Computationally Derived Spatial Immune Signature Identifies Trastuzumab Responders in HER2+ Breast Cancer: NSABP B41 Clinical Trial Validation

PURPOSE: Trastuzumab-based chemotherapy has improved outcomes in human epidermal growth factor receptor 2-positive (HER2+) breast cancer, but treatment benefit varies among patients. Predictive signatures are needed to identify patients most likely to respond to these therapies. EXPERIMENTAL DESIGN: We developed DeSTIL (Density and Spatial architecture of Tumor-Infiltrating Lymphocytes), a computational signature derived from hematoxylin and eosin slides. The signature captures spatial organization of immune cells and interactions with non-immune cells. DeSTIL was trained on HER2+ breast cancer slides from The Cancer Genome Atlas (n = 250) and validated in phase III NSABP B-41 randomized clinical trial (n=221), which compared chemotherapy plus trastuzumab, lapatinib, or combination. The DeSTIL scores were dichotomized into positive and negative groups, and event-free survival (EFS) was assessed using Cox proportional hazards with interaction terms. RESULTS: In NSABP B41, DeSTIL-positive patients (n=61) showed significantly improved EFS with trastuzumab compared to the combination arm (HR = 0.09, 95% CI 0.01-0.77; p = 0.006) and a significant signature-treatment interaction (p = 0.024). No EFS difference was observed in DeSTIL-negative patients (n=160). Gene expression analysis supported the image-derived signature stratifying DeSTIL-positive and DeSTIL-negative tumors. In an exploratory pCR analysis, a classifier trained on University Hospitals Cleveland slides achieved an AUC of 0.70 in the training cohort and 0.63 in the trastuzumab arm of the NSABP B-41 validation cohort. CONCLUSIONS: DeSTIL identifies a subset of HER2+ patients who derive greater benefit from trastuzumab. These findings support the potential of computationally derived immune architecture to inform selection of standard HER2-targeted therapies.