Abstract 2666: Mapping intratumoral heterogeneity in colorectal cancer: Spatially resolved subclones and tumor microenvironment

Abstract Background: Colorectal cancer (CRC) is the third most common malignancy, with over 1.85 million new cases and 850, 000 deaths annually. Significant intratumoral heterogeneity in CRC contributes to recurrence, chemotherapy resistance, and poor prognosis. This study aimed to explore the spatial distribution of subtype clones and the diversity of the tumor microenvironment (TME), which are not captured by the traditional gene expression-based CMS classification. Additionally, it sought to investigate cancer trajectories and their contributions to metastatic phenotypes using spatial transcriptomics (ST). Methods: Spatial analysis was performed using public 10X Genomics Visium data from 4 CRC and 4 CRC-liver metastasis (CRC-LM) patients (GSE226997, GSE217414). Cell-type deconvolution utilized single-cell RNA-seq datasets (GSE178318, GSE132465). Copy number alterations (CNA) were inferred, and subclone development trajectories were modeled using inferCNV, DPT, and PAGA analyses. Pathway and functional enrichment analyses, expression score calculations, and correlation analyses were conducted using ClusterProfiler, AddModuleScore, and statistical methods. A Wilcoxon test with an adjusted p-value < 0.05 was used to determine statistical significance. Results: Distinct CRC and CRC-LM subclones were identified through CNA inference, revealing spatially segregated CNA clusters. These included malignant subclones and boundary-associated clusters, characterized by varying proportions of differentiation and mesenchymal traits. Immune-related signaling pathways demonstrated differential activation, with increased MAPK, JAK-STAT, and TNFα-NFκB in specific regions and elevated WNT, VEGF signaling, MYC, and E2F4 in others. Certain subclones also showed enrichment of SPP1+ macrophages and myofibroblasts, indicating diverse invasive characteristics. Evolutionary trajectories of subclones, inferred through hierarchical trees, revealed CSC features and a common ancestral clone. Progression toward malignancy was associated with enhanced pathway activity linked to critical biological processes. In CRC-LM, subclones were categorized by TAM subtypes, with one subtype displaying significantly elevated SPP1 expression compared to primary CRC. Immune-related features were reduced in metastatic tissues, reflecting a less immunogenic TME. Conclusion: Intratumoral heterogeneity in CRC evolves from a single common ancestral clone into distinct progression states, resulting in spatially unique TMEs. Understanding the interactions between clones across different progression states offers valuable insights into disease dynamics and therapeutic opportunities. Citation Format: YeonJu Lee, Woong-Yang Park. Mapping intratumoral heterogeneity in colorectal cancer: Spatially resolved subclones and tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2666.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-2666
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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article

Abstract 2666: Mapping intratumoral heterogeneity in colorectal cancer: Spatially resolved subclones and tumor microenvironment

Woong‐Yang Park, YeonJu Lee
Cancer Research
Radiomics and Machine Learning in Medical Imaging
article

Abstract 2666: Mapping intratumoral heterogeneity in colorectal cancer: Spatially resolved subclones and tumor microenvironment

Woong‐Yang Park, YeonJu Lee
article en

Abstract

Abstract Background: Colorectal cancer (CRC) is the third most common malignancy, with over 1.85 million new cases and 850, 000 deaths annually. Significant intratumoral heterogeneity in CRC contributes to recurrence, chemotherapy resistance, and poor prognosis. This study aimed to explore the spatial distribution of subtype clones and the diversity of the tumor microenvironment (TME), which are not captured by the traditional gene expression-based CMS classification. Additionally, it sought to investigate cancer trajectories and their contributions to metastatic phenotypes using spatial transcriptomics (ST). Methods: Spatial analysis was performed using public 10X Genomics Visium data from 4 CRC and 4 CRC-liver metastasis (CRC-LM) patients (GSE226997, GSE217414). Cell-type deconvolution utilized single-cell RNA-seq datasets (GSE178318, GSE132465). Copy number alterations (CNA) were inferred, and subclone development trajectories were modeled using inferCNV, DPT, and PAGA analyses. Pathway and functional enrichment analyses, expression score calculations, and correlation analyses were conducted using ClusterProfiler, AddModuleScore, and statistical methods. A Wilcoxon test with an adjusted p-value < 0.05 was used to determine statistical significance. Results: Distinct CRC and CRC-LM subclones were identified through CNA inference, revealing spatially segregated CNA clusters. These included malignant subclones and boundary-associated clusters, characterized by varying proportions of differentiation and mesenchymal traits. Immune-related signaling pathways demonstrated differential activation, with increased MAPK, JAK-STAT, and TNFα-NFκB in specific regions and elevated WNT, VEGF signaling, MYC, and E2F4 in others. Certain subclones also showed enrichment of SPP1+ macrophages and myofibroblasts, indicating diverse invasive characteristics. Evolutionary trajectories of subclones, inferred through hierarchical trees, revealed CSC features and a common ancestral clone. Progression toward malignancy was associated with enhanced pathway activity linked to critical biological processes. In CRC-LM, subclones were categorized by TAM subtypes, with one subtype displaying significantly elevated SPP1 expression compared to primary CRC. Immune-related features were reduced in metastatic tissues, reflecting a less immunogenic TME. Conclusion: Intratumoral heterogeneity in CRC evolves from a single common ancestral clone into distinct progression states, resulting in spatially unique TMEs. Understanding the interactions between clones across different progression states offers valuable insights into disease dynamics and therapeutic opportunities. Citation Format: YeonJu Lee, Woong-Yang Park. Mapping intratumoral heterogeneity in colorectal cancer: Spatially resolved subclones and tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2666.

Cancer ResearchVol. 85(8_Supplement_1)
Sungkyunkwan University (KR)
Openalex Percentile: Top 87%
Radiomics and Machine Learning in Medical Imaging
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