Abstract 3423: Spatial-resolved single-cell analysis of the tumor microenvironment in Alaska Native colorectal cancer patients
Authors: Hang Yin, Diana Redwood, Kimberly Smythe, Daniel Jones, McGarry Houghton, Kevin C. Barry, Amanda L. Koehne, Elizabeth Donato, Cecilia Yeung, Mingang Lin, James J. Tiesinga, Tabitha A. Harrison, Sushma S. Thomas, Li Hsu, Jane C. Figueiredo, Li Li, Timothy K. Thomas, Christopher Li, Ulrike Peters, Jeroen R. Huyghe
Journal: Cancer Research (2024)

Abstract Tribal Health Organizations recognize the high rates of colorectal cancer (CRC) among Alaska Native peoples and are undertaking initiatives to address it. The tumor microenvironment (TME) is a complex ecosystem including tumor, stromal, and immune cells. Understanding the cell composition and spatial organization of the TME among Alaska Native patients with CRC will provide new insights into disease progression. We performed spatial profiling on 3 tissue microarrays (TMA) from 37 patients using the Akoya Biosciences’ s PhenoCycler system. Patients with CRC were selected from a nested case-control study which includes 16 patients who died of CRC and 21 patients who lived as long as patients with lethal CRC and matched on age at diagnosis, sex, tumor site and tumor stage. We designed a 40-antibody panel that captured tumor, epithelium, stromal, vascular, and immune cells, as well as cell functional states (e.g., PD1). Initial images were processed using QuPath for image stitching, artifact removal, background subtraction, cell segmentation, and measurement of average intensity of each marker per cell. Cell quality control (QC) was performed to filter out low quality cells based on cell size and log10-transformed sum of intensity. After quantile normalization and arcsinh transformation, cells that passed QC were clustered using the R package ‘Seurat’ and manually annotated based on the cell type and function marker intensities for each cluster. We identified 1.17 million cells and 15 cell types. Those cell types included 3 stromal and vascular cells, 1 epithelium, 1 mixed immune cluster, and 10 different immune cells. We quantified each cell type as a fraction of total cells on a per-patient basis. Among the subset of immune cells, the proportions of macrophages, CD4+T cells, and CD8+T cells were high (21%, 11.2%, and 14.5%, respectively), and the proportion of B cells was low (5.1%). We also identified regulatory T cells, cytotoxic CD8+T cells, and monocytes at 1-3%. We observed differences in the composition of cell clusters by CRC-specific death. The frequency of epithelium was higher among patients with lethal CRC, and the frequency of CD4+T cells and CD8+T cells were higher among patients without lethal CRC. In summary, the overall composition of tumor and immune cells varies between patients with and without CRC-specific death, indicating TME heterogeneity. Further investigation of spatial domains and relationships with clinical molecular features may facilitate discovery of novel predictors of CRC-specific death among Alaska Native peoples. We are clustering cell types into different cellular neighborhoods using spatial information and conducting statistical analysis integrating RNA sequencing data from the same patients. Further, we are generating spatial profiling data for an additional 5 TMAs comprising 60 additional patients and will present results of the combined data analyses. Citation Format: Hang Yin, Diana Redwood, Kimberly Smythe, Daniel Jones, McGarry Houghton, Kevin C. Barry, Amanda L. Koehne, Elizabeth Donato, Cecilia Yeung, Mingang Lin, James J. Tiesinga, Tabitha A. Harrison, Sushma S. Thomas, Li Hsu, Jane C. Figueiredo, Li Li, Timothy K. Thomas, Christopher Li, Ulrike Peters, Jeroen R. Huyghe. Spatial-resolved single-cell analysis of the tumor microenvironment in Alaska Native colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3423.