cancer Res 17:73, 2015.
DeMichele A, Yee D, Berry D, et al. The Neoadjuvant Model Is Still the Future for Drug Development in Breast Cancer. Clinical Cancer Research 21:2911-2915, 2015.
Price ER, Wong J, Mukhtar R, et al. How to use magnetic resonance imaging following neoadjuvant chemotherapy in locally advanced breast cancer. World J Clinical Cases 3:607-613, 2015.
Clark AS, Chen J, Kapoor S, et al. Pretreatment vitamin D level and response to neoadjuvant chemotherapy in women with breast cancer on the I‐SPY trial (CALGB 150007/150015/ACRIN6657). Cancer Medicine 3:693-701, 2014.
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Clin Cancer Res 30: 729-740, 2024.

Neoadjuvant Trebananib plus Paclitaxel-based Chemotherapy for Stage II/III Breast Cancer in the Adaptively Randomized I-SPY2 Trial—Efficacy and Biomarker Discovery

Albain KS, Yau C, Petricoin EF, Wolf DM, Lang JE, Chien AJ, Haddad T, Forero-Torres A, Wallace AM, Kaplan H, Pusztai L, Euhus D, Nanda R, Elias AD, Clark AS, Godellas C, Boughey JC, Isaacs C, Tripathy D, Lu J, Yung RL, Gallagher RI, Wulfkuhle JD, Brown-Swigart L, Krings G, Chen YY, Potter DA, Stringer-Reasor E, Blair S, Asare SM, Wilson A, Hirst GL, Singhrao R, Buxton M, Clennell JL, Sanil A, Berry S, Asare AL, Matthews JB, DeMichele AM, Hylton NM, Melisko M, Perlmutter J, Rugo HS, Symmans WF, Veer LJ van’t, Yee D, Berry DA, Esserman LJ

Purpose: The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial.

Patients and Methods: I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy “graduates” if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction.

Results: There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%–99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease.

Conclusions: The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority >90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted.

JAMA Network Open 6:e 2349646, 2023.

Race, Gene Expression Signatures, and Clinical Outcomes of Patients With High-Risk Early Breast Cancer

Kyalwazi B, Yau C, Campbell MJ, Yoshimatsu TF, Chien AJ, Wallace AM, Forero-Torres A, Pusztai L, Ellis ED, Albain KS, Blaes AH, Haley BB, Boughey JC, Elias AD, Clark AS, Isaacs CJ, Nanda R, Han HS, Yung RL, Tripathy D, Edmiston KK, Viscusi RK, Northfelt DW, Khan QJ, Asare SM, Wilson A, Hirst GL, Lu R, Symmans WF, Yee D, DeMichele AM, Veer LJ van ’t, Esserman LJ, Olopade OI.

Importance  There has been little consideration of genomic risk of recurrence by breast cancer subtype despite evidence of racial disparities in breast cancer outcomes.

Objective  To evaluate associations between clinical trial end points, namely pathologic complete response (pCR) and distant recurrence–free survival (DRFS), and race and examine whether gene expression signatures are associated with outcomes by race.

Design, Setting, and Participants  This retrospective cohort study used data from the Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2 (I-SPY 2) multicenter clinical trial of neoadjuvant chemotherapy with novel agents and combinations for patients with previously untreated stage II/III breast cancer. Analyses were conducted of associations between race and short- and long-term outcomes, overall and by receptor subtypes, and their association with 28 expression biomarkers. The trial enrolled 990 female patients between March 30, 2010, and November 5, 2016, with a primary tumor size of 2.5 cm or greater and clinical or molecular high risk based on MammaPrint or hormone receptor (HR)-negative/ERBB2 (formerly HER2 or HER2/neu)–positive subtyping across 9 arms. This data analysis was performed between June 10, 2021, and October 20, 2022.

Exposure  Race, tumor receptor subtypes, and genomic biomarker expression of early breast cancer.

Main Outcomes and Measures  The primary outcomes were pCR and DRFS assessed by race, overall, and by tumor subtype using logistic regression and Cox proportional hazards regression models. The interaction between 28 expression biomarkers and race, considering pCR and DRFS overall and within subtypes, was also evaluated.

Results  The analytic sample included 974 participants (excluding 16 self-reporting as American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, or multiple races due to small sample sizes), including 68 Asian (7%), 120 Black (12%), and 786 White (81%) patients. Median (range) age at diagnosis was 47 (25-71) years for Asian, 49 (25-77) for Black, and 49 (23-73) years for White patients. The pCR rates were 32% (n = 22) for Asian, 30% for Black (n = 36), and 32% for White (n = 255) patients (P = .87). Black patients with HR-positive/ERBB2-negative tumors not achieving pCR had significantly worse DRFS than their White counterparts (hazard ratio, 2.28; 95% CI, 1.24-4.21; P = .01), with 5-year DRFS rates of 55% (n = 32) and 77% (n = 247), respectively. Black patients with HR-positive/ERBB2-negative tumors, compared with White patients, had higher expression of an interferon signature (mean [SD], 0.39 [0.87] and −0.10 [0.99]; P = .007) and, compared with Asian patients, had a higher mitotic score (mean [SD], 0.07 [1.08] and −0.69 [1.06]; P = .01) and lower estrogen receptor/progesterone receptor signature (mean [SD], 0.31 [0.90] and 1.08 [0.95]; P = .008). A transforming growth factor β signature had a significant association with race relative to pCR and DRFS, with a higher signature associated with lower pCR and worse DRFS outcomes among Black patients only.

Conclusions and Relevance  The findings show that women with early high-risk breast cancer who achieve pCR have similarly good outcomes regardless of race, but Black women with HR-positive/ERBB2-negative tumors without pCR may have worse DRFS than White women, highlighting the need to develop and test novel biomarker-informed therapies in diverse populations.

Cell Rep Med Published online 2023: 101312:, 2023.

Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Tri

Gallagher RI, Wulfkuhle J, Wolf DM, Brown-Swigart L, Yau C, O’Grady N, Basu A, Lu R, Campbell MJ, Magbanua MJ, Coppé JP, Investigators IS 2, Asare SM, Sit L, Matthews JB, Perlmutter J, Hylton N, Liu MC, Symmans WF, Rugo HS, Isaacs C, DeMichele AM, Yee D, Pohlmann PR, Hirst GL, Esserman LJ, Veer LJ van ‘t, Petricoin EF

Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures.We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance.We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.

Med Res Arch 11 (7.2):, 2023

Advocate involvement in Clinical Trials: Lessons from the Patient-centric I-SPY2 Breast Cancer Trial

Perlmutter J, Brain S, Brown T, Collyar D, Delson A, Heditsian D, LeStage B, Parker B, Samson S, Venticinque J, Matthews J.

The innovative I-SPY Breast Trial is presented as an example of an unusually patient-centric clinical trial that has been significantly impacted by extensive advocate involvement. In the introduction we briefly define what we mean by patient-centric trials and describe the overall structure, goals, and evolution of I-SPY. We then describe: 1) the roles and philosophy of advocate involvement; 2) attributes of the trial design that make it especially patient-centric; and 3) educational material and communications approaches aimed at empowering and supporting trial participants. For each section, in addition to describing I-SPY practices, we provide aspirational suggestions that could enhance I-SPY and/or other clinical trials. Embedding advocates into every aspect of clinical trial design and operations, empowering trial participants with excellent patient educational material and incorporating and learning from patient-reported outcomes serves as a model approach to achieve more patient-centric clinical trials.

Ann Surg Oncol (published online) :1-10, 2023

Changes in Surgical Management of the Axilla Over 11 Years – Report on More Than 1500 Breast Cancer Patients Treated with Neoadjuvant Chemotherapy on the Prospective I-SPY2 Trial

Boughey JC, Yu H, Dugan CL, Piltin MA, Postlewait L, Son JD, Edmiston KK, Godellas CV, Lee MC, Carr MJ, Tonneson JE, Crown A, Lancaster RB, Woriax HE, Ewing CA, Chau HS, Patterson AK, Wong JM, Alvarado MD, Yang RL, Chan TW, Sheade JB, Ahrendt GM, Larson KE, Switalla K, Tuttle TM, Tchou JC, Rao R, Tamirisa N, Singh P, Gould RE, Terando A, Sauder C, Hewitt K, Chiba A, Esserman LJ, Mukhtar RA.

Background: Axillary surgery after neoadjuvant chemotherapy (NAC) is becoming less extensive. We evaluated the evolution of axillary surgery after NAC on the multi-institutional I-SPY2 prospective trial.

Methods: We examined annual rates of sentinel lymph node (SLN) surgery with resection of clipped node, if present), axillary lymph node dissection (ALND), and SLN and ALND in patients enrolled in I-SPY2 from January 1, 2011 to December 31, 2021 by clinical N status at diagnosis and pathologic N status at surgery. Cochran-Armitage trend tests were calculated to evaluate patterns over time.

Results: Of 1578 patients, 973 patients (61.7%) had SLN-only, 136 (8.6%) had SLN and ALND, and 469 (29.7%) had ALND-only. In the cN0 group, ALND-only decreased from 20% in 2011 to 6.25% in 2021 (p = 0.0078) and SLN-only increased from 70.0% to 87.5% (p = 0.0020). This was even more striking in patients with clinically node-positive (cN+) disease at diagnosis, where ALND-only decreased from 70.7% to 29.4% (p < 0.0001) and SLN-only significantly increased from 14.6% to 56.5% (p < 0.0001). This change was significant across subtypes (HR-/HER2-, HR+/HER2-, and HER2+). Among pathologically node-positive (pN+) patients after NAC (n = 525) ALND-only decreased from 69.0% to 39.2% (p < 0.0001) and SLN-only increased from 6.9% to 39.2% (p < 0.0001).

Conclusions: Use of ALND after NAC has significantly decreased over the past decade. This is most pronounced in cN+ disease at diagnosis with an increase in the use of SLN surgery after NAC. Additionally, in pN+ disease after NAC, there has been a decrease in use of completion ALND, a practice pattern change that precedes results from clinical trials.

Ann Surg (published ahead of print): , 2023

Breast Conservation Surgery and Mastectomy have Similar Locoregional Recurrence Following Neoadjuvant Chemotherapy: Results from 1,462 Patients on the Prospective, Randomized I-SPY2 Trial

Mukhtar RA, Chau H, Woriax H, Piltin M, Ahrendt G, Tchou J, Yu H, Ding Q, Dugan CL, Sheade J, Crown A, Carr M, Wong J, Son J, Yang R, Chan T, Terando A, Alvarado M, Ewing C, Tonneson J, Tamirisa N, Gould R, Singh P, Godellas C, Larson K, Chiba A, Rao R, Sauder C, Postlewait L, Lee MC, Symmans WF, Esserman LJ, ISPY-2 Locoregional Working Group, Boughey JC

Neoadjuvant chemotherapy (NAC) increases rates of successful breast conserving surgery (BCS) in patients with breast cancer. However, some studies suggest that BCS after NAC may confer increased risk of locoregional recurrence (LRR). We assessed LRR rates and locoregional recurrence free survival (LRFS) in patients enrolled on I-SPY2 (NCT01042379), a prospective NAC trial for patients with clinical stage II-III, molecularly high-risk breast cancer. Cox proportional hazards models were used to evaluate associations between surgical procedure (BCS vs. mastectomy) and LRFS adjusted for age, tumor receptor subtype, clinical T category, clinical nodal status, and Residual Cancer Burden (RCB). In 1,462 patients, surgical procedure was not associated with LRR or LRFS on either univariate or multivariate analyses. The unadjusted incidence of LRR was 5.4% after BCS, and 7.0% after mastectomy, at median follow up time of 3.5 years. The strongest predictor of LRR was RCB class, with each increasing RCB class having significantly higher hazard ratio for LRR compared to RCB 0 on multivariate analysis. Triple negative receptor subtype was also associated with increased risk of LRR (HR 2.91, 95% CI 1.8-4.6, P<0.0001), regardless of type of operation. In this large multi-institutional prospective trial of patients completing NAC, we found no increased risk of LRR or differences in LRFS following BCS compared to mastectomy. Tumor receptor subtype and extent of residual disease after NAC were significantly associated with recurrence. These data demonstrate that BCS can be an excellent surgical option after NAC for appropriately selected patients.

Frontiers in Oncol 13: 1192208, 2023

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes

Yu K, Basu A, Yau C, et al.

Introduction: Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes.

Methods: In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival.

Results: We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line.

Conclusion: We applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel.

Cancer Cell:, 2023.

Clinical significance and biology of circulating tumor DNA in high-risk early-stage HER2-negative breast cancer receiving neoadjuvant chemotherapy

Magbanua MGM, Brown-Swigart L, Ahmed Z, Sayaman RW, Renner D, Kalashnikova E, Hirst GL, Yau C, Wolf DM, Li W, Delson AL, Asare A, Liu MC, Albain K, Chien AJ, Forero-Torres A, Isaacs C, Nanda R, Tripathy D, Rodriguez A, Sethi H, Aleshin A, Rabinowitz M, Perlmutter J, Symmans WF, Yee D, Hylton NM, Esserman LJ, DeMichele AM, Rugo HS, van ’t Veer LJ

Circulating tumor DNA (ctDNA) analysis may improve early-stage breast cancer treatment via non-invasive tumor burden assessment. To investigate subtype-specific differences in the clinical significance and biology of ctDNA shedding, we perform serial personalized ctDNA analysis in hormone receptor (HR)-positive/HER2-negative breast cancer and triple-negative breast cancer (TNBC) patients receiving neoadjuvant chemotherapy (NAC) in the I-SPY2 trial. ctDNA positivity rates before, during, and after NAC are higher in TNBC than in HR-positive/HER2-negative breast cancer patients. Early clearance of ctDNA 3 weeks after treatment initiation predicts a favorable response to NAC in TNBC only. Whereas ctDNA positivity associates with reduced distant recurrence-free survival in both subtypes. Conversely, ctDNA negativity after NAC correlates with improved outcomes, even in patients with extensive residual cancer. Pretreatment tumor mRNA profiling reveals associations between ctDNA shedding and cell cycle and immune-associated signaling. On the basis of these findings, the I-SPY2 trial will prospectively test ctDNA for utility in redirecting therapy to improve response and prognosis.

Breast Cancer Res Treat 199: 281–291, 2023.

Association of baseline ROR1 and ROR2 gene expression with clinical outcomes in the I-SPY2 neoadjuvant breast cancer trial

Parker BA, Shatsky RA, Schwab RB, Wallace AM, I-SPY 2 Consortium, Wolf DM, Hirst GL, Brown-Swigart L, Esserman LJ, Veer LJ van ’t, Ghia EM, Yau C, Kipps TJ

Purpose: ROR1 and ROR2 are Type 1 tyrosine kinase-like orphan receptors for Wnt5a that are associated with breast cancer progression. Experimental agents targeting ROR1 and ROR2 are in clinical trials. This study evaluated whether expression levels of ROR1 or ROR2 correlated with one another or with clinical outcomes.

Methods: We interrogated the clinical significance of high-level gene expression of ROR1 and/or ROR2 in the annotated transcriptome dataset from 989 patients with high-risk early breast cancer enrolled in one of nine completed/graduated/experimental and control arms in the neoadjuvant I-SPY2 clinical trial (NCT01042379).

Results: High ROR1 or high ROR2 was associated with breast cancer subtypes. High ROR1 was more prevalent among hormone receptor-negative and human epidermal growth factor receptor 2-negative (HR-HER2-) tumors and high ROR2 was less prevalent in this subtype. Although not associated with pathologic complete response, high ROR1 or high ROR2 each was associated with event-free survival (EFS) in distinct subtypes. High ROR1 associated with a worse EFS in HR + HER2- patients with high post-treatment residual cancer burden (RCB-II/III) (HR 1.41, 95% CI = 1.11–1.80) but not in patients with minimal post-treatment disease (RCB-0/I) (HR 1.85, 95% CI = 0.74–4.61). High ROR2 associated with an increased risk of relapse in patients with HER2 + disease and RCB-0/I (HR 3.46, 95% CI = 1.33–9.020) but not RCB-II/III (HR 1.07, 95% CI = 0.69–1.64).

Conclusion: High ROR1 or high ROR2 distinctly identified subsets of breast cancer patients with adverse outcomes. Further studies are warranted to determine if high ROR1 or high ROR2 may identify high-risk populations for studies of targeted therapies.

Communications Med 3: 46, 2023

Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy

Chitalia R, Miliotis M, Jahani N, Tastsoglou S, McDonald ES, Belenky V, Cohen EA, Newitt D, Veer LJ van’t, Esserman L, Hylton N, DeMichele A, Hatzigeorgiou A, Kontos D

Background: Early changes in breast intratumor heterogeneity during neoadjuvant chemotherapy may reflect the tumor’s ability to adapt and evade treatment. We investigated the combination of precision medicine predictors of genomic and MRI data towards improved prediction of recurrence free survival (RFS).

Methods: A total of 100 women from the ACRIN 6657/I-SPY 1 trial were retrospectively analyzed. We estimated MammaPrint, PAM50 ROR-S, and p53 mutation scores from publicly available gene expression data and generated four, voxel-wise 3-D radiomic kinetic maps from DCE-MR images at both pre- and early-treatment time points. Within the primary lesion from each kinetic map, features of change in radiomic heterogeneity were summarized into 6 principal components.

Results: We identify two imaging phenotypes of change in intratumor heterogeneity (p < 0.01) demonstrating significant Kaplan-Meier curve separation (p < 0.001). Adding phenotypes to established prognostic factors, functional tumor volume (FTV), MammaPrint, PAM50, and p53 scores in a Cox regression model improves the concordance statistic for predicting RFS from 0.73 to 0.79 (p = 0.002).

Conclusions: These results demonstrate an important step in combining personalized molecular signatures and longitudinal imaging data towards improved prognosis

Breast Cancer Res Treat 198: 383–390, 2023.

Outcomes and clinicopathologic characteristics associated with disseminated tumor cells in bone marrow after neoadjuvant chemotherapy in high-risk early stage breast cancer: the I-SPY SURMOUNT study

Magbanua MGM, van ‘t Veer L, Clark AS, Chien AJ, Boughey JC, Han HS, Wallace A, Beckwith H, Liu MC, Yau C, Wileyto EP, Ordonez A, Solanki TI, Hsiao F, Lee JC, Basu A, Brown-Swigart L, Perlmutter J, Delson AL, Bayne L, Deluca S, Yee SS, Carpenter EL, Esserman LJ, Park JW, Chodosh LA, DeMichele A

Purpose: Disseminated tumor cells (DTCs) expressing epithelial markers in the bone marrow are associated with recurrence and death, but little is known about risk factors predicting their occurrence. We detected EPCAM+/CD45− cells in bone marrow from early stage breast cancer patients after neoadjuvant chemotherapy (NAC) in the I-SPY 2 Trial and examined clinicopathologic factors and outcomes.

Methods: Patients who signed consent for SURMOUNT, a sub-study of the I-SPY 2 Trial (NCT01042379), had bone marrow collected after NAC at the time of surgery. EPCAM+CD45− cells in 4 mLs of bone marrow aspirate were enumerated using immunomagnetic enrichment/flow cytometry (IE/FC). Patients with > 4.16 EPCAM+CD45− cells per mL of bone marrow were classified as DTC-positive. Tumor response was assessed using the residual cancer burden (RCB), a standardized approach to quantitate the extent of residual invasive cancer present in the breast and the axillary lymph nodes after NAC. Association of DTC-positivity with clinicopathologic variables and survival was examined.

Results: A total of 73 patients were enrolled, 51 of whom had successful EPCAM+CD45− cell enumeration. Twenty-four of 51 (47.1%) were DTC-positive. The DTC-positivity rate was similar across receptor subtypes, but DTC-positive patients were significantly younger (p = 0.0239) and had larger pretreatment tumors compared to DTC-negative patients (p = 0.0319). Twenty of 51 (39.2%) achieved a pathologic complete response (pCR). While DTC-positivity was not associated with achieving pCR, it was significantly associated with higher RCB class (RCB-II/III, 62.5% vs. RCB-0/I; 33.3%; Chi-squared p = 0.0373). No significant correlation was observed between DTC-positivity and distant recurrence-free survival (p = 0.38, median follow-up = 3.2 years).

Conclusion: DTC-positivity at surgery after NAC was higher in younger patients, those with larger tumors, and those with residual disease at surgery.

npj Breast Cancer 8: 128, 2022.

Safety and efficacy of HSP90 inhibitor ganetespib for neoadjuvant treatment of stage II/III breast cancer

Nguyen AA-T, Onishi N, Carmona-Bozo J, Li W, aaLang JE, Forero-Torres A, Yee D, Yau C, Wolf D, Park J, Parker BA, Chien AJ, Wallace AM, Murthy R, Albain KS, Ellis ED, Beckwith H, Haley BB, Elias AD, Boughey JC, Yung RL, Isaacs C, Clark AS, Han HS, Nanda R, Khan QJ, Edmiston KK, Stringer-Reasor E, Price E, Joe B, Liu MC, Brown-Swigart L, Petricoin EF, Wulfkuhle JD, Buxton M, Clennell JL, Sanil A, Berry S, Asare SM, Wilson A, Hirst GL, Singhrao R, Asare AL, Matthews JB, Melisko M, Perlmutter J, Rugo HS, Symmans WF, van ‘t Veer LJ, Hylton NM, DeMichele AM, Berry DA, Esserman LJKornak J, Newitt DC, Hylton NM

HSP90 inhibitors destabilize oncoproteins associated with cell cycle, angiogenesis, RAS-MAPK activity, histone modification, kinases and growth factors. We evaluated the HSP90-inhibitor ganetespib in combination with standard chemotherapy in patients with high-risk early-stage breast cancer. I-SPY2 is a multicenter, phase II adaptively randomized neoadjuvant (NAC) clinical trial enrolling patients with stage II-III breast cancer with tumors 2.5 cm or larger on the basis of hormone receptors (HR), HER2 and Mammaprint status. Multiple novel investigational agents plus standard chemotherapy are evaluated in parallel for the primary endpoint of pathologic complete response (pCR). Patients with HER2-negative breast cancer were eligible for randomization to ganetespib from October 2014 to October 2015. Of 233 women included in the final analysis, 140 were randomized to the standard NAC control; 93 were randomized to receive 150 mg/m2 ganetespib every 3 weeks with weekly paclitaxel over 12 weeks, followed by AC. Arms were balanced for hormone receptor status (51–52% HR-positive). Ganetespib did not graduate in any of the biomarker signatures studied before reaching maximum enrollment. Final estimated pCR rates were 26% vs. 18% HER2-negative, 38% vs. 22% HR-negative/HER2-negative, and 15% vs. 14% HR-positive/HER2-negative for ganetespib vs control, respectively. The predicted probability of success in phase 3 testing was 47% HER2-negative, 72% HR-negative/HER2-negative, and 19% HR-positive/HER2-negative. Ganetespib added to standard therapy is unlikely to yield substantially higher pCR rates in HER2-negative breast cancer compared to standard NAC, and neither HSP90 pathway nor replicative stress expression markers predicted response. HSP90 inhibitors remain of limited clinical interest in breast cancer, potentially in other clinical settings such as HER2-positive disease or in combination with anti-PD1 neoadjuvant chemotherapy in triple negative breast cancer.

Cancers 14: 4436-4448, 2022.

Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy

Li W, Le NN, Onishi N, Newitt DC, Wilmes LJ, Gibbs JE, Carmona-Bozo J, Liang J, Partridge SC, Price ER, Joe BN, Kornak J, Magbanua MJM, Nanda R, LeStage B, Esserman LJ, I-SPY Imaging Working Group, I-SPY Investigator Network, van’t Veer LJ, Hylton NM

Immunotherapy targets patients’ immune systems to fight cancer. The aim of this retrospective study is to assess tumor response to pre-operative immunotherapy and predict pathologic complete response using MRI at an early treatment time- point. Based on our analysis with a cohort from the multi-center I-SPY 2 clinical trial, we found diffusion-weighted MRI is superior to dynamic contrast-enhanced MRI, where the latter is a standard and most-commonly used MRI modality, in assessing immunotherapy, while no significant difference was observed in the control cohort where only standard chemotherapy was provided. This study tested the hypothesis that a change in the apparent diffusion coefficient (ADC) measured in diffusion-weighted MRI (DWI) is an independent imaging marker, and ADC performs better than functional tumor volume (FTV) for assessing treatment response in patients with locally advanced breast cancer receiving neoadjuvant immunotherapy. A total of 249 patients were randomized to standard neoadjuvant chemotherapy with pembrolizumab (pembro) or without pembrolizumab (control). DCE-MRI and DWI, performed prior to and 3 weeks after the start of treatment, were analyzed. Percent changes of tumor ADC metrics (mean, 5th to 95th percentiles of ADC histogram) and FTV were evaluated for the prediction of pathologic complete response (pCR) using a logistic regression model. The area under the ROC curve (AUC) estimated for the percent change in mean ADC was higher in the pembro cohort (0.73, 95% confidence interval [CI]: 0.52 to 0.93) than in the control cohort (0.63, 95% CI: 0.43 to 0.83). In the control cohort, the percent change of the 95th percentile ADC achieved the highest AUC, 0.69 (95% CI: 0.52 to 0.85). In the pembro cohort, the percent change of the 25th percentile ADC achieved the highest AUC, 0.75 (95% CI: 0.55 to 0.95). AUCs estimated for percent change of FTV were 0.61 (95% CI: 0.39 to 0.83) and 0.66 (95% CI: 0.47 to 0.85) for the pembro and control cohorts, respectively. Tumor ADC may perform better than FTV to predict pCR at an early treatment time-point during neoadjuvant immunotherapy.

JAMA Surgery 157:1034–1041, 2022.

Association of Residual Ductal Carcinoma In Situ With Breast Cancer Recurrence in the Neoadjuvant I-SPY2 Trial

Osdoit M, Yau C, Symmans WF, Boughey JC, Ewing CA, Balassanian R, Chen Y-Y, Krings G, Wallace AM, Zare S, Fadare O, Lancaster R, Wei S, Godellas CV, Tang P, Tuttle TM, Klein M, Sahoo S, Hieken TJ, Carter JM, Chen B, Ahrendt G, Tchou J, Feldman M, Tousimis E, Zeck J, Jaskowiak N, Sattar H, Naik AM, Lee MC, Rosa M, Khazai L, Rendi MH, Lang JE, Lu J, Tawfik O, Asare SM, Esserman LJ, Mukhtar RA

Importance: Pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer strongly correlates with overall survival and has become the standard end point in neoadjuvant trials. However, there is controversy regarding whether the definition of pCR should exclude or permit the presence of residual ductal carcinoma in situ (DCIS).

Objective: To examine the association of residual DCIS in surgical specimens after neoadjuvant chemotherapy for breast cancer with survival end points to inform standards for the assessment of pathologic complete response.

Design, Setting, and Participants: The study team analyzed the association of residual DCIS after NAC with 3-year event-free survival (EFS), distant recurrence-free survival (DRFS), and local-regional recurrence (LRR) in the I-SPY2 trial, an adaptive neoadjuvant platform trial for patients with breast cancer at high risk of recurrence. This is a retrospective analysis of clinical specimens and data from the ongoing I-SPY2 adaptive platform trial of novel therapeutics on a background of standard of care for early breast cancer. I-SPY2 participants are adult women diagnosed with stage II/III breast cancer at high risk of recurrence.

Interventions: Participants were randomized to receive taxane and anthracycline-based neoadjuvant therapy with or without 1 of 10 investigational agents, followed by definitive surgery.

Main Outcomes and Measures: The presence of DCIS and EFS, DRFS, and LRR.

Results: The study team identified 933 I-SPY2 participants (aged 24 to 77 years) with complete pathology and follow-up data. Median follow-up time was 3.9 years; 337 participants (36%) had no residual invasive disease (residual cancer burden 0, or pCR). Of the 337 participants with pCR, 70 (21%) had residual DCIS, which varied significantly by tumor-receptor subtype; residual DCIS was present in 8.5% of triple negative tumors, 15.6% of hormone-receptor positive tumors, and 36.6% of ERBB2-positive tumors. Among those participants with pCR, there was no significant difference in EFS, DRFS, or LRR based on presence or absence of residual DCIS.

Conclusions and Relevance: The analysis supports the definition of pCR as the absence of invasive disease after NAC regardless of the presence or absence of DCIS.

Scientific Data 9:440, 2022.

Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1

Chitalia R, Pati S, Bhalerao M, Thakur SP, Jahani N, Belenky V, McDonald ES, Gibbs J, Newitt DC, Hylton NM, Kontos D, Bakas S

Breast cancer is one of the most pervasive forms of cancer and its inherent intra- and inter-tumor heterogeneity contributes towards its poor prognosis. Multiple studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of having consistency in: a) data quality, b) quality of expert annotation of pathology, and c) availability of baseline results from computational algorithms. To address these limitations, here we propose the enhancement of the I-SPY1 data collection, with uniformly curated data, tumor annotations, and quantitative imaging features. Specifically, the proposed dataset includes a) uniformly processed scans that are harmonized to match intensity and spatial characteristics, facilitating immediate use in computational studies, b) computationally-generated and manually-revised expert annotations of tumor regions, as well as c) a comprehensive set of quantitative imaging (also known as radiomic) features corresponding to the tumor regions. This collection describes our contribution towards repeatable, reproducible, and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments.

Cancer Cell 40: P609-623.E6, 2022.

Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies

Wolf DM, Yau C, Wulfkuhle J, Brown-Swigart L, Gallagher RI, Lee PRE, Zhu Z, Magbanua MJ, Sayaman R, O’Grady N, Basu A, Delson A, Coppé JP, Lu R, Braun J, I-SPY2 Investigators, Asare SM, Sit L, Matthews JB, Perlmutter J, Hylton N, Liu MC, Pohlmann P, Symmans WF, Rugo HS, Isaacs C, DeMichele AM, Yee D, Berry DA, Pusztai L, Petricoin EF, Hirst GL, Esserman LJ, van ‘t Veer LJ

Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status to better predict drug responses. We assess the predictive performance of mechanism-of-action biomarkers from ∼990 patients treated with 10 regimens targeting diverse biology. We explore >11 subtyping schemas and identify treatment-subtype pairs maximizing the pathologic complete response (pCR) rate over the population. The best performing schemas incorporate Immune, DNA repair, and HER2/Luminal phenotypes. Subsequent treatment allocation increases the overall pCR rate to 63% from 51% using HR/HER2-based treatment selection. pCR gains from reclassification and improved patient selection are highest in HR+ subsets (>15%). As new treatments are introduced, the subtyping schema determines the minimum response needed to show efficacy. This data platform provides an unprecedented resource and supports the usage of response-based subtypes to guide future treatment prioritization.

Annals of Oncology 33: 814–823, 2022.

Treatment Efficacy Score—continuous residual cancer burden-based metric to compare neoadjuvant chemotherapy efficacy between randomized trial arms in breast cancer trials

Marczyk M, Mrukwa A, Yau C, Wolf D, Chen Y-Y, Balassanian R, Nanda R, Parker BA, Krings G, Sattar H, Zeck JC, Albain KS, Boughey JC, Liu MC, Elias AD, Clark AS, Venters SJ, Shad S, Basu A, Asare SM, Buxton M, Asare AL, Rugo HS, Perlmutter J, DeMichele AM, Yee D, Berry DA, Veer L van’t, Symmans WF, Esserman L, Pusztai L, I-SPY Consortium

Background: Difference in pathologic complete response (pCR) rate after neoadjuvant chemotherapy does not capture the impact of treatment on downstaging of residual cancer in the experimental arm. We developed a method to compare the entire distribution of residual cancer burden (RCB) values between clinical trial arms to better quantify the differences in cytotoxic efficacy of treatments.

Patients and methods: The Treatment Efficacy Score (TES) reflects the area between the weighted cumulative distribution functions of RCB values from two trial arms. TES is based on a modified Kolmogorov–Smirnov test with added weight function to capture the importance of high RCB values and uses the area under the difference between two distribution functions as a statistical metric. The higher the TES the greater the shift to lower RCB values in the experimental arm. We developed TES from the durvalumab + olaparib arm (n = 72) and corresponding controls (n = 282) of the I-SPY2 trial. The 11 other experimental arms and control cohorts (n = 947) were used as validation sets to assess the performance of TES. We compared TES to Kolmogorov–Smirnov, Mann–Whitney, and Fisher’s exact tests to identify trial arms with higher cytotoxic efficacy and assessed associations with trial arm level survival differences. Significance was assessed with a permutation test.

Results: In the validation set, TES identified arms with a higher pCR rate but was more accurate to identify regimens as less effective if treatment did not reduce the frequency of high RCB values, even if the pCR rate improved. The correlation between TES and survival was higher than the correlation between the pCR rate difference and survival.

Conclusions: TES quantifies the difference between the entire distribution of pathologic responses observed in trial arms and could serve as a better early surrogate to predict trial arm level survival differences than pCR rate difference alone.

Tomography 8: 1208–1220, 2022.

Effect of Inter-Reader Variability on Diffusion-Weighted MRI Apparent Diffusion Coefficient Measurements and Prediction of Pathologic Complete Response for Breast Cancer

Le NN, Li W, Onishi N, Newitt DC, Gibbs JE, Wilmes LJ, Kornak J, Partridge SC, LeStage B, Price ER, Joe BN, Esserman LJ, Hylton NM

This study evaluated the inter-reader agreement of tumor apparent diffusion coefficient (ADC) measurements performed on breast diffusion-weighted imaging (DWI) for assessing treatment response in a multi-center clinical trial of neoadjuvant chemotherapy (NAC) for breast cancer. DWIs from 103 breast cancer patients (mean age: 46 ± 11 years) acquired at baseline and after 3 weeks of treatment were evaluated independently by two readers. Three types of tumor regions of interests (ROIs) were delineated: multiple-slice restricted, single-slice restricted and single-slice tumor ROIs. Compared to tumor ROIs, restricted ROIs were limited to low ADC areas of enhancing tumor only. We found excellent agreement (intraclass correlation coefficient [ICC] ranged from 0.94 to 0.98) for mean ADC. Higher ICCs were observed in multiple-slice restricted ROIs (range: 0.97 to 0.98) than in other two ROI types (both in the range of 0.94 to 0.98). Among the three ROI types, the highest area under the receiver operating characteristic curves (AUCs) were observed for mean ADC of multiple-slice restricted ROIs (0.65, 95% confidence interval [CI]: 0.52–0.79 and 0.67, 95% CI: 0.53–0.81 for Reader 1 and Reader 2, respectively). In conclusion, mean ADC values of multiple-slice restricted ROI showed excellent agreement and similar predictive performance for pathologic complete response between the two readers.

Translat Oncol 20: 101411, 2022.

Impact of deformable registration methods for prediction of recurrence free survival response to neoadjuvant chemotherapy in breast cancer: Results from the ISPY 1/ACRIN 6657 trial

Thakran S, Cohen E, Jahani N, Weinstein SP, Pantalone L, Hylton N, Newitt D, DeMichele A, Davatzikos C, Kontos D

Purpose: Image registration plays a vital role in spatially aligning multiple MRI scans for better longitudinal assessment of tumor morphological features. The objective was to evaluate the effect of registration accuracy of six established deformable registration methods(ANTs, DRAMMS, ART, NiftyReg, SSD-FFD, and NMI-FFD) on the predictive value of extracted radiomic features when modeling recurrence-free-survival(RFS) for women after neoadjuvant chemotherapy(NAC) for locally advanced breast cancer.

Methods: 130 women had DCE-MRI scans available from the first two visits in the ISPY1/ACRIN-6657 cohort. We calculated the transformation field from each of the different deformable registration methods, and used it to compute voxel-wise parametric-response-maps(PRM) for established four kinetic features.104-radiomic features were computed from each PRM map to characterize intra-tumor heterogeneity. We evaluated performance for RFS using Cox-regression, C-statistic, and Kaplan-Meier(KM) plots.

Results: A baseline model(F1:Age, Race, and Hormone-receptor-status) had a 0.54 C-statistic, and model F2(baseline + functional-tumor-volume at early treatment visit(FTV2)) had 0.63. The F2+ANTs had the highest C-statistic(0.72) with the smallest landmark differences(5.40±4.40mm) as compared to other models. The KM curve for model F2 gave p=0.004 for separation between women above and below the median hazard compared to the model F1(p=0.31). A models augmented with radiomic features, also achieved significant KM curve separation(p<0.001) except the F2+ART model.

Conclusion: Incorporating image registration in quantifying changes in tumor heterogeneity during NAC can improve prediction of RFS. Radiomic features of PRM maps derived from warping the DCE-MRI kinetic maps using ANTs registration method further improved the early prediction of RFS as compared to other methods.

Tomography8:891–904, 2022.

Post-Processing Bias Field Inhomogeneity Correction for Assessing Background Parenchymal Enhancement on Breast MRI as a Quantitative Marker of Treatment Response

Nguyen AA-T, Onishi N, Carmona-Bozo J, Li W, Kornak J, Newitt DC, Hylton NM
Background parenchymal enhancement (BPE) of breast fibroglandular tissue (FGT) in dynamic contrast-enhanced breast magnetic resonance imaging (MRI) has shown an association with response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. Fully automated segmentation of FGT for BPE calculation is a challenge when image artifacts are present. Low spatial frequency intensity nonuniformity due to coil sensitivity variations is known as bias or inhomogeneity and can affect FGT segmentation and subsequent BPE measurement. In this study, we utilized the N4ITK algorithm for bias correction over a restricted bilateral breast volume and compared the contralateral FGT segmentations based on uncorrected and bias-corrected images in three MRI examinations at pre-treatment, early treatment and inter-regimen timepoints during NAC. A retrospective analysis of 2 cohorts was performed: one with 735 patients enrolled in the multi-center I-SPY 2 TRIAL and the sub-cohort of 340 patients meeting a high-quality benchmark for segmentation. Bias correction substantially increased the FGT segmentation quality for 6.3–8.0% of examinations, while it substantially decreased the quality for no examination. Our results showed improvement in segmentation quality and a small but statistically significant increase in the resulting BPE measurement after bias correction at all timepoints in both cohorts. Continuing studies are examining the effects on pCR prediction.

Lancet Oncol 23: 149-160, 2021.

Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients

Yau C, Osdoit M, van der Noordaa M, Shad S, Wei J, de Croze D, Hamy AS, Laé M, Reyal F, Sonke GS, Steenbruggen TG, van Seijen M, Wesseling J, Martín M, Del Monte-Millán M, López-Tarruella S; I-SPY 2 Trial Consortium, Boughey JC, Goetz MP, Hoskin T, Gould R, Valero V, Edge SB, Abraham JE, Bartlett JMS, Caldas C, Dunn J, Earl H, Hayward L, Hiller L, Provenzano E, Sammut SJ, Thomas JS, Cameron D, Graham A, Hall P, Mackintosh L, Fan F, Godwin AK, Schwensen K, Sharma P, DeMichele AM, Cole K, Pusztai L, Kim MO, van ‘t Veer LJ, Esserman LJ, Symmans WF.

Background: Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings.

Methods: In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I-III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype.

Findings: We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20-80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0-186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41-1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79-2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36-1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73-2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes).

Interpretation: RCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient’s residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy.

Nature Comm 12: 6428, 2021.

Neoadjuvant T-DM1/pertuzumab and paclitaxel/trastuzumab/pertuzumab for HER2+ breast cancer in the adaptively randomized I-SPY2 trial

Clark AS, Yau C, Wolf DM, Petricoin EF, Veer LJ van ‘t, Yee D, Moulder SL, Wallace AM, Chien AJ, Isaacs C, Boughey JC, Albain KS, Kemmer K, Haley BB, Han HS, Forero-Torres A, Elias A, Lang JE, Ellis ED, Yung R, Tripathy D, Nanda R, Wulfkuhle JD, Brown-Swigart L, Gallagher RI, Helsten T, Roesch E, Ewing CA, Alvarado M, Crane EP, Buxton M, Clennell JL, Paoloni M, Asare SM, Wilson A, Hirst GL, Singhrao R, Steeg K, Asare A, Matthews JB, Berry S, Sanil A, Melisko M, Perlmutter J, Rugo HS, Schwab RB, Symmans WF, Hylton NM, Berry DA, Esserman LJ, DeMichele AM

HER2-targeted therapy dramatically improves outcomes in early breast cancer. Here we report the results of two HER2-targeted combinations in the neoadjuvant I-SPY2 phase 2 adaptive platform trial for early breast cancer at high risk of recurrence: ado-trastuzumab emtansine plus pertuzumab (T-DM1/P) and paclitaxel, trastuzumab and pertuzumab (THP). Eligible women have >2.5 cm clinical stage II/III HER2+ breast cancer, adaptively randomized to T-DM1/P, THP, or a common control arm of paclitaxel/trastuzumab (TH), followed by doxorubicin/cyclophosphamide, then surgery. Both T-DM1/P and THP arms ‘graduate’ in all subtypes: predicted pCR rates are 63%, 72% and 33% for T-DM1/P (n = 52), THP (n = 45) and TH (n = 31) respectively. Toxicity burden is similar between arms. Degree of HER2 pathway signaling and phosphorylation in pretreatment biopsy specimens are associated with response to both T-DM1/P and THP and can further identify highly responsive HER2+ tumors to HER2-directed therapy. This may help identify patients who can safely de-escalate cytotoxic chemotherapy without compromising excellent outcome.

Nature Comm 12: 6427, 2021.

RAB5A expression is a predictive biomarker for trastuzumab emtansine in breast cancer

Engebraaten O, Yau C, Berg K, Borgen E, Garred Ø, Berstad MEB, Fremstedal ASV, DeMichele A, Veer L van ’t, Esserman L, Weyergang A

HER2 is a predictive biomarker for HER2-targeted therapeutics. For antibody–drug conjugates (ADCs; e.g., trastuzumab emtansine (T-DM1)), HER2 is utilized as a transport gate for cytotoxic agents into the cell. ADC biomarkers may therefore be more complex, also reflecting the intracellular drug transport. Here we report on a positive correlation between the early endosome marker RAB5A and T-DM1 sensitivity in five HER2-positive cell lines. Correlation between RAB5A expression and T-DM1 sensitivity is confirmed in breast cancer patients treated with trastuzumab emtansine/pertuzumab in the I-SPY2 trial (NCT01042379), but not in the trastuzumab/paclitaxel control arm. The clinical correlation is further verified in patients from the KAMILLA trial (NCT01702571). In conclusion, our results suggest RAB5A as a predictive biomarker for T-DM1 response and outline proteins involved in endocytic trafficking as predictive biomarkers for ADCs.

Npj Breast Cancer 7: 131, 2021.

Ganitumab and metformin plus standard neoadjuvant therapy in stage 2/3 breast cancer

Yee D, Isaacs C, Wolf DM, Yau C, Haluska P, Giridhar KV, Forero-Torres A, Chien AJ, Wallace AM, Pusztai L, Albain KS, Ellis ED, Beckwith H, Haley BB, Elias AD, Boughey JC, Kemmer K, Yung RL, Pohlmann PR, Tripathy D, Clark AS, Han HS, Nanda R, Khan QJ, Edmiston KK, Petricoin EF, Stringer-Reasor E, Falkson CI, Majure M, Mukhtar RA, Helsten TL, Moulder SL, Robinson PA, Wulfkuhle JD, Brown-Swigart L, Buxton M, Clennell JL, Paoloni M, Sanil A, Berry S, Asare SM, Wilson A, Hirst GL, Singhrao R, Asare AL, Matthews JB, Hylton NM, DeMichele A, Melisko M, Perlmutter J, Rugo HS, Symmans WF, van‘t Veer LJ, Berry DA, Esserman LJ

I-SPY2 is an adaptively randomized phase 2 clinical trial evaluating novel agents in combination with standard-of-care paclitaxel followed by doxorubicin and cyclophosphamide in the neoadjuvant treatment of breast cancer. Ganitumab is a monoclonal antibody designed to bind and inhibit function of the type I insulin-like growth factor receptor (IGF-1R). Ganitumab was tested in combination with metformin and paclitaxel (PGM) followed by AC compared to standard-of-care alone. While pathologic complete response (pCR) rates were numerically higher in the PGM treatment arm for hormone receptor-negative, HER2-negative breast cancer (32% versus 21%), this small increase did not meet I-SPY’s prespecified threshold for graduation. PGM was associated with increased hyperglycemia and elevated hemoglobin A1c (HbA1c), despite the use of metformin in combination with ganitumab. We evaluated several putative predictive biomarkers of ganitumab response (e.g., IGF-1 ligand score, IGF-1R signature, IGFBP5 expression, baseline HbA1c). None were specific predictors of response to PGM, although several signatures were associated with pCR in both arms. Any further development of anti-IGF-1R therapy will require better control of anti-IGF-1R drug-induced hyperglycemia and the development of more predictive biomarkers.

JAMA Onc 7: 1654-1663, 2021.

Assessment of Residual Cancer Burden and Event-Free Survival in Neoadjuvant Treatment for High-risk Breast Cancer: An Analysis of Data From the I-SPY2 Randomized Clinical Trial

Symmans WF, Yau C, Chen YY, Balassanian R, Klein ME, Pusztai L, Nanda R, Parker BA, Datnow B, Krings G, Wei S, Feldman MD, Duan X, Chen B, Sattar H, Khazai L, Zeck JC, Sams S, Mhawech-Fauceglia P, Rendi M, Sahoo S, Ocal IT, Fan F, Grasso LeBeau L, Vinh T, Troxell ML, Chien AJ, Wallace AM, Forero-Torres A, Ellis E, Albain KS, Murthy RK, Boughey JC, Liu MC, Haley BB, Elias AD, Clark AS, Kemmer K, Isaacs C, Lang JE, Han HS, Edmiston K, Viscusi RK, Northfelt DW, Khan QJ, Leyland-Jones B, Venters SJ, Shad S, Matthews JB, Asare SM, Buxton M, Asare AL, Rugo HS, Schwab RB, Helsten T, Hylton NM, van ’t Veer L, Perlmutter J, DeMichele AM, Yee D, Berry DA, Esserman LJ

Importance  Residual cancer burden (RCB) distributions may improve the interpretation of efficacy in neoadjuvant breast cancer trials.

Objective  To compare RCB distributions between randomized control and investigational treatments within subtypes of breast cancer and explore the relationship with survival.

Design, Setting, and Participants  The I-SPY2 is a multicenter, platform adaptive, randomized clinical trial in the US that compares, by subtype, investigational agents in combination with chemotherapy vs chemotherapy alone in adult women with stage 2/3 breast cancer at high risk of early recurrence. Investigational treatments graduated in a prespecified subtype if there was 85% or greater predicted probability of higher rate of pathologic complete response (pCR) in a confirmatory, 300-patient, 1:1 randomized, neoadjuvant trial in that subtype. Evaluation of a secondary end point was reported from the 10 investigational agents tested in the I-SPY2 trial from March 200 through 2016, and analyzed as of September 9, 2020. The analysis plan included modeling of RCB within subtypes defined by hormone receptor (HR) and ERBB2 status and compared control treatments with investigational treatments that graduated and those that did not graduate.

Interventions  Neoadjuvant paclitaxel plus/minus 1 of several investigational agents for 12 weeks, then 12 weeks of cyclophosphamide/doxorubicin chemotherapy followed by surgery.

Main Outcomes and Measures  Residual cancer burden (pathological measure of residual disease) and event-free survival (EFS).

Results  A total of 938 women (mean [SD] age, 49 [11] years; 66 [7%] Asian, 103 [11%] Black, and 750 [80%] White individuals) from the first 10 investigational agents were included, with a median follow-up of 52 months (IQR, 29 months). Event-free survival worsened significantly per unit of RCB in every subtype of breast cancer (HR-positive/ERBB2-negative: hazard ratio [HZR], 1.75; 95% CI, 1.45-2.16; HR-positive/ERBB2-positive: HZR, 1.55; 95% CI, 1.18-2.05; HR-negative/ERBB2-positive: HZR, 2.39; 95% CI, 1.64-3.49; HR-negative/ERBB2-negative: HZR, 1.99; 95% CI, 1.71-2.31). Prognostic information from RCB was similar from treatments that graduated (HZR, 2.00; 95% CI, 1.57-2.55; 254 [27%]), did not graduate (HZR, 1.87; 95% CI, 1.61-2.17; 486 [52%]), or were control (HZR, 1.79; 95% CI, 1.42-2.26; 198 [21%]). Investigational treatments significantly lowered RCB in HR-negative/ERBB2-negative (graduated and nongraduated treatments) and ERBB2-positive subtypes (graduated treatments), with improved EFS (HZR, 0.61; 95% CI, 0.41-0.93) in the exploratory analysis.

Conclusions and Relevance  In this randomized clinical trial, the prognostic significance of RCB was consistent regardless of subtype and treatment. Effective neoadjuvant treatments shifted the distribution of RCB in addition to increasing pCR rate and appeared to improve EFS. Using a standardized quantitative method to measure response advances the interpretation of efficacy.

Radiology 301: 295–308, 2021.

Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response

Onishi N, Li W, Newitt DC, Harnish RJ, Strand F, Nguyen AA-T, Arasu VA, Gibbs J, Jones EF, Wilmes LJ, Kornak J, Joe BN, Price ER, Ojeda-Fournier H, Eghtedari M, Zamora KW, Woodard S, Umphrey HR, Nelson MT, Church AL, Bolan PJ, Kuritza T, Ward K, Morley K, Wolverton D, Fountain K, Paniagua DL, Hardesty L, Brandt KR, McDonald ES, Rosen M, Kontos D, Abe H, Sheth D, Crane E, Dillis C, Sheth P, Hovanessian-Larsen L, Bang DH, Porter B, Oh KY, Jafarian N, Tudorica LA, Niell B, Drukteinis J, Newell MS, Giurescu ME, Berman E, Lehman CD, Partridge SC, Fitzpatrick KA, Borders MH, Yang WT, Dogan B, Goudreau SH, Chenevert T, Yau C, DeMichele A, Berry DA, Esserman LJ, Hylton NM

Background: Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC.

Purpose: To investigate the relationship between lack of BPE suppression and pathologic response.

Materials and Methods: A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts.

Results: A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05.

Conclusions: In hormone receptor–positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response.

Clin Cancer Res 27: 5299-5306, 2021.

Tumor-Specific Major Histocompatibility-II Expression Predicts Benefit to Anti–PD-1/L1 Therapy in Patients With HER2-Negative Primary Breast Cancer

Gonzalez-Ericsson PI, Wulfkhule JD, Gallagher RI, Sun X, Axelrod M, Sheng Q, Luo N, Gomez H, Sanchez V, Sanders M, Pusztai L, Petricoin E, Blenman KRM, Balko JM

Purpose: Immunotherapies targeting PD-1/L1 enhance pathologic complete response (pCR) rates when added to standard neoadjuvant chemotherapy (NAC) regimens in early-stage triple-negative, and possibly high-risk estrogen receptor–positive breast cancer. However, immunotherapy has been associated with significant toxicity, and most patients treated with NAC do not require immunotherapy to achieve pCR. Biomarkers discerning patients benefitting from the addition of immunotherapy from those who would achieve pCR to NAC alone are clearly needed. In this study,we tested the ability of MHC-II expression on tumor cells, to predict immunotherapy-specific benefit in the neoadjuvant breast cancer setting.

Patients and Methods: This was a retrospective tissue-based analysis of 3 cohorts of patients with breast cancer: (i) primary
nonimmunotherapy-treated breast cancers (n ¼ 381), (ii) triplenegative breast cancers (TNBC) treated with durvalumab and standard NAC (n ¼ 48), and (iii) HER2-negative patients treated with standard NAC (n¼87) or NAC and pembrolizumab (n¼66).

Results: HLA-DR positivity on ≥5% of tumor cells, defined a priori, was observed in 10% and 15% of primary non-immunotherapy–
treated hormone receptor–positive and triple-negative breast cancers, respectively. Quantitative assessment of MHC-II on tumor cells was predictive of durvalumabþ NAC and pembrolizumabþ NAC (ROC AUC, 0.71; P ¼ 0.01 and AUC, 0.73; P ¼ 0.001, respectively), but not NAC alone (AUC, 0.5; P ¼ 0.99).

Conclusions: Tumor-specific MHC-II has a strong candidacy as a specific biomarker of anti–PD-1/L1 immunotherapy benefit when added to standard NAC in HER2-negative breast cancer. Combined with previous studies in melanoma, MHC-II has the potential to be a pan-cancer biomarker. Validation is warranted in existing and future phase II/III clinical trials in this setting.

Cancer Cell 39: 989-998, 2021.

Durvalumab with olaparib and paclitaxel for high-risk HER2-negative stage II/III breast cancer: Results from the adaptively randomized I-SPY2 trial

Pusztai L, Yau C, Wolf DM, Han HS, Du L, Wallace AM, Stringer-Reasor E, Boughey JC, Chien AJ, Elias AD, Beckwith H, Nanda R, Albain KS, Clark AS, Forero-Torres A, Liu MC, Brown-Swigart L, Petricoin EF, Wulfkuhle, Matthews JB, Perlmutter J, Melisko M, Rugo HS, Schwab RB, Fraser WF, Yee D, van ‘t Veer LJ, Hylton NM, DeMichele AM, Berry DA, Esserman LJ

The combination of PD-L1 inhibitor durvalumab and PARP inhibitor olaparib added to standard paclitaxel neoadjuvant chemotherapy (durvalumab/olaparib/paclitaxel [DOP]) was investigated in the phase II I-SPY2 trial of stage II/III HER2-negative breast cancer. Seventy-three participants were randomized to DOP and 299 to standard of care (paclitaxel) control. DOP increased pathologic complete response (pCR) rates in all HER2-negative (20%-37%), hormone receptor (HR)-positive/HER2-negative (14%-28%), and triple-negative breast cancer (TNBC) (27%-47%). In HR-positive/HER2-negative cancers, MammaPrint ultra-high (MP2) cases benefited selectively from DOP (pCR 64% versus 22%), no benefit was seen in MP1 cancers (pCR 9% versus 10%). Overall, 12.3% of patients in the DOP arm experienced immune-related grade 3 adverse events versus 1.3% in control. Gene expression signatures associated with immune response were positively associated with pCR in both arms, while a mast cell signature was associated with non-pCR. DOP has superior efficacy over standard neoadjuvant chemotherapy in HER2-negative breast cancer, particularly in a highly sensitive subset of high-risk HR-positive/HER2-negative patients.

JAMIA Open 4: ooab038, 2021.

PRoBE the cloud toolkit: finding the best biomarkers of drug response within a breast cancer clinical trial

O’Grady N, Gibbs DL, Abdilleh K, Asare A, Asare S, Venters S, Brown-Swigart L, Hirst GL, Wolf D, Yau C, Veer LJ van ’t, Esserman L, Basu A

Objectives: In this paper, we discuss leveraging cloud-based platforms to collect, visualize, analyze, and share data in the context of a clinical trial. Our cloud-based infrastructure, Patient Repository of Biomolecular Entities (PRoBE), has given us the opportunity for uniform data structure, more efficient analysis of valuable data, and increased collaboration between researchers.

Materials and Methods: We utilize a multi-cloud platform to manage and analyze data generated from the clinical Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis 2 (I-SPY 2 TRIAL). A collaboration with the Institute for Systems Biology Cancer Gateway in the Cloud has additionally given us access to public genomic databases. Applications to I-SPY 2 data have been built using R Shiny, while leveraging Google’s BigQuery tables and SQL commands for data mining.

Results: We highlight the implementation of PRoBE in several unique case studies including prediction of biomarkers associated with clinical response, access to the Pan-Cancer Atlas, and integrating pathology images within the cloud. Our data integration pipelines, documentation, and all codebase will be placed in a Github repository.

Discussion and conclusion: We are hoping to develop risk stratification diagnostics by integrating additional molecular, magnetic resonance imaging, and pathology markers into PRoBE to better predict drug response. A robust cloud infrastructure and tool set can help integrate these large datasets to make valuable predictions of response to multiple agents. For that reason, we are continuously improving PRoBE to advance the way data is stored, accessed, and analyzed in the I-SPY 2 clinical trial.

ASCO EDUCATIONAL BOOK 41: 12-23, 2021.

The Way of the Future: Personalizing Treatment Plans Through Technology

Liefaard M, Lips E, Wesseling J, Hylton N, Lou B, Mansi T, Pusztai L

Advances in tissue analysis methods, image analysis, high-throughput molecular profiling, and computational tools increasingly allow us to capture and quantify patient-to-patient variations that impact cancer risk, prognosis, and treatment response. Statistical models that integrate patient-specific information from multiple sources (e.g., family history, demographics, germline variants, imaging features) can provide individualized cancer risk predictions that can guide screening and prevention strategies. The precision, quality, and standardization of diagnostic imaging are improving through computer-aided solutions, and multigene prognostic and predictive tests improved predictions of prognosis and treatment response in various cancer types. A common theme across many of these advances is that individually moderately informative variables are combined into more accurate multivariable prediction models. Advances in machine learning and the availability of large data sets fuel rapid progress in this field. Molecular dissection of the cancer genome has become a reality in the clinic, and molecular target profiling is now routinely used to select patients for various targeted therapies. These technology-driven increasingly more precise and quantitative estimates of benefit versus risk from a given intervention empower patients and physicians to tailor treatment strategies that match patient values and expectations.

NPJ 7 :, 2021.

Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk

Magbanua MJM, Li W, Wolf DM, Yau C, Hirst GL, Brown-Swigart L, Newitt DC, Gibbs J, Delson AL, Kalashnikova E, Aleshin A, Zimmermann B, Chien AJ, Tripathy D, Esserman L, Hylton N, van ‘t Veer L

We investigated whether serial measurements of circulating tumor DNA (ctDNA) and functional tumor volume (FTV) by magnetic resonance imaging (MRI) can be combined to improve prediction of pathologic complete response (pCR) and estimation of recurrence risk in early breast cancer patients treated with neoadjuvant chemotherapy (NAC). We examined correlations between ctDNA and FTV, evaluated the additive value of ctDNA to FTV-based predictors of pCR using area under the curve (AUC) analysis, and analyzed the impact of FTV and ctDNA on distant recurrence-free survival (DRFS) using Cox regressions. The levels of ctDNA (mean tumor molecules/mL plasma) were significantly correlated with FTV at all time points (p < 0.05). Median FTV in ctDNA-positive patients was significantly higher compared to those who were ctDNA-negative (p < 0.05). FTV and ctDNA trajectories in individual patients showed a general decrease during NAC. Exploratory analysis showed that adding ctDNA information early during treatment to FTV-based predictors resulted in numerical but not statistically significant improvements in performance for pCR prediction (e.g., AUC 0.59 vs. 0.69, p = 0.25). In contrast, ctDNA-positivity after NAC provided significant additive value to FTV in identifying patients with increased risk of metastatic recurrence and death (p = 0.004). In this pilot study, we demonstrate that ctDNA and FTV were correlated measures of tumor burden. Our preliminary findings based on a limited cohort suggest that ctDNA at surgery improves FTV as a predictor of metastatic recurrence and death. Validation in larger studies is warranted.

Annals of Oncology :, 2021.

Predicted sensitivity to endocrine therapy for stage II-III hormone receptor-positive and HER2-negative (HR+/HER2−) breast cancer before chemo-endocrine therapy

Du L, Yau C, Brown-Swigart L, Gould R, Krings G, Hirst GL, Bedrosian I, Layman RM, Carter JM, Klen M, Venters S, Sonal S, van der Noordaa M, Chien AJ, Haddad T, Isaacs C, Pusztai L, Albain K, Nanda R, Tripathy D, Liu MC, Boughey J, Schwab R, Hylton N, DeMichele A, Perlmutter J, Yee D, Berry D, van ‘t Veer L, Valero V, Esserman L, Symmans WF

Highlights

•The SET2,3 assay added independent prognostic information to RCB after neoadjuvant chemotherapy.

•The SETER/PR index of endocrine transcriptional activity added to contemporary genomic signatures and assays.

•SET2,3 was prognostic within both luminal subtypes of breast cancer.

•Patients with a high SET2,3 result might be appropriate for clinical trials of neoadjuvant endocrine-based therapy.

Background

We proposed that a test for sensitivity to the adjuvant endocrine therapy component of treatment for patients with stage II-III breast cancer (SET2,3) should measure transcription related to estrogen and progesterone receptors (SETER/PR index) adjusted for a baseline prognostic index (BPI) combining clinical tumor and nodal stage with molecular subtype by RNA4 (ESR1, PGR, ERBB2, and AURKA).

Patients and methods

Patients with clinically high-risk, hormone receptor-positive (HR+), human epidermal growth factor receptor 2 (HER2)-negative (HR+/HER2−) breast cancer received neoadjuvant taxane–anthracycline chemotherapy, surgery with measurement of residual cancer burden (RCB), and then adjuvant endocrine therapy. SET2,3 was measured from pre-treatment tumor biopsies, evaluated first in an MD Anderson Cancer Center (MDACC) cohort (n = 307, 11 years’ follow-up, U133A microarrays), cut point was determined, and then independent, blinded evaluation was carried out in the I-SPY2 trial (n = 268, high-risk MammaPrint result, 3.8 years’ follow-up, Agilent-44K microarrays, NCI Clinical Trials ID: NCT01042379). Primary outcome measure was distant relapse-free survival. Multivariate Cox regression models tested prognostic independence of SET2,3 relative to RCB and other molecular prognostic signatures, and whether other prognostic signatures could substitute for SETER/PR or RNA4 components of SET2,3.

Results

SET2,3 added independent prognostic information to RCB in the MDACC cohort: SET2,3 [hazard ratio (HR) 0.23, P = 0.004] and RCB (HR 1.77, P < 0.001); and the I-SPY2 trial: SET2,3 (HR 0.27, P = 0.031) and RCB (HR 1.68, P = 0.008). SET2,3 provided similar prognostic information irrespective of whether RCB-II or RCB-III after chemotherapy, and in both luminal subtypes. Conversely, RCB was most strongly prognostic in cancers with low SET2,3 status (MDACC P < 0.001, I-SPY2 P < 0.001). Other molecular signatures were not independently prognostic; they could effectively substitute for RNA4 subtype within the BPI component of SET2,3, but they could not effectively substitute for SETER/PR index.

Conclusions

SET2,3 added independent prognostic information to chemotherapy response (RCB) and baseline prognostic score or subtype. Approximately 40% of patients with clinically high-risk HR+/HER2− disease had high SET2,3 and could be considered for clinical trials of neoadjuvant endocrine-based treatment.

Fac Rev 10:, 2021.

Recent advances in neoadjuvant therapy for breast cancer

Potter DA, Herrera-Ponzanelli CA, Hinojosa D, Castillo R, Hernandez-Cruz I, Arrieta VA, Franklin MJ, Yee D

Neoadjuvant trials for early breast cancer have accelerated the identification of novel active agents, enabling streamlined conduct of registration trials with fewer subjects. Measurement of neoadjuvant drug effects has also enabled the identification of patients with high risk of distant recurrence and has justified development of additional adjuvant approaches to improve outcomes. Neoadjuvant evaluation of new drugs was significantly improved by the introduction of pathologic complete response (pCR) rate as a quantitative surrogate endpoint for distant disease-free survival (DDFS) and event free survival (EFS). The neoadjuvant phase 2 platform trial I-SPY 2 simultaneously tests multiple drugs across multiple breast cancer subtypes using Bayesian methods of adaptive randomization for assessment of drug efficacy. In addition to the pCR endpoint, the I-SPY 2 trial has demonstrated that the residual cancer burden (RCB) score measures gradations of tumor response that correlate with DDFS and EFS across treatments and subtypes. For HER2-positive and triple-negative breast cancers that have failed to attain pCR with neoadjuvant chemotherapy (NAC), effective modifications of adjuvant treatment have improved outcomes and changed the standard of care for these subtypes. Neoadjuvant therapy is therefore preferred for stage II and III, as well as some stage I, HER2-positive and triple-negative tumors. Neoadjuvant endocrine therapy (NET) strategies have also emerged from innovative trials for stage II and III estrogen receptor (ER)-positive/HER2-negative tumors, as in the ALTERNATE trial. From neoadjuvant trials, opportunities have emerged to de-escalate therapy on the basis of metrics of response to chemotherapy or hormonal therapy. Neoadjuvant therapy for early breast cancer is therefore emerging as a promising approach to accelerate new drug development, optimize treatment strategies, and (where appropriate) de-escalate neoadjuvant therapy.

J Mag Res Imaging 53:271–282, 2021.

Denoising and Multiple Tissue Compartment Visualization of Multi‐b‐Valued Breast Diffusion MRI

Tan ET, Wilmes LJ, Joe BN, Onishi N, Arasu VA, Hylton NM, Marinelli L, Newitt DC

Background: Multi-b-valued/multi-shell diffusion provides potentially valuable metrics in breast MRI but suffers from low signal-to-noise ratio and has potentially long scan times.

Purpose: To investigate the effects of model-based denoising with no loss of spatial resolution on multi-shell breast diffusion MRI; to determine the effects of downsampling on multi-shell diffusion; and to quantify these effects in multi-b-valued (three directions per b-value) acquisitions.

Study Type: Prospective (“fully-sampled” multi-shell) and retrospective longitudinal (multi-b).

Subjects: One normal subject (multi-shell) and 10 breast cancer subjects imaging at four timepoints (multi-b).

Field Strength/Sequence: 3T multi-shell acquisition and 1.5T multi-b acquisition.

Assessment: The “fully-sampled” multi-shell acquisition was retrospectively downsampled to determine the bias and error from downsampling. Mean, axial/parallel, radial diffusivity, and fractional anisotropy (FA) were analyzed. Denoising was applied retrospectively to the multi-b-valued breast cancer subject dataset and assessed subjectively for image noise level and tumor conspicuity.

Statistical Tests: Parametric paired t-test (P < 0.05 considered statistically significant) on mean and coefficient of variation of each metric—the apparent diffusion coefficient (ADC) from all b-values, fast ADC, slow ADC, and perfusion fraction. Paired and two-sample t-tests for each metric comparing normal and tumor tissue.

Results: In the multi-shell data, denoising effectively suppressed FA (–45% to –78%), with small biases in mean diffusivity (–5% in normal, +23% in tumor, and –4% in vascular compartments). In the multi-b data, denoising resulted in small biases to the ADC metrics in tumor and normal contralateral tissue (by –3% to +11%), but greatly reduced the coefficient of variation for every metric (by –1% to –24%). Denoising improved differentiation of tumor and normal tissue regions in most metrics and timepoints; subjectively, image noise level and tumor conspicuity were improved in the fast ADC maps.

Data Conclusion: Model-based denoising effectively suppressed erroneously high FA and improved the accuracy of diffusivity metrics.

NPJ Breast Cancer 6:63, 2020.

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL

Li W, Newitt DC, Gibbs J, Wilmes LJ, Jones EF, Arasu VA, Strand F, Onishi N, Nguyen AA-T, Kornak J, Joe BN, Price ER, Ojeda-Fournier H, Eghtedari M, Zamora KW, Woodard SA, Umphrey H, Bernreuter W, Nelson M, Church AL, Bolan P, Kuritza T, Ward K, Morley K, Wolverton D, Fountain K, Lopez-Paniagua D, Hardesty L, Brandt K, McDonald ES, Rosen M, Kontos D, Abe H, Sheth D, Crane EP, Dillis C, Sheth P, Hovanessian-Larsen L, Bang DH, Porter B, Oh KY, Jafarian N, Tudorica A, Niell BL, Drukteinis J, Newell MS, Cohen MA, Giurescu M, Berman E, Lehman C, Partridge SC, Fitzpatrick KA, Borders MH, Yang WT, Dogan B, Goudreau S, Chenevert T, Yau C, DeMichele A, Berry D, Esserman LJ, Hylton NM

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

Ann Oncol 32:229-239, 2020.

Circulating tumor DNA in neoadjuvant-treated breast cancer reflects response and survival

Magbanua M, Brown-Swigart L, Wu H, Hirst GL, Yau C, Wolf DM, Tin A, Salari R, Shchegrova S, Pawar H, Delson AL, DeMichele A, Liu MC, Chien AJ, Tripathy D, Asare S, Lin C, Billings P, Aleshin A, Sethi H, Louie M, Zimmermann B, Esserman L, van ‘t Veer L

Background: Pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) is strongly associated with favorable outcome. We examined the utility of serial circulating tumor DNA (ctDNA) testing for predicting pCR and risk of metastatic recurrence.                                            

Patients and methods: Cell-free DNA (cfDNA) was isolated from 291 plasma samples of 84 high-risk early breast cancer patients treated in the neoadjuvant I-SPY 2 TRIAL with standard NAC alone or combined with MK-2206 (AKT inhibitor) treatment. Blood was collected at pretreatment (T0), 3 weeks after initiation of paclitaxel (T1), between paclitaxel and anthracycline regimens (T2), or prior to surgery (T3). A personalized ctDNA test was designed to detect up to 16 patient-specific mutations (from whole-exome sequencing of pretreatment tumor) in cfDNA by ultra-deep sequencing. The median follow-up time for survival analysis was 4.8 years.    

Results: At T0, 61 of 84 (73%) patients were ctDNA positive, which decreased over time (T1: 35%; T2: 14%; and T3: 9%). Patients who remained ctDNA positive at T1 were significantly more likely to have residual disease after NAC (83% non-pCR) compared with those who cleared ctDNA (52% non-pCR; odds ratio 4.33, P = 0.012). After NAC, all patients who achieved pCR were ctDNA negative (n = 17, 100%). For those who did not achieve pCR (n = 43), ctDNA-positive patients (14%) had a significantly increased risk of metastatic recurrence [hazard ratio (HR) 10.4; 95% confidence interval (CI) 2.3-46.6]; interestingly, patients who did not achieve pCR but were ctDNA negative (86%) had excellent outcome, similar to those who achieved pCR (HR 1.4; 95% CI 0.15-13.5).    

Conclusions: Lack of ctDNA clearance was a significant predictor of poor response and metastatic recurrence, while clearance was associated with improved survival even in patients who did not achieve pCR. Personalized monitoring of ctDNA during NAC of high-risk early breast cancer may aid in real-time assessment of treatment response and help fine-tune pCR as a surrogate endpoint of survival.    

Keywords: breast cancer; circulating tumor DNA; neoadjuvant chemotherapy; pathologic complete response.

NPJ Breast Cancer 6:52, 2020.

The quality of life index: a pilot study integrating treatment efficacy and quality of life in oncology

Basu A, Philip EJ, Dewitt B, Hanmer J, Chattopadhyay A, Yau C, Melisko ME, Esserman LJ

The majority of women diagnosed with breast cancer will experience some form of drug-related toxicity and subsequent impairments in Health-related Quality of Life (HRQoL). Despite this, HRQoL is assessed inconsistently and there is no validated method to integrate HRQoL data into the assessment of therapeutic agents. This proof of concept study utilizes data from the neoadjuvant I-SPY 2 clinical trial to describe the development of the Quality of Life Index (QoLI) measure. The QoLI represents a single composite score that incorporates validated longitudinal measures of clinical efficacy and QoL and one that permits a more comprehensive, direct comparison of individual therapeutic agents. Preliminary data suggest the QoLI is able to distinguish between agents based on their efficacy and toxicity; with further validation, the QoLI has the potential to provide more patient-centered evaluations in clinical trials and help guide treatment decision making in breast cancer and other oncologic diseases.

NPJ Breast Cancer 6:48, 2020.

Mechanism of action biomarkers predicting response to AKT inhibition in the I-SPY 2 breast cancer trial

Wolf DM, Yau C, Wulfkuhle J, Brown-Swigart L, Gallagher RI, Magbanua MJM, O’Grady N, Hirst G, Asare S, Tripathy D, Berry D, Esserman L, Chien AJ, Petricoin EF, I-SPY 2 Trial Investigators, van ‘t Veer L

The AKT inhibitor MK2206 (M) was evaluated in I-SPY 2 and graduated in the HER2+, HR−, and HR− HER2+ signatures. We hypothesized that AKT signaling axis proteins/genes may specifically predict response to M and tested 26 phospho-proteins and 10 genes involved in AKT-mTOR-HER signaling; in addition, we tested 9 genes from a previous study in the metastatic setting. One hundred and fifty patients had gene expression data from pretreatment biopsies available for analysis (M: 94, control: 56) and 138 had protein data (M: 87, control: 51). Logistic modeling was used to assess biomarker performance in pre-specified analysis. In general, phospho-protein biomarkers of activity in the AKT-mTOR-HER pathway appeared more predictive of response to M than gene expression or total protein biomarkers in the same pathway; however, the nature of the predictive biomarkers differed in the HER2+ and TN groups. In the HER2+ subset, patients achieving a pCR in M had higher levels of multiple AKT kinase substrate phospho-proteins (e.g., pmTOR, pTSC2). In contrast, in the TN subset responding patients had lower levels of AKT pathway phospho-proteins, such as pAKT, pmTOR, and pTSC2. Pathway mutations did not appear to account for these associations. Additional exploratory whole-transcriptome analysis revealed immune signaling as strongly associated with response to M in the HER2+ subset. While our sample size is small, these results suggest that the measurement of particular AKT kinase substrate phospho-proteins could be predictive of MK2206 efficacy in both HER2+ and TN tumors and that immune signaling may play a role in response in HER2+ patients.

JAMA Oncol 6:1355-1362, 2020.

Association of Event-Free and Distant Recurrence–Free Survival With Individual-Level Pathologic Complete Response in Neoadjuvant Treatment of Stages 2 and 3 Breast Cancer

I-SPY Trial Consortium

Importance: Pathologic complete response (pCR) is a known prognostic biomarker for long-term outcomes. The I-SPY2 trial evaluated if the strength of this clinical association persists in the context of a phase 2 neoadjuvant platform trial.

Objective: To evaluate the association of pCR with event-free survival (EFS) and pCR with distant recurrence–free survival (DRFS) in subpopulations of women with high-risk operable breast cancer treated with standard therapy or one of several novel agents.

Design, Setting, and Participants: Multicenter platform trial of women with operable clinical stage 2 or 3 breast cancer with no prior surgery or systemic therapy for breast cancer; primary tumors were 2.5 cm or larger. Women with tumors that were ERBB2 negative/hormone receptor (HR) positive with low 70-gene assay score were excluded. Participants were adaptively randomized to one of several different investigational regimens or control therapy within molecular subtypes from March 2010 through 2016. The analysis included participants with follow-up data available as of February 26, 2019.

Interventions: Standard-of-care neoadjuvant therapy consisting of taxane treatment with or without (as control) one of several investigational agents or combinations followed by doxorubicin and cyclophosphamide.

Main Outcome and Measures: Pathologic complete response and 3-year EFS and DRFS.

Results: Of the 950 participants (median [range] age, 49 [23-77] years), 330 (34.7%) achieved pCR. Three-year EFS and DRFS for patients who achieved pCR were both 95%. Hazard ratios for pCR vs non-pCR were 0.19 for EFS (95% CI, 0.12-0.31) and 0.21 for DRFS (95% CI, 0.13-0.34) and were similar across molecular subtypes, varying from 0.14 to 0.18 for EFS and 0.10 to 0.20 for DRFS.

Conclusions & Relevance: The 3-year outcomes from the I-SPY2 trial show that, regardless of subtype and/or treatment regimen, including 9 novel therapeutic combinations, achieving pCR after neoadjuvant therapy implies approximately an 80% reduction in recurrence rate. The goal of the I-SPY2 trial is to rapidly identify investigational therapies that may improve pCR when validated in a phase 3 confirmatory trial. Whether pCR is a validated surrogate in the sense that a therapy that improves pCR rate can be assumed to also improve long-term outcome requires further study.

J Breast Imaging 2:352-360, 2020.

Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2− Patients

Arasu VA, Kim P, Li W, Strand F, McHargue C, Harnish R, Newitt DC, Jones EF, Glymour M, Kornak J, Esserman LJ, Hylton NM, ISPY2 investigators

Objective

Women with advanced HER2− breast cancer have limited treatment options. Breast MRI functional tumor volume (FTV) is used to predict pathologic complete response (pCR) to improve treatment efficacy. In addition to FTV, background parenchymal enhancement (BPE) may predict response and was explored for HER2− patients in the I-SPY-2 TRIAL.

Methods

Women with HER2− stage II or III breast cancer underwent prospective serial breast MRIs during four neoadjuvant chemotherapy timepoints. BPE was quantitatively calculated using whole-breast manual segmentation. Logistic regression models were systematically explored using pre-specified and optimized predictor selection based on BPE or combined with FTV.

Results

A total of 352 MRI examinations in 88 patients (29 with pCR, 59 non-pCR) were evaluated. Women with hormone receptor (HR)+HER2− cancers who achieved pCR demonstrated a significantly greater decrease in BPE from baseline to pre-surgery compared to non-pCR patients (odds ratio 0.64, 95% confidence interval (CI): 0.39–0.92, P = 0.04). The associated BPE area under the curve (AUC) was 0.77 (95% CI: 0.56–0.98), comparable to the range of FTV AUC estimates. Among multi-predictor models, the highest cross-validated AUC of 0.81 (95% CI: 0.73–0.90) was achieved with combined FTV+HR predictors, while adding BPE to FTV+HR models had an estimated AUC of 0.82 (95% CI: 0.74–0.92).

Conclusion

Among women with HER2− cancer, BPE alone demonstrated association with pCR in women with HR+HER2− breast cancer, with similar diagnostic performance to FTV. BPE predictors remained significant in multivariate FTV models, but without added discrimination for pCR prediction. This may be due to small sample size limiting ability to create subtype-specific multivariate models.

Cancers 12:1511, 2020.

Current Landscape of Breast Cancer Imaging and Potential Quantitative Imaging Markers of Response in ER-Positive Breast Cancers Treated with Neoadjuvant Therapy

Jones EF, Hathi DK, Freimanis R, Mukhtar RA, Chien AJ, Esserman LJ, Veer LJ van’t, Joe BN, Hylton NM
In recent years, neoadjuvant treatment trials have shown that breast cancer subtypes identified on the basis of genomic and/or molecular signatures exhibit different response rates and recurrence outcomes, with the implication that subtype-specific treatment approaches are needed. Estrogen receptor-positive (ER+) breast cancers present a unique set of challenges for determining optimal neoadjuvant treatment approaches. There is increased recognition that not all ER+ breast cancers benefit from chemotherapy, and that there may be a subset of ER+ breast cancers that can be treated effectively using endocrine therapies alone. With this uncertainty, there is a need to improve the assessment and to optimize the treatment of ER+ breast cancers. While pathology-based markers offer a snapshot of tumor response to neoadjuvant therapy, non-invasive imaging of the ER disease in response to treatment would provide broader insights into tumor heterogeneity, ER biology, and the timing of surrogate endpoint measurements. In this review, we provide an overview of the current landscape of breast imaging in neoadjuvant studies and highlight the technological advances in each imaging modality. We then further examine some potential imaging markers for neoadjuvant treatment response in ER+ breast cancers.

Tomogr 6:216-222, 2020.

Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer

Li W, Newitt DC, Yun BL, Jones EF, Arasu V, Wilmes LJ, Gibbs J, Nguyen AA, Onishi N, Kornak J, Joe BN, Esserman LJ, Hylton NM
This retrospective study examined magnetic resonance imaging (MRI)–derived tumor sphericity (SPH) as a quantitative measure of breast tumor morphology, and investigated the association between SPH and reader-assessed morphological pattern (MP). In addition, association of SPH with pathologic complete response was evaluated in patients enrolled in an adaptively randomized clinical trial designed to rapidly identify new agents for breast cancer. All patients underwent MRI examinations at multiple time points during the treatment. SPH values from pretreatment (T0) and early-treatment (T1) were investigated in this study. MP on T0 dynamic contrast-enhanced MRI was ranked from 1 to 5 in 220 patients. Mean SPH values decreased with the increased order of MP. SPH was higher in patients with pathologic complete response than in patients without (difference at T0: 0.04, 95% confidence interval [CI]: 0.02–0.05, P < .001; difference at T1: 0.03, 95% CI: 0.02–0.04, P < .001). The area under the receiver operating characteristic curve was estimated as 0.61 (95% CI, 0.57–0.65) at T0 and 0.58 (95% CI, 0.55–0.62) at T1. When the analysis was performed by cancer subtype defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status, highest area under the receiver operating characteristic curve were observed in HR−/HER2+: 0.67 (95% CI, 0.54–0.80) at T0, and 0.63 (95% CI, 0.51–0.76) at T1. Tumor SPH showed promise to quantify MRI MPs and as a biomarker for predicting treatment outcome at pre- or early-treatment time points.

Tomography 6:101–110, 2020.

Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy

Nguyen AA-T, Arasu VA, Strand F, Li W, Onishi N, Gibbs J, Jones EF, Joe BN, Esserman LJ, Newitt DC, Hylton NM
Breast parenchymal enhancement (BPE) has shown association with breast cancer risk and response to neoadjuvant treatment. However, BPE quantification is challenging, and there is no standardized segmentation method for measurement. We investigated the use of a fully automated breast fibroglandular tissue segmentation method to calculate BPE from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for use as a predictor of pathologic complete response (pCR) following neoadjuvant treatment in the I-SPY 2 TRIAL. In this trial, patients had DCE-MRI at baseline (T0), after 3 weeks of treatment (T1), after 12 weeks of treatment and between drug regimens (T2), and after completion of treatment (T3). A retrospective analysis of 2 cohorts was performed: one with 735 patients and another with a final cohort of 340 patients, meeting a high-quality benchmark for segmentation. We evaluated 3 subvolumes of interest segmented from bilateral T1-weighted axial breast DCE-MRI: full stack (all axial slices), half stack (center 50% of slices), and center 5 slices. The differences between methods were assessed, and a univariate logistic regression model was implemented to determine the predictive performance of each segmentation method. The results showed that the half stack method provided the best compromise between sampling error from too little tissue and inclusion of incorrectly segmented tissues from extreme superior and inferior regions. Our results indicate that BPE calculated using the half stack segmentation approach has potential as an early biomarker for response to treatment in the hormone receptor–negative and human epidermal growth factor receptor 2–positive subtype.

Tomography 6:77–85, 2020.

Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial

Onishi N, Li W, Gibbs J, Wilmes LJ, Nguyen A, Jones EF, Arasu V, Kornak J, Joe BN, Esserman LJ, Newitt DC, Hylton NM
We investigated the impact of magnetic resonance imaging (MRI) protocol adherence on the ability of functional tumor volume (FTV), a quantitative measure of tumor burden measured from dynamic contrast-enhanced MRI, to predict response to neoadjuvant chemotherapy. We retrospectively reviewed dynamic contrast-enhanced breast MRIs for 990 patients enrolled in the multicenter I-SPY 2 TRIAL. During neoadjuvant chemotherapy, each patient had 4 MRI visits (pretreatment [T0], early-treatment [T1], inter-regimen [T2], and presurgery [T3]). Protocol adherence was rated for 7 image quality factors at T0–T2. Image quality factors confirmed by DICOM header (acquisition duration, early phase timing, field of view, and spatial resolution) were adherent if the scan parameters followed the standardized imaging protocol, and changes from T0 for a single patient’s visits were limited to defined ranges. Other image quality factors (contralateral image quality, patient motion, and contrast administration error) were considered adherent if imaging issues were absent or minimal. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of FTV change (percent change of FTV from T0 to T1 and T2) in predicting pathological complete response. FTV changes with adherent image quality in all factors had higher estimated AUC than those with non-adherent image quality, although the differences did not reach statistical significance (T1, 0.71 vs. 0.66; T2, 0.72 vs. 0.68). These data highlight the importance of MRI protocol adherence to predefined scan parameters and the impact of data quality on the predictive performance of FTV in the breast cancer neoadjuvant setting.

Tomography 6:86-92, 2020.

Retrospective Correction of ADC for Gradient Nonlinearity Errors in Multicenter Breast DWI Trials: ACRIN6698 Multiplatform Feasibility Study

Malyarenko DI, Newitt DC, Amouzandeh G, Wilmes LJ, Tan ET, Marinelli L, Devaraj A, Peeters JM, Giri S, Endt AV, Hylton NM, Partridge SC, Chenevert TL
The presented analysis of multisite, multiplatform clinical oncology trial data sought to enhance quantitative utility of the apparent diffusion coefficient (ADC) metric, derived from diffusion-weighted magnetic resonance imaging, by reducing technical interplatform variability owing to systematic gradient nonlinearity (GNL). This study tested the feasibility and effectiveness of a retrospective GNL correction (GNC) implementation for quantitative quality control phantom data, as well as in a representative subset of 60 subjects from the ACRIN 6698 breast cancer therapy response trial who were scanned on 6 different gradient systems. The GNL ADC correction based on a previously developed formalism was applied to trace-DWI using system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. For quantitative DWI phantom images acquired in typical breast imaging positions, the GNC improved interplatform accuracy from a median of 6% down to 0.5% and reproducibility of 11% down to 2.5%. Across studied trial subjects, GNC increased low ADC (<1 µm2/ms) tumor volume by 16% and histogram percentiles by 5%–8%, uniformly shifting percentile-dependent ADC thresholds by ∼0.06 µm2/ms. This feasibility study lays the grounds for retrospective GNC implementation in multiplatform clinical imaging trials to improve accuracy and reproducibility of ADC metrics used for breast cancer treatment response prediction.

JAMA Oncol 6:676-684, 2020.

Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women With Early-Stage Breast Cancer

Nanda R, Liu MC, Yau C, Shatsky R, Pusztai L, Wallace A, Chien AJ, Forero-Torres A, Ellis E, Han H, Clark A, Albain K, Boughey JC, Jaskowiak NT, Elias A, Isaacs C, Kemmer K, Helsten T, Majure M, Stringer-Reasor E, Parker C, Lee MC, Haddad T, Cohen RN, Asare S, Wilson A, Hirst GL, Singhrao R, Steeg K, Asare A, Matthews JB, Berry S, Sanil A, Schwab R, Symmans WF, van ‘t Veer L, Yee D, DeMichele A, Hylton NM, Melisko M, Perlmutter J, Rugo HS, Berry DA, Esserman LJ
An Analysis of the Ongoing Phase 2 Adaptively Randomized I-SPY2 Trial

Importance

Approximately 25% of patients with early-stage breast cancer who receive (neo)adjuvant chemotherapy experience a recurrence within 5 years. Improvements in therapy are greatly needed.

Objective

To determine if pembrolizumab plus neoadjuvant chemotherapy (NACT) in early-stage breast cancer is likely to be successful in a 300-patient, confirmatory randomized phase 3 neoadjuvant clinical trial.

Design, Setting, and Participants

The I-SPY2 study is an ongoing open-label, multicenter, adaptively randomized phase 2 platform trial for high-risk, stage II/III breast cancer, evaluating multiple investigational arms in parallel. Standard NACT serves as the common control arm; investigational agent(s) are added to this backbone. Patients with ERBB2 (formerly HER2)-negative breast cancer were eligible for randomization to pembrolizumab between November 2015 and November 2016.

Interventions

Participants were randomized to receive taxane- and anthracycline-based NACT with or without pembrolizumab, followed by definitive surgery.

Main Outcomes and Measures

The primary end point was pathologic complete response (pCR). Secondary end points were residual cancer burden (RCB) and 3-year event-free and distant recurrence-free survival. Investigational arms graduated when demonstrating an 85% predictive probability of success in a hypothetical confirmatory phase 3 trial.

Results

Of the 250 women included in the final analysis, 181 were randomized to the standard NACT control group (median [range] age, 47 [24.77] years). Sixty-nine women (median [range] age, 50 [27-71] years) were randomized to 4 cycles of pembrolizumab in combination with weekly paclitaxel followed by AC; 40 hormone receptor (HR)-positive and 29 triple-negative. Pembrolizumab graduated in all 3 biomarker signatures studied. Final estimated pCR rates, evaluated in March 2017, were 44% vs 17%, 30% vs 13%, and 60% vs 22% for pembrolizumab vs control in the ERBB2-negative, HR-positive/ERBB2-negative, and triple-negative cohorts, respectively. Pembrolizumab shifted the RCB distribution to a lower disease burden for each cohort evaluated. Adverse events included immune-related endocrinopathies, notably thyroid abnormalities (13.0%) and adrenal insufficiency (8.7%). Achieving a pCR appeared predictive of long-term outcome, where patients with pCR following pembrolizumab plus chemotherapy had high event-free survival rates (93% at 3 years with 2.8 years’ median follow-up).

Conclusions and Relevance

When added to standard neoadjuvant chemotherapy, pembrolizumab more than doubled the estimated pCR rates for both HR-positive/ERBB2-negative and triple-negative breast cancer, indicating that checkpoint blockade in women with early-stage, high-risk, ERBB2-negative breast cancer is highly likely to succeed in a phase 3 trial. Pembrolizumab was the first of 10 agents to graduate in the HR-positive/ERBB2-negative signature.

Trial Registration  ClinicalTrials.gov Identifier: NCT01042379

J Clin Oncol 38:1059-1069, 2020.

MK-2206 and Standard Neoadjuvant Chemotherapy Improves Response in Patients With Human Epidermal Growth Factor Receptor 2–Positive and/or Hormone Receptor–Negative Breast Cancers in the I-SPY 2 Trial

Chien AJ, Tripathy D, Albain KS, Symmans WF, Rugo HS, Melisko ME, Wallace AM, Schwab R, Helsten T, Forero-Torres A, Stringer-Reasor E, Ellis ED, Kaplan HG, Nanda R, Jaskowiak N, Murthy R, Godellas C, Boughey JC, Elias AD, Haley BB, Kemmer K, Isaacs C, Clark AS, Lang JE, Lu J, Korde L, Edmiston KK, Northfelt DW, Viscusi RK, Yee D, Perlmutter J, Hylton NM, van’t Veer LJ, DeMichele A, Wilson A, Peterson G, Buxton MD, Paoloni M, Clennell J, Berry S, Matthews JB, Steeg K, Singhrao R, Hirst GL, Sanil A, Yau C, Asare SM, Berry DA, Esserman LJ, on behalf of I-SPY 2 Consortium

Purpose

The phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin is a key pathway of survival and therapeutic resistance in breast cancer. We evaluated the pan-Akt inhibitor MK-2206 in combination with standard therapy in patients with high-risk early-stage breast cancer.

Patients and Methods

I-SPY 2 is a multicenter, phase II, open-label, adaptively randomized neoadjuvant platform trial that screens experimental therapies and efficiently identifies potential predictive biomarker signatures. Patients are categorized by human epidermal growth factor receptor 2 (HER2), hormone receptor (HR), and MammaPrint statuses in a 2 × 2 × 2 layout. Patients within each of these 8 biomarker subtypes are adaptively randomly assigned to one of several experimental therapies, including MK-2206, or control. Therapies are evaluated for 10 biomarker signatures, each of which is a combination of these subtypes. The primary end point is pathologic complete response (pCR). A therapy graduates with one or more of these signatures if and when it has an 85% Bayesian predictive probability of success in a hypothetical phase III trial, adjusting for biomarker covariates. Patients in the current report received standard taxane- and anthracycline-based neoadjuvant therapy without (control) or with oral MK-2206 135 mg/week.

Results

MK-2206 graduated with 94 patients and 57 concurrently randomly assigned controls in 3 graduation signatures: HR-negative/HER2-positive, HR-negative, and HER2-positive. Respective Bayesian mean covariate-adjusted pCR rates and percentage probability that MK-2206 is superior to control were 0.48:0.29 (97%), 0.62:0.36 (99%), and 0.46:0.26 (94%). In exploratory analyses, MK-2206 evinced a numerical improvement in event-free survival in its graduating signatures. The most significant grade 3-4 toxicity was rash (14% maculopapular, 8.6% acneiform).

Conclusion

The Akt inhibitor MK-2206 combined with standard neoadjuvant therapy resulted in higher estimated pCR rates in HR-negative and HER2-positive breast cancer. Although MK-2206 is not being further developed at this time, this class of agents remains of clinical interest.

Scientific Reports 9:12114, 2019.

Prediction of Treatment Response to Neoadjuvant Chemotherapy for Breast Cancer via Early Changes in Tumor Heterogeneity Captured by DCE-MRI Registration

Jahani N, Cohen E, Hsieh M-K, Weinstein SP, Pantalone L, Hylton N, Newitt D, Davatzikos C, Kontos D
We analyzed DCE-MR images from 132 women with locally advanced breast cancer from the I-SPY1 trial to evaluate changes of intra-tumor heterogeneity for augmenting early prediction of pathologic complete response (pCR) and recurrence-free survival (RFS) after neoadjuvant chemotherapy (NAC). Utilizing image registration, voxel-wise changes including tumor deformations and changes in DCE-MRI kinetic features were computed to characterize heterogeneous changes within the tumor. Using five-fold cross-validation, logistic regression and Cox regression were performed to model pCR and RFS, respectively. The extracted imaging features were evaluated in augmenting established predictors, including functional tumor volume (FTV) and histopathologic and demographic factors, using the area under the curve (AUC) and the C-statistic as performance measures. The extracted voxel-wise features were also compared to analogous conventional aggregated features to evaluate the potential advantage of voxel-wise analysis. Voxel-wise features improved prediction of pCR (AUC = 0.78 (±0.03) vs 0.71 (±0.04), p< 0.05 and RFS (C-statistic = 0.76 ( ± 0.05), vs 0.63 ( ± 0.01)), p< 0.05, while models based on analogous aggregate imaging features did not show appreciable performance changes (p>0.05). Furthermore, all selected voxel-wise features demonstrated significant association with outcome (p< 0.05). Thus, precise measures of voxel-wise changes in tumor heterogeneity extracted from registered DCE-MRI scans can improve early prediction of neoadjuvant treatment outcomes in locally advanced breast cancer.

NPJ Breast Cancer 5:17, 2019.

A case report of vanishing bile duct syndrome after exposure to pexidartinib (PLX3397) and paclitaxel

Piawah S, Hyland C, Umetsu SE, Esserman LJ, Rugo HS, Chien AJ
Pexidartinib (PLX3397) is a small molecule tyrosine kinase and colony-stimulating factor-1 inhibitor with FDA breakthrough therapy designation for tenosynovial giant-cell tumor, and currently under study in several other tumor types, including breast cancer, non-Hodgkin’s lymphoma, and glioblastoma. Here, we report a case of severe drug-induced liver injury requiring liver transplantation due to vanishing bile duct syndrome (VBDS) after exposure to pexidartinib in the I-SPY 2 Trial, a phase 2 multicenter randomized neoadjuvant chemotherapy trial in patients with Stage II–III breast cancer. We also review the current literature on this rare, idiosyncratic, and potentially life-threatening entity.

J Magn Reson Imaging 50:1742-1753, 2019.

Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL

Li W, Newitt DC, Wilmes LJ, Jones EF, Arasu V, Gibbs J, La Yun B, Li E, Partridge SC, Kornak J; I-SPY 2 Consortium, Esserman LJ, Hylton NM

BACKGROUND:
The change in apparent diffusion coefficient (ADC) measured from diffusion-weighted imaging (DWI) has been shown to be predictive of pathologic complete response (pCR) for patients with locally invasive breast cancer undergoing neoadjuvant chemotherapy.

PURPOSE:
To investigate the additive value of tumor ADC in a multicenter clinical trial setting.

STUDY TYPE:
Retrospective analysis of multicenter prospective data.

POPULATION:
In all, 415 patients who enrolled in the I-SPY 2 TRIAL from 2010 to 2014 were included.

FIELD STRENGTH/SEQUENCE:
1.5T or 3T MRI system using a fat-suppressed single-shot echo planar imaging sequence with b-values of 0 and 800 s/mm2 for DWI, followed by a T1-weighted sequence for dynamic contrast-enhanced MRI (DCE-MRI) performed at pre-NAC (T0), after 3 weeks of NAC (T1), mid-NAC (T2), and post-NAC (T3).

ASSESSMENT:
Functional tumor volume and tumor ADC were measured at each MRI exam; pCR measured at surgery was assessed as the binary outcome. Breast cancer subtype was defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status.

STATISTICAL TESTS:
A logistic regression model was used to evaluate associations between MRI predictors with pCR. The cross-validated area under the curve (AUC) was calculated to assess the predictive performance of the model with and without ADC.

RESULTS:
In all, 354 patients (128 HR+/HER2-, 60 HR+/HER2+, 34 HR-/HER2+, 132 HR-/HER2-) were included in the analysis. In the full cohort, adding ADC predictors increased the AUC from 0.76 to 0.78 at mid-NAC and from 0.76 to 0.81 at post-NAC. In HR/HER2 subtypes, the AUC increased from 0.52 to 0.65 at pre-NAC for HR+/HER2-, from 0.67 to 0.73 at mid-NAC and from 0.72 to 0.76 at post-NAC for HR+/HER2+, from 0.71 to 0.81 at post-NAC for triple negatives.

DATA CONCLUSION:
The addition of ADC to standard functional tumor volume MRI showed improvement in the prediction of treatment response in HR+ and triple-negative breast cancer.

Radiol 291:546–546, 2019.

Diffusion-weighted MRI in Multicenter Trials of Breast Cancer

Partridge SC, Newitt DC, Chenevert TL, Rosen MA, Hylton NM, for the ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators

We greatly appreciated the insightful commentary by Dr Nandita M. deSouza (1) on our recent article reporting results of American College of Radiology Imaging Network (ACRIN) trial 6698, a multicenter trial investigating diffusion-weighted (DW) MRI for monitoring breast cancer response to therapy (2). Dr deSouza accurately described a number of important challenges and pitfalls of implementing DW MRI in multicenter trials and in utilizing the apparent diffusion coefficient (ADC) as an imaging biomarker to monitor therapy, in particular emphasizing the need for rigorous quality control and standardization measures (1).

Specifically, Dr deSouza stated: “The inclusion of test-retest studies in multicenter trials using quantitative imaging biomarkers is invaluable….The use of a test-retest approach in the I-SPY 2 trial would have confirmed the validity of the ADC changes….” and “The I-SPY 2 [Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2] trial has been a marathon multicenter undertaking….However, future trials must incorporate rigorous quality assurance, quality control, and reproducibility measures to both data acquisition and processing when treatment decisions are proposed based on interpretation of quantified parameter changes such as ADC.”

We heartily agree and would therefore like to respectfully point out that the ACRIN 6698 trial did in fact include a secondary aim to perform a test-retest ADC repeatability substudy. We regret that space limitations did not allow us to include this information along with the primary analysis in our article, and so Dr deSouza was not aware of the test-retest study at the time of her commentary. However, we have since published the ACRIN 6698 test-retest study results (3) and would like to make the readers aware of that additional information, which may be helpful for interpreting results of the study and in planning future trials incorporating quantitative breast DW imaging. In the ACRIN 6698 test-retest study, a coffee-break design was used to assess variability between repeat DW images, and both intra- and interreader agreement in tumor ADC quantitation were assessed. Overall, the results showed that excellent repeatability and reproducibility of breast tumor ADC measures could be achieved in a multi-institution setting using a standardized protocol and quality assurance procedure, but also supported the need for ongoing quality control methods to ensure consistent image quality and reduce data loss.

J Mag Res Imag 49:1617-1628, 2019.

Test–retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial

Newitt DC, Zheng Z, Gibbs JE, Partridge SC, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Aliu S, Li W, Cimino L,Joe BN, Umphrey H, Ojeda‐Fournier H, Dogan B, Oh K, Abe H, Drukteinis J, Esserman LJ, Hylton NM, for the ACRIN Trial Team and I‐SPY 2 TRIAL Investigators

Background: Quantitative diffusion‐weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker.

Purpose: To evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi‐institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures.

Study Type: Prospective.

Subjects: In all, 89 women from nine institutions undergoing neoadjuvant chemotherapy for invasive breast cancer.

Field Strength/Sequence: DWI was acquired before and after patient repositioning using a four b‐value, single‐shot echo‐planar sequence at 1.5T or 3.0T.

Assessment: A QA procedure by trained operators assessed artifacts, fat suppression, and signal‐to‐noise ratio, and determine study analyzability. Mean tumor ADC was measured via manual segmentation of the multislice tumor region referencing DWI and contrast‐enhanced images. Twenty cases were evaluated multiple times to assess intra‐ and interoperator variability. Segmentation similarity was assessed via the Sørenson–Dice similarity coefficient.

Statistical Tests: Repeatability and reproducibility were evaluated using within‐subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), agreement index (AI), and repeatability coefficient (RC). Correlations were measured by Pearson’s correlation coefficients.

Results: In all, 71 cases (80%) passed QA evaluation: 44 at 1.5T, 27 at 3.0T; 60 pretreatment, 11 after 3 weeks of taxane‐based treatment. ADC repeatability was excellent: wCV = 4.8% (95% confidence interval [CI] 4.0, 5.7%), ICC = 0.97 (95% CI 0.95, 0.98), AI = 0.83 (95% CI 0.76, 0.87), and RC = 0.16 * 10−3 mm2/sec (95% CI 0.13, 0.19). The results were similar across field strengths and timepoint subgroups. Reproducibility was excellent: interreader ICC = 0.92 (95% CI 0.80, 0.97) and intrareader ICC = 0.91 (95% CI 0.78, 0.96).

Data Conclusion: Breast tumor ADC can be measured with excellent repeatability and reproducibility in a multi‐institution setting using a standardized protocol and QA procedure. Improvements to DWI image quality could reduce loss of data in clinical trials.

Radiol 289:618-627, 2018.

Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial

Partridge SC, Zhang Z, Newitt DC, Gibbs JE, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Romanoff J, Cimino L, Joe BN, Umphrey HR, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis JS, Esserman LJ, Hylton NM for the ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators

Purpose: To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer.

Materials and Methods: In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment. Percentage change in tumor ADC from that before treatment (ΔADC) was measured at each time point. Performance for predicting pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype.

Results: The final analysis included 242 patients with evaluable serial imaging data, with a mean age of 48 years ± 10 (standard deviation); 99 patients had HR-positive (hereafter, HR+)/HER2-negative (hereafter, HER2-) disease, 77 patients had HR-/HER2- disease, 42 patients had HR+/HER2+ disease, and 24 patients had HR-/HER2+ disease. Eighty (33%) of 242 patients experienced pCR. Overall, ΔADC was moderately predictive of pCR at midtreatment/12 weeks (AUC = 0.60; 95% confidence interval [CI]: 0.52, 0.68; P = .017) and after treatment (AUC = 0.61; 95% CI: 0.52, 0.69;  P = .013). Across the four disease subtypes, midtreatment ΔADC was predictive only for HR+/HER2- tumors (AUC = 0.76; 95% CI: 0.62, 0.89; P < .001). In a test subset, a model combining tumor subtype and midtreatment ΔADC improved predictive performance (AUC = 0.72; 95% CI: 0.61, 0.83) over ΔADC alone (AUC = 0.57; 95% CI: 0.44, 0.70;  P = .032.).

Conclusion: After 12 weeks of therapy, change in breast tumor apparent diffusion coefficient at MRI predicts complete pathologic response to neoadjuvant chemotherapy.

NPJ Breast Cancer 4:26, 2018.

Surgical Standards for Management of the Axilla in Breast Cancer Clinical Trials with Pathological Complete Response Endpoint

Boughey JC, Alvarado MD, Lancaster RB, Fraser Symmans W, Mukhtar R, Wong JM, Ewing CA, Potter DA, Tuttle TM, Hieken TJ, Carter JM, Jakub JW, Kaplan HG, Buchanan CL, Jaskowiak NT, Sattar HA, Mueller J, Nanda R, Isaacs CJ, Pohlmann PR, Lynce F, Tousimis EA, Zeck JC, Lee MC, Lang JE, Mhawech-Fauceglia P, Rao R, Taback B, Chen M, Kalinsky KM, Hibshoosh H, Killelea B, Sanft T, Hirst GL, Asare S, Matthews JB, Perlmutter J, Esserman LJ; and I-SPY 2 Investigators

Advances in the surgical management of the axilla in patients treated with neoadjuvant chemotherapy, especially those with node positive disease at diagnosis, have led to changes in practice and more judicious use of axillary lymph node dissection that may minimize morbidity from surgery. However, there is still significant confusion about how to optimally manage the axilla, resulting in variation among practices. 

From the viewpoint of drug development, assessment of response to neoadjuvant chemotherapy remains paramount and appropriate assessment of residual disease-the primary endpoint of many drug therapy trials in the neoadjuvant setting-is critical. Therefore decreasing the variability, especially in a multicenter clinical trial setting, and establishing a minimum standard to ensure consistency in clinical trial data, without mandating axillary lymph node dissection, for all patients is necessary. 

The key elements, which include proper staging and identification of nodal involvement at diagnosis, and appropriately targeted management of the axilla at the time of surgical resection are presented. The following protocols have been adopted as standard procedure by the I-SPY2 trial for management of axilla in patients with node positive disease, and present a framework for prospective clinical trials and practice.

JCO Precision Oncology 2:1-20, 2018.

Evaluation of the HER/PI3K/AKT Family Signaling Network as a Predictive Biomarker of Pathologic Complete Response for Patients With Breast Cancer Treated With Neratinib in the I-SPY 2 TRIAL

Wulfkuhle JD, Yau C, Wolf DM, Vis DJ, Gallagher RI, Brown-Swigart L, Hirst G, Voest EE, DeMichele A, Hylton N, Symmans F, Yee D, Esserman L, Berry D, Liu M, Park JW, Wessels LFA, van’t Veer L, Petricoin EF

Purpose

In the I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2), the pan–erythroblastic oncogene B inhibitor neratinib was available to all hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) subtypes and graduated in the HR-negative/HER2-positive signature. We hypothesized that neratinib response may be predicted by baseline HER2 epidermal growth factor receptor (EGFR) signaling activation/phosphorylation levels independent of total levels of HER2 or EGFR proteins.

Materials and Methods

Complete experimental and response data were available for between 130 and 193 patients. In qualifying analyses, which used logistic regression and treatment interaction analysis, 18 protein/phosphoprotein, 10 mRNA, and 12 DNA biomarkers that related to HER family signaling were evaluated. Exploratory analyses used Wilcoxon rank sum and t tests without multiple comparison correction.

Results

HER pathway DNA biomarkers were either low prevalence or nonpredictive. In expression biomarker analysis, only one gene (STMN1) was specifically associated with response to neratinib in the HER2-negative subset. In qualifying protein/phosphoprotein analyses that used reverse phase protein microarrays, six HER family markers were associated with neratinib response. After analysis was adjusted for HR/HER2 status, EGFR Y1173 (pEGFR) showed a significant biomarker-by-treatment interaction (P = .049). Exploratory analysis of HER family signaling in patients with triple-negative (TN) disease found that activation of EGFR Y1173 (P = .005) and HER2 Y1248 (pHER2) (P = .019) were positively associated with pathologic complete response. Exploratory analysis in this pEGFR/pHER2–activated TN subgroup identified elevated levels of estrogen receptor α (P < .006) in these patients.

Conclusion

Activation of HER family phosphoproteins associates with response to neratinib, but only EGFR Y1173 and STMN1 appear to add value to the graduating signature. Activation of HER2 and EGFR in TN tumors may identify patients whose diseases respond to neratinib and implies that there is a subset of patients with TN disease who paradoxically exhibit HER family signaling activation and may achieve clinical benefit with neratinib; this concept must be validated in future studies.

Am J Roentgenol 210:1376-1385, 2018.

MRI, Clinical Examination, and Mammography for Preoperative Assessment of Residual Disease and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: ACRIN 6657 Trial

Scheel JR, Kim E, Partridge SC, Lehman CD, Rosen MA, Bernreuter WK, Pisano ED, Marques HS, Morris EA, Weatherall PT, Polin SM, Newstead GM, Esserman LJ, Schnall MD, Hylton NM; ACRIN 6657 Trial Team and I-SPY Investigators Network

OBJECTIVE: The objective of our study was to determine the accuracy of preoperative measurements for detecting pathologic complete response (CR) and assessing residual disease after neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer.

SUBJECTS AND METHODS: The American College of Radiology Imaging Network 6657 Trial prospectively enrolled women with ≥ 3 cm invasive breast cancer receiving NACT. Preoperative measurements of residual disease included longest diameter by mammography, MRI, and clinical examination and functional volume on MRI. The accuracy of preoperative measurements for detecting pathologic CR and the association with final pathology size were assessed for all lesions, separately for single masses and nonmass enhancements (NMEs), multiple masses, and lesions without ductal carcinoma in situ (DCIS).

RESULTS: In the 138 women with all four preoperative measures, longest diameter by MRI showed the highest accuracy for detecting pathologic CR for all lesions and NME (AUC = 0.76 and 0.84, respectively). There was little difference across preoperative measurements in the accuracy of detecting pathologic CR for single masses (AUC = 0.69-0.72). Longest diameter by MRI and longest diameter by clinical examination showed moderate ability for detecting pathologic CR for multiple masses (AUC = 0.78 and 0.74), and longest diameter by MRI and longest diameter by mammography showed moderate ability for detecting pathologic CR for tumors without DCIS (AUC = 0.74 and 0.71). In subjects with residual disease, longest diameter by MRI exhibited the strongest association with pathology size for all lesions and single masses (r = 0.33 and 0.47). Associations between preoperative measures and pathology results were not significantly influenced by tumor subtype or mammographic density.

CONCLUSION: Our results indicate that measurement of longest diameter by MRI is more accurate than by mammography and clinical examination for preoperative assessment of tumor residua after NACT and may improve surgical planning.

Cancer Imaging 18:12, 2018.

Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival “early on” in neoadjuvant treatment of breast cancer

Drukker K, Li H, Antropova N, Edwards A, Papaioannou J, Giger ML

Background: The hypothesis of this study was that MRI-based radiomics has the ability to predict recurrence-free survival “early on” in breast cancer neoadjuvant chemotherapy.

Methods: A subset, based on availability, of the ACRIN 6657 dynamic contrast-enhanced MR images was used in which we analyzed images of all women imaged at pre-treatment baseline (141 women: 40 with a recurrence, 101 without) and all those imaged after completion of the first cycle of chemotherapy, i.e., at early treatment (143 women: 37 with a recurrence vs. 105 without). Our method was completely automated apart from manual localization of the approximate tumor center. The most enhancing tumor volume (METV) was automatically calculated for the pre-treatment and early treatment exams. Performance of METV in the task of predicting a recurrence was evaluated using ROC analysis. The association of recurrence-free survival with METV was assessed using a Cox regression model controlling for patient age, race, and hormone receptor status and evaluated by C-statistics. Kaplan-Meier analysis was used to estimate survival functions.

Results: The C-statistics for the association of METV with recurrence-free survival were 0.69 with 95% confidence interval of [0.58; 0.80] at pre-treatment and 0.72 [0.60; 0.84] at early treatment. The hazard ratios calculated from Kaplan-Meier curves were 2.28 [1.08; 4.61], 3.43 [1.83; 6.75], and 4.81 [2.16; 10.72] for the lowest quartile, median quartile, and upper quartile cut-points for METV at early treatment, respectively.

Conclusion: The performance of the automatically-calculated METV rivaled that of a semi-manual model described for the ACRIN 6657 study (published C-statistic 0.72 [0.60; 0.84]), which involved the same dataset but required semi-manual delineation of the functional tumor volume (FTV) and knowledge of the pre-surgical residual cancer burden.

Breast Cancer Res 19:99, 2017.

The BRCA1 ness signature is associated significantly with response to PARP inhibitor treatment versus control in the I-SPY 2 randomized neoadjuvant setting

Severson TM, Wolf DM, Yau C, Peeters J, Wehkam D, Schouten PC, Chin S-F, Majewski IJ, Michaut M, Bosma A, Pereira B, Bismeijer T, Wessels L, Caldas C, Bernards R, Simon IM, Glas AM, Linn S, van t Veer L

Background: Patients with BRCA1-like tumors correlate with improved response to DNA double-strand break-inducing therapy. A gene expression-based classifier was developed to distinguish between BRCA1-like and non-BRCA1-like tumors. We hypothesized that these tumors may also be more sensitive to PARP inhibitors than standard treatments.

Methods: A diagnostic gene expression signature (BRCA1ness) was developed using a centroid model with 128 triple-negative breast cancer samples from the EU FP7 RATHER project. This BRCA1ness signature was then tested in HER2-negative patients (n = 116) from the I-SPY 2 TRIAL who received an oral PARP inhibitor veliparib in combination with carboplatin (V-C), or standard chemotherapy alone. We assessed the association between BRCA1ness and pathologic complete response in the V-C and control arms alone using Fisher’s exact test, and the relative performance between arms (biomarker × treatment interaction, likelihood ratio p < 0.05) using a logistic model and adjusting for hormone receptor status (HR).

Results: We developed a gene expression signature to identify BRCA1-like status. In the I-SPY 2 neoadjuvant setting the BRCA1ness signature associated significantly with response to V-C (p = 0.03), but not in the control arm (p = 0.45). We identified a significant interaction between BRCA1ness and V-C (p = 0.023) after correcting for HR.

Conclusions: A genomic-based BRCA1-like signature was successfully translated to an expression-based signature (BRC1Aness). In the I-SPY 2 neoadjuvant setting, we determined that the BRCA1ness signature is capable of predicting benefit of V-C added to standard chemotherapy compared to standard chemotherapy alone.

Trial registration: I-SPY 2 TRIAL beginning December 31, 2009: Neoadjuvant and Personalized Adaptive Novel Agents to Treat Breast Cancer (I-SPY 2), NCT01042379.

NPJ Breast Cancer 3:, 2017.

DNA repair deficiency biomarkers and the 70-gene ultra-high risk signature as predictors of veliparib/carboplatin response in the I-SPY 2 breast cancer trial

Wolf DM, Yau C, Sanil A, Glas A, Petricoin E, Wulfkuhle J, Severson TM, Linn S, Brown-Swigart L, Hirst G, Buxton M, DeMichele A, Hylton N, Symmans F, Yee D, Paoloni M, Esserman L, Berry D, Rugo H, Olopade O, van t Veer L

Veliparib combined with carboplatin (VC) was an experimental regimen evaluated in the biomarker-rich neoadjuvant I-SPY 2 trial for breast cancer. VC showed improved efficacy in the triple negative signature. However, not all triple negative patients achieved pathologic complete response and some HR+HER2- patients responded. 

Pre-specified analysis of five DNA repair deficiency biomarkers (BRCA1/2 germline mutation; PARPi-7, BRCA1ness, and CIN70 expression signatures; and PARP1 protein) was performed on 116 HER2- patients (VC: 72 and concurrent controls: 44). We also evaluated the 70-gene ultra-high risk signature (MP1/2), one of the biomarkers used to define subtype in the trial. We used logistic modeling to assess biomarker performance. Successful biomarkers were combined using a simple voting scheme to refine the ‘predicted sensitive’ group and Bayesian modeling used to estimate the pathologic complete response rates. 

BRCA1/2 germline mutation status associated with VC response, but its low prevalence precluded further evaluation. PARPi-7, BRCA1ness, and MP1/2 specifically associated with response in the VC arm but not the control arm. Neither CIN70 nor PARP1 protein specifically predicted VC response. When we combined the PARPi-7 and MP1/2 classifications, the 42% of triple negative patients who were PARPi7-high and MP2 had an estimated pCR rate of 75% in the VC arm. Only 11% of HR+/HER2- patients were PARPi7-high and MP2; but these patients were also more responsive to VC with estimated pathologic complete response rates of 41%. PARPi-7, 

BRCA1ness and MP1/2 signatures may help refine predictions of VC response, thereby improving patient care.

Breast Cancer Res Treat 165:181-191, 2017.

Comparison of residual cancer burden, American Joint Committee on Cancer staging and pathologic complete response in breast cancer after neoadjuvant chemotherapy: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657).

Campbell JI, Yau C, Krass P, Moore D, Carey LA, Au A, Chhieng D, Giri D, Livasy C, Mies C, Rabban J, Sarode VR, Singh B, Esserman L, Chen Y-Y
PURPOSE: Several pathologic staging systems characterize residual tumor in patients undergoing neoadjuvant chemotherapy for breast cancer. Pathologic complete response (pCR) is now accepted by the Food and Drug Administration as an endpoint for granting accelerated drug approval. Two other systems of post-neoadjuvant pathologic tumor staging-residual cancer burden (RCB) and the American Joint Committee on Cancer post-neoadjuvant therapy staging system (yAJCC)-have been developed to characterize residual tumors when patients do not achieve pCR. The optimal system and the ways in which these systems complement each other have not been fully determined.
 
METHODS: Using data from the I-SPY 1 TRIAL, we compared pCR, RCB, and yAJCC as predictors of early recurrence-free survival (RFS) to identify ways to improve post-neoadjuvant pathologic evaluation.
 
RESULTS: Among 162 patients assessed, pCR identified patients at lowest risk of recurrence, while RCB and yAJCC identified patients at highest risk. Hormone-receptor (HR) and HER2 subtypes further improved risk prediction. Recursive partitioning indicated that triple-negative or HER2+ patients with yAJCC III or RCB 3 have the highest recurrence risk, with an RFS of 27%. Our analysis also highlighted discrepancies between RCB and yAJCC stratification: 31% of patients had discrepant RCB and yAJCC scores. We identified differential treatment of lymph node involvement and tumor cellularity as drivers of these discrepancies.
 
CONCLUSIONS: These data indicate that there is benefit to reporting both RCB and yAJCC for patients in order to identify those at highest risk of relapse.

Breast Cancer Res Treat 165:129-138, 2017.

Receptor activator of nuclear factor kappa B (RANK) expression in primary breast cancer correlates with recurrence-free survival and development of bone metastases in I-SPY1 (CALGB 150007/150012; ACRIN 6657)

Vidula N, Yau C, Li J, Esserman LJ, Rugo HS

Purpose: Image registration plays a vital role in spatially aligning multiple MRI scans for better longitudinal assessment of tumor morphological features. The objective was to evaluate the effect of registration accuracy of six established deformable registration methods(ANTs, DRAMMS, ART, NiftyReg, SSD-FFD, and NMI-FFD) on the predictive value of extracted radiomic features when modeling recurrence-free-survival(RFS) for women after neoadjuvant chemotherapy(NAC) for locally advanced breast cancer.

Methods: 130 women had DCE-MRI scans available from the first two visits in the ISPY1/ACRIN-6657 cohort. We calculated the transformation field from each of the different deformable registration methods, and used it to compute voxel-wise parametric-response-maps(PRM) for established four kinetic features.104-radiomic features were computed from each PRM map to characterize intra-tumor heterogeneity. We evaluated performance for RFS using Cox-regression, C-statistic, and Kaplan-Meier(KM) plots.

Results: A baseline model(F1:Age, Race, and Hormone-receptor-status) had a 0.54 C-statistic, and model F2(baseline + functional-tumor-volume at early treatment visit(FTV2)) had 0.63. The F2+ANTs had the highest C-statistic(0.72) with the smallest landmark differences(5.40±4.40mm) as compared to other models. The KM curve for model F2 gave p=0.004 for separation between women above and below the median hazard compared to the model F1(p=0.31). A models augmented with radiomic features, also achieved significant KM curve separation(p<0.001) except the F2+ART model.

Conclusion: Incorporating image registration in quantifying changes in tumor heterogeneity during NAC can improve prediction of RFS. Radiomic features of PRM maps derived from warping the DCE-MRI kinetic maps using ANTs registration method further improved the early prediction of RFS as compared to other methods.

Clin Breast Cancer 17:e155–e159, 2017.

Dedicated Breast Positron Emission Tomography for the Evaluation of Early Response to Neoadjuvant Chemotherapy in Breast Cancer

Jones EF, Ray KM, Li W, Seo Y, Franc BL, Chien AJ, Esserman LJ, Pampaloni MH, Joe BN, Hylton NM

Neoadjuvant chemotherapy provides an opportunity to assess tumor response to targeted therapies in vivo, and imaging plays a critical role in assessing the effectiveness of such therapies.

Currently no clinical standard exists for evaluating response to neoadjuvant chemotherapy, although positron emission tomography (PET) and contrast enhanced magnetic resonance imaging (MRI) are promising candidate technologies.

Positron emission tomography with fluorodeoxyglucose provides information about tumor metabolism that can powerfully predict treatment response early in the course of therapy, before anatomic changes become evident on MRI scans.

The recent development of a high-resolution, breast specific PET imaging system allows more detailed characterization of the primary breast tumor than conventional whole body PET systems.

We report on the usage of dedicated breast PET to provide early assessment of treatment response in a patient with bilateral synchronous breast cancers.

J Mag Res Imaging 46:290-302, 2017.

MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial

Bolan PJ, Kim E, Herman BA, Newstead GM, Rosen MA, Schnall MD, Pisano ED, Weatherall PT, Morris EA, Lehman CD, Garwood M, Nelson MT, Yee D, Polin SM, Esserman LJ, Gatsonis CA, Metzger GJ, Newitt DC, Partridge SC, Hylton NM, for the ACRIN Trial team ISPY‐1 Investigators

Purpose: To estimate the accuracy of predicting response to neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer using MR spectroscopy (MRS) measurements made very early in treatment.

Materials and Methods: This prospective Health Insurance Portability and Accountability Act (HIPAA)–compliant protocol was approved by the American College of Radiology and local-site institutional review boards. One hundred nineteen women with invasive breast cancer of ≥3 cm undergoing NACT were enrolled between September 2007 and April 2010. MRS measurements of the concentration of choline-containing compounds ([tCho]) were performed before the first chemotherapy regimen (time point 1, TP1) and 20–96 h after the first cycle of treatment (TP2). The change in [tCho] was assessed for its ability to predict pathologic complete response (pCR) and radiologic response using the area under the receiver operating characteristic curve (AUC) and logistic regression models.

Results: Of the 119 subjects enrolled, only 29 cases (24%) with eight pCRs provided usable data for the primary analysis. Technical challenges in acquiring quantitative MRS data in a multi-site trial setting limited the capture of usable data. In this limited data set, the decrease in tCho from TP1 to TP2 had poor ability to predict either pCR (AUC = 0.53, 95% confidence interval [CI]: 0.27–0.79) or radiologic response (AUC = 0.51, 95% CI: 0.27–0.75).

Conclusion: The technical difficulty of acquiring quantitative MRS data in a multi-site clinical trial setting led to a low yield of analyzable data, which was insufficient to accurately measure the ability of early MRS measurements to predict response to NACT.

Tomography 2:378-387, 2016.

Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL.

Li W, Arasu V, Newitt DC, Jones EF, Wilmes L, Gibbs J, Kornak J, Joe BN, Esserman LJ, Hylton NM, ACRIN 6657 Trial Team and I-SPY Investigators Network

Functional tumor volume (FTV) measurements by dynamic contrast-enhanced magnetic resonance imaging can predict treatment outcomes for women receiving neoadjuvant chemotherapy for breast cancer. Here, we explore whether the contrast thresholds used to define FTV could be adjusted by breast cancer subtype to improve predictive performance. Absolute FTV and percent change in FTV (ΔFTV) at sequential time-points during treatment were calculated and investigated as predictors of pathologic complete response at surgery. Early percent enhancement threshold (PEt) and signal enhancement ratio threshold (SERt) were varied. The predictive performance of resulting FTV predictors was evaluated using the area under the receiver operating characteristic curve. A total number of 116 patients were studied both as a full cohort and in the following groups defined by hormone receptor (HR) and HER2 receptor subtype: 45 HR+/HER2-, 39 HER2+, and 30 triple negatives. High AUCs were found at different ranges of PEt and SERt levels in different subtypes. Findings from this study suggest that the predictive performance to treatment response by MRI varies by contrast thresholds, and that pathologic complete response prediction may be improved through subtype-specific contrast enhancement thresholds. A validation study is underway with a larger patient population.

New Engl J Med 375:23-34, 2016.

Adaptive randomization of veliparib-carboplatin treatment in breast cancer

Rugo HS, Olopade OI, DeMichele A, Yau C, van t Veer LJ, Buxton MB, Hogarth M, Hylton NM, Paoloni M, Perlmutter J, Symmans WF, Yee D, Chien AJ, Wallace AM, Kaplan HG, Boughey JC, Haddad TC, Albain KS, Liu MC, Isaacs C, Khan QJ, Lang JE, Viscusi RK, Pusztai L, Moulder SL, Chui SY, Kemmer KA, Elias AD, Edmiston KK, Euhus DM, Haley BB, Nanda R, Northfelt DW, Tripathy D, Wood WC, Ewing C, Schwab R, Lyandres J, Davis SE, Hirst GL, Sanil A, Berry DA, Esserman LJ for the I-SPY Investigators

BACKGROUND

The genetic and clinical heterogeneity of breast cancer makes the identification of effective therapies challenging. We designed I-SPY 2, a phase 2, multicenter, adaptively randomized trial to screen multiple experimental regimens in combination with standard neoadjuvant chemotherapy for breast cancer. The goal is to match ex- perimental regimens with responding cancer subtypes. We report results for veli- parib, a poly(ADP-ribose) polymerase (PARP) inhibitor, combined with carboplatin.

METHODS

In this ongoing trial, women are eligible for participation if they have stage II or III breast cancer with a tumor 2.5 cm or larger in diameter; cancers are categorized into eight biomarker subtypes on the basis of status with regard to human epidermal growth factor receptor 2 (HER2), hormone receptors, and a 70-gene assay. Patients undergo adaptive randomization within each biomarker subtype to receive regimens that have better performance than the standard therapy. Regimens are evaluated within 10 biomarker signatures (i.e., prospectively defined combinations of bio- marker subtypes).

Veliparib–carboplatin plus standard therapy was considered for HER2-negative tumors and was therefore evaluated in 3 signatures. The primary end point is pathological complete response. Tumor volume changes measured by mag- netic resonance imaging during treatment are used to predict whether a patient will have a pathological complete response. Regimens move on from phase 2 if and when they have a high Bayesian predictive probability of success in a subsequent phase 3 neoadjuvant trial within the biomarker signature in which they performed well.

RESULTS

With regard to triple-negative breast cancer, veliparib–carboplatin had an 88% pre- dicted probability of success in a phase 3 trial. A total of 72 patients were random- ly assigned to receive veliparib–carboplatin, and 44 patients were concurrently as- signed to receive control therapy; at the completion of chemotherapy, the estimated rates of pathological complete response in the triple-negative population were 51% (95% Bayesian probability interval [PI], 36 to 66%) in the veliparib–carboplatin group versus 26% (95% PI, 9 to 43%) in the control group. The toxicity of veliparib– carboplatin was greater than that of the control.

CONCLUSIONS

The process used in our trial showed that veliparib–carboplatin added to standard therapy resulted in higher rates of pathological complete response than standard therapy alone specifically in triple-negative breast cancer. (Funded by the QuantumLeap Health- care Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379.)

N Engl J Med 375:11-22, 2016.

Adaptive Randomization of Neratinib in Early Breast Cancer

Park JW, Liu MC, Yee D, Yau C, van t Veer LJ, Symmans WF, Paoloni M, Perlmutter J, Hylton NM, Hogarth M, DeMichele A, Buxton MB, Chien AJ, Wallace AM, Boughey JC, Haddad TC, Chui SY, Kemmer KA, Kaplan HG, Isaacs C, Nanda R, Tripathy D, Albain KS, Edmiston KK, Elias AD, Northfelt DW, Pusztai L, Moulder SL, Lang JE, Viscusi RK, Euhus DM, Haley BB, Khan QJ, Wood WC, Melisko M, Schwab R, Helsten T, Lyandres J, Davis SE, Hirst GL, Sanil A, Esserman LJ, Berry DA, I-SPY 2 Investigators

BACKGROUND: The heterogeneity of breast cancer makes identifying effective therapies challenging. The I-SPY 2 trial, a multicenter, adaptive phase 2 trial of neoadjuvant therapy for high-risk clinical stage II or III breast cancer, evaluated multiple new agents added to standard chemotherapy to assess the effects on rates of pathological complete response (i.e., absence of residual cancer in the breast or lymph nodes at the time of surgery).

METHODS: We used adaptive randomization to compare standard neoadjuvant chemotherapy plus the tyrosine kinase inhibitor neratinib with control. Eligible women were categorized according to eight biomarker subtypes on the basis of human epidermal growth factor receptor 2 (HER2) status, hormone-receptor status, and risk according to a 70-gene profile. Neratinib was evaluated against control with regard to 10 biomarker signatures (prospectively defined combinations of subtypes). The primary end point was pathological complete response. Volume changes on serial magnetic resonance imaging were used to assess the likelihood of such a response in each patient. Adaptive assignment to experimental groups within each disease subtype was based on Bayesian probabilities of the superiority of the treatment over control. Enrollment in the experimental group was stopped when the 85% Bayesian predictive probability of success in a confirmatory phase 3 trial of neoadjuvant therapy reached a prespecified threshold for any biomarker signature (“graduation”). Enrollment was stopped for futility if the probability fell to below 10% for every biomarker signature.

RESULTS: Neratinib reached the prespecified efficacy threshold with regard to the HER2-positive, hormone-receptor-negative signature. Among patients with HER2-positive, hormone-receptor-negative cancer, the mean estimated rate of pathological complete response was 56% (95% Bayesian probability interval [PI], 37 to 73%) among 115 patients in the neratinib group, as compared with 33% among 78 controls (95% PI, 11 to 54%). The final predictive probability of success in phase 3 testing was 79%.

CONCLUSIONS: Neratinib added to standard therapy was highly likely to result in higher rates of pathological complete response than standard chemotherapy with trastuzumab among patients with HER2-positive, hormone-receptor-negative breast cancer. (Funded by QuantumLeap Healthcare Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379).

Radiol 279:44–55, 2016.

Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival—Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL

Hylton NM, Gatsonis CA, Rosen MA, Lehman CD, Newitt DC, Partridge SC, Bernreuter WK, Pisano ED, Morris EA, Weatherall PT, Polin SM, Newstead GM, Marques HS, Esserman LJ, Schnall MD, For the ACRIN 6657 Trial Team and I-SPY 1 TRIAL Investigators

Background: The hypothesis of this study was that MRI-based radiomics has the ability to predict recurrence-free survival “early on” in breast cancer neoadjuvant chemotherapy.

Methods: A subset, based on availability, of the ACRIN 6657 dynamic contrast-enhanced MR images was used in which we analyzed images of all women imaged at pre-treatment baseline (141 women: 40 with a recurrence, 101 without) and all those imaged after completion of the first cycle of chemotherapy, i.e., at early treatment (143 women: 37 with a recurrence vs. 105 without). Our method was completely automated apart from manual localization of the approximate tumor center. The most enhancing tumor volume (METV) was automatically calculated for the pre-treatment and early treatment exams. Performance of METV in the task of predicting a recurrence was evaluated using ROC analysis. The association of recurrence-free survival with METV was assessed using a Cox regression model controlling for patient age, race, and hormone receptor status and evaluated by C-statistics. Kaplan-Meier analysis was used to estimate survival functions.

Results: The C-statistics for the association of METV with recurrence-free survival were 0.69 with 95% confidence interval of [0.58; 0.80] at pre-treatment and 0.72 [0.60; 0.84] at early treatment. The hazard ratios calculated from Kaplan-Meier curves were 2.28 [1.08; 4.61], 3.43 [1.83; 6.75], and 4.81 [2.16; 10.72] for the lowest quartile, median quartile, and upper quartile cut-points for METV at early treatment, respectively.

Conclusion: The performance of the automatically-calculated METV rivaled that of a semi-manual model described for the ACRIN 6657 study (published C-statistic 0.72 [0.60; 0.84]), which involved the same dataset but required semi-manual delineation of the functional tumor volume (FTV) and knowledge of the pre-surgical residual cancer burden.

Breast Cancer Res 17:73, 2015.

Serial expression analysis of breast tumors during neoadjuvant chemotherapy reveals changes in cell cycle and immune pathways associated with recurrence and response

Magbanua MJM, Wolf DM, Yau C, Davis SE, Crothers J, Au A, Haqq CM, Livasy C, Rugo HS, Esserman L, Park JW, van t Veer LJ

The molecular biology involving neoadjuvant chemotherapy (NAC) response is poorly understood. To elucidate the impact of NAC on the breast cancer transcriptome and its association with clinical outcome, we analyzed gene expression data derived from serial tumor samples of patients with breast cancer who received NAC in the I-SPY 1 TRIAL. Expression data were collected before treatment (T1), 24–96 hours after initiation of chemotherapy (T2) and at surgery (TS). Expression levels between T1 and T2 (T1 vs. T2; n = 36) and between T1 and TS (T1 vs. TS; n = 39) were compared. Subtype was assigned using the PAM50 gene signature. Differences in early gene expression changes (T2 − T1) between responders and nonresponders, as defined by residual cancer burden, were evaluated. Cox proportional hazards modeling was used to identify genes in residual tumors associated with recurrence-free survival (RFS). Pathway analysis was performed with Ingenuity software. When we compared expression profiles at T1 vs. T2 and at T1 vs. TS, we detected significantly altered expression of 150 and 59 transcripts, respectively. We observed notable downregulation of proliferation and immune-related genes at T2. Lower concordance in subtype assignment was observed between T1 and TS (62 %) than between T1 and T2 (75 %). Analysis of early gene expression changes (T2 − T1) revealed that decreased expression of cell cycle inhibitors was associated with poor response. Increased interferon signaling (TS − T1) and high expression of cell proliferation genes in residual tumors (TS) were associated with reduced RFS. Serial gene expression analysis revealed candidate immune and proliferation pathways associated with response and recurrence. Larger studies incorporating the approach described here are warranted to identify predictive and prognostic biomarkers in the NAC setting for specific targeted therapies. ClinicalTrials.gov identifier: NCT00033397 . Registered 9 Apr 2002.

Clinical Cancer Research 21:2911-2915, 2015.

The Neoadjuvant Model Is Still the Future for Drug Development in Breast Cancer

DeMichele A, Yee D, Berry DA, Albain KS, Benz CC, Boughey J, Buxton M, Chia SK, Chien AJ, Chui SY, Clark A, Edmiston K, Elias AD, Forero-Torres A, Haddad TC, Haley B, Haluska P, Hylton NM, Isaacs C, Kaplan H, Korde L, Leyland-Jones B, Liu MC, Melisko M, Minton SE, Moulder SL, Nanda R, Olopade OI, Paoloni M, Park JW, Parker BA, Perlmutter J, Petricoin EF, Rugo H, Symmans F, Tripathy D, van’t Veer LJ, Viscusi RK, Wallace A, Wolf D, Yau C, Esserman LJ

The many improvements in breast cancer therapy in recent years have so lowered rates of recurrence that it is now difficult or impossible to conduct adequately powered adjuvant clinical trials. Given the many new drugs and potential synergistic combinations, the neoadjuvant approach has been used to test benefit of drug combinations in clinical trials of primary breast cancer. A recent FDA-led meta-analysis showed that pathologic complete response (pCR) predicts disease-free survival (DFS) within patients who have specific breast cancer subtypes. This meta-analysis motivated the FDA’s draft guidance for using pCR as a surrogate endpoint in accelerated drug approval. Using pCR as a registration endpoint was challenged at ASCO 2014 Annual Meeting with the presentation of ALTTO, an adjuvant trial in HER2-positive breast cancer that showed a nonsignificant reduction in DFS hazard rate for adding lapatinib, a HER-family tyrosine kinase inhibitor, to trastuzumab and chemotherapy. This conclusion seemed to be inconsistent with the results of NeoALTTO, a neoadjuvant trial that found a statistical improvement in pCR rate for the identical lapatinib-containing regimen. We address differences in the two trials that may account for discordant conclusions. However, we use the FDA meta-analysis to show that there is no discordance at all between the observed pCR difference in NeoALTTO and the observed HR in ALTTO. This underscores the importance of appropriately modeling the two endpoints when designing clinical trials. The I-SPY 2/3 neoadjuvant trials exemplify this approach. Clin Cancer Res; 21(13); 2911-5. ©2015 AACR.

World J Clinical Cases 3:607-613, 2015.

How to use magnetic resonance imaging following neoadjuvant chemotherapy in locally advanced breast cancer

Price ER, Wong J, Mukhtar R, Hylton N, Esserman LJ

Magnetic resonance imaging (MRI) is highly sensitive in identifying residual breast cancer following neoadjuvant chemotherapy (NAC), and consequently is a commonly used imaging modality in locally advanced breast cancer patients. In these patients, tumor response is an important prognostic indicator. However, discrepancies between MRI findings and surgical pathology are well documented. Overestimation of residual disease by MRI may result in greater surgery than is actually required while underestimation may result in insufficient surgery. Thus, it is important to understand when MRI findings are reliable and when they are less accurate. MRI most accurately predicts pathology in triple negative, Her2 positive and hormone receptor negative tumors, especially if they are of a solid imaging phenotype. In these cases, post-NAC MRI is highly reliable for surgical planning. Hormone receptor positive cancers and those demonstrating non mass enhancement show lower concordance with surgical pathology, making surgical guidance more nebulous in these cases. Radiologists and surgeons must assess MRI response to NAC in the context of tumor subtype. Indiscriminate interpretations will prevent MRI from achieving its maximum potential in the pre-operative setting.

Cancer Medicine 3:693-701, 2014.

Pretreatment vitamin D level and response to neoadjuvant chemotherapy in women with breast cancer on the I‐SPY trial (CALGB 150007/150015/ACRIN6657)

Clark AS, Chen J, Kapoor S, Friedman C, Mies C, Esserman L, DeMichele A, I-SPY 1 TRIAL Investigators

Laboratory studies suggest that vitamin D (vitD) enhances chemotherapy- induced cell death. The objective of this study was to determine whether pretreatment vitD levels were associated with response to neoadjuvant chemo- therapy (NACT) in women with breast cancer. Study patients (n = 82) were enrolled on the I-SPY TRIAL, had HER2-negative tumors, and available pre- treatment serum. VitD levels were measured via DiaSorin radioimmunoassay. The primary outcome was pathologic residual cancer burden (RCB; dichoto- mized 0/1 vs. 2/3). Secondary outcomes included biomarkers of proliferation, differentiation, and apoptosis (Ki67, grade, Bcl2, respectively) and 3-year relapse-free survival (RFS). Mean and median vitD values were 22.7 ng/mL (SD 11.9) and 23.1 ng/mL, respectively; 72% of patients had levels deemed “insufficient” (<30 ng/mL) by the Institute of Medicine (IOM). VitD level was not associated with attaining RCB 0/1 after NACT (univariate odds ratio [OR], 1.01; 95% CI, 0.96–1.05) even after adjustment for hormone receptor status (HR), grade, Ki67, or body mass index (BMI). Lower vitD levels were associ- ated with higher tumor Ki67 adjusting for race (OR, 0.95; 95% CI, 0.90–0.99). VitD level was not associated with 3-year RFS, either alone (hazard ratio [HzR], 0.98; 95% CI, 0.95–1.02) or after adjustment for HR, grade, Ki-67, BMI, or response. VitD insufficiency was common at the time of breast cancer diag- nosis among women who were candidates for NACT and was associated with a more proliferative phenotype. However, vitD levels had no impact on tumor response to NACT or short-term prognosis.

Translat Oncol 7:94-100, 2014.

Real-Time Measurement of Functional Tumor Volume by MRI to Assess Treatment Response in Breast Cancer Neoadjuvant Clinical Trials: Validation of the Aegis SER Software Platform

Newitt DC, Aliu SO, Witcomb N, Sela G, Kornak J, Esserman L, Hylton NM

PURPOSE: To evaluate the Aegis software implementation for real-time calculation of functional tumor volume (FTV) in the neoadjuvant breast cancer treatment trial setting.

METHODS: The validation data set consisted of 689 contrast-enhanced magnetic resonance imaging (MRI) examinations from the multicenter American College of Radiology Imaging Network 6657 study. Subjects had stage III tumors ≥3 cm in diameter and underwent MRI before, during, after receiving anthracycline-cyclophosphamide chemotherapy. Studies were previously analyzed by the University of California San Francisco core laboratory using the three-timepoint signal enhancement ratio (SER) FTV algorithm; FTV measurement was subsequently implemented on the Hologic (formerly Sentinelle Medical Inc) Aegis platform. All cases were processed using predefined volumes of interest with no user interaction. Spearman rank correlation was evaluated for all study sites and visits. Cox proportional hazards analysis was used to compare predictive performance of the platforms for recurrence-free survival (RFS) time.

RESULTS: Overall agreement between platforms was good; ρ varied from 0.96 to 0.98 for different study visits. Site-by-site analysis showed considerable variation, from ρ = 0.54 to near perfect agreement (ρ = 1.000) for several sites. Mean absolute difference between platforms ranged from 1.67 cm3 pretreatment to 0.2 cm3 posttreatment. The two platforms showed essentially identical performance for predicting RFS using pretreatment or posttreatment FTV.

CONCLUSION: Implementation of the SER FTV algorithm on a commercial platform for real-time MRI volume assessments showed very good agreement with the reference core laboratory system, but variations by site and outlier analysis point out sensitivities to implementation-specific differences.

Ann Surg Oncol 21:2889-2896, 2014.

Local Recurrence Rates are Low in High-Risk Neoadjuvant Breast Cancer in the I-SPY 1 Trial (CALGB 150007/150012; ACRIN 6657)

Cureton EL, Yau C, Alvarado MD, Krontiras H, Ollila DW, Ewing CA, Monnier S, Esserman LJ

Background. Increasingly, women with stage 2 and 3 breast cancers receive neoadjuvant therapy, after which many are eligible for breast-conserving surgery (BCS). The question often arises as to whether BCS, if achievable, provides adequate local control. We report the results of local recurrence (LR) from the I-SPY 1 Trial in the setting of maximal multidisciplinary treatment where approxi- mately 50 % of patients were treated with BCS.

Methods. We analyzed data from the I-SPY 1 Trial. Women with tumors C3 cm from nine clinical breast centers received neoadjuvant doxorubicin, cyclophospha- mide and paclitaxel followed by definitive surgical therapy, and radiation at physician discretion. LR following mas- tectomy and BCS were analyzed in relation to clinical characteristics and response to therapy as measured by residual cancer burden.

Results. Of the 237 patients enrolled in the I-SPY 1 Trial, 206 were available for analysis. Median tumor size was 6.0 cm, and median follow-up was 3.9 years. Fourteen patients (7 %) had LR and 45 (22 %) had distant recur- rence (DR). Of the 14 patients with LR, nine had synchronous DR; one had DR [ 2 years later. Only four (2 % of evaluable patients) had LR alone. The rate of LR was low after mastectomy and after BCS, even in the setting of significant residual disease.

Conclusions. Overall, these patients at high risk for early recurrence, treated with maximal multidisciplinary treat- ment, had low LR. Recurrence was associated with aggressive biological features such as more advanced stage at presentation, where LR occurs most frequently in the setting of DR.

Cancer Cell 24:30-44, 2013.

Par-4 Downregulation Promotes Breast Cancer Recurrence by Preventing Multinucleation following Targeted Therapy

Alvarez JV, Pan T-C, Ruth J, Feng Y, Zhou A, Pant D, Grimley JS, Wandless TJ, DeMichele A, I-SPY 1 TRIAL Investigators, Chodosh LA

Summary

Most deaths from breast cancer result from tumor recurrence, but mechanisms underlying tumor relapse are largely unknown. We now report that Par-4 is downregulated during tumor recurrence and that Par-4 downregulation is necessary and sufficient to promote recurrence. Tumor cells with low Par-4 expression survive therapy by evading a program of Par-4-dependent multinucleation and apoptosis that is otherwise engaged following treatment. Low Par-4 expression is associated with poor response to neoadjuvant chemotherapy and an increased risk of relapse in patients with breast cancer, and Par-4 is downregulated in residual tumor cells that survive neoadjuvant chemotherapy. Our findings identify Par-4-induced multinucleation as a mechanism of cell death in oncogene-addicted cells and establish Par-4 as a negative regulator of breast cancer recurrence.

Significance

Recurrent breast cancer is typically an incurable disease. Consequently, the propensity of breast cancers to recur following surgery, radiation, and adjuvant therapy is the most important determinant of clinical outcome. Residual neoplastic cells that persist following treatment constitute the reservoir from which recurrent tumors arise and are a major obstacle to the successful treatment of human cancers. Accordingly, understanding the mechanisms by which residual tumor cells survive treatment is a critical research priority. Our findings establish downregulation of the tumor suppressor Par-4 in mice and in women as a mechanism of tumor cell survival and recurrence following targeted therapy and chemotherapy. As such, therapies that target pathways repressed by Par-4—or that restore Par-4 expression—may hold significant clinical promise.

Ann Surg Oncol 20:3823-3830, 2013.

Clinically Meaningful Tumor Reduction Rates Vary by Prechemotherapy MRI Phenotype and Tumor Subtype in the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657)

Mukhtar RA, Yau C, Rosen M, Tandon VJ, I-SPY Trial and ACRIN 6657 Investigastors, Hylton N, Esserman LJ

Purpose. This study was designed to determine (1) rates of clinically meaningful tumor reduction in breast tumor size following neoadjuvant chemotherapy (NAC), (2) which receptor subtypes and MRI phenotypes are associ- ated with clinically meaningful tumor reduction, and (3) whether MRI phenotype impacts concordance between pathologic and MRI size.

Methods. We analyzed data from the I-SPY TRIAL, a multicenter, prospective NAC trial. Reduction in tumor size from [4 to B4 cm was considered clinically mean- ingful, as crossing this threshold was considered a reasonable cutoff for potential breast conservation therapy (BCT). MRI phenotypes were scored between one (well- defined) and five (diffuse) on pre-NAC MRIs.

Results. Of 174 patients with tumors [4 cm, 141 (81 %) had clinically meaningful tumor reduction. Response to therapy varied by MRI phenotype (p = 0.003), with well- defined phenotypes more likely than diffuse phenotypes to have clinically meaningful tumor shrinkage (91 vs. 72 %, p = 0.037). Her2? and triple-negative (Tneg) tumors had the highest rate of clinically meaningful tumor reduction (p = 0.005). The concordance between tumor diameter on MRI and surgical pathology was highest for Her2? and Tneg tumors, especially among tumors with solid imaging phenotypes (p = 0.004).

Discussion. NAC allows most patients with large breast tumors to have clinically meaningful tumor reduction, meaning response that would impact ability to undergo BCT. However, response varies by imaging and tumor subtypes. Concordance between tumor size on MRI and surgical pathology was higher in well-defined tumors, especially those with a Tneg subtype, and lower in HR+ diffuse tumors.

Clinical Cancer Research 19:2817-2823, 2013.

Developing Safety Criteria for Introducing New Agents into Neoadjuvant Trials

DeMichele A, Berry DA, Zujewski J, Hunsberger S, Rubinstein L, Tomaszewski JE, Kelloff G, Perlmutter J, Buxton M, Lyandres J, Albain KS, Benz C, Chien AJ, Haluska P, Leyland-Jones B, Liu MC, Munster P, Olopade O, Park JW, Parker BA, Pusztai L, Tripathy D, Rugo H, Yee D, Esserman L

New approaches to drug development are critically needed to lessen the time, cost, and resources necessary to identify and optimize active agents. Strategies to accelerate drug development include testing drugs earlier in the disease process, such as the neoadjuvant setting. The U.S. Food and Drug Administration (FDA) has issued guidance designed to accelerate drug approval through the use of neoadjuvant studies in which the surrogate short-term endpoint, pathologic response, can be used to identify active agents and shorten the time to approval of both efficacious drugs and biomarkers identifying patients most likely to respond. However, this approach has unique challenges. In particular, issues of patient safety are paramount, given the exposure of potentially curable patients to investigational agents with limited safety experience. Key components to safe drug development in the neoadjuvant setting include defining a study population at sufficiently poor prognosis with standard therapy to justify exposure to investigational agents, defining the extent and adequacy of safety data from phase I, detecting potentially harmful interactions between investigational and standard therapies, improving study designs, such as adaptive strategies, that limit patient exposure to ineffective agents, and intensifying safety monitoring in the course of the trial. The I-SPY2 trial is an example of a phase II neoadjuvant trial of novel agents for breast cancer in which these issues have been addressed, both in the design and conduct of the trial. These adaptations of phase II design enable acceleration of drug development by reducing time and cost to screen novel therapies for activity without compromising safety. Clin Cancer Res; 19(11); 2817–23. ©2013 AACR.

Breast Cancer Res Treat 139:759-767, 2013.

Molecular subtyping of early-stage breast cancer identifies a group of patients who do not benefit from neoadjuvant chemotherapy.

Glück S, de Snoo F, Peeters J, Stork-Sloots L, Somlo G

The aim of this study was to analyze the correlation between the pathologic complete response (pCR) rate after neoadjuvant chemotherapy and long-term outcome (distant metastases-free survival [DMFS]) in patients with early-stage breast cancer using BluePrint and MammaPrint molecular subtyping versus clinical subtyping using immunohistochemistry/fluorescence in situ hybridization (IHC/FISH) for the determination of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 (HER2). Data were analyzed from 437 patients in four neoadjuvant chemotherapy trials. BluePrint and MammaPrint outcomes were determined from 44K Agilent arrays, the I-SPY 1 data portal, or Affymetrix U133A arrays. The pCR rate differed substantially among BluePrint molecular subgroups: 6 % in Luminal A-type, 10 % in Luminal B-type, 47 % in HER2-type, and 37 % in Basal-type patients. In the Luminal A-type group (n = 90; including seven HER2-positive patients and eight triple-negative patients by IHC/FISH), the 5-year DMFS rate was 93 %. The pCR rate provided no prognostic information, suggesting these patients may not benefit from chemotherapy. Forty-three of 107 (40 %) HER2-positive patients were classified as Luminal-type by BluePrint and may have lower response rates to targeted therapy. Molecular subtyping identified 90 of 435 (21 %) patients as Luminal A-type (BluePrint Luminal-type/MammaPrint Low Risk) with excellent survival. The pCR rate provided no prognostic information. Molecular subtyping can improve the stratification of patients in the neoadjuvant setting: Luminal A-type (MammaPrint Low Risk) patients have a good prognosis with excellent survival and do not seem to benefit from chemotherapy. We observed marked benefit in response and DMFS to neoadjuvant treatment in patients subtyped as HER2-type and Basal-type. BluePrint with MammaPrint molecular subtyping helps to improve prognostic estimation and the choice of therapy versus IHC/FISH.

Cureus 4:e76, 2012.

A Model for Accelerating Identification and Regulatory Approval of Effective Investigational Agents

Esserman LJ, Barker AD, Woodcock J, Buxton M, Berry DA, Patterson R, King M, DeMichele A, Hylton N, Rubin EH, Parkinson D, Wholley D, Van’t Veer L, Yee D, Park J, Tripathy D, Perlmutter J, Buetow K, Hogarth M, Gray JW, Dilts D

A path for accelerated regulatory review of new drug and biomarker combinations is badly needed to transform the current clinical drug development process into an efficient, effective system that meets current and future healthcare needs. However, this type of radical transformation will not occur by layering regulatory change on existing clinical practice patterns. Here, we summarize a May 2011 I-SPY 2 TRIAL (Investigating Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular AnaLysis) workshop that included key leaders from the Food and Drug Administration (FDA), academia, industry, advocacy, and clinical trial-focused foundations that addressed this critical need. The workshop identified key aspects of the organization, trial design, and regulatory and industry alignment required to rapidly move successful agents from trial to clinical care. The workshop specifically focused on providing input for the development of a new evidence-based regulatory path for review of drugs and biomarkers that derive from neoadjuvant, modular, adaptive phase 2 screening trials achieved through precompetitive collaborations. The workshop participants agreed that new models, exemplified by the I-SPY 2 TRIAL for breast cancer, could address the need to more efficiently review and advance new drug and biomarker combinations. A three-tier model for trial development best describes this process. As practiced in I SPY 2, integrating imaging and biomarker information obtained through adaptive trials in the neoadjuvant breast cancer care setting is the first step. The second tier is replicable structural processes, including real-time data collection. The third is partner alignment achieved through pre-competitive collaboration and the potential to position successful drugs for accelerated regulatory approval in the neoadjuvant setting, where patients are likely to have the greatest benefit. Many elements of this model were incorporated into a new FDA draft guidance document which was released for public comment on May 31, 2012.

Clinical Cancer Research 18:6426-6435, 2012.

Molecular Analysis of HER2 Signaling in Human Breast Cancer by Functional Protein Pathway Activation Mapping

Wulfkuhle JD, Berg D, Wolff C, Langer R, Tran K, Illi J, Espina V, Pierobon M, Deng J, DeMichele A, Walch A, Bronger H, Becker I, Waldhör C, Höfler H, Esserman L, Investigators OBOTI-S1T, Liotta LA, Becker K-F, Petricoin EF

Purpose: Targeting of the HER2 protein in human breast cancer represents a major advance in oncology but relies on measurements of total HER2 protein and not HER2 signaling network activation. We used reverse-phase protein microarrays (RPMA) to measure total and phosphorylated HER2 in the context of HER family signaling to understand correlations between phosphorylated and total levels of HER2 and downstream signaling activity.

Experimental Design: Three independent study sets, comprising a total of 415 individual patient samples from flash-frozen core biopsy samples and formalin-fixed and paraffin-embedded (FFPE) surgical and core samples, were analyzed via RPMA. The phosphorylation and total levels of the HER receptor family proteins and downstream signaling molecules were measured in laser capture microdissected (LCM) enriched tumor epithelium from 127 frozen pretreatment core biopsy samples and whole-tissue lysates from 288 FFPE samples and these results were compared with FISH and immunohistochemistry (IHC).

Results: RPMA measurements of total HER2 were highly concordant (>90% all sets) with FISH and/or IHC data, as was phosphorylation of HER2 in the FISH/IHC+ population. Phosphorylation analysis of HER family signaling identified HER2 activation in some FISH/IHC tumors and, identical to that seen with FISH/IHC+ tumors, the HER2 activation was concordant with EGF receptor (EGFR) and HER3 phosphorylation and downstream signaling endpoint activation.

Conclusions: Molecular profiling of HER2 signaling of a large cohort of human breast cancer specimens using a quantitative and sensitive functional pathway activation mapping technique reveals IHC/FISH/pHER2+ tumors with HER2 pathway activation independent of total HER2 levels and functional signaling through HER3 and EGFR. Clin Cancer Res; 18(23); 6426–35. ©2012 AACR.

J Clin Oncol 30:3242-3249, 2012.

Pathologic complete response predicts recurrence-free survival more effectively by cancer subset: results from the I-SPY 1 TRIAL--CALGB 150007/150012, ACRIN 6657

Esserman LJ, Berry DA, DeMichele A, Carey L, Davis SE, Buxton M, Hudis C, Gray JW, Perou C, Yau C, Livasy C, Krontiras H, Montgomery L, Tripathy D, Lehman C, Liu MC, Olopade OI, Rugo HS, Carpenter JT, Dressler L, Chhieng D, Singh B, Mies C, Rabban J, Chen Y-Y, Giri D, van t Veer L, Hylton N

PURPOSE: Neoadjuvant chemotherapy for breast cancer provides critical information about tumor response; how best to leverage this for predicting recurrence-free survival (RFS) is not established. The I-SPY 1 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis) was a multicenter breast cancer study integrating clinical, imaging, and genomic data to evaluate pathologic response, RFS, and their relationship and predictability based on tumor biomarkers.

PATIENTS AND METHODS: Eligible patients had tumors ≥ 3 cm and received neoadjuvant chemotherapy. We determined associations between pathologic complete response (pCR; defined as the absence of invasive cancer in breast and nodes) and RFS, overall and within receptor subsets.

RESULTS: In 221 evaluable patients (median tumor size, 6.0 cm; median age, 49 years; 91% classified as poor risk on the basis of the 70-gene prognosis profile), 41% were hormone receptor (HR) negative, and 31% were human epidermal growth factor receptor 2 (HER2) positive. For 190 patients treated without neoadjuvant trastuzumab, pCR was highest for HR-negative/HER2-positive patients (45%) and lowest for HR-positive/HER2-negative patients (9%). Achieving pCR predicted favorable RFS. For 172 patients treated without trastuzumab, the hazard ratio for RFS of pCR versus no pCR was 0.29 (95% CI, 0.07 to 0.82). pCR was more predictive of RFS by multivariate analysis when subtype was taken into account, and point estimates of hazard ratios within the HR-positive/HER2-negative (hazard ratio, 0.00; 95% CI, 0.00 to 0.93), HR-negative/HER2-negative (hazard ratio, 0.25; 95% CI, 0.04 to 0.97), and HER2-positive (hazard ratio, 0.14; 95% CI, 0.01 to 1.0) subtypes are lower. Ki67 further improved the prediction of pCR within subsets.CONCLUSION:In this biologically high-risk group, pCR differs by receptor subset. pCR is more highly predictive of RFS within every established receptor subset than overall, demonstrating that the extent of outcome advantage conferred by pCR is specific to tumor biology.

Breast Cancer Res Treat 136:35-43, 2012.

Lobular histology and response to neoadjuvant chemotherapy in invasive breast cancer

Lips EH, Mukhtar RA, Yau C, de Ronde JJ, Livasy C, Carey LA, Loo CE, Vrancken-Peeters M-JTFD, Sonke GS, Berry DA, van t Veer LJ, Esserman LJ, Wesseling J, Rodenhuis S, Hwang ES, I-SPY 1 TRIAL Investigators

Invasive lobular carcinoma (ILC) has been reported to be less responsive to neoadjuvant chemotherapy (NAC) than invasive ductal carcinoma (IDC). We sought to determine whether ILC histology indeed predicts poor response to NAC by analyzing tumor characteristics such as protein expression, gene expression, and imaging features, and by comparing NAC response rates to those seen in IDC after adjustment for these factors. We combined datasets from two large prospective NAC trials, including in total 676 patients, of which 75 were of lobular histology. Eligible patients had tumors C3 cm in diameter or pathologic documentation of positive nodes, and underwent serial biopsies, expression microarray analysis, and MRI imaging. We compared pathologic complete response (pCR) rates and breast conservation surgery (BCS) rates between ILC and IDC, adjusted for clinicopathologic factors. On univariate analysis, ILCs were significantly less likely to have a pCR after NAC than IDCs (11 vs. 25%, p = 0.01). However, the known differences in tumor characteristics between the two histologic types, including hormone receptor (HR) status, HER2 status, histological grade, and p53 expression, accounted for this difference with the lowest pCR rates among HR?/HER2- tumors in both ILC and IDC (7 and 5%, respectively). ILC which were HR- and/or HER2? had a pCR rate of 25%.

Radiology 263:663-672, 2012.

Locally Advanced Breast Cancer: MR Imaging for Prediction of Response to Neoadjuvant Chemotherapy—Results from ACRIN 6657/I-SPY TRIAL

Hylton NM, Blume JD, Bernreuter WK, Pisano ED, Rosen MA, Morris EA, Weatherall PT, Lehman CD, Newstead GM, Polin S, Marques HS, Esserman LJ, Schnall MD

Purpose:

To compare magnetic resonance (MR) imaging findings and clinical assessment for prediction of pathologic response to neoadjuvant chemotherapy (NACT) in patients with stage II or III breast cancer.

Materials and Methods:

The HIPAA-compliant protocol and the informed consent process were approved by the American College of Radiology Institutional Review Board and local-site institutional review boards. Women with invasive breast cancer of 3 cm or greater undergoing NACT with an anthracycline-based regimen, with or without a taxane, were enrolled between May 2002 and March 2006. MR imaging was per- formed before NACT (first examination), after one cycle of anthracyline-based treatment (second examination), between the anthracycline-based regimen and taxane (third examination), and after all chemotherapy and prior to surgery (fourth examination). MR imaging assessment included measurements of tumor longest diameter and volume and peak signal enhancement ratio. Clinical size was also recorded at each time point. Change in clinical and MR imaging predictor variables were compared for the ability to predict pathologic complete response (pCR) and residual cancer burden (RCB). Univariate and multivariate random-effects logistic regression models were used to characterize the ability of tumor response measurements to predict pathologic outcome, with area under the receiver operating characteristic curve (AUC) used as a summary statistic.

Results:

Data in 216 women (age range, 26–68 years) with two or more imaging time points were analyzed. For prediction of both pCR and RCB, MR imaging size measurements were superior to clinical examination at all time points, with tumor volume change showing the greatest relative benefit at the second MR imaging examination. AUC differences between MR imaging volume and clinical size predictors at the early, mid-, and posttreatment time points, respectively, were 0.14, 0.09, and 0.02 for prediction of pCR and 0.09, 0.07, and 0.05 for prediction of RCB. In multivariate analysis, the AUC for predicting pCR at the second imaging examination increased from 0.70 for volume alone to 0.73 when all four predictor variables were used. Additional predictive value was gained with adjustments for age and race.

Conclusion:

MR imaging findings are a stronger predictor of pathologic response to NACT than clinical assessment, with the greatest advantage observed with the use of volumetric measurement of tumor response early in treatment.

Breast Cancer Res Treat 132 : 871-879 , 2012 .

Locally advanced breast cancers are more likely to present as Interval Cancers: results from the I-SPY 1 TRIAL (CALGB 150007/150012, ACRIN 6657, InterSPORE Trial)

Lin C, Buxton MB, Moore D, Krontiras H, Carey L, DeMichele A, Montgomery L, Tripathy D, Lehman C, Liu M, Olapade O, Yau C, Berry D, Esserman LJ and I-SPY Trial Investigators

Interval cancers (ICs), defined as cancers detected between regular screening mammograms, have been shown to be of higher grade, larger size, and associated with lower survival, compared with screen-detected cancers (SDCs) and comprise 17% of cancers from population-based screening programs. We sought to determine the frequency of ICs in a study of locally advanced breast cancers, the I-SPY 1 TRIAL. Screening was defined as having a mammogram with 2 years, and the proportion of ICs at 1 and 2 years was calculated for screened patients. Differences in clinical characteristics for ICs versus SDCs and screened versus non-screened cancers were assessed. For the 219 evaluable women, mean tumor size was 6.8 cm. Overall, 80% of women were over 40 and eligible for screening; however, only 31% were getting screened. Among women screened, 85% were ICs, with 68% diagnosed within 1 year of a previously normal mammogram. ICs were of higher grade (49% vs. 10%) than SDCs. Among non-screened women, 28% (43/152) were younger than the recommended screening age of 40. Of the entire cohort, 12% of cancers were mammographically occult (MO); the frequency of MO cancers did not differ between screened (11%) and non-screened (15%). ICs were common in the I-SPY 1 TRIAL suggesting the potential need for new approaches beyond traditional screening to reduce mortality in women who present with larger palpable cancers.

Breast Cancer Res Treat 132:1049-1062, 2012.

Chemotherapy response and recurrence-free survival in neoadjuvant breast cancer depends on biomarker profiles: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657)

Esserman LJ, Berry DA, Cheang MCU, Yau C, Perou CM, Carey L, DeMichele A, Gray JW, Conway-Dorsey K, Lenburg ME, Buxton MB, Davis SE, van’t Veer LJ, Hudis C, Chin K, Wolf D, Krontiras H, Montgomery L, Tripathy D, Lehman C, Liu MC, Olopade OI, Rugo HS, Carpenter JT, Livasy C, Dressler L, Chhieng D, Singh B, Mies C, Rabban J, Chen Y-Y, Giri D, Au A, Hylton N, I-SPY 1 TRIAL Investigators

Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with ≥ 3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group.

JAMA 306:2608-2609, 2011.

Accelerating identification and regulatory approval of investigational cancer drugs

Esserman LJ, Woodcock J

The development of new drugs is becoming increasingly expensive—and oncology drugs, in particular, have a high clinical failure rate. The current return on capital investment in drug development by US public companies was recently reported as less than 0.3%. The low probability of success, coupled with rapidly accelerating expenses, means that drug development is increasingly the purview of only 2 organization types: a few large companies and myriad small, venture capital–funded start-up firms. At an estimated cost of $1.0 billion to $1.8 billion for developing a successful new drug, funding for such risky ventures, particularly for oncology drugs, may diminish.

Clinical Pharmacol & Therapeutics 86:97-100, 2009.

I-SPY 2: an adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy

Barker AD, Sigman CC, Kelloff GJ, Hylton NM, Berry DA, Esserman LJ

I-SPY 2 (investigation of serial studies to predict your therapeutic response with imaging and molecular analysis 2) is a process targeting the rapid, focused clinical development of paired oncologic therapies and biomarkers. The framework is an adaptive phase II clinical trial design in the neoadjuvant setting for women with locally advanced breast cancer. I-SPY 2 is a collaborative effort among academic investigators, the National Cancer Institute, the US Food and Drug Administration, and the pharmaceutical and biotechnology industries under the auspices of the Foundation for the National Institutes of Health Biomarkers Consortium.

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