Hirst, Gillian L.

PURPOSEThe phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin is a key pathway of survival and therapeutic resistance in breast cancer. We evaluated the pan-Akt inhibitor MK-2206 in combination with standard therapy in patients with high-risk early-stage breast cancer.PATIENTS AND METHODSI-SPY 2 is a multicenter, phase II, open-label, adaptively randomized neoadjuvant platform trial that screens experimental therapies and efficiently identifies potential predictive biomarker signatures. Patients are categorized by human epidermal growth factor receptor 2 (HER2), hormone receptor (HR), and MammaPrint statuses in a 2 × 2 × 2 layout. Patients within each of these 8 biomarker subtypes are adaptively randomly assigned to one of several experimental therapies, including MK-2206, or control. Therapies are evaluated for 10 biomarker signatures, each of which is a combination of these subtypes. The primary end point is pathologic complete response (pCR). A therapy graduates with one or more of these signatures if and when it has an 85% Bayesian predictive probability of success in a hypothetical phase III trial, adjusting for biomarker covariates. Patients in the current report received standard taxane- and anthracycline-based neoadjuvant therapy without (control) or with oral MK-2206 135 mg/week.RESULTSMK-2206 graduated with 94 patients and 57 concurrently randomly assigned controls in 3 graduation signatures: HR-negative/HER2-positive, HR-negative, and HER2-positive. Respective Bayesian mean covariate-adjusted pCR rates and percentage probability that MK-2206 is superior to control were 0.48:0.29 (97%), 0.62:0.36 (99%), and 0.46:0.26 (94%). In exploratory analyses, MK-2206 evinced a numerical improvement in event-free survival in its graduating signatures. The most significant grade 3-4 toxicity was rash (14% maculopapular, 8.6% acneiform).CONCLUSIONThe Akt inhibitor MK-2206 combined with standard neoadjuvant therapy resulted in higher estimated pCR rates in HR-negative and HER2-positive breast cancer. Although MK-2206 is not being further developed at this time, this class of agents remains of clinical interest.

Abstract Background: Pembrolizumab (Pembro), an anti-PD-1 immune checkpoint inhibitor, has been approved for the treatment of a variety of cancers. 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. TN breast cancers tend to have high numbers of immune infiltrates, including T cells and tumor associated macrophages (TAMs). We utilized multiplex multispectral imaging to evaluate the presence and spatial proximity of various immune cell populations as specific predictors of response to Pembro. Methods: Pre-treatment biopsies were available from 54 patients. FFPE sections were immunostained using Opal fluorescence reagent kits on a fully automated Ventana Discovery platform and imaged with a Vectra automated imaging system. Image analyses were performed with a variety of software packages. Immune biomarkers included CD3, CD8, FoxP3, CD68, PD-1, PD-L1, and cytokeratins. Cell densities were determined per area of tissue. Spatial analyses were performed to quantitate proximity of cell types. We used logistic regression with the likelihood ratio test to evaluate associations between pathologic complete response (pCR) with immune cell counts, ratios, and spatial proximity measurements. This analysis was also performed adjusting for HR status, and within receptor subsets, sample size permitting. Our statistics are descriptive rather than inferential and do not adjust for multiple hypothesis testing or multiplicities of other biomarkers outside this study. Results: Densities of CD3+ T cells ranged from 193-5155 cells/mm2, with CD8+ cytotoxic T cells (Tc) ranging from 103 to 3774 cells/mm2 and FoxP3+ Tregs from 0-416 cells/mm2. Densities of PD-1+ T cells and PD-1+ Tc cells ranged from 0-1341 cells/mm2 and 0-698 cells/mm2, respectively. Macrophage cell densities ranged from 84-2644 cells/mm2. PD-L1+ tumor cell densities ranged from 0-2981 cells/mm2. High PD-L1 expression (>=10% of tumor cells positive for PD-L1) was observed in 12% of the cases. Overall T cell density was positively associated with pathological complete response (pCR), as were Treg cell density and PD-1+ T cell density. The ratio of macrophages to Tc cells was negatively associated with response. Finally, the spatial distribution of CD3+ T cells in proximity to cancer cells correlated positively with pCR. Conclusion: Cell density, immune cell ratios and spatial resolution provide insight to response and resistance. We confirmed the observation that T cell density predicts pCR, but more specifically that Treg and PD1+ T cell densities increase the chance of pCR. An increase in macrophages relative to cytotoxic T cells predicts resistance. The closer the T cells are to the tumor, the better the response. These results demonstrate the utility of characterizing the immune microenvironment, in the context of therapy with immuno-oncology agents, not only to predict response, but to gain insight and learn now to potentiate agents and combinations. Citation Format: Michael J. Campbell, Christina Yau, Jennifer Bolen, Scott Vandenberg, Clifford Hoyt, Lamorna Brown-Swigart, Gillian Hirst, Rita Nanda, Minetta Liu, Smita Asare, Laura van'tVeer, Douglas Yee, Angie DeMichele, Don Berry, Laura Esserman, I SPY 2 TRIAL Investigators. Analysis of immune cell infiltrates as predictors of response to the checkpoint inhibitor pembrolizumab in 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 CT003.

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.

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 ctDNA analysis offers a non-invasive approach for monitoring response and resistance to treatment. Serial ctDNA testing during neoadjuvant therapy (NAT) may provide early indicators of emerging resistance and disease progression. In this study, we analyzed ctDNA from high-risk early breast cancer patients who received NAT and definitive surgery in the I-SPY 2 TRIAL (NCT01042379). We hypothesize that (1) assessment of ctDNA levels early in treatment will improve the performance of molecular and imaging-based predictors of pathologic complete response (pCR) to NAT; and (2) levels of ctDNA after NAT are associated with residual cancer burden and recurrence [distant recurrence free survival (DRFS)]. Methods: ctDNA analysis was performed in 84 high-risk stage II and III breast cancer patients randomized to neoadjuvant investigational agent (n=52), AKT inhibitor MK-2206 (M) in combination with paclitaxel (T) followed by doxorubicin and cyclophosphamide (AC) (M+T-&gt;AC), or standard-of-care (T-&gt;AC) (n=32). HER2+ patients also received trastuzumab (H). Serial plasma was collected before NAT (T0), early treatment (3 weeks, T1), between regimens (12 weeks, T2), and after NAT prior to surgery (T3). Mutational profiles derived from pretreatment tumor biopsy and normal matched DNA whole exome sequencing were used to design personalized assays targeting 16 patient-specific somatic variants to detect ctDNA in serial plasma. Results: Of the 84 patients in this study, 43% were HR-/HER2- (TNBC), 35% HR+/HER2-, and 23% HER2+. In total, 74% (61 of 83), 35% (28 of 79), 14% (9 of 65), and 8% (5 of 61) were positive for ctDNA at timepoints T0, T1, T2, and T3, respectively. At T0, ctDNA positivity and levels (average number of mutant molecules detected per mL) were significantly associated with increased tumor burden (by clinical and MRI examination), more aggressive tumor biology (as reflected in higher Mammaprint scores and grade) and subtype (HER2+ and TNBC). Twenty-seven percent (27%) of the 84 patients achieved a pCR and all patients who were ctDNA-positive at T3 (n=5) did not achieve a pCR. Currently, data are being collected to: (1) assess the relationship of ctDNA and MRI imaging in predicting tumor response to therapy; (2) examine the relationship of ctDNA levels before and after NAT with 3-year DRFS and event-free survival (EFS). The results of these analyses will be presented at the SABCS 2018 meeting. Conclusions: Our study provides a platform to evaluate the clinical significance of ctDNA for serial monitoring of response to NAT. Accurate and early response prediction by highly sensitive ctDNA analysis can facilitate a timely and judicious change in treatment to improve patients' chances of achieving a pCR. Finally, personalized ctDNA testing may complement imaging and pathologic evaluation of tumor response to fine-tune pCR as a surrogate endpoint for improved DRFS and EFS. Citation Format: Magbanua MJM, Brown-Swigart L, Hirst GL, Yau C, Wolf D, Ma AA, Bergin E, Venters S, Sethi H, Wu H-T, Salari R, Tin T, Sawyer S, Louie M, Zimmermann B, Lin C-HJ, Keats J, Liang WS, Cuyugan L, Enriquez D, Tripathy D, Chien AJ, Forero A, DeMichele A, Liu M, Delson AL, Asare S, Esserman L, van't Veer L, I-SPY 2 Consortium. Personalized serial circulating tumor DNA (ctDNA) analysis in high-risk early stage breast cancer patients to monitor and predict response to neoadjuvant therapy and outcome in 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 PD2-01.

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 Background: Patients achieving a pathologic complete response (pCR) following neoadjuvant therapy have significantly improved event-free survival relative to those who do not; and pCR is an FDA-accepted endpoint to support accelerated approval of novel agents/combinations in the neoadjuvant treatment of high risk early stage breast cancer. Previous studies have shown that recurrence risk increased with increasing burden of residual disease (as assessed by the RCB index). As well, these studies suggest that patients with minimum residual disease (RCB-I class) also have favorable outcomes (comparable to those achieving a pCR) within high risk tumor subtypes. In this study, we assess whether integrating RCB with MRI functional tumor volume (FTV), which in itself is prognostic, can improve prediction of distant recurrence free survival (DRFS); and identify a subset of patients with minimal residual disease with comparable DRFS as those who achieved a pCR. Imaging tools can then be used to identify the subset that will do well early and guide the timing of surgical therapy. Method: We performed a pooled analysis of 596 patients from the I-SPY2 TRIAL with RCB, pre-surgical MRI FTV data and known follow-up (median 2.5 years). We first assessed whether FTV predicts residual disease (pCR or pCR/RCB-I) using ROC analysis. We applied a power transformation to normalize the pre-surgical FTV distribution; and assessed its association with DRFS using a bi-variate Cox proportional hazard model adjusting for HR/HER2 subtype. We also fitted a bivariate Cox model of RCB index adjusting for subtype; and assessed whether adding pre-surgical FTV to this model further improves association with DRFS using a likelihood ratio (LR) test. For the Cox modeling, penalized splines approximation of the transformed FTV and RCB index with 2 degrees of freedom was used to allow for non-linear effects of FTV and RCB on DRFS. Result: Pre-surgical MRI FTV is significantly associated with DRFS (Wald p&lt;0.00001), and more effective at predicting pCR/RCB-I than predicting pCR alone (AUC: 0.72 vs. 0.65). Larger pre-surgical FTV remains associated with worse DRFS adjusting for subtype (Wald p &lt;0.00001). The RCB index is also significantly associated with DRFS adjusting for subtype (Wald p&lt;0.00001). Adding FTV to a model containing RCB and subtype further improves association with DRFS (LR p=0.0007). RCB-I patients have excellent DRFS (94% at 3 years compared to 95% in the pCR group). Efforts are underway to identify an optimal threshold for dichotomizing pre-surgical FTV and FTV change measures for use in combination with pCR/RCB-I class to generate integrated RCB (iRCB) groups as a composite predictor of DRFS. Conclusion: Pre-surgical MRI FTV is effective at predicting minimal residual disease (RCB0/I) in the I-SPY 2 TRIAL. Despite the association between FTV and RCB, FTV appears to provide independent added prognostic value (to RCB and subtype), suggesting that integrating MRI volume measures and RCB into a composite predictor may improve DRFS prediction. Citation Format: Hylton NM, Symmans WF, Yau C, Li W, Hatzis C, Isaacs C, Albain KS, Chen Y-Y, Krings G, Wei S, Harada S, Datnow B, Fadare O, Klein M, Pambuccian S, Chen B, Adamson K, Sams S, Mhawech-Fauceglia P, Magliocco A, Feldman M, Rendi M, Sattar H, Zeck J, Ocal I, Tawfik O, Grasso LeBeau L, Sahoo S, Vinh T, Yang S, Adams A, Chien AJ, Ferero-Torres A, Stringer-Reasor E, Wallace A, Boughey JC, Ellis ED, Elias AD, Lang JE, Lu J, Han HS, Clark AS, Korde L, Nanda R, Northfelt DW, Khan QJ, Viscusi RK, Euhus DM, Edmiston KK, Chui SY, Kemmer K, Wood WC, Park JW, Liu MC, Olopade O, Tripathy D, Moulder SL, Rugo HS, Schwab R, Lo S, Helsten T, Beckwith H, Haugen PK, van't Veer LJ, Perlmutter J, Melisko ME, Wilson A, Peterson G, Asare AL, Buxton MB, Paoloni M, Clennell JL, Hirst GL, Singhrao R, Steeg K, Matthews JB, Sanil A, Berry SM, Abe H, Wolverton D, Crane EP, Ward KA, Nelson M, Niell BL, Oh K, Brandt KR, Bang DH, Ojeda-Fournier H, Eghtedari M, Sheth PA, Bernreuter WK, Umphrey H, Rosen MA, Dogan B, Yang W, Joe B, I-SPY 2 TRIAL Consortium, Yee D, Pusztai L, DeMichele A, Asare SM, Berry DA, Esserman LJ. Refining neoadjuvant predictors of three year distant metastasis free survival: Integrating volume change as measured by MRI with residual cancer burden [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 P2-07-03.

Abstract Background In clinically node-negative (cN0) breast cancer patients with triple negative (TN) and HER2+ disease and breast pathological complete response (breast pCR), low rates of nodal positivity after neoadjuvant chemotherapy (NAC) have been demonstrated. In these patients, the omission of surgical axillary staging has been proposed. However, this information is not routinely known preoperatively. We aimed to validate the correlation between pathologic breast response and pathologic nodal status, and evaluate the relationship between response of the breast tumor on MRI and pathologic nodal status after NAC in cN0 patients in the I-SPY2 trial. Methods We identified all patients with cT1-4 cN0 breast cancer prior to NAC from graduated arms of the I-SPY2 trial, a prospective neoadjuvant chemotherapy trial. Absence of residual disease post-NAC was defined as longest diameter (LD) of 0 mm on MRI. Breast pCR was defined as the absence of invasive tumor in the breast at surgery. Associations between ypN0 and patient, MRI, and tumor characteristics were assessed using chi-square tests and univariate regression. Results Of 365 cT1-4 cN0 patients included, 128 had HR+/HER2- tumors (35%), 60 HR+/HER2+ tumors (16%), 34 HR-/HER2+ tumors (9%) and 143 TN tumors (39%). Overall, 283 patients (78%) were ypN0 after NAC and 152 patients (42%) had a breast pCR. ypN0 rate was higher in patients with a breast pCR than those with residual disease (93% vs 66%, p&lt;0.001). Patients with HR-/HER2+ and TN tumors were more likely to be ypN0 (97% and 87% respectively) than patients with HR+/HER2- and HR+/HER2+ disease (66% and 71% respectively, p&lt;0.001). Other characteristics associated with ypN0 were tumor grade (grade I 57%, grade II 66%, grade III 84%; p=0.002), MammaPrint Classification (High Risk 1 68% and High Risk 2 87%; p&lt;0.001) and absence of residual tumor in the breast on MRI (87% vs 72% in patients with evidence of tumor on MRI post-NAC/pre-surgery; p=0.003). In patients with HR-/HER2+, HR+/HER2+, HR-/HER2+ or TN disease and a breast pCR, ypN0 rate was respectively 82%, 96%, 96% and 97% (table 1). In patients with HR+/HER2-, HR+/HER2+, HR-/HER2+ or TN disease and with no evidence of residual disease in the breast on MRI, rate of ypN0 was 71%, 80%, 94% and 96% respectively. Conclusion In cT1-4 cN0 breast cancer patients with HR+/HER2+, HR-/HER2+ and TN tumors and a breast pCR, ypN0 rates after NAC are extremely high. In patients with HR-/HER2+ and TN tumors with no residual breast disease on MRI after NAC and pre-surgery, ypN0 rates are high enough to consider omission of axillary surgery. In patients with HR+ tumors, MRI is unsufficiently predictive for pathological response and can therefore not be used to select ypN0 patients. Research on the prediction of ypN0 in cN+ I-SPY2 patients is ongoing. Nodal status in patients with pCR and absence of residual disease on MRI Number of positive nodesBreast Cancer Subtype0123AllBreast pCR HR+/HER2-27(82)2(6)4(12)033(100)HR+/HER2+24(96)01(4)025(100)HR-/HER2+24(96)1(4)0025(100)TN67(97)2(3)0069(100)Absence of residual disease on MRI HR+/HER2-24(71)7(21)3(9)034(100)HR+/HER2+16(80)3(15)01(5)20(100)HR-/HER2+15(94)1(6)0016(100)TN54(96)2(4)0056(100) Citation Format: van der Noordaa ME, Esserman L, Yau C, Mukhtar R, Price E, Hylton N, Abe H, Wolverton D, Crane EP, Ward KA, Nelson M, Niell BL, Oh K, Brandt KR, Bang DH, Ojeda-Fournier H, Eghtedari M, Sheth PA, Bernreuter WK, Umphrey H, Rosen MA, Dogan B, Yang W, Joe B, van 't Veer L, Hirst G, Lancaster R, Wallace A, Alvaredo M, Symmans F, Asare S, Boughey JC, I-SPY2 Consortium. Role of breast MRI in predicting pathologically negative nodes after neoadjuvant chemotherapy in cN0 patients in the I-SPY2 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 PD4-04.

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.