Abstract 6930: Spatial analysis of multi-ancestral tumors to understand how intercellular signaling impacts tumor invasion
Authors: Stangis Mary M. , Cheng Lingxin , Albrecht Dawn , Snow Santina , Wirtz Tessa , Matkowskyj Kristina A. , Dinh Huy Q. , Kendziorski Christina , Halberg Richard B. 
Published: March 2024

Colorectal cancer (CRC) persists as a leading cause of cancer-related deaths in the United States. Intratumoral heterogeneity stems from a multi-ancestral origin or clonal divergence and contributes to treatment resistance. Unfortunately, tumors in existing mouse models are largely homogenous, rendering predictions of drug efficacy inaccurate. To investigate whether signaling between distinct neoplastic clones in a tumor and cells in the surrounding microenvironment impacts CRC biology, we performed spatial transcriptomic analysis on samples collected from a transgenic mouse model previously established in the Halberg laboratory. This model (referred to as B6.FCTG3KM) develops three types of tumors: homotypic Adenomatous Polyposis Coli (APC)-deficient tumors that express red fluorescent protein (RFP), homotypic APC-deficient tumors that express constitutively active phosphoinositide 3-kinase (PI3K) and green fluorescent protein (GFP), and heterotypic tumors. Previous characterization of the model clearly demonstrated that heterotypic tumors are significantly more aggressive than either type of homotypic tumor.

Analysis was conducted on four serially sectioned slides containing three tumors and adjacent normal tissue obtained from the colon of a male B6.FCTG3KM mouse using the 10x Genomics Visium CytAssist platform with the mouse whole transcriptome probe set. Collected tumors were staged using traditional histopathology techniques by a board-certified pathologist (Matkowskyj). Immunohistochemistry and immunofluorescence were used to assess β-catenin localization and to re-probe for RFP and GFP expression. Sequencing was performed on the Illumina NovaSeqX platform to an average depth of 255,528,294 reads per sample. Data analysis was performed using the 10x Genomics SpaceRanger and Kendziorski laboratory R/SpatialView packages. A fold-change threshold of 1.5 and an adjusted p-value threshold of 0.05 were used when establishing marker genes for each of the 8 clusters identified. One distinct cluster was identified by marker genes including Notum, Wif1, and Dkk2, factors previously implicated in CRC tumorigenesis, and corresponded to the center of each region of surface-level dysplastic epithelia. The remainder of the surface-level dysplastic epithelia corresponded to a second cluster, with marker genes including those coding for TRIM family proteins (Trim5, Trim10, Trim40, Trim12c), and matrix metalloproteinases (Mmp12, Mmp9, Mmp10, Mmp13). A third cluster corresponded to the desmoplastic stroma underlying each neoplasm. Ongoing analyses are underway to identify clonal interactions that alter gene expression and tumor aggressiveness.

Citation Format: Mary M. Stangis, Lingxin Cheng, Dawn Albrecht, Santina Snow, Tessa Wirtz, Kristina A. Matkowskyj, Huy Q. Dinh, Christina Kendziorski, Richard B. Halberg. Spatial analysis of multi-ancestral tumors to understand how intercellular signaling impacts tumor invasion [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 6930.