ArticleTranslational cancer research2023
Extracellular matrix-based gene signature for predicting prognosis in colon cancer and immune microenvironment.
Article in Translational cancer research, 2023. 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.
- In Silico Analysis of the Dual Role of Tumor Microenvironment on Colon Cancer Subtypes.Cancer informatics · 2026Article
- Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.Scientific reports · 2025Article
- The Tumor Stroma of Squamous Cell Carcinoma: A Complex Environment That Fuels Cancer Progression.Cancers · 2024Review
- Subtyping or not subtyping-Translational cancer research · 2023Article
- Integrative analysis reveals a four-gene signature for predicting survival and immunotherapy response in colon cancer patients using bulk and single-cell RNA-seq data.Frontiers in oncology · 2023Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: The extracellular matrix (ECM) plays a vital role in progression, expansion, and prognosis of malignancies. In this study, we aimed to explore a novel ECM-based prognostic model for patients with colon cancer (CC). Methods: ECM-related genes were obtained from Molecular Signatures database. Differential expression analysis was performed using the CC dataset from The Cancer Genome Atlas (TCGA) database. Four ECM-related genes related to overall survival were identified using the Cox regression and LASSO analysis. Then an ECM-related signature was developed and verified in three independent CC cohorts (GSE33882, GSE39582 and GSE29621) from the Gene Expression Omnibus (GEO). A prognostic nomogram was developed incorporating the ECM-related gene signature with clinical risk factors. CIBERSORT was used to explore the immune cell infiltration level. Human Protein Atlas (HPA) database was utilized to validate the expression levels of identified prognostic ECM genes. Results: Four ECM-related genes ( Conclusions: In the present study, a novel risk model based on ECM-signature could effectively reflect individual risk classification and provide potential therapeutic targets for CC patients. Moreover, the prognostic nomogram may help predict individualized survival.
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