Hirst, Gillian L.

Abstract Background: Pembrolizumab (Pembro), an anti-PD-1 immune checkpoint inhibitor, has been approved for the treatment of a variety of cancers including melanoma, non-small cell lung cancer, head and neck squamous cell carcinoma, and urothelial carcinoma. Pembro was recently evaluated in HER2- breast cancer patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the triple negative (TN), HR+HER2-, and HER2- signatures. HER2- patients were randomized to receive Pembro+paclitaxel followed by doxorubicin/cyclophosphamide (P+T -> AC) vs. T -> AC. We and others have shown that TN breast cancers tend to have high numbers of immune infiltrates, including T cells and tumor associated macrophages (TAMs). We evaluated expression signatures representing 14 immune cell types (TILs, T cells, CD8 T cells, exhausted T cells, Th1, Tregs, cytotoxic cells, NK, NK CD56dim, dendritic cells, mast cells, B cells, macrophages, and neutrophils) as specific predictors of response to Pembro. Methods: Data from 248 patients (Pembro: 69; controls: 179) were available. Pre-treatment biopsies were assayed using Agilent gene expression arrays. Signature scores are calculated by averaging cell type specific genes. 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 Pembro response if it associates with response in the Pembro arm but not the control arm, and if the biomarker x treatment interaction is significant (likelihood ratio test, p<0.05). This analysis is also performed adjusting for HR status as covariates, and within receptor subsets. 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: 10 out of the 14 cell-type signatures tested are associated with response in the Pembro arm. Higher expression levels of 9 of these cell-type signatures are associated with higher pCR rates (T cells, exhausted T cells, Th1, cytotoxic cells, NK, NK CD56dim, dendritic cells, B cells, and macrophages), whereas higher mast cell signature expression is associated with non-pCR. Interestingly, many of these same signatures also associate or trend towards association with response in the control arm; and in a model adjusting for HR status, only 3 of these signatures (Th1, B cells and dendritic cells) show significant interaction with treatment. Within the whole population and the TN subtype, the dendritic cell signature is the strongest predictor of specific response to Pembro (OR/1SD: 4.04 and 4.4, LR p < 0.001 overall and in TN). Although other immune signatures (T cells, exhausted T cells, NK, and macrophages) also associate with response in the Pembro arm in the TN subtype, only the dendritic cell and Th1 signatures have a significant interaction with treatment. In contrast, in the HR+HER2- subtype, only 3 signatures (Th1, B cells, and mast cells) associate with response to Pembro; but none of these signatures have significant interaction with treatment. Of note, in both the Pembro and control arms, HR+HER2- patients with higher average mast cell marker expression have lower pCR rates (OR/1SD: 0.33 and 0.51, LRp: 0.006 and 0.04 in Pembro and control arm). Conclusion: As expected, multiple immune cell expression signatures are predictive of response in the Pembro arm; but only dendritic cells and Th1 cells are specific to Pembro in both the population as a whole and the TN subtype. Interestingly, the presence of mast cells may impede response, especially in HR+HER2- patients. Correlation of these signatures with multiplex-IF immune markers is pending. Citation Format: Campbell M, Yau C, Borowsky A, Vandenberg S, Wolf D, Rimm D, Nanda R, Liu M, Brown-Swigart L, Hirst G, Asare S, van't Veer L, Yee D, DeMichele A, Berry D, Esserman L. Analysis of immune infiltrates (assessed via multiplex fluorescence immunohistochemistry) and immune gene expression signatures as predictors of response to the checkpoint inhibitor pembrolizumab in the neoadjuvant I-SPY 2 trial [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 PD6-08.

Abstract Background: Pathological complete response (pCR) is accepted by FDA as a surrogate endpoint for accelerated approval of targeted agents in combination with chemotherapy based on better long-term outcomes compared to residual disease (Cortazar 2014). Methods: The multi-center, adaptively-randomized I-SPY2 platform trial uses pCR as the primary endpoint to identify investigational agents that will improve outcomes in women with stage 2/3 breast cancer with high risk of early recurrence, across all signatures, based on hormone receptor (HR), HER2, and 70-gene (MammaPrint) status. For patients with HR+ HER2- tumors, only 70-gene (Mammaprint) high-risk patients are enrolled. To date, 1200+ patients have been randomized to one of 14 arms: control (paclitaxel followed by AC); veliparib/carboplatin; neratinib; MK2206; trebananib; trastuzumab/pertuzumab; ado-trastuzumab emtansine/pertuzumab; pembrolizumabx4; ganitumab/metformin; ganetespib; PLX-3397. 7 agents graduated in at least one signature (> 85% probability of success in a 300-patient phase III confirmatory trial); 2 did not graduate; 1 stopped for toxicity, and 3 are enrolling (patritumab/trastuzumab, talazoparib/irinotecan, pembrolizumabx8). Local pathologists were centrally trained using the Residual Cancer Burden (RCB) assessment to ensure uniform evaluation and response classification; RCB 0 = pCR. Results: We evaluated the relationship between pCR and event free (EFS) and distant disease free survival (DDFS) in the first 522 pts (median follow-up:2.5 years). 180 pts achieved pCR (36%) while 338 did not (RCB=1-3). There were 82 EFS and 65 DRFS events. Over the entire group (including all arms), pCR was highly associated with 3-year EFS (p<0.001 for both). Pts achieving pCR had a 3% recurrence risk (RR) at 3 years; those with non-pCR had 24% RR over this time period. For distant recurrence, the 3-year RR with pCR was 2%, compared to 20% in pts with non-pCR. As expected, pCR rates varied by breast cancer subtype (HR+/HER2: 18% (35/196), HR+/HER2+: 40% (33/82), HR-/HER2+:68% (34/50), HR-/HER2-:41% (76/188)). The relationship between pCR and EFS was significant and clinically impactful within each subtype. 3-year survival (pCR group)Hazard Ratio OverallOverallHR+/HER2-HER2+TNBCEFS97%0.08 (0.03-0.23)0.14 (0.02-1.04)0 (NA)0.11 (0.03-0.37)DDFS98%0.08 (0.03-0.26)0.17 (0.01-1.23)0 (NA)0.09 (0.02-0.40) Conclusions: The first long-term efficacy results from the I-SPY2 TRIAL demonstrate that achieving pCR is a very strong surrogate endpoint for improved EFS and DDFS in a high-risk population, across all treatment arms, regardless of subtype. I-SPY2 shows substantially lower estimated EFS hazards for patients achieving pCR, compared to the 5 yr EFS hazard ratio for pCR vs not in Cortazar (hazard ratio 0.49), demonstrating important differences between a metaanalysis compared to a platform trial with uniform high-risk eligibility, standardized pathology assessment, and multiple targeted therapies. Our data support the use of pCR as a primary endpoint for accelerated approval of new drugs if EFS is evaluated in the same population. Based on these findings, the I-SPY2 TRIAL will test whether therapy can be deescalated or escalated for individual patients with the goal of achieving pCR for all. Citation Format: Yee D, DeMichele A, Isaacs C, Symmans F, Yau C, Albain KS, Hylton NM, Forero-Torres A, van't Veer LJ, Perlmutter J, Rugo HS, Melisko M, Chen Y-Y, Balassanian R, Krings G, Datnow B, Hasteh F, Tipps A, Weidner N, Zhang H, Tickman R, Thornton S, Ritter J, Amin K, Klein M, Chen B, Keeney G, Ocal T, Feldman M, Klipfel N, Sattar H, Mueller J, Gwin K, Baker G, Kallakury B, Zeck J, Duan X, Ersahin C, Gamez R, Troxell M, Mansoor A, Grasso LeBeau L, Sams S, Wisell J, Wei S, Harada S, Vinh T, Stamatakos MD, Tawfik O, Fan F, Adams A, Rendi M, Minton S, Magliocco A, Sahoo S, Fang Y, Hirst G, Singhrao R, Asare SM, Wallace AM, Chien AJ, Ellis ED, Han HS, Clark AS, Boughey JC, Elias AD, Nanda R, Korde L, Murthy R, Lang J, Northfelt D, Khan Q, Edmiston KK, Viscusi R, Haley B, Kemmer K, Zelnak A, Berry DA, Esserman LJ. Pathological complete response predicts event-free and distant disease-free survival in the I-SPY2 TRIAL [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 GS3-08.

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 <-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->AC). HER2- patients were randomized to receive N+T- >AC vs. T->AC. For HER2+ patients, neratinib was administered in place of trastuzumab (N+T->AC vs. H+T->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 < 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 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 <-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 < 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.

Abstract Background: We hypothesize that response to the pan-ERBB inhibitor, neratinib (N), may be predicted by pre-treatment HER2-EGFR signaling. In the I-SPY 2 TRIAL, N graduated in the HR-/HER2+ signature. All patients received at least standard chemotherapy. For HER2+ patients, N was administered in place of trastuzumab. We evaluated 18 HER family signaling proteins as biomarkers of N response using reverse phase protein microarray (RPMA) data from pre-treatment LCM purified tumor epithelium. Methods: 168 patients (N: 106, concurrent controls: 62) had RPMA and pCR data. 18 biomarkers relating to HER family signaling were evaluated: AKT S473, AKT T308, EGFR, EGFR Y1068, EGFR Y1148, EGFR Y1173, EGFR Y992, ERBB2, ERBB2 Y1248, ERBB3 total, ERBB3 Y1289, ERK1/2 T202/Y204, Heregulin, mTOR, mTOR S2448, PI3K p85 Y458/p55 Y199, PTEN S380, and SHC Y317. We assessed association between biomarker and response in the N and control arms alone (likelihood ratio test), and relative performance between arms (biomarker x treatment interaction) using a logistic model. Analysis was also performed adjusting for HR/HER2 status. In an exploratory analysis, we selected the marker with the greatest interaction (phosphorylated EGFR (Y1173)) to dichotomize patients optimally based on the data and assessed it in the context of the graduating signature by adding the EGFR Y1173-High patients to the HR-/HER2+ subtype and evaluating the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data and does not account for multiplicities. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Results: 7 HER pathway markers (EGFR Y1068, EGFR Y1173, EGFR Y992, ERBB2 total, ERBB2 Y1248, ERBB3 Y1289, SHC Y317) are associated with response in the N but not the control arm. However, the difference in performance between arms did not reach significance by permutation testing. Adjusting for HR/HER2 status, EGFR Y1173 shows a significant biomarker x treatment interaction (p = 0.049). In an exploratory analysis, we dichotomized patients by their EGFR Y1173 levels and evaluated the distribution of pCR rates (Table 1). Neratinib (n=106)Control (n=62)EGFR Y1173 Low (n=31)EGFR Y1173 High (n=75)EGFR Y1173 Low (n=29)EGFR Y1173 High (n=33)HR-/HER2+ (n=28)0 / 412 / 181 / 11 / 5Not HR-/HER2+ (n=140)3 / 2724 / 575 / 285 / 28Table 1 OR between EGFR Y1173 groups in the N relative to control arm is 10.1. When EGFR Y1173 High patients are added to the graduating HR-/HER2+ subset, the OR associated with treatment is 3.2 and is comparable to that in the HR-/HER2+ signature (OR: 2.1), while increasing the prevalence of biomarker-positive patients by ∼50%. Evaluation of EGFR Y1173 under the I-SPY 2 Bayesian model is pending. Conclusion: Our sample size is too small to draw definitive conclusions. Our exploratory analysis reveals that HER family phosphoproteins associate with response to N, but only phosphorylated EGFR Y1173 appears to add value to the graduating signature. Given that this biomarker would expand the patient population that may benefit, it merits evaluation in other ongoing trials of neratinib. Citation Format: Julia D Wulfkuhle, Christina Yau, Denise M Wolf, Rosa I Gallagher, Ashish Sanil, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, I-SPY 2 TRIAL Investigators, Meredith Buxton, Angela DeMichele, Nola Hylton, William F Symmans, Laura van't Veer, Douglas Yee, Melissa Paoloni, Laura Esserman, Donald Berry, Minetta C Liu, John W Park, Emanuel F Petricoin III. Evaluation of HER family protein signaling network as a predictive biomarker for pCR for breast cancer patients treated with neratinib 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 P3-06-15.