Abstract 3116: Spatial single-cell atlas of stage III colorectal cancer

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Abstract Background: Spatial heterogeneity and multicellular interactions within the tumor microenvironment drive tumor progression and response to therapy, yet, tumor molecular profiling often requires dissociation of cells, losing the spatial context. Spatial proteomic technologies enable capturing single-cell information with the spatial context allowing us to link cancer-causing mutations to outcomes in cell signaling, responses and survival that will aid in diagnosis, prognostication, and treatment of cancer. We aim to capture single cells in intact tissue sections of stage III colorectal tumors from 52 patients to spatially characterize cell types, interactions, and organization of the tumor microenvironment in relation to genetic alterations and clinical outcomes. Methods: Using Hyperion Imaging Mass Cytometry (IMC), we profiled 16 protein markers across 170 tissue regions, capturing molecular signatures of tissue architecture, tumor cells, and immune cells. We developed an analysis pipeline to quantify single-cell protein expression and identify cell phenotypes. We preserved spatial information to characterize the interactions between neighboring cells and identify multicellular communities. We also generated whole exome sequencing data, RNAseq data and histopathological images from sections of the same tissue blocks. We compared cellular and spatial features between tumors harboring prognostic genomic evens such as TP53 deletion and MSI and between patients stratified by clinical outcomes such as survival and recurrence. Results: We spatially profiled over 800,000 cells to identify 10 tumor, immune and stromal cell phenotypes, and validated identified cell types against matched histopathology and CIBERSORTx deconvoluted RNAseq. To quantify cell-cell interactions, we measured the distance between neighboring cells and performed neighborhood enrichment analysis. We characterized the multicellular organization of the tumor microenvironment to identify 7 consistent cell neighborhoods of up to 10 adjacent cells. We quantified p53 expression in individual tumor cells and found that TP53 deletion (all heterozygous) had no significant association with p53 expression or p53+ tumor cell abundance, suggesting spatial proteomics reveals additional information absent in traditional sequencing. We find that MSI is exclusive of TP53 deletion and that MSI positive tumors had few p53+ tumor cells, increased CD8+ T cell composition and B cells that were further away from p53+ tumor cells compared to MSI negative tumors. Conclusions: Using Hyperion IMC to acquire a spatial single-cell atlas of stage III colorectal cancer enabled us to characterize the tumor microenvironment by defining cell types, quantifying cell interactions, and identifying multicellular communities. These features enable the linkage of prognostic genetic alternations and clinical outcomes with changes in the tumor microenvironment. Citation Format: Andrew Su, Minh Tran, HoJoon Lee, Anuja Sathe, Xiangqi Bai, Richard Cruz, Lance Pflieger, Quan Nguyen, Hanlee P. Ji, Terence Rhodes. Spatial single-cell atlas of stage III colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3116.

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