Abstract 61: Defining spatial biomarkers of survival across solid tumors using a pan-cancer proteomics atlas.

Abstract The spatial architecture of the tumor microenvironment (TME) governs cancer progression and therapeutic response, yet pan-cancer analyses linking multicellular organization to patient survival remain unclear. As part of the PROSPECTS (Pancancer Reconstruction Of Spatial Profiles and Therapeutic TargETs) Initiative, we assembled a large-scale spatial proteomic atlas comprising 415 patients across six major malignancies: Head and Neck Squamous Cell Carcinoma (HPV-positive and HPV-negative), Lung Cancer (NSCLC and LUAD), Triple-Negative Breast Cancer, High-Grade Serous Ovarian Cancer, Colorectal Adenocarcinoma, and Hepatocellular Carcinoma (HCC). Our dataset includes over 1,000 tissue cores and over 4.4 million single cells with balanced representation across indications: HNSCC (1,218,385 cells, 145 patients), Lung (906,537 cells; 63 patients), Breast (765,232 cells; 60 patients), Ovarian (590,945 cells; 53 patients), Colorectal (511,610 cells; 37 patients), and Liver (474,237 cells; 57 patients). Using a 30-plex antibody Phenocycler, we spatially mapped 15 major cell types at single-cell resolution. We developed a next-generation multi-scale computational pipeline within AstroSuite (Stratica Biosciences), integrating TACIT and Constellation algorithms to quantify TME architecture at the levels of cell state, intercellular distance, and higher-order motifs including pairwise, triplet, and quartet cellular neighborhoods. These deep spatial metrics were linked to overall survival with adjustment for clinical covariates. We identified marked heterogeneity in TME structure, with each cancer type exhibiting distinct prognostic architectures. In TNBC, Tumor Cell-Neutrophil interactions emerged as one of the strongest adverse prognostic features (P=0.00001). In Lung cancers, vascular-immune and stromal-tumor interfaces were key, particularly vascular endothelial cell-Macrophage adjacency (P=0.0003) and Fibroblast-Tumor Cell interactions (P=0.002). Despite these cancer-specific patterns, PROSPECTS uncovered conserved spatial signatures. A recurrent fibroblast-tumor cell interface motif appeared across malignancies, though stromal drivers varied: Myofibroblast-Treg interactions were prognostic in Colorectal cancer (P=0.002), while Fibroblast-Treg interactions predicted outcome in Ovarian cancer (P=0.002). In HCC, immune-to-immune interactions such as Treg-B Cell crosstalk (P=0.002) were significantly associated with survival. Complex spatial syntax proved superior to simple pairwise interactions for prognosis, highlighting the value of higher-order TME modeling. This work establishes the first pan-cancer spatial proteomic comparison linking TME organization to clinical outcome, revealing that spatially resolved cellular interaction networks constitute a new class of clinically actionable biomarkers. Citation Format: Khoa Huynh, Joaquin Reyna, Bruno Matuck, KEVIN BYRD, Jinze Liu. Defining spatial biomarkers of survival across solid tumors using a pan-cancer proteomics atlas [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 61.