ArticleIn vivo (Athens, Greece)
A Prognostic Model of Colon Cancer Based on the Microenvironment Component Score
Article in In vivo (Athens, Greece). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Tumor Vascular Features and Colorectal Cancer-Specific Mortality.JAMA network open · 2026Article
- Gradient boosting reveals spatially diverse cholesterol gene signatures in colon cancer.Frontiers in genetics · 2024Article
- Review
- C1QC is a prognostic biomarker with immune-related value in kidney renal clear cell carcinoma.Frontiers in genetics · 2023Article
- A Detailed Overview About the Single-Cell Analyses of Solid Tumors Focusing on Colorectal Cancer.Pathology oncology research : POR · 2022Review
- Immune Checkpoint Inhibitor Resistance in Rectal Adenocarcinoma Containing a Mismatch Repair Deficiency Component: A Case Report.Cancer diagnosis & prognosisArticle
- Role of Traditional Chinese Medicine Syndrome Type, Gut Microbiome, and Host Immunity in Predicting Early and Advanced Stage Colorectal Cancer.Integrative cancer therapiesArticle
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimThe development of colon cancer is influenced by the tumour immune microenvironment, in which specific immune cell subsets may be useful predictors for patient's clinical outcome and devising treatment strategies. MATERIALS AND
methodsThe distribution of tumour-infiltrating immune cell subpopulations of three cohorts of The Cancer Genome Atlas (n=225), GSE39582 (n=493), and GSE17536 (n=137) datasets were analysed on the basis of single cell RNA sequencing data via the Cibersortx software. A prognostic model was constructed via a penalised Cox regression model with least absolute shrinkage and selection operator (LASSO) penalty according to the one standard error rule.
resultsConventional type 2 dendritic cells were correlated with a good prognosis, whereas NLRP3-expressing macrophages, C1QC-expressing tumour-associated macrophages, and GALTB-expressing B cells were correlated with a poor prognosis. We constructed a prognostic model based on prognosis related cell subsets including nine specific immune cell subsets. By using the LASSO method, we found that the model had a superior prediction ability in all three cohorts of patients.
conclusionMultiple immune cell subpopulations in the tumour microenvironment are associated with the prognosis of colon cancer. The established prognostic model has important clinical value in predicting the clinical outcome of patients with colon cancer and in treatment decision.
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