ArticleTranslational oncology2026
Comprehensive single-cell analysis reveals cellular heterogeneity and immune interactions in colorectal cancer.
Article in Translational oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- The microbiota-NK cell axis in colorectal cancer: a spatial and subset-centric framework.Frontiers in immunology · 2026Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) presents considerable therapeutic challenges due to its diverse cellular composition and intricate microenvironment. Our study utilized single-cell RNA sequencing (scRNA-seq) on CRC tissues, examining 18,741 individual cells, which were grouped into six primary cell populations: epithelial, fibroblast, endothelial, T and NK, B, and myeloid. The epithelial cells exhibited notable variations in gene copy numbers. Within T_NK cells, we identified four distinct subsets. CytoTRACE analysis indicated that subtype C3 exhibited lower differentiation potential, whereas subtypes C0 and C1 showed higher differentiation potential. Consistently, Monocle pseudotime trajectory analysis positioned C3 cells at the terminal stage of differentiation, while C0 cells were enriched at the early stage of the developmental trajectory, suggesting functional heterogeneity among T/NK subpopulations. Through functional analyses with GSVA and ssGSEA, subtype C3 displayed the highest inflammation-associated activity scores. Further exploration of transcription factors defined three unique regulatory clusters among T_NK cells, illuminating their gene-regulation networks. We developed a prognostic signature using markers from subtype C3 T_NK cells combined with age-associated genes, revealing a significant correlation with patient survival outcomes. This prognostic model proved effective in categorizing CRC patients according to risk. Additionally, immune profiling employing ESTIMATE, CIBERSORT, and Xcell algorithms underscored the complexity of immune cell populations within CRC tumors. Analysis of tumor mutational burden (TMB) highlighted differential patterns between patient groups and its relationship to prognostic risk levels. Collectively, these insights provide a detailed perspective on CRC cell diversity and immune dynamics, supporting the advancement of targeted and personalized therapeutic interventions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.