Abstract Background: The recent groundbreaking neoadjuvant immune checkpoint blockade (NICB) clinical trials in melanoma have demonstrated decisively that the administration of ICB prior to intent-to-cure surgeries will become the new standard-of-care for metastatic melanoma and beyond. The paradigm shifts from radiographic to pathologic response assessment also presents an unparalleled “window of opportunity” for the acquisition of abundant “on-treatment” tissues to elucidate the mechanisms and biomarkers of response and for guiding post-surgery personalized therapy decisions. To date, single-cell/bulk RNA studies have demonstrated that TCF7+ stem-like CD8+ T cells and tertiary lymphoid structures (TLS) are positive predictors of ICB response. However, how these immune cells organize and communicate within the spatial context of the neoadjuvant tumor microenvironment remains poorly understood. Methods: We investigated a unique cohort of 91 FFPE biospecimens from 87 patients with stage III metastatic melanoma, including 60 treated with NICB (31 complete response, 7 partial response, 22 non-response) and 27 treatment-naïve. We deployed state-of-the-art technologies, including multiplexed error-robust fluorescent in situ hybridization (MERFISH), single cell sequencing of FFPE blocks, and multiplexed IF for this rich digital resource. Importantly, to analyze these challenging high dimensional spatial datasets, we developed 3 novel computational algorithms, including SCIRA, a scalable quantification method for spatial receptor-ligand (R-L) interactions; GC-SCAN, a graph-based clustering method to detect Germinal Center (GC)/TLS structures in single cell spatial data; and PathNet, an end-to-end AI algorithm for automated GC/TLS detection on H Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6564.
Liu et al. (2026) studied this question.