Abstract PS2-07-27: Qutils: open-source image-based infiltrating immune cell detection and outcomes in calgb 40502, calgb 40603, and calgb 40601 phase iii breast cancer clinical trials

Abstract Background: Stromal tumor infiltrating lymphocytes (sTILs) are associated with improved response to chemotherapy and better overall survival (OS) in triple-negative breast cancer (TNBC). Quantification of sTILs via hematoxylin and eosin (H700,000 cells via The Cancer Genome Atlas Program (TCGA) slide images, implemented in the widely used open-source QuPath digital pathology suite. QuTILs was applied to digital H 2) to benchmark diverse image-based characteristics of TIL abundance and spatial architecture; and 3) to evaluate the association between image-based TIL levels and RNA-seq-based immune deconvolution metrics (CIBERSORT, EPIC, quanTIseq). Results: QuTILs average processing time was 7.9 minutes for whole-slide total TIL count and area density on a standard laptop workstation. In CALGB 40502, there was positive but modest correlation between pathologist TILs and QuTILs total TILs %, higher in the TNBC subgroup of CALGB 40502 (Pearson r = 0.55). In Cox proportional hazards models, the CALGB 40502 TNBC cohort showed significant univariate association for total TILs % with increasing decile (higher total TIL%) associated with reduced hazard (hazard ratio HR: 0.712, 95% CI: 0.559-0.906; P = 0.006), which remained significant in multivariable model incorporating age, race, and treatment arm (HR: 0.713, 95% CI: 0.556-0.915; P = 0.008). In validation TNBC clinical trial CALGB 40603, marginal TILs % was significant in the univariable Cox model (HR: 0.786, 95% CI: 0.639-0.966). Evaluation of TILs % by QuTILs with RNAseq-based deconvolution metrics in cohort-stratified and deconvolution method-stratified multivariable models showed that decile total TILs % by QuTILs was shown to significantly predict outcome in the EPIC (HR: 0.668, 95% CI: 0.466-0.957) and quanTIseq (HR: 0.646, 95% CI: 0.446-0.936) sets, with a similar magnitude as in clinical Cox, suggesting that RNA-based deconvolution estimates may not supplement the prognostic power of image-based TIL estimates. Exploratory analyses of pre- versus post-neoadjuvant therapy H Wilcoxon signed rank P 0.001) but no significant change in QuTILs total TIL% among all pairs in CALGB 40601 (n = 82 pairs, pre-median=15.92%, post-median=15.10%; P = 0.886). Conclusions: QuTILs provides a computationally efficient open-source workflow for sTIL identification from digital H 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-07-27.