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Abstract Purpose In breast MRI, contrast enhancement of normal fibroglandular tissue is referred to as background parenchymal enhancement (BPE). Hormonal status significantly affects the degree of BPE, potentially due to the association with mammary vascularity and activity1-5. Studies have shown that BPE may be associated with breast cancer survival6, treatment response to neoadjuvant chemotherapy (NAC)7,8 and future breast cancer risk9. In most patients undergoing NAC, BPE is suppressed by the nonspecific anti-proliferative effects of chemotherapy on normal breast and/or ovary5,10. However, some patients exhibit equivalent or even stronger BPE post-NAC compared to pre-NAC. We hypothesized that non-suppressed BPE in post-NAC MRI may be associated with inferior treatment response. This study aimed to investigate the association between BPE suppression and treatment response as defined by pathologic complete response (pCR). Methods This study included patients with stage II/III breast cancer enrolled in the I-SPY 2 TRIAL being treated with standard NAC with or without investigational agents. The whole cohort was split into two subgroups based on hormone receptor status (HR+, n= 536; HR-, n=452). Patients underwent dynamic contrast enhanced MRIs at four time points during NAC: baseline (T0), after 3 weeks of the first regimen (T1), inter-regimen (T2), and pre-surgery (T3). Using in-house software, the contralateral breast parenchyma was automatically segmented for the entire breast volume. Quantitative BPE (qBPE) was calculated as the mean early (~150s post-contrast injection) percent enhancement of the central 50% of the axial slices. A breast radiologist reviewed all exams and excluded those where automated segmentation failed to accurately define tissue. For T1, T2 and T3, BPE was categorized based on the change from T0 as suppressed (qBPE < qBPE[T0]) or non-suppressed (qBPE ≥ qBPE[T0]). Chi-squared test was used to examine the association between BPE suppression and pCR, with p<0.05 considered statistically significant. Results HR+ cohort: pCR rates were lower for patients with non-suppressed BPE than those with suppressed BPE at every visit (T1-T3) (Table 1). The difference was statistically significant at T2 (p=0.04) and T3 (p=0.01). Table 1: HR+ cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall22.8122414536BPE at T1suppressed23.6822663480.45non-suppressed20.532124156BPE at T2suppressed25.7972803770.04*non-suppressed16.01789106BPE at T3suppressed25.7982833810.01*non-suppressed12.5128496 HR- cohort: pCR rates were slightly lower for the non-suppressed BPE group, but no statistically significant association was found (Table 2). Table 2: HR- cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall44.7202250452BPE at T1suppressed46.81411603010.66non-suppressed44.45265117BPE at T2suppressed48.81441512950.79non-suppressed47.3434891BPE at T3suppressed49.31461502960.94non-suppressed48.9434588 Conclusion In HR+ breast cancer, lack of BPE suppression may indicate inferior treatment response. The contrasting results in HR+ and HR- cohorts are noteworthy in terms of the possible relationship between suppression of normal mammary and ovarian activity and treatment response in HR+ cancer. Reference Radiographics 2014; 34: 234-47. Radiology 1997; 203: 137-44. Radiology 1997; 203: 145-9. Breast J 2005; 11: 236-41. AJR Am J Roentgenol 2015; 204: 669-73. Eur Radiol 2018; 28: 4705-16. Eur Radiol 2016; 26: 1590-6. Transl Oncol 2015; 8: 204-9. J Clin Oncol 2019; : JCO1800378. Radiology 2015; 277: 687-96. Citation Format: Natsuko Onishi, Wen Li, David C. Newitt, Roy Harnish, Jessica Gibbs, Ella F. Jones, Alex Nguyen, Lisa Wilmes, Bonnie N. Joe, Michael J. Campbell, Amrita Basu, Laura J. van’t Veer, Angela DiMichele, Douglas Yee, Donald A. Berry, Kathy S. Albain, Judy C. Boughey, A. Jo Chien, Amy S. Clark, Kirsten K. Edmiston, Anthony D. Elias, Erin D. Ellis, David M. Euhus, Heather S. Han, Claudine Isaacs, Qamar J. Khan, Julie E. Lang, Janice Lu, Jane L. Meisel, Zaha Mitri, Rita Nanda, Donald W. Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K. Viscusi, Anne M. Wallace, Rachel Yung, Michelle E. Melisko, Jane Perlmutter, Hope S. Rugo, Richard Schwab, W. Fraser Symmans, Smita M. Asare, Julie E. Yau, Christina Yau, Laura J. Esserman, Nola M. Hylton. Lack of background parenchymal enhancement suppression in breast MRI during neoadjuvant chemotherapy may be associated with inferior treatment response in hormone receptor positive breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-05.

Abstract Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype. Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%. Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors. Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100% Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-04.

Abstract Background: The IMpassion130 study demonstrated prolonged overall survival when atezolizumab, a PD-L1 inhibitor, was added to nab-paclitaxel in PD-L1 positive patients with advanced triple negative breast cancer (TNBC). Approximately 40% of tumors were PD-L1 positive, utilizing a cutoff of ≥ 1% immune cell (IC) staining with the Ventana SP142 immunohistochemical (IHC) assay. The Food and Drug Administration (FDA) approved this assay as a companion test to determine patient eligibility for atezolizumab therapy. However, literature in lung cancer shows that pathologists have a high discordance in assessing PD-L1 on IC. The FDA companion test documentation for SP142 shows high inter-laboratory reproducibility with nearly 95% overall percent agreement (OPA) between 2 readers for 2 category scoring of IC (positive versus negative) in TNBC in a central laboratory. PD-L1 testing for breast cancer is now becoming widespread in pathology laboratories. The goal of this study was to assess concordance in PD-L1 scoring between 19 pathologists from 14 institutions examining the same 86 TNBC tissues stained with the SP142 and SP263 antibodies. We also present a new method to determine the minimum number for evaluators needed to estimate concordance between large numbers of readers as occurs in real life setting. Methods: Full tissue sections were stained exactly as prescribed on the label on the Ventana Benchmark with the SP142 and SP263 PD-L1 assays. Sixty-eight and 76 cases were evaluable respectively. Stained slides were scanned and digital files distributed to pathologists who independently scored cases as either negative (< 1% IC staining) or positive (≥ 1% IC staining) and estimated the % of IC staining for positive cases. We applied a method that we call Observers Needed to Evaluate Subjective Tests (ONEST). For any combination of pathologists, we can quantify the degree of overall agreement using the proportion of tissue samples upon which all selected pathologists agreed, which can lead to a plot of non-increasing trajectory of agreement as the number of pathologists increases. We computed and plotted the empirical estimate of the overall agreement with the 95% confidence interval (CI) from 1000 randomly selected permutations of the pathologists. Results: PD-L1 was interpreted as positive with SP263 in an average of 78% of cases compared to 58% with the SP142 assay (p<.0001). IC positive continuous scores ranged from 1-95% (mean=20%) and 1-90% (mean=10%) for SP263 and SP142. Complete 2 category (positive vs negative) scoring concordance across all observers was achieved in 38 cases (50%) with SP263 and 26 cases (38%) with SP142. The intraclass correlation coefficient (ICC) for 2 category scoring of SP263 and SP142 was 0.513 and 0.560 respectively. ONEST plots made for each assay for 19 pathologists showed a decrease in OPA as number of observers increased, reaching a low plateau of approximately 0.46 at 10 observers for SP263 and 0.42 at 8 observers for SP142. Conclusions: Utilizing the FDA approved SP142 assay, we found a higher prevalence of PD-L1 positive tumors than published in the IMpassion130 trial but lower prevalence than seen with the SP263 assay. The different proportion of positive cases seen with two different assays highlights the need to establish cutoffs for each assay to correspond with clinical benefit. The ICC of scoring immune cells with both PD-L1 assays showed poor reproducibility across multiple pathologists. The ONEST analysis finds a plateau with 10 pathologists, only reaching an OPA of 0.4 for immune cell assessment. This suggests that more than half of the pathologists in real world situations may mis-assign patient IC scores. This could lead to a high percentage of patients either receiving atezolizumab, when they are unlikely to benefit or not receiving atezolizumab when they may benefit. Citation Format: Emily Suzanne Reisenbichler, Gang Han, Vasiliki Pelekanou, Vesal Yaghoobi, Fahad S Ahmed, Andrew Bellizzi, Veerle Bossuyt, Jane Brock, Kimberly Cole, Oluwole Fadare, Omar Hameed, Krisztina Hanley, Beth T Harrison, M G Kuba, Amy Ly, Dylan Miller, Mirna Podoll, Anja C Roden, Mary A Sanders, Kamaljeet Singh, Shi Wei, Hannah Wen, Lajos Pusztai, David L Rimm. Prospective multi-institutional evaluation of pathologist assessment of PD-L1 assays in triple negative breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD5-01.

Abstract Background: The I-SPY 2 TRIAL enrolls women with locally advanced, molecular high-risk breast cancer. An integrated Residual Cancer Burden (iRCB), based on MRI volume change through treatment, is used to predict pathologic complete response (pCR) in the randomization/evaluation Bayesian engine. With the goal of effective de-escalation of treatment for patients exhibiting an early response, biomarkers are being assessed for their ability to predict pCR, alone or with MR data, during treatment. Here, we present the results of a pilot study to examine if invasive tumor cellularity in mid-treatment tissue core biopsies predicts pCR in a 40-patient cohort of I-SPY 2 patients. Other pathologic variables evaluated include Ki67, tumoral histologic features, and stromal tumor-infiltrating lymphocytes (sTILs). Methods: I-SPY 2 TRIAL pathologists (N=4) were provided images of H&E-stained and Ki67 IHC- labelled (DAKO/Agilent, clone MIB-1) core biopsy sections from 40 patients at the inter-regimen time point, ~12-weeks into treatment. Of the 40 patients, 35 had 4 cores, 3 had 3 cores, and 2 had 2 cores assessed. In total, images from 153 cores were evaluated. For each core, pathologists were asked to score the % area occupied by tumor bed (treatment changes and/or residual cancer), % of viable invasive tumor (0-100%) within tumor bed (with Nottingham grading, % Ki67 labelled, and % sTILs, using standardized guidelines). As decided by the pathologist group, only cores with identified tumor bed were included in the initial analysis. Concordance between pathologists was assessed for all scored criteria, using % agreement for dichotomous variables, and Pearson correlation (r)/standard deviation (sd) for continuous variables. The maximum and average cellularity recorded over all cores/patient, averaged over all pathologists, were analyzed for association with pCR using t- tests (significance threshold: p<0.05). Fisher’s Exact test was used for dichotomous variables, and Pearson’s correlation for association of continuous variables with the residual cancer burden (RCB) index. Results: Pathologist were in general agreement about the presence or absence of tumor bed, with greater than 82% agreement between any two (83-96%), and an overall agreement of 77%. For scoring the % of the tumor bed involved by invasive cancer, correlations between pairs of pathologists ranged from 0.79-0.95 (mean(r)=0.87, sd=5%), and agreement on a binary presence/absence of invasive cancer was 78%. Both the mean (t-test: p=7.59E-05) and maximum (t-test: p=0.0012) %invasive tumor at 12 weeks, scored as an average over all pathologists, were significantly higher in patients who did not achieve pCR than in responders. We also treated %invasive cellularity as a dichotomous variable (present/absent). 90% (9/10) of patients scored by all pathologists as 0% invasive tumor cells (absent) achieved a pCR, vs only 20% (6/30) of patients scored as >0% invasive cellularity by one or more pathologists (present) (OR=32, Fisher p=0.0005); yielding a positive predictive value for pCR of 0.9. Ki67 and sTILS at 12 weeks were fairly concordant across pathologists ((r,sd)=(0.92, 8.45%) and (0.82,5.5%), respectively), but did not associate with response (p>0.05 for pCR, RCB01, or RCB index). Tumor histologic grade at 12 weeks, assessed in 29/30 patients with non-zero cellularity, trended toward association (Fisher p=0.078): 44% (4/9) with Grade 3 went on to have a pCR, vs. 15% (2/13) with Grade 2 and 0 with Grade 1. These data demonstrate the utility of invasive tumor cellularity as a predictor of pCR in a clinical setting. Conclusion: In this pilot study we demonstrate that the absence of invasive cancer cells within identified tumor bed in mid-treatment core biopsy samples is highly predictive of pCR. Citation Format: Sara J Venters, Denise M Wolf, Lamorna Brown-Swigart, Christina Yau, Amy L Delson, Bev Parker, Ron Balassanian, Jodi Carter, Yunn-Yi Chen, Kimberly Cole, Laila Khazai, Molly Klein, Dina Kokh, Gregor Krings, Sunati Sahoo, Jane Wei, I-SPY 2 TRIAL Consortium, Laura J Esserman, Laura J van't Veer, W Fraser Symmans. Assessing biomarkers to inform treatment de-escalation: Mid-treatment biopsy cellularity predicts pCR in the I-SPY 2 Trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-10-02.

Abstract Background: Strong background parenchymal enhancement (BPE) may cause overestimation in tumor volume measured from dynamic contrast-enhanced (DCE) MRI, which may adversely affect the ability of MR tumor volume to predict treatment outcome for patients undergoing neoadjuvant chemotherapy (NAC). Specifically, an overestimation of tumor volume can result in misclassification of patients with complete pathologic response (pCR) as non-responders, leading to less confidence in MRI prediction. As well, overestimation of extent of disease might lead to more aggressive surgical therapy than necessary. This study investigated whether high BPE in the contralateral breast influences the predictive performance of MRI-measured functional tumor volume (FTV) for patients with locally advanced breast cancer undergoing NAC. Methods: patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Each patient had 4 MRI exams: pre-NAC (T0), after 3 weeks of NAC (T1), between NAC regimens (T2), and post-NAC (T3). FTV was calculated at each MRI exam by summing voxels meeting enhancement thresholds. Background parenchymal enhancement (BPE) in the contralateral breast was calculated automatically as mean percentage enhancement on the early (nominal 150sec post-contrast) image in the fibroglandular tissue segmented from 5 continuous axial slices centered in the inferior-to-superior stack. For each treatment time point, patients having both FTV and BPE measurements were included in the analysis. The area under the ROC curve (AUC) was estimated as the association between FTV and pCR at T1, T2, and T3. The analysis was conducted in the full patient cohort and in sub-cohorts defined by hormone receptor (HR) and HER2 status. In each patient cohort, a cut-off BPE value was selected to classify patients with high vs. low BPE by testing AUCs estimated with low-BPE patients reached maximum when the cut-off value varied from median to maximum in steps of 10%. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Table 1 shows the number of patients, pCR rate, and AUC of FTV for predicting pCR using all patients available vs. a subset patients with low BPE (< BPE cut-off). In the full cohort, AUC increased slightly across all time points after patients with high BPE were removed. In the HR+/HER2- subtype, AUC increased at T1 after removal of cases with high BPE (0.65 vs. 0.71). For HR-/HER2+, AUC increased substantially after removal of high BPE cases (0.65 to 0.86 at T1, 0.71 to 0.87 at T2, and 0.71 to 0.89 at T3), with greater improvement at the early time point (T1) compared to later time points (T2 and T3). Only a slight improvement in the AUC was observed in the HR+/HER2+ and HR-/HER2- subtypes across all time points. Conclusions: High background parenchymal enhancement adversely affected the predictive performance of functional tumor volume measured by DCE-MRI, at early treatment time point for HR+/HER2- and across all time points for HR-/HER2+ cancer subtype. The adverse effect might be offset using subtype-optimized enhancement threshold in calculating functional tumor volume. Table 1 Effect of BPE on the prediction of pCR using FTV at various treatment time pointsT1T2T3npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offFullAll64734%0.662762334%0.701761134%0.6925Subset45334%0.6831133%0.7230534%0.72HR+/HER2-All26218%0.651924918%0.718225518%0.7519Subset13118%0.7124818%0.7120419%0.76HR+/HER2+All10636%0.642110538%0.62269634%0.7120Subset5332%0.668438%0.665740%0.73HR-/HER2+All5175%0.65204774%0.71204973%0.7116Subset3073%0.862871%0.872475%0.89HR-/HER2-All22842%0.682822243%0.751821143%0.6916Subset15940%0.7111137%0.7810540%0.75 Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Roy Harnish, Ella F Jones, Lisa J Wilmes, Jessica Gibbs, Elissa Price, Bonnie N Joe, A. Jo Chien, Donald A Berry, Judy C Boughey, Kathy S Albain, Amy S Clark, Kirsten K Edmiston, Anthony D Elias, Erin D Ellis, David M Euhus, Heather S Han, Claudine Isaacs, Qamar J Khan, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Christina Yau, Smita M Asare, Angela DeMichele, Sally Goudreau, Hiroyuki Abe, Deepa Sheth, Dulcy Wolverton, Kelly Fountain, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Theresa Kuritza, Kevin Morley, Michael Nelson, An Church, Bethany Niell, Jennifer Drukteinis, Karen Y Oh, Neda Jafarian, Kathy Brandt, Sadia Choudhery, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Mohammad Eghedari, Pulin Sheth, Linda Hovanessian-Larsen, Mark Rosen, Elizabeth S McDonald, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Laura J Esserman, Nola M Hylton. The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-01.

Abstract Introduction: Male breast cancer (BCa) is a rare disease accounting for less than 1% of all breast cancers (BC) and 1% of all cancers in males. The clinical management is largely extrapolated from female BCa. Few studies have examined the genomic landscape of male BCas, with six male BCas included in The Cancer Genome Atlas (TCGA). Familial studies of male BCas have shown genomic changes similar to female BCa, while a larger targeted sequencing study of 59 male breast cancers identified recurrent mutations affecting PIK3CA and GATA3. To date, there is still limited information regarding the genomic landscape of male BCas; particularly in the context of identifying targeted treatments. To reveal genomic changes that characterize male BCas in the context of known cancer driver genes linked to prognosis and targeted agents, we performed a targeted sequencing study on 248 male BCas from the International Male Breast Cancer Program. Methods: 248 primary M0, ER+ve, HER2-ve male BCas enrolled in the Part 1 (retrospective joint analysis) International Male Breast Cancer Program of 1483 patients diagnosed between 1990-2010 (Cardoso et al. Annals of Oncology, 2018) were processed for nucleic acid extraction from formalin-fixed paraffin embedded (FFPE) tissues. Using the Thermo Fisher Scientific Oncomine Comprehensive Assay v3 (OCAv3), a validated targeted sequencing panel currently used in the NCI-MATCH trial (NCT02465060), we evaluated mutational and copy number variations (CNVs) of genes that are prognostic or predictive to targeted therapies currently in use in the clinic or late-stage clinical trials. The OCAv3 DNA pan-cancer panel assays 115 genes for determining mutational status (48 full coding and 67 hotspot) as well as copy-number assessment in 43 genes. The OCAv3 uses Ampliseq-based technology linked to the Oncomine NGS workflow to identify actionable mutations and CNVs Results: Of the 248 samples assayed, 216 passed strict quality control parameters (87.1%). Using the Oncomine NGS workflow, actionable mutations at ≥5% variant allele frequency (VAF) were most frequently identified in PIK3CA (29.2%), BRCA2 (11.1%), NF1 (11.6%), indels in TP53 (10.6%), ATR (5.6%), ATRX (5.1%), indel BRCA2 (5.1%), TP53 point mutations (4.6%), MET (4.6%), ATM (4.6%), NOTCH2 (4.6%), CHEK1 (4.2%), FANCI (4.2%), PTEN (3.2%) with a number of additional genes identified at lower frequencies. Gene amplifications were most frequently detected in MYC (24.5%), FGFR1 (14.8%), CCND1 (12%), FGF3 (9.7%), FGF19 (9.7%), MDM2 (6.5%), CDK4 (1.4%), FGFR3, MDM4, ERBB2 (0.9% each), and FLT3, AR, MYCL, CDK6, IGF1R, FGFR4, KRAS, AKT3 and ESR1 (0.5% each). Although the results here describe the mutations and copy-number changes deemed to be actionable, further analysis of all non-actionable somatic mutations and CNVs will be presented and compared to female BCas previously assayed using the same panel. Conclusion: In this targeted sequencing study of the largest series of male BCas to our knowledge, we have revealed that PIK3CA continues to be a frequently altered gene in both male and female BCas. However, there is an enrichment of mutations in genes related to DNA repair in male BCs. Interestingly, while MYC is commonly amplified in female BCa, a higher frequency of amplified cases were seen in male BCas, in contrast to female BCas. Together with our previously generated transcriptional profiling data in this data set, we believe that both common and unique biological processes comprising male and female BCas will ultimately improve their clinical management and move towards the goal of precision medicine. This work has been funded by the Breast Cancer Research Foundation (BCRF). Citation Format: Jane Bayani, Coralie Poncet, Cheryl Crozier, Quang M Trinh, Megan Hopkins, Aime Lambert Uwimana, Tammy Piper, Carrie Cunningham, Monika Sobol, Stefan Aebi, Kim Benstead, Oliver Bogler, Lissandra Dal Lago, Florentine Hilbers, Ingrid Hedenfalk, Larissa Korde, Barbro Linderholm, John Martens, Lavinia Middleton, Melissa Murray, Catherine Kelly, Cecilia Nilsson, Monika Nowaczyk, Stephanie Peeters, Aleksandra Peric, Peggy Porter, Carolien Schröder, Isabel T Rubio, Kathryn J Ruddy, Christi van Asperen, Danielle Van Den Weyngaert, Carolien HM van Deurzen, Elise van Leeuwen-Stok, Joanna Vermeij, Eric Winer, Lincoln D Stein, Sharon H Giordano, Fatima Cardoso, John MS Bartlett. The genomic landscape of male breast cancers using the oncomine comprehensive assay for actionable mutations [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-03.

Abstract Background: A variety of investigational HER2-inhibitor agents/combinations have been tested in I-SPY 2, including neratinib (N), TDM1 combined with pertuzumab (P) (TDM1/P), and trastuzumab (H) combined with pertuzumab (H/P; prior to this combination becoming standard of care), all with trastuzumab as control (Ctr). All three experimental arms graduated, showing improved efficacy over control in one or more receptor subsets (HR+HER2+, HR-HER2+, or/and HER2+). Here we assess 10 biomarkers in the HER2, ER/PR, and proliferation pathways on multiple levels of resolution (expression, protein, phospho-protein) as predictors of response in these four arms, hypothesizing that highly HER2-activated, proliferative tumors may be more sensitive to HER2-inhibition than those that are more luminal and quiescent. Methods: 192 HER2+ patients were considered in this analysis: (31 Ctr, 65 N, 52 TDM1/P, and 44 H/P). 10 biomarkers relating to HER2, ER, or proliferation were evaluated from pre-treatment biopsies: HER2 IHC (n=145), 3 expression signatures (n=192), BluePrint subtype (n=192), and 5 protein/phospho-protein analytes by RPPA (n=175). Each biomarker was tested for association with pCR in the whole population and within each arm using a logistic model. This analysis was adjusted for HR status and treatment arm as covariates, and performed within receptor subtypes. This analysis does not adjust for multiplicities of other biomarkers. Results: In the population as a whole, HER2 and HER2-signaling biomarkers, evaluated at multiple levels of resolution: IHC, total-/phospho-protein by RPPA, and mRNA (HER2 amplicon module) - are highly correlated (rho=0.8 [0.65-0.92]). Higher HER2 levels and activity are associated with response: HER2 IHC 3+ status (LR p=0.00032), total quantitative ERBB2 protein by RPPA (LR p=5.4E-09), ERBB2 activation levels (LR p=6.58E-06 (pERBB2 (Y1248)) and 9.95E-06 (pEGFR Y1173)), and the ERBB2 amplicon expression signature (LR p=2.38E-08). In contrast, higher average ER/PR expression associates with non-response to HER2-targeted therapy (LR p=4.28E-08). Both HER2 and ER/PR signaling phenotypes are captured by BluePrint subtyping; and consistent with the individual pathway markers, tumors classified Luminal-type had a lower pCR rate relative to those classified as Her2-type (or Basal-type) (LR p=4.84E-11). These associations all retain significance in a model adjusting for HR status and treatment arm, and in the HR+HER2+ subset. In addition, we quantitatively assessed proliferation markers at the total protein (RPPA: Ki67), phospho-protein (pAURKA) and mRNA (proliferation signature Module11_Prolif) levels. All three proliferation biomarkers predict response overall; but this association is strongest within the HR+HER2+ subset (LR p=0.0012 (Module11_prolif), 0.0036 (pAURK), and 0.045 (Ki67)). None of the biomarkers tested were associated with response in the HR-HER2+ subset. Numbers are small within individual arms. Within the HR+HER2+ subtype, higher HER2 and lower ER/PR is observed in responders in all experimental arms; but the proliferation markers Module11_Prolif (LR p=0.0031) and Ki67 total protein (LR p=0.0029) are associated with response to TDM1/P but not H/P or N. Conclusion: High HER2 signaling at the expression, protein, and phospho-protein levels, and low ER signaling, all predict response to HER2-inhibition across treatment arms. Proliferation markers may be useful for prioritizing therapies in the HR+HER2+ subset. Citation Format: Denise M Wolf, Christina Yau, Julia Wulfkuhle, Lamorna Brown-Swigart, Smita M. Asare, Gillian L. Hirst, Laura Sit, Jane Perlmutter, I-SPY 2 TRIAL Consortium, Minetta Liu, John Park, Angela DeMichele, Douglas Yee, Don Berry, Laura Esserman, Emanuel Petricoin, Laura van t' Veer. HER2 signaling, ER, and proliferation biomarkers predict response to multiple HER2-targeted agents/combinations plus standard neoadjuvant therapy in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-02.

Abstract Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR) at surgery. The goal is to identify (graduate) regimens with ≥ 85% Bayesian predictive probability of success (i.e., demonstrating superiority to control) in a future 300-patient phase 3 1:1 randomized neoadjuvant trial with pCR endpoint within signatures defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status. Regimens may leave the trial for futility (< 10% probability of success), maximum sample size accrual (with probability of success ≥ 10% and < 85%), or safety concerns as recommended by the independent DSMB. For HER2+ patients, the I-SPY2 control arm was 12 weekly cycles of paclitaxel+trastuzumab (TH, control) followed by doxorubicin/cyclophosphamide (AC) q2-3 weeks x4 and surgery. Patritumab is a fully human monoclonal antibody that inhibits HER3. In this experimental arm for HER2+ patients, patritumab was given q3w x 4 cycles (18mg/kg loading dose followed by 9mg/kg/dose) concurrent with paclitaxel and trastuzumab q1w x 12 weeks (PTH, treatment), followed by AC q2-3w. Methods: Women with tumors ≥ 2.5cm were eligible for screening. MP low/HR+ tumors were ineligible. MRI scans (baseline, 3 weeks after start of therapy, prior to AC, and prior to surgery) were used in a longitudinal statistical model to predict pCR for individual patients. Analysis was intention to treat. Patients who switched to non-protocol therapy count as non-pCR. Patients on treatment arm therapy at the time of arm closure are non-evaluable. Graduation potential was in 3 of 10 pre-defined signatures: all HER2+, HR-/HER2+, and HR+/HER2+. Results: The PTH regimen was stopped at the recommendation of the Safety Working Group and DSMB based on a safety event (bilateral sensorineural hearing loss, Gr 3) observed in one patient. At the time of arm closure, N=31 patients had received PTH treatment; 4 patients receiving PTH were changed to non-protocol therapy and removed from the analysis. The final estimated pCR report will consider 27 PTH and 31 TH as evaluable patients. Accrual was insufficient to assess graduation, however, there appears to be good signal in the HER2+HR- but not HER2+HR+ signatures. I-SPY 2 TRIAL Est. pCR at time of arm closureSignaturesPTH (Treatment)N= 31TH (Control)N = 31All (HER2+)0.40 (0.22 - 0.59), n=310.23 (0.09 - 0.37), n=31HR-/HER2+0.64 (0.36 - 0.91), n=110.30 (0.12 - 0.47), n=12HR+/HER2+0.28 (0.08 - 0.48), n=200.20 (0.06 - 0.34), n=19 HR+/HER2+0.28 (0.08 - 0.48), n=200.20 (0.06 - 0.34), n=19The patient who developed Gr3 sensorineural hearing loss 6 days after the 2nd patritumab (and 4th paclitaxel/trastuzumab) treatment, did not recover her hearing after patritumab was stopped, and also reported Gr3 vulvovaginal pain, vulvitis, and vaginal inflammation. Other gynecological symptoms in the PTH arm include: 1 pt with Gr1 vaginal hemorrhage, and 1 pt with Gr2 dyspareunia. There was a higher frequency of Gr3 hypokalaemia (12.5% vs. 3.2%). One pt in the PTH arm reported Gr3 small intestinal obstruction which resolved with conservative management. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial; PTH was stopped due to safety concerns, although there was activity in the HER2+ HR- signature. This is the first report of Gr3 hearing loss associated with patritumab/paclitaxel/trastuzumab, and thus attribution is uncertain. Citation Format: Teresa L Helsten, Shelly S Lo, Christina Yau, Kevin Kalinsky, Anthony D Elias, Anne M Wallace, A. Jo Chien, Janice Lu, Julie E Lang, Kathy S Albain, Erica Stringer-Reasor, Amy S Clark, Judy C Boughey, Erin D Ellis, Douglas Yee, Angela DeMichele, Claudine Isaacs, Jane Perlmutter, Hope S Rugo, Richard Schwab, Nola M. Hylton, W. Fraser Symmans, Michelle E Melisko, Laura J van't Veer, Amy Wilson, Ruby Singhrao, Smita M Asare, Ashish Sanil, Donald A Berry, Laura J Esserman. Evaluation of patritumab/paclitaxel/trastuzumab over standard paclitaxel/trastuzumab in early stage, high-risk HER2 positive breast cancer: Results from the neoadjuvant I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-11-02.

Abstract Background: I-SPY2 is a multicenter, response-adaptive randomization phase 2 trial to evaluate novel agents when added to standard neoadjuvant therapy for women with high-risk stage II/III breast cancer - weekly paclitaxel + investigational treatment x 12 wks followed by doxorubicin & cyclophosphamide(AC) q3 wks x 4 vs. weekly paclitaxel/AC (control). The primary endpoint is pathologic complete response (pCR). The goal for all investigational arms is to identify/graduate regimens with ≥85% Bayesian predictive probability of success (i.e. demonstrating superiority to control) in a future 300-patient phase 3 1:1 randomized neoadjuvant trial with a pCR endpoint within signatures defined by hormone-receptor (HR) & HER2 status & MammaPrint (MP). Findings from the graduated, previously reported Pembro4 arm (Nanda et al, ASCO 2017) supported investigation of de-escalating therapy, and determining if pembrolizumab (an anti-PD-1 antibody) alone q3 wks x 4 after weekly paclitaxel x 12 wks + pembrolizumab q3 wks x 4 was sufficient to sustain response without AC. Methods: Women with tumors ≥2.5cm were eligible for screening. MP low/HR+ were ineligible. MRI scans (at baseline, 3 wks, 12 wks, and prior to surgery) were used in a longitudinal statistical model to predict pCR for individual patients (pts). Pts who receive non-protocol therapy (e.g., carboplatin or AC for the Pembro8-noAC arm) count as non-pCR. Pembro8-noAC was open to HER2- pts for evaluation in 3 of 10 pre-defined signatures: HER2-, HR+/HER2-, and HR-/HER2-. Regimens exit the trial for futility (<10% probability of success), maximum sample size accrual (10% <probability of success <85%), or safety as recommended by the independent DSMB. Results: Pembro8-noAC was randomized to 73 pts, 3 of whom progressed while receiving pembrolizumab alone on study. Randomization to this arm continued after the first report because the rate of progression during AC over the course of the trial was estimated to be 6.5% based on serial MRI studies. However, notification of the third case prompted the study team to ask the DSMB for the summary response for this arm. Although it did not meet formal stopping rules for either graduation or futility, Pembro8-noAC was not near the target threshold pCR rates of 60% for HR-/HER2- and 30% for HR+/HER2+. As a result of this information, combined with the on-treatment progressions, assignment to Pembro8-noAC was discontinued. Treatment with pembrolizumab alone was no longer allowed due to the potential concern for progression, and investigators were given the option to administer AC with pembrolizumab or proceed with definitive surgery following the 12 weeks of paclitaxel + pembrolizumab. 34 pts had surgery results at the time the study was closed. Of the remaining 39 pts, 34 pts have on-therapy MRI assessments. Estimated pCR rates were based on all pts with information at the time (see table). Immune-related adverse events included grade 3 colitis (n=2), grade 3 pneumonitis (n=1), grade 3 transaminitis (n=1), grade 3 hypothyroidism (n=1), and grade 1-2 adrenal insufficiency (n=5). Conclusion: Although Pembro8-noAC is performing at least as well as standard paclitaxel/AC, the likelihood is very low that the regimen would be successful in a phase 3 trial. Pembrolizumab alone following 12 weeks of paclitaxel + pembrolizumab was not sufficient to sustain a response. This was quickly assessed with a small number of patients. Estimated pCR rateSignature(95% prob interval)Pembro8-noACControlHER2-0.210.2(0.09-0.32)(0.15-0.25)HR-/HER2-0.270.27(0.09-0.45)(0.19-0.35)HR+/HER2-0.150.15(0.01-0.29)(0.09-0.20) Citation Format: Minetta C. Liu, Patricia A Robinson, Christina Yau, Anne M Wallace, A. Jo Chien, Erica Stringer-Reasor, Rita Nanda, Douglas Yee, Kathy S Albain, Judy C Boughey, Heather S Han, Anthony D Elias, Kevin Kalinsky, Amy S Clark, Kathleen Kemmer, Claudine Isaacs, Julie E Lang, Janice Lu, Tara Sanft, Angela DeMichele, Nola M Hylton, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Patricia K Haugen, Amy Wilson, Ruby Singhrao, Smita Asare, Ashish Sanil, Donald A Berry, Laura J Esserman. Evaluation of a novel agent plus standard neoadjuvant therapy in early stage, high-risk HER2 negative breast cancer: Results from the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-09-02.

Abstract Background: Achieving a pathologic complete response (pCR) has been shown on the patient level to predict excellent long-term event-free survival outcomes. Residual cancer burden (RCB) quantifies the extent of residual disease for patients who did not achieve pCR. A high proportion of metastatic events to the central nervous system (CNS), a known chemotherapy sanctuary site, was previously observed among the small number of relapses in patients achieving a pCR (Symmans et al 2017), raising the possibility that these CNS events may be independent of response in the breast. I-SPY2 is an adaptively randomized, phase II, platform trial that evaluates new drugs and combinations in the neoadjuvant setting for women with high-risk primary breast cancer. In this study, we evaluated the type and sites of recurrences by RCB classes in the I-SPY 2 TRIAL. Methods: I-SPY 2 patients enrolled prior to 11/2016 across 9 experimental and control arms, with available RCB and event-free survival (EFS) data were included in this analysis. The median follow-up is 3.8 years. We summarized the EFS event type, further sub-dividing the distant recurrence events by their site of relapse (CNS-only, CNS and other sites, Non-CNS). We estimated the overall and site-specific distant recurrence incidence in each RCB class at 3 years using a competing risk (Fine-Gray) model. In addition, we assessed the association between RCB and distant recurrence free survival including all distant recurrences (DRFS), as well as excluding the CNS-only recurrences (non-CNS DRFS) using a Cox model. Our statistics do not adjust for multiplicities beyond variables evaluated in this study. Results: Among 938 subjects, there were 180 EFS events, including 28 (16%) local recurrences (without distant recurrence and/or death) and 152 DRFS events. Among the DRFS events, 25 patients died without a distant recurrence. 127 experienced distant recurrences, including 22 (17.3%) with CNS-only, 16 (12.6%) with CNS and other sites, 87 (68.5%) with non-CNS distant recurrence; 2 (1.6%) patients had missing recurrence site information. Incidence of CNS-only recurrences are low and are similar across RCB classes (pCR/RCB-0 (n=338): 1%, RCB-I (n=129): 3%, RCB-II (n=328): 2%, RCB-III (n=143): 2% at 3 years). In contrast, the incidence of non-CNS recurrences increase with increasing RCB (RCB-0: 2%, RCB-I: 4%, RCB-II: 11%, RCB-III: 19% at 3 years). DRFS of RCB-I patients do not significantly differ from those achieving a pCR/RCB-0 (DRFS at 3 years: 92% vs. 95%, hazard ratio: 1.77 (0.87-3.63)); the small numerical difference is further reduced when the CNS-only recurrences are excluded (non-CNS DRFS at 3 years: 95% vs. 96%, hazard ratio: 1.48 (0.61-3.58)). CNS recurrences among DRFS events are proportionally higher within the pCR (5/16 (31%)) and RCB-I (5/12 (42%)) than in the RCB-II (8/57 (14%)) and RCB-III (4/42 (9%)) groups largely because of the relative low frequency of non-CNS recurrence events. Conclusions: In our high-risk I-SPY 2 cohort, CNS-only recurrences are uncommon but appear similar across RCB groups, independent of response, suggesting that the CNS is a treatment sanctuary site. In contrast, non-CNS recurrence rates increase as RCB increases. These findings, if confirmed, support the use of RCB to identify patients with excellent outcomes beyond those achieving a pCR; and suggest that inclusion of CNS only recurrences as an outcome event may impact the association between neoadjuvant therapy response and long-term outcome. Citation Format: Christina Yau, Angela DeMichele, W. Fraser Symmans, Lajos Pusztai, Douglas Yee, Amy S. Clark, Christos Hatzis, Jeffrey B. Matthews, Jodi Carter, Yunn-Yi Chen, Kimberly Cole, Laila Khazai, Molly Klein, Dina Kokh, Gregor Krings, Sunati Sahoo, Kathy S. Albain, A. Jo Chien, Kirsten K. Edmiston, Anthony D. Elias, Erin D. Ellis, David M. Euhus, Heather S. Han, Claudine Isaacs, Qamar J. Khan, Julie E. Lang, Janice Lu, Jane L. Meisel, Zaha Mitri, Rita Nanda, Donald W. Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K. Viscusi, Anne M. Wallace, Rachel Yung, Nola M. Hylton, Judy C. Boughey, Michelle E. Melisko, Jane Perlmutter, Hope S. Rugo, Richard Schwab, Laura J. van' t Veer, Donald A. Berry, Laura J. Esserman. Site of recurrence after neoadjuvant therapy: Clues to biology and impact on endpoints [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-20-02.