Single-cell RNA sequencing analysis reveals cellular heterogeneity and immune microenvironment dynamics in colorectal cancer

(CCT) T cells and their progenitors in colorectal cancer, and their association with immunotherapy response at the transcriptomic level.MethodsWe used single-cell sequencing data and The Cancer Genome Atlas database for comprehensive bioinformatics analysis, including single-cell sequencing data analysis, Gene Set Variation Analysis, pseudotime analysis, cell communication analysis, and construction and validation of a prognostic model.ResultsKey findings include the identification and annotation of various T-cell subtypes in colorectal cancer, construction of a pseudotime trajectory of CCT T cells and their progenitors showing dynamic gene expression changes, and enhanced interactions between CCT T cell progenitors and other cells in the PD-1 immunotherapy group. We developed and validated a prognostic model comprising 15 gene features with strong prognostic stratification performance, revealing that high-risk patients exhibit transcriptomic associations with potentially reduced responses to immune checkpoint inhibitors (ICIs). Pathway enrichment analysis highlighted critical pathways, including leukocyte adhesion and T cell activation, indicating complex influences on disease progression and treatment responses within the colorectal cancer immune landscape.ConclusionsThis study emphasizes the potential importance of targeted therapies that modulate immune interactions and functional states to improve colorectal cancer prognosis, particularly in high-risk patients who show an association at the transcriptomic level with reduced ICI responsiveness.

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Publication Details

Journal
The International Journal of Biological Markers
Published
2026-04-12
DOI
https://doi.org/10.1177/03936155261441324
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Single-cell RNA sequencing analysis reveals cellular heterogeneity and immune microenvironment dynamics in colorectal cancer

Hongjian Gao, Xing Dong Li, Zhi-Tao Yin, Yi You et al.
The International Journal of Biological Markers
Single-cell and spatial transcriptomics
article

Single-cell RNA sequencing analysis reveals cellular heterogeneity and immune microenvironment dynamics in colorectal cancer

Hongjian Gao, Xing Dong Li, Zhi-Tao Yin, Yi You, Lu-ji Qiao, Rong-xiang Si
article en

Abstract

(CCT) T cells and their progenitors in colorectal cancer, and their association with immunotherapy response at the transcriptomic level.MethodsWe used single-cell sequencing data and The Cancer Genome Atlas database for comprehensive bioinformatics analysis, including single-cell sequencing data analysis, Gene Set Variation Analysis, pseudotime analysis, cell communication analysis, and construction and validation of a prognostic model.ResultsKey findings include the identification and annotation of various T-cell subtypes in colorectal cancer, construction of a pseudotime trajectory of CCT T cells and their progenitors showing dynamic gene expression changes, and enhanced interactions between CCT T cell progenitors and other cells in the PD-1 immunotherapy group. We developed and validated a prognostic model comprising 15 gene features with strong prognostic stratification performance, revealing that high-risk patients exhibit transcriptomic associations with potentially reduced responses to immune checkpoint inhibitors (ICIs). Pathway enrichment analysis highlighted critical pathways, including leukocyte adhesion and T cell activation, indicating complex influences on disease progression and treatment responses within the colorectal cancer immune landscape.ConclusionsThis study emphasizes the potential importance of targeted therapies that modulate immune interactions and functional states to improve colorectal cancer prognosis, particularly in high-risk patients who show an association at the transcriptomic level with reduced ICI responsiveness.

The International Journal of Biological Markers
Shenyang Anorectal Hospital (CN)
Good health and well-being
Openalex Percentile: Top 18%
Single-cell and spatial transcriptomics
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