Barcaru, Andrei

PURPOSE Neoadjuvant immunotherapy (IO) has become the standard of care for early-stage triple-negative breast cancer (TNBC), but not yet for other subtypes. We previously developed a clinical-grade mRNA-based immune classifier (ImPrint) predicting response to IO that is now being used in I-SPY2.2 as part of the response predictive subtypes. We report the performance of ImPrint in hormone receptor–positive and human epidermal growth factor receptor 2–negative (HR+HER2–) patients from five IO arms. METHODS A total of 204 HR+HER2– (MammaPrint high-risk) patients from five IO arms (anti–PD-1, anti–PD-L1/poly [ADP-ribose] polymerase inhibitor combination, anti–PD-1/toll-like receptor 9 dual-IO combination, and anti–PD-1 ± lymphocyte activation gene 3 dual-IO combination) and 191 patients from the chemotherapy-only control arm were included in this analysis. Patients were classified as ImPrint+ (likely sensitive) versus ImPrint– (likely resistant), using pretreatment mRNA. Performance of ImPrint for predicting pathologic complete response (pCR) to IO-containing arms was characterized and compared with tumor grade (III), MammaPrint (ultra) High2 risk (MP2), and estrogen receptor (ER)-low (ER ≤ 10%). RESULTS Overall, the pCR rate across the five IO arms was 33%. 26% of HR+HER2– patients were ImPrint+, and pCR rates with IO were 75% in ImPrint+ versus 17% in ImPrint–, with the highest pCR rate >90% in a dual-IO arm. In the control arm, pCR rates were 33% in ImPrint+ and 8% in ImPrint–. Tumor grade (III), MP2, and ER-low showed pCR rates in IO of 45%, 56%, and 63%, respectively, with lower pCR odds ratios (OR < 7.5) compared with ImPrint (OR = 14.5). CONCLUSION Using an accurate selection strategy, HR+HER2– patients could achieve pCR rates similar to what is seen with best neoadjuvant therapies in TNBC and HER2+ (ie, pCR rate >65%-70%). ImPrint, an Food and Drug Administration IDE-enabled assay, may represent a way to identify HR+HER2– patients for IO that best balances likely benefit versus risk of serious immune-related adverse events.

Abstract Background: Neoadjuvant immunotherapy (IO) has become standard of care for early-stage triple negative breast cancer (TNBC). I-SPY2 was the first randomized trial to examine the efficacy of IO therapy in high-risk HR+HER2- breast cancer, where most IO arms showed improved efficacy relative to control. We also previously showed immune-gene expression signatures associate with pathologic complete response (pCR) in HR+HER2- treated with IO; and developed a clinically applicable Immune classifier (ImPrint) predicting response to IO that is now being used in I-SPY2.2 as part of the Response Predictive Subtypes. Here we report the performance of ImPrint in HR+HER2- patients from 5 IO arms. Methods: 204 HR+HER2- (MammaPrint high risk) patients from 5 IO arms (anti-PD1, anti-PDL1/PARPi, anti-PD1/TLR9 dual-IO, and anti-PD1 +/- LAG3 dual-IO) and 191 patients from the control arm were included in this analysis. Patients were classified ImPrint+ (likely sensitive) vs. ImPrint- (likely resistant), by Agendia, Inc, using pre-treatment mRNA. Performance of ImPrint for predicting pCR to IO was characterized and compared to that of MammaPrint (ultra) High2 risk (MP2) and tumor grade (III). Based on the DRFS of pCR vs. non-pCR HR+HER2-/ImPrint+ patients (median follow up ~4.5yr), we predicted the DRFS in the IO vs. control arms using an exponential model as a function of the pCR rates. Results: Overall, the pCR rate over the 5 IO arms was 33%. 28% of HR+HER2- patients were ImPrint+; and pCR rates with IO were 76% in ImPrint+ vs. 16% in ImPrint-, with the highest pCR rate &gt;90% in a dual-IO arm. In the control arm, pCR rates were 33% in ImPrint+ and 8% in ImPrint-. Based on the pCR rates in the IO vs. control (76% vs. 33%), the predicted DRFS of HR+HER2-/ImPrint+ patients are 91% vs 80% at 5 years, respectively. This translates to a risk reduction of 52% for the IO arm relative to standard chemotherapy in HR+HER2-/ImPrint+ patients. We also compared MP2 and tumor grade (III) to ImPrint+ as pCR predictors, as these markers have been used or proposed as selection markers for neoadjuvant IO trials in HR+HER2-. The pCR rates for MP2, Grade III, at 56%, 45%, respectively, are much smaller than that for ImPrint+ at 75% pCR; thus ImPrint appears to be a more precise predictive biomarker for neoadjuvant IO therapy in the HR+HER2- breast cancers. Conclusion: These results suggest that a subset of high risk HR+HER2- breast cancers is highly sensitive to immunotherapy, and by using a specific and sensitive selection strategy patients could achieve pCR rates similar to what is seen with best neoadjuvant therapies in TNBC and HER2+ (i.e., pCR rate &gt; 65-70%). ImPrint, an FDA IDE-enabled assay currently being further evaluated in I-SPY2, may represent the way to identify patients for IO that best balances likely benefit vs risk of serious immune-related adverse events. Citation Format: Denise M. Wolf, Christina Yau, Lajos Pusztai, Rita Nanda, Jo Chien, Erica Stringer-Reasor, Rebecca Shatsky, Claudine Isaacs, MInetta Liu, Hyo Han, Hatem Soliman, Michael Campbell, Annuska Glas, Andrei Barcaru, Lorenza Mittempergher, Midas Kuilman, Lamorna Brown Swigart, Gillian Hirst, Hongmei Yu, Philip Beineke, Amrita Basu, I-SPY2 Investigators, Douglas Yee, W. Fraser Symmans, Angela DeMichele, Jane Perlmutter, Amy Delson, Laura Huppert, Hope Rugo, Amy Clark, Nola Hylton, Paula Pohlmann, Laura Esserman, Laura van 't Veer. Immune subtyping identifies a subset of HR+HER2- early-stage breast cancer patients with a very high likelihood of response to neoadjuvant immunotherapy (IO): Results from 5 IO arms of the I-SPY2 TRIAL [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1207.

514 Background: The remarkable increase of novel Immuno-Oncology drugs in many malignancies has led to the need for biomarkers to identify who would benefit. Various predictive biomarkers have been developed (PD-1/PD-L1 expression, mutations in mismatch repair genes and microsatellite instability, tumor mutational burden and immune infiltration), none have consistently predicted efficacy. The I-SPY2 consortium qualified several expression-based immune biology related signatures that predict response to PD1 checkpoint inhibition. Here we assessed whole transcriptome data of high-risk early-breast cancer (EBC) patients who received Pembrolizumab within the neoadjuvant biomarker-rich I-SPY2 trial (NCT01042379), aiming to migrate the I-SPY2 research findings to a robust clinical grade platform signature to predict sensitivity to PD1 checkpoint inhibition. Methods: Whole transcriptome microarray data were available from pre-treatment biopsies of 69 HER2- patients enrolled in the Pembrolizumab (4 cycles) arm of the I-SPY2 trial. All patients had a High-Risk 70-gene MammaPrint profile. Pathologic complete response (pCR) was defined as no residual invasive cancer in breast or nodes at the time of surgery. Of the 69 patients, 31 had a pCR (12 HR (hormonal receptor)+HER2-, 19 Triple Negative (TN)), while 38 (28 HR+HER2-, 10 TN) had residual disease (RD). To identify the most predictive genes associated with pCR, gene selection was performed comparing pCR and RD groups by iteratively splitting the dataset in training and test, balancing for HR status. Due to limited sample size, leave one out cross validation was used for performance assessment. Genes with effect size > 0.45 were considered significant. Results: A signature of 53 genes, named ImPrint, was identified with overall sensitivity and specificity > 90% and > 80% for predicting pCR to pembrolizumab in all patients. Sensitivity and specificity in TN were > 95% and ≥70%, and in HR+HER2- > 80% and > 85%, respectively. The Positive Predictive Value (PPV) is 77% for the HR+HER2- subgroup. Biological annotation of the 53 genes showed that over 90% of the genes have known immune system related functions, of which 63% were previously known to be involved in immune response (including genes coding PD-L1 and PD-1, as well as those identified in I-SPY2). Conclusions: In the signature development phase, ImPrint predicts pCR to Pembrolizumab in a set of 69 high risk EBC with high sensitivity and specificity. The signature features genes with immune-related functions known to be involved in immune response indicating that it might aid identifying patients with an immune-active phenotype. Importantly, ImPrint appears effective in identifying a subset of HR+HER2- patients who could benefit from immunotherapy. External validation in independent dataset(s) is ongoing and will be presented at the time of the meeting.