ArticleTranslational oncology2025
Understanding the cellular and molecular heterogeneity in colorectal cancer through the use of single-cell RNA sequencing.
Article in Translational oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Integrative transcriptomic analysis reveals tumor-adjacent mucosal remodeling in colorectal cancer.Functional & integrative genomics · 2026Article
- Reading the tumour at single-cell resolution: Original research in the Precision Therapeutics special issue.Translational oncology · 2026Article
- The CGRP-nociceptor axis in cancer: tumor-specific programs of immune evasion, stromal remodeling, and tumor growth.Frontiers in oncology · 2026Review
- Exploring the role of adenosine deaminase in esophageal cancer and its potential for traditional Chinese medicine intervention.Frontiers in molecular biosciences · 2026Article
- Modulation of Human Immune Cells by Propyl-Propane Thiosulfonate (PTSO) Inhibits Colorectal Tumor Progression in a Humanized Mouse Model.Nutrients · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
The very prevalent nature, genetic variability, and intricate tumor microenvironment (TUME) of colorectal cancer (COREC) are its defining features. In order to better understand the molecular and cellular make-up of COREC, this work used single-cell RNA sequencing (SRNAS) to isolate and characterize important cell types as well as their interactions within the TUME. Our analysis of 51,204 cells yielded six distinct types: epithelial, fibroblast, endothelial, T&NK, B, and myeloid. C3 B cells were shown to be the most active in immunological regulation, according to chemokine signaling study, which was one of seven clusters of B cells that were thoroughly subtyped. The examination of copy number variation (CONUV) revealed a great deal of genetic variability, especially in epithelial cells. We traced the activity of three key transcription factor clusters (M1, M2, and M3) across all B cell subtypes using transcription factor analysis. We created a predictive model that correctly sorts patients according to survival results by using marker genes from C3 B cells. In addition, the relationship between genetic changes and the immune system was better understood by tumor mutational burden (TUMUB) and immune infiltration studies. Our research sheds light on the genetic complexity and cellular variety of COREC, which in turn opens up new possibilities for targeted treatments and individualized approaches to patient care.
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