Dissecting spatial tumor-immune microenvironment in response and resistance to immune checkpoint blockade in metastatic melanoma

Abstract

Immune checkpoint blockade (ICB) therapies have markedly improved the prognosis for patients with stage III & IV metastatic melanoma by prolonging progression-free and overall survival rates. However, the variability in mechanisms of immune evasion and resistance present significant challenges in the clinical efficacy of ICBs. This project aims to define drivers of immunotherapy response and resistance by employing advanced genomic, single cell mRNA analyses, and spatial profiling techniques on tissue biopsies from metastatic melanoma patients. In this study, we developed a framework to analyze response and resistance, both intrinsic and acquired, via immune features in the tumor microenvironment in a standardized, uniformly processed, and deeply clinically annotated cohort of metastatic melanoma patients (n=61) treated with ICB as part of the human tumor atlas network (HTAN) initiative1,2. From the tumor samples, we conducted single-nucleus RNA sequencing, and for a subset of the samples, high-resolution spatial imaging (including protein mIHC, CODEX, and MERFISH transcriptomics). Standardized processing and data pipelines allowed for the integration of genomic, transcriptomic, and spatial features to elucidate characteristics and mechanisms in the tumor microenvironment and their relationships with resistance. For this thesis, I focused on MERFISH spatial transcriptomics analysis. Single-nucleus RNA sequencing analysis revealed CXCL13+CD4+ T cells and ISG+CD8+ T cells as the strongest predictors of durable clinical benefit (DCB) among all immune populations, independent of clinical confounders. We also identified five recurrent cellular neighborhood modules: extreme responders are enriched in B cell–enriched RCNs with close T–B cell distance, non-responders in tumor–myeloid and tumor–myeloid–stromal interface RCNs, and non-extreme responders in tumor-dominant and stromal–immune interface RCNs. This project integrates transcriptomic and spatial features to elucidate shared tumor and microenvironmental states and their relationships with resistance, guiding more personalized and effective treatment strategies for metastatic melanoma.