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Veer, Laura van ‘t

https://orcid.org/0000-0002-9838-8298

Mayo Clinic

University of California, San Francisco

Citations 34

Abstract P2-20-02: Site of recurrence after neoadjuvant therapy: Clues to biology and impact on endpoints
Clark, Amy S. , Matthews, Jeffrey B. , Chen, Yunn‐Yi , Cole, Kimberly, Khazai, Laila , Klein, Molly, Kokh, Dina, Krings, Gregor , Sahoo, Sunati , Albain, Kathy S. , Chien, A. Jo , Edmiston, Kirsten K., Ellis, Erin D. , Euhus, David , Han, Heather, Khan, Qamar J. , Lu, Janice , Mitri, Zaha, Nanda, Rita, Northfelt, Donald W. , Sanft, Tara , Stringer-Reasor, Erica , Viscusi, Rebecca K., Yung, Rachel L. , Melisko, Michelle , Perlmutter, Jane , Schwab, Richard B. , Veer, Laura van ‘t , Berry, Donald A. , Yau, Christina , DeMichele, Angela , Symmans, W. Fraser , Pusztai, Lajos , Yee, Douglas , Hatzis, Christos , Carter, Jodi M. , Elias, Anthony , Isaacs, Claudine , Lang, Julie E. , Meisel, Jane Lowe , Wallace, Anne M. , Hylton, Nola M. , Boughey, Judy C. , Rugo, Hope S. , Veer, Laura J. van’t , Esserman, Laura J.

Cancer Research | March 26, 2020 | Volume: 80 | Issue: 4_Supplement | Pages: P2-20-02-P2-20-02

10.1158/1538-7445.sabcs19-p2-20-02 Get It

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.
Abstract GS5-01: Residual cancer burden after neoadjuvant therapy and long-term survival outcomes in breast cancer: A multi-center pooled analysis
Noordaa, Marieke van der, Wei, Jane , Reyal, Fabien , Laé, Marick , Monte, Maria del, Gould, Rebekah , Steenbruggen, Tessa G. , Seijen, Maartje van , Edge, Stephen B. , Sammut, Stephen‐John , Provenzano, Elena , Graham, Ashley , Mackintosh, Lorna, Wang, Alice , Cole, Kimberly, Veer, Laura van ‘t , Yau, Christina , Noordaa, Marieke E. M. van der, Osdoit, Marie , Hamy, Anne‐Sophie , Martín, Miguel , Boughey, Judy C. , Wesseling, Jelle , Sonke, Gabe S. , Abraham, Jean , Hall, Peter S , Graham, Ashley, Cameron, David , Sharma, Priyanka , Pusztai, Lajos , Kim, Mi‐Ok , Veer, Laura J. van’t , Esserman, Laura J. , Symmans, W. Fraser

Cancer Research | March 26, 2020 | Volume: 80 | Issue: 4_Supplement | Pages: GS5-01-GS5-01

10.1158/1538-7445.sabcs19-gs5-01 Get It

Abstract Background: Recent studies have demonstrated independent validation of the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. However, a pooled subject-level analysis of multiple cohorts is needed to determine estimates of long-term prognosis for each class of RCB in each phenotypic subtype of breast cancer (BC) to better inform on patient outcomes. Also, a pooled subject-level analysis allows more detailed analyses of generalizability of the prognostic meaning of RCB assessments in a broader experience of practice settings. Method: Subject-level RCB results, with relevant clinical and pathologic stage, tumor subtype and grade, demographic, treatment and follow-up data from 11 institutes/trials are being collected for combined analysis. The association between the continuous RCB index and event-free survival (EFS), and distant recurrence free survival (DRFS) were assessed using mixed effect Cox models with the incorporation of random RCB coefficients to account for between-study heterogeneity. We will also allow for differences in baseline hazard across biological BC subtypes and, if needed, across studies as well. In addition to this stratified mixed effect model, a multivariate analysis adjusting for age, T-category, nodal status and grade was performed within each subtype. In addition, mixed effect Cox models will be employed to evaluate association between RCB index with EFS and DRFS within each HR/HER2 subtype. Kaplan Meier estimates of EFS and DRFS at 5 and 10 years were computed for each RCB class within subtype. Results: We analyzed subject-level data from 9 institutes/trials representing 4077 patients currently available from an anticipated final total of 4,800 patients (to be presented at the meeting). There were 950 EFS and 876 DRFS events during follow up (median 65 months, IQR: 70 months). RCB index (continuous) was independently prognostic within each subtype: HR+/HER2- (EFS HR (per unit increase in RCB index) =1.64, 95%CI 1.48-1.82; DRFS HR=1.68, 1.51-1.87), HR+/HER2+ (EFS HR=1.80, 1.57-2.05; DRFS HR=1.93, 1.67-2.24), HR-/HER2+ (EFS HR=2.15, 1.76-2.62; DRFS HR=2.10, 1.77-2.50), and HR-/HER2- (EFS HR=2.05, 1.89-2.22; DRFS HR=2.16, 1.90-2.46); and remained prognostic in multivariate models adjusting for age, grade, and clinical T and N stage at diagnosis. Table 1 contains the response rate and estimated EFS at 5 years and 10 years for each RCB class within each HR/HER2 phenotype (DRFS results were similar). Conclusions: Long-term prognosis after pCR was similarly excellent in all phenotypic subtypes. RCB index and classification was independently and strongly prognostic in all subtypes, and generalizable to multiple practice settings. Prognostic differences by RCB class occurred within 5 years in HR- BC, but extended to 10 years in HR+ BC. RCB-I had slightly worse EFS than pCR in HR- BC and HR+/HER2+ BC (after 5 years), but the same EFS as pCR in HR+/HER2- BC. Complete analysis of all subjects, including neoadjuvant treatments, will be presented at the meeting. PhenotypeOutcomepCRRCB-IRCB-IIRCB-IIIHR+/HER2-Frequency (%)11%10%52%27%(N=1467)5 yr EFS (95% CI)91% (86-96)93% (89-98)82% (79-85)70% (65-75)10 yr EFS (95% CI)84% (75-93)88% (82-95)71% (67-75)52% (46-58)HR+/HER2+Frequency (%)38%18%35%9%(N=762)5 yr EFS (95% CI)94% (91-97)93% (88-98)78% (73-84)49% (37-65)10 yr EFS (95% CI)91% (86-96)79% (70-90)65% (59-73)42% (29-60)HR-/HER2+Frequency (%)66%11%18%5%(N=550)5 yr EFS (95% CI)93% (90-96)88% (79-97)60% (50-71)45% (30-69)10 yr EFS (95% CI)90% (86-94)84% (74-95)56% (46-68)45% (30-69)HR-/HER2-Frequency (%)41%13%33%13%(N=1293)5 yr EFS (95% CI)92% (90-94)85% (79-91)68% (63-72)28% (21-36)10 yr EFS (95% CI)87% (82-91)80% (72-88)63% (58-68)24% (18-33) Citation Format: Christina Yau, Marieke van der Noordaa, Jane Wei, Marie Osdoit, Fabien Reyal, Anne-Sophie Hamy, Marick Lae, Miguel Martin, Maria del Monte, I-SPY 2 TRIAL Consortium, Judy C Boughey, Rebekah Gould, Jelle Wesseling, Tessa Steenbruggen, Maartje van Seijen, Gabe Sonke, Stephen Edge, Stephen-John Sammut, Elena Provenzano, Jean Abraham, Peter Hall, Ashley Graham, Lorna Mackintosh, David Cameron, Alice Wang, Priyanka Sharma, Kimberly Cole, Lajos Pusztai, Mi-Ok Kim, Laura van ‘t Veer, Laura Esserman, W. Fraser Symmans. Residual cancer burden after neoadjuvant therapy and long-term survival outcomes in breast cancer: A multi-center pooled analysis [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 GS5-01.
Abstract CT136: Evaluation of talazoparib in combination with irinotecan in early stage, high-risk HER2 negative breast cancer: Results from the I-SPY 2 TRIAL
Schwab, Richard B. , Clark, Amy S. , Hylton, Nola, Wolfe, Denise, Chien, A. Jo , Forero‐Torres, Andres , Stringer-Reasor, Erica , Nanda, Rita , Jaskowiak, Nora , Haddad, Tufia C. , Han, Heather, Albain, Kathy S. , Ellis, Erin D. , Shah, Payal , Lu, Janice , Tripathy, Debasish , Kemmer, Kathleen, Haley, Barbara , Majure, Melanie, Roesch, Erin , Ewing, Cheryl, Perlmutter, Jane , Melisko, Michelle , Wilson, Amy , Singhrao, Ruby , Veer, Laura van ‘t , Asare, Smita , Berry, Don, Yau, Christina , Li, Wen , Wallace, Anne M. , Boughey, Judy C. , Lee, Catherine A. A. , Isaacs, Claudine , Elias, Anthony , Lang, Julie E. , Yee, Douglas , Vaklavas, Christos , Ewing, Cheryl A. , Helsten, Teresa L. , Symmans, W. Fraser , Rugo, Hope S. , Veer, Laura J. van’t , DeMichele, Angela , Berry, Donald A. , Esserman, Laura J.

Cancer Research | August 7, 2019 | Volume: 79 | Issue: 13_Supplement | Pages: CT136-CT136

10.1158/1538-7445.am2019-ct136 Get It

Abstract Background: I-SPY2 is a multicenter, Phase II trial using response-adaptive randomization within biomarker subtypes to evaluate novel agents as neoadjuvant therapy for high-risk at least T2N0 breast cancer. The primary endpoint is pathologic complete response (pCR) at surgery. The goal is to identify regimens that have ≥ 85% Bayesian predictive probability of success in a 300-patient phase 3 neoadjuvant trial defined by hormone-receptor (HR) and HER2 status, and MammaPrint (MP). Regimens may leave the trial for futility (< 10% probability of success), maximum sample size accrual (with probability of success ≥ 10% and < 85%), or as recommended by the independent DSMB. For HER2- subjects the control arm is weekly paclitaxel x12 then doxorubicin & cyclophosphamide (AC) q2-3 weeks x4. For this arm, paclitaxel was omitted and replaced with maximum tolerated dose PARPi talazoparib with synergy dosed irinotecan (25mg/m2). Paclitaxel could be given adjuvantly for these subjects and non-responding subjects could be taken off of experimental therapy. Methods: Women with tumors ≥ 2.5cm were eligible for screening. MP low/HR+ tumors were ineligible. MRI scans (baseline, 3 cycles after start of therapy, prior to AC, and prior to surgery) were used in a longitudinal statistical model to predict pCR for individual patients. Talazoparib was given at 1mg daily with 25mg/m2 irinotecan q2wks. Analysis was intention to treat. Subjects who switched to non-protocol therapy count as non-pCR. Subjects on experimental therapy at time of arm closure are non-evaluable. Talazoparib/irinotecan (TI) was open only to HER2- tumors and eligible for graduation in 3 of 10 pre-defined signatures: HER2-, HR+HER2- and HR-/HER2-. Results: TI did not meet criteria for graduation and was stopped at the recommendation of the DSMB based on expectations of limited activity beyond that seen with standard treatment. Maximum sample size had been reached at the time of this recommendation and subjects currently receiving TI were allowed to continue or change to standard therapy. Exploratory “as treated” analysis for response in gBRCA mutation carriers showed 6/10 gBRCA carriers attained a pCR in the TI arm. Except for 1 patient these gBRCA pCR subjects had >90% tumor reduction by MRI after TI and prior to AC (range: 68-96%). In the TI arm pCR rates were also higher in subjects with a PARPi7-High/MP2 gene expression signature (0.344 vs 0.146). Expected differences in toxicity were seen between arms including g3/4 peripheral neuropathy on control therapy which included paclitaxel (2.6% vs none) and g3/4 neutropenia with TI (30.2% vs 8.2%). Notably gBRCA mutation carriers receiving TI had higher rates of g3/4 neutropenia (60% vs 25.9%). Conclusion: The I-SPY2 study finds the probability that investigational regimens will be successful in a Phase III neoadjuvant trial; TI did not reach the efficacy threshold of 85% probability of success in Phase III in any of the 3 signatures. However by adding talazoparib with synergy dosed irinotecan we were able to omit paclitaxel and observe similar estimated pCR rates. This informs current work to evolve the I-SPY2 trial design to reduce toxicity without compromising outcomes and develop successful combinations targeted to biology, including DNA repair deficiency. Citation Format: Richard Schwab, Amy S. Clark, Christina Yau, Nola Hylton, Wen Li, Denise Wolfe, A Jo Chien, Anne M. Wallace, Andres Forero-Torres, Erica Stringer-Reasor, Rita Nanda, Nora Jaskowiak, Judy Boughey, Tufia Haddad, Heather S. Han, Catherine Lee, Kathy Albain, Claudine Isaacs, Anthony D. Elias, Erin D. Ellis, Payal Shah, Julie E. Lang, Janice Lu, Debasish Tripathy, Kathleen Kemmer, Douglas Yee, Barbara Haley, Melanie Majure, Erin Roesch, Christos Vaklavas, Cheryl Ewing, Teresa Helsten, W Fraser Symmans, Jane Perlmutter, Hope S. Rugo, Michelle Melisko, Amy Wilson, Ruby Singhrao, Laura van 't Veer, Angela DeMichele, Smita Asare, Don Berry, Laura J. Esserman. Evaluation of talazoparib in combination with irinotecan in early stage, high-risk HER2 negative breast cancer: Results from the I-SPY 2 TRIAL [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT136.
Abstract 2679: Integration of DNA repair deficiency and immune biomarkers to predict which early-stage triple-negative breast cancer patients are likely to respond to platinum-containing regimens vs. immunotherapy: The neoadjuvant I-SPY 2 trial
Wulfkuhle, Julia , Petricoin, Emanuel F. , Hirst, Gillian L. , Asare, Smita , Rugo, Hope, Nanda, Rita , Liu, Minetta C. , Esserman, Laura, Veer, Laura van ‘t , Hirst, Gillian L , Wolf, Denise M. , Yau, Christina , Swigart, Lamorna Brown , Yee, Douglas , DeMichele, Angela , Olopade, Olufunmilayo I. , Veer, Laura J. van’t

Cancer Research | August 7, 2019 | Volume: 79 | Issue: 13_Supplement | Pages: 2679-2679

10.1158/1538-7445.am2019-2679 Get It

Abstract Background: Triple negative breast cancer (TNBC), generally considered aggressive with few options beyond standard chemotherapy, is currently experiencing a period of optimism, with multiple trials showing increased efficacy of platinum containing regimens (with and without PARP-inhibition), and more recently, immunotherapy. In I-SPY 2, veliparib/carboplatin (VC) and the immune checkpoint inhibitor pembrolizumab (Pembro) graduated in the TN subtype. As part of the I-SPY 2 biomarker program, we previously identified the signature PARPi7, a measure of DNA repair deficiency (DRD), as predicting response to VC. As well, immune signatures, including one representing dendritic cells, predicted response to Pembro. Here we investigate the overlap between these biomarkers to identify patient subgroups more likely to respond to immunotherapy or platinum-based therapy and estimate response rates to VC and Pembro in patients positive for one, both, or neither biomarker. Methods: 153 TNBC patients (Control: 85; VC: 39; Pembro: 29) were considered in this analysis. Continuous DNA repair deficiency and immune signatures assayed at the pre-treatment time point were evaluated as published (Wolf, 2017; Danaher, 2017). To identify optimal dichotomizing thresholds, 2-fold cross-validation was repeated 500 times. Bayesian logistic regression was used to estimate pCR rates by arm for patient subsets defined by biomarker combinations. Our study is exploratory with no claims for generalizability; and this analysis does not adjust for multiplicities. Results: Using the optimal dichotomizing cutpoints, 54% of TNBC patients are classified as DRD+, and 67% Immune+. As expected, DRD+ patients have a high estimated pCR rate to VC (75%); and Immune+ patients have a high estimated pCR rate to Pembro (82%). Combining these biomarkers, 40% of TNBC are positive for both biomarkers, 40% for only one biomarker (26% Immune+/DRD-, 14% Immune-/DRD+), and 20% for neither. The Immune+/DRD+ TN subset predicted sensitive to both VC and Pembro has a higher estimated pCR rate to both VC and Pembro relative to control (estimated pCR rates: VC: 75%, Pembro: 73% vs. control: 18%). In contrast, the Immune+/DRD- group, predicted to be sensitive to Pembro, has the highest pCR rate to Pembro (VC: 48%, Pembro: 83% vs. control 21%), whereas the Immune-/DRD+ group is most responsive to VC (VC: 63%, Pembro: 41% vs. control 29%). For the 20% of Immune-/DRD- TNBC patients, their estimated response rates are lower than the biomarker-positive patients (VC: 27%, Pembro: 43% vs. control: 19%). Conclusion: Molecular phenotypes capturing immune activation and DNA repair deficiency may predict response of TNBC and help prioritize selection of platinum or immunotherapy containing regimens. Citation Format: Denise M. Wolf, Christina Yau, Julia Wulfkuhle, Emanuel Petricoin, Lamorna Brown-Swigart, Gillian Hirst, Smita Asare, I-SPY 2 Consortium, Douglas Yee, Angela DeMichele, Hope Rugo, Olufunmilayo Olopade, Rita Nanda, Minetta Liu, Laura Esserman, Laura van t' Veer. Integration of DNA repair deficiency and immune biomarkers to predict which early-stage triple-negative breast cancer patients are likely to respond to platinum-containing regimens vs. immunotherapy: The neoadjuvant I-SPY 2 trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2679.
Quantitative MHC II protein expression levels in tumor epithelium to predict response to the PD1 inhibitor pembrolizumab in the I-SPY 2 Trial.
Wulfkuhle, Julia , Hirst, Gillian L. , Campbell, Michael J. , Nanda, Rita , Liu, Minetta C. , Berry, Donald A. , Veer, Laura van ‘t , Petricoin, Emanuel, Investigators, I-SPY 2, Hirst, Gillian L , Yau, Christina , Wolf, Denise M. , Gallagher, Rosa I. , Swigart, Lamorna Brown , Pusztai, Lajos , Esserman, Laura J. , Veer, Laura J. van’t , Investigators, I-SPY 2

Journal of Clinical Oncology | May 27, 2019 | Volume: 37 | Issue: 15_suppl | Pages: 2631-2631

10.1200/jco.2019.37.15_suppl.2631 Get It

2631 Background: Response to immune checkpoint inhibitors has been associated with immune activation and mutational load within a tumor. Previous results in other tumors have implicated MHC II protein tumor cell expression as a response predictor to immune checkpoint inhibitors. In the I-SPY 2 TRIAL, the anti-PD1 therapeutic antibody pembrolizumab (P) was available to HER2-negative subtypes and graduated in both the HR+/HER2- and TNBC signatures. Pre-specified biomarker analysis was performed to test tumor MHC II expression as a predictor of response to P in the I-SPY 2 TRIAL based on its central role in tumor antigen presentation. Methods: 156 patients (P: 67, controls: 89) had RPPA and pCR data. RPPA-based quantitative data for pan-MHC II protein isotypes HLA-DR/DP/DQ/DX and HLA-DR protein isotype was obtained from LCM-enriched tumor epithelium, and protein levels were assessed for association with pCR in the P and control arms separately using the Wilcoxon Rank Sum test (p < 0.05). Analysis was also performed in the HR+ and HR- subgroups. Markers were analyzed individually; p-values are descriptive and were not corrected for multiple comparisons. Results: Across all P- treated patients, the HLA class II molecules –DR and -DR/DP/DQ/DX had a positive association with response to P (p = 0.014 and p = 0.001). Expression of HLA-DR/DP/DQ/DX also had a positive association with response to P in HR+ tumors. Neither of these associations were seen in the control arm samples. Conclusions: The observation of elevation of MHC II protein expression in HER2- responding patients treated with P suggests that activation of antigen peptide exchange facilitated by these molecules in T and B cells may enhance response to P treatment.
Abstract P3-10-02: Identifying breast cancer molecular phenotypes to predict response in a modern treatment landscape: Lessons from ˜1000 patients across 10 arms of the I-SPY 2 TRIAL
Wolf, DM, Wulfkuhle, Julia , Petricoin, EF, Asare, S, Lee, EP, Pohlmann, Paula R. , Liu, MC, Symmans, F., Berry, Deborah L., Esserman, LJ, Veer, Laura van ‘t , Yau, Christina , Campbell, Marion , Swigart, Lamorna Brown , Hirst, Gillian L. , Zhu, Zheying , Delson, Amy , Hylton, Nola M. , DeMichele, Angela , Yee, Douglas , Berry, D, Veer, Laura J. van’t , Pohlmann, Paula

Cancer Research | May 11, 2019 | Volume: 79 | Issue: 4_Supplement | Pages: P3-10-02-P3-10-02

10.1158/1538-7445.sabcs18-p3-10-02 Get It

Abstract Background: The explosion in new treatment options targeting immune checkpoints, HER signaling, DNA repair deficiency, AKT, and other pathways calls for updated breast cancer subtypes beyond HR and HER2 status to predict which patients will respond to which treatments. Here we leverage the I-SPY 2 TRIAL biomarker program over the past 8 years across 10 treatment arms to elucidate a minimal set of biomarkers that may improve response prediction in a modern treatment context, and to investigate which new patient phenotypes are identified by these response-predictive biomarkers. Methods: 986 patients were considered in this analysis. Treatments included paclitaxel alone (or with trastuzumab (H) in HER2+) or combined with investigational agents: veliparib/carboplatin (VC); neratinib; MK2206; ganitumab; ganetespib; AMG386; TDM1/pertuzumab (P); H/P; and pembrolizumab (Pembro). 24 prospectively defined, mechanism-of-action and pathway-based expression and phospho-protein signatures/biomarkers assayed from pre-treatment biopsies were previously found to be predictive in a particular agent/arm in pre-specified analysis. Here we evaluate these biomarkers in all patients. We assessed association between each biomarker and response in the population as a whole and within each arm and HR/HER2 subtype using a logistic model. To identify optimal dichotomizing thresholds for select biomarkers, 2-fold cross-validation was repeated 500 times. Our analysis is exploratory and does not adjust for multiplicities. Results: Our initial set of 24 predictive biomarkers reflects DNA repair deficiency (n=2), immune activation (n=7), ER signaling (n=2), HER2 signaling (n=4), proliferation (n=2), phospho-activation of AKT/mTOR (n=2), and ANG/TIE2 (n=1) pathways, among others. Biomarkers reflecting similar biology are correlated and cluster together. We make use of this correlation structure to reduce the dimensionality of the biomarker set to five predictive signals: proliferation, DNA repair deficiency (DRD), immune-engaged (Immune+), luminal/ER (lum), and HER2-activated. These biomarkers, when dichotomized, identify patient groups with differential predicted sensitivities to I-SPY 2 agents and are present at different proportions within receptor subtypes. For instance, in the HER2- subset, Immune+/DRD+ patients are predicted sensitive to both VC and Pembro, and account for 39% of TN, but only 12% of HR+HER2-. On the other end of the spectrum, only 17% of TN are Immune-/DRD-, compared to the majority (56%) of HR+HER2-. There are also subsets of patients positive for only one marker. For the HER2+ subset, 67% are HER2-activated+, and 25% lum+; of these HER2-activated+ patients are more likely to be Immune+ (44%), vs 23% in lum+. HER2-activated+/Immune+ patients have higher predicted sensitivity to HER2-targeted agents than lum+ or Immune- patients. In all, these molecular phenotypes predict sensitivity to one or more I-SPY 2 investigational agents for 75% of the ˜ 1000 patients. Conclusion: Molecular phenotypes reflecting proliferation, immune engagement, HER2-activation, luminal/ER-signaling, and DNA repair deficiency may provide a roadmap to guide treatment prioritization for emerging therapeutics. Citation Format: Wolf DM, Yau C, Wulfkuhle J, Petricoin E, Campbell M, Brown-Swigart L, Hirst G, Asare S, Zhu Z, Lee EP, Delson A, Pohlmann P, I-SPY 2 TRIAL Consortium, Hylton N, Liu MC, Symmans F, DeMichele A, Yee D, Berry D, Esserman L, van 't Veer L. Identifying breast cancer molecular phenotypes to predict response in a modern treatment landscape: Lessons from ˜1000 patients across 10 arms of the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-10-02.
Abstract PD6-14: Analysis of DNA repair deficiency biomarkers as predictors of response to the PD1 inhibitor pembrolizumab: Results from the neoadjuvant I-SPY 2 trial for stage II-III high-risk breast cancer
Sanil, Ashish, Singhrao, Ruby , Investigators, I-SPY 2 TRIAL, Asare, Smita , Berry, Donald A. , Esserman, L., Veer, Laura van ‘t , Nanda, Rita , Yau, Christina , Wolf, Denise M. , Swigart, Lamorna Brown , Hirst, Gillian L. , Investigators, I-SPY 2 TRIAL, DeMichele, Angela , Veer, Laura J. van’t , Liu, Ming , Yee, Douglas

Cancer Research | February 15, 2018 | Volume: 78 | Issue: 4_Supplement | Pages: PD6-14-PD6-14

10.1158/1538-7445.sabcs17-pd6-14 Get It

Abstract Background: Pembrolizumab (P), an anti-PD-1 immune checkpoint inhibitor, has been approved for treatment of microsatellite instability-high and mismatch repair deficient cancers. In I-SPY 2, patients were randomized to receive standard chemotherapy alone or in combination with an experimental agent. P was one of the experimental agents evaluated in HER2- patients in I-SPY 2 and graduated in the TN, HR+HER2-, and HER2- signatures. We hypothesize that a combination of two signatures predicting response to veliparib/carboplatin therapy in I-SPY 2 [MammaPrint High2 (MP2)/PARPi7-high] and reflecting DNA damage repair deficiency, may also predict response to P. In addition, we also tested 9 gene expression signatures reflecting different aspects of DNA damage and repair: FA, MMR, BER, HR, TLS, NER, NHEJ, DR, and DNA damage sensing (DDS) pathways. Methods: Data from 249 patients (P: 69 and controls: 180) were available. Pre-treatment biopsies were assayed using Agilent gene expression arrays. All I-SPY 2 qualifying biomarker analyses follow a pre-specified analysis plan. We used logistic modeling to assess biomarker performance. A biomarker is considered a specific predictor of P response if it associates with response in the P arm but not the control arm, and if the biomarker x treatment interaction is significant (likelihood ratio test, p&lt;0.05). This analysis is also performed adjusting for HR status as a covariate, and within receptor subsets, sample size permitting. For successful biomarkers, we use Bayesian modeling to estimate the pCR rates of 'predicted sensitive' patients in each arm. Our statistics are descriptive rather than inferential and do not adjust for multiplicities of other biomarkers outside this study. Results: MP2 status associates with pCR in P (OR=7.7; p=0.00021), but also to a lesser extent in the control arm (OR=2.4:p=0.045), with an OR ratio of 3.3 which trends toward significance, even after adjusting for HR status (LR p=0.083). A majority of TN patients are MP2; and TN/MP2 patients have an estimated pCR rate of 67% in P (vs. 23% in control). Although only ~30% of HR+HER2- patients were MP2, their estimated pCR rate in P is 61%, compared to 29% in unselected HR+/HER2- patients. PARPi7 predicted response in the P arm only in the HR+HER2- group (LR p= 0.025), but not in the population as a whole or the TN subtype. Combining MP2 and PARPi7 into MP2/PARPi7-high did not improve performance over MP2 as a single biomarker. Of the 9 DDR pathway signatures tested, both BER and DDS associate with pCR in P, but only DDS (which includes ATM, ATR, CHEK1-2) associates with pCR in the P arm (LR p=0.00029), and not the control arm (LR p=0.53), with a significant interaction with treatment (LR p=0.0064) that retains significance in a model adjusting for HR status. When dichotomized to optimize the biomarker x treatment interaction, the estimated pCR rate is 75% in P vs 18% in control, in the DDS+ subset. Conclusion: In this small study, MP2 status and a DNA damage sensing pathway but not the PARPi7 or other repair pathways show promise as predictive biomarkers for immune checkpoint inhibition therapy in breast cancer. Citation Format: Yau C, Wolf D, Brown-Swigart L, Hirst G, Sanil A, Singhrao R, I-SPY 2 TRIAL Investigators, Asare S, DeMichele A, Berry D, Esserman L, van 't Veer L, Nanda R, Liu M, Yee D. Analysis of DNA repair deficiency biomarkers as predictors of response to the PD1 inhibitor pembrolizumab: Results from the neoadjuvant I-SPY 2 trial for stage II-III high-risk breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD6-14.
Abstract P3-06-29: MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL
Sanil, Ashish, Chien, Jo, Nanda, Rita , Chiu, Steven, Albain, Kathy S. , Kaplan, Hank, Moulder, Stacey, Viscusi, Rebecca K., Northfelt, Donald W. , Edmiston, Kirsten K., Styblo, Toncred M., Haley, Barbara , Flynn, Susan, Buxton, Meredith , Hylton, Nola, Paoloni, Melissa, Berry, Don, Liu, Minetta C. , Park, John W., Veer, Laura van ‘t , Yau, Christina , Wolf, Denise M. , Wallace, Anne M. , Boughey, Judy C. , Yee, Douglas , Tripathy, Debu , DeMichele, Angela , Isaacs, Claudine , Elias, Anthony , Swigart, Lamorna Brown , Hirst, Gillian L. , Symmans, W. Fraser , Esserman, Laura J. , Berry, Donald A. , Veer, Laura J. van’t

Cancer Research | May 4, 2015 | Volume: 75 | Issue: 9_Supplement | Pages: P3-06-29-P3-06-29

10.1158/1538-7445.sabcs14-p3-06-29 Get It

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score &lt;-0.154. MP1/MP2 classification was added to HR and HER2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. Neratinib (N), one of the experimental agents evaluated in I-SPY 2, graduated in the HR-HER2+ signature. All patients received at least standard chemotherapy (paclitaxel followed by doxorubicin/cyclophosphamide; T-&gt;AC). HER2- patients were randomized to receive N+T- &gt;AC vs. T-&gt;AC. For HER2+ patients, neratinib was administered in place of trastuzumab (N+T-&gt;AC vs. H+T-&gt;AC). Here, we assess the performance of MP1/MP2 class as a specific biomarker of neratinib response. Methods: 115 patients in the neratinib arm and 76 concurrently randomized controls had Agilent 44K microarrays and pCR data available for analysis. We assess association between MP1/MP2 and response in the neratinib and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p &lt; 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate, and in receptor subsets. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Our analyses do not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: There are 133 MP1 patients (neratinib: 74, Control: 59) and 58 MP2 patients (neratinib: 41, Control: 17), 84% (49) of which are Her2-. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. Neratinib (n=115)Control (n=76)MP1 (n=74)MP2 (n=41)MP1 (n=59)MP2 (n=17)HER2- (n=105)0 / 1715 / 337 / 395 / 16HER2+ (n=86)22 / 574 / 85 / 200 / 1 MP2, one of the 10 eligible signatures, did not meet the graduation threshold; and MP1/MP2 did not show a significant biomarker x treatment interaction (OR in neratinib relative to control arm = 1.25). The MP1/MP2 x treatment interaction remains non-significant after adjustment for HR and HER2 status (p=0.54). In HER2- patients receiving neratinib, 45% (15/33) of MP2 patients achieved a pCR, compared to 0% (0/17) of MP1 patients. In the HER2- controls, there is a 31% pCR rate in MP2 (5/16) vs. 18% in MP1 (7/39) patients (OR=2.14). This difference in performance between treatment arms appears significant (p=0.041). 90% of HER2+ patients are MP1, thus MP1/MP2 status x treatment interaction within the HER2+ subtype cannot be evaluated. Conclusion: Within the I-SPY 2 population as a whole, MP1/MP2 stratification does not appear to be a specific biomarker of response to neratinib relative to the control arm. The number of HER2- patients is small and precludes any definitive conclusion, but these data motivate further investigation of the biological mechanisms distinguishing MP1 from MP2 to better understand chemotherapy and/or neratanib responsiveness. Citation Format: Christina Yau, Denise M Wolf, Ashish Sanil, Jo Chien, Anne Wallace, Judy Boughey, Doug Yee, Debu Tripathy, Angela DeMichele, Rita Nanda, Steven Chiu, Claudine Isaacs, Kathy Albain, Hank Kaplan, Stacey Moulder, Rebecca Viscusi, Donald Northfelt, Kirsten Edmiston, Anthony Elias, Toncred Styblo, Barbara Haley, Lamorna Brown-Swigart, Susan Flynn, Gillian L Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, W Fraser Symmans, Laura Esserman, Don Berry, Minetta C Liu, John W Park, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-29.
Abstract P3-06-25: MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL
Sanil, Ashish, Chien, Jo, Kaplan, Hank, Albain, Kathy S. , Viscuzi, Rebecca, Moulder, Stacey, Chui, Steven, Styblo, Toncred M., Edmiston, Kirsten K., Northfelt, Donald W. , Haley, Barbara , Flynn, Susan, Buxton, Meredith , Hylton, Nola, Paoloni, Melissa, Symmans, Fraser, Berry, Don, Veer, Laura van ‘t , Wolf, Denise M. , Yau, Christina , Wallace, Anne M. , DeMichele, Angela , Yee, Douglas , Isaacs, Claudine , Boughey, Judy C. , Khan, Qamar J. , Elias, Anthony , Tripathy, Debu , Swigart, Lamorna Brown , Hirst, Gillian L. , Esserman, Laura J. , Berry, Donald A. , Rugo, Hope S. , Olopade, Olufunmilayo I. , Veer, Laura J. van’t

Cancer Research | May 4, 2015 | Volume: 75 | Issue: 9_Supplement | Pages: P3-06-25-P3-06-25

10.1158/1538-7445.sabcs14-p3-06-25 Get It

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score &lt;-0.154. MP1/MP2 classification was added to HR and Her2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. HER2- patients were randomized to receive standard chemotherapy or the oral PARP inhibitor veliparib in combination with carboplatin (V/C) and chemotherapy. V/C graduated in the triple-negative (TN) signature, where MP2 was not an eligible signature for graduation. Here, we assess the performance of MP1/MP2 class as a specific biomarker of response to V/C. Methods:115 HER2- patients (V/C: 71 and concurrent controls: 44) were considered in this analysis. We assess association between MP1/MP2 and response in the V/C and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p &lt; 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate. To assess MP1/MP2 in the context of the graduating signature, we added the MP2 patients to the graduating TN subset and evaluated the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). This analysis does not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: In the V/C arm vs. concurrent controls, there were 66 MP1 (V/C: 32, Control: 34) and 49 MP2 patients (V/C: 39, Control: 10), 78% of which are TN. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. V/C (n=71)Control (n=44)MP1 (n=32)MP2 (n=39)MP1 (n=34)MP2 (n=10)TN (n=59)3 / 819 / 303 / 132 / 8HR+HER2- (n=56)1 / 244 / 94 / 210 / 2 The OR between MP1/MP2 risk groups for predicting pCR is 9.71 in the V/C arm (p=6.63E-05), in comparison to an OR of 0.97 in the control arm (p=1). There is a significant biomarker x treatment interaction (p=0.023), which remains upon adjusting for HR status (p= 0.028). Based on the I-SPY 2 Bayesian model, a Phase III trial with 300 MP2 patients has a 95% predictive probability of success. When the MP2 patients are added to the graduating TN subset, the OR associated with V/C is 4.36, which is comparable to that of the TN signature (OR: 4.29), while increasing the prevalence of biomarker-positive patients by ∼10%. Conclusion: In our exploratory analysis, MP2 suggests higher sensitivity to V/C combination therapy relative to controls. This observation has prompted an investigation into the biological mechanisms distinguishing the MP1/MP2 subtype that may account for this specificity. Citation Format: Denise M Wolf, Christina Yau, Ashish Sanil, Jo Chien, Anne Wallace, Angela DeMichele, Hank Kaplan, Doug Yee, Claudine Isaacs, Kathy Albain, Rebecca Viscuzi, Judy Boughey, Stacey Moulder, Steven Chui, Qamar Khan, Toncred Styblo, Kirsten Edmiston, Donald Northfelt, Anthony Elias, Barbara Haley, Debu Tripathy, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, Fraser Symmans, Laura Esserman, Don Berry, Hope Rugo, Olufunmilayo I. Olopade, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-25.