Abstract 7750: Integration of spatial single cell proteomics and spatial metabolomics reveals tumor microenvironment predictive of immunotherapy response in mucosal melanoma

Abstract Background: Mucosal melanoma (MuM) is a rare melanoma subtype, accounting for only 1-2% of all melanoma cases, yet is highly aggressive, demonstrating poorer responsiveness to immune checkpoint blockade than the more common cutaneous melanoma. However, the biological mechanisms driving therapeutic resistance in MuM remain poorly understood. This study aims to uncover spatial and molecular mechanisms underlying response and resistance of MuM to immune checkpoint blockade therapies. Study Design and Methods: An integrative spatial multi-omics framework was applied, which combined single-cell spatial proteomics using COMET platform with high mass resolution spatial metabolomics using imaging mass spectrometry (MALDI-IMS). We comprehensively profiled cellular compositions and spatially defined cellular neighborhoods (CNs) across 97 FFPE tissue cores from 26 MuM patients treated with PD-1/PD-L1 or CTLA-4 inhibitors. Spatial organization, cell-cell interactions, proteomic profiles and metabolomic features of CNs were further compared across responders and non-responders. Results: The comprehensive approach enabled spatially resolved profiling of 695,444 single cells, which were categorized into 25 cellular phenotypes spanning 9 major cell lineages. Spatial cellar neighborhood analysis revealed 15 biologically distinct CNs that differed in their composition and spatial distribution of tumor, immune, and stromal cell compartments. In patients who responded to immunotherapy, three tumor-associated CNs—the central tumor, invasive tumor, and tumor boundary CNs—were significantly enriched and collectively formed unique spatial organization patterns. Notably, the invasive tumor CN and tumor boundary CN were characterized by spatial proximity among Ki67+ tumor cells, CD163+ macrophages, and CD11c+ dendritic cells. These CD163+ macrophages exhibited reduced expression of IRF4 and Arg1, consistent with lower immunosuppressive activity. Conversely, non-responders exhibited a stromal-dominant CN composed primarily of SMA- stromal cells and demonstrated reduced immune infiltration in both pre-treatment and post-treatment samples. Spatial metabolomic profiling further revealed a pronounced reduction of tryptophan-derived indole metabolites in responders, which significantly correlated with CD11c and CD163 expression, indicating coordinated immunometabolic remodeling within the tumor microenvironment. Conclusions: These findings highlight that spatial tumor-immune architecture, stromal exclusion, and metabolic rewiring collectively shape immunotherapy response in MuM. The identified spatially resolved tryptophan-derived metabolite signatures offer promising biomarkers and potential therapeutic targets to improve treatment outcomes in this clinically challenging melanoma subtype. Citation Format: Jun Wang, Priyadharsini Nagarajan, Sungnam Cho, Yunhe Liu, Erin H. Seeley, Yibo Dai, Yang Liu, Jared K. Burks, Jennifer L. McQuade, Adi Diab, Linghua Wang, Suhendan Ekmekcioglu. Integration of spatial single cell proteomics and spatial metabolomics reveals tumor microenvironment predictive of immunotherapy response in mucosal melanoma abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7750.