ArticleBioscience reports2020
A novel prognostic risk score model based on immune-related genes in patients with stage IV colorectal cancer.
Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Immunorepertoire-based characterization of adaptive immunity in human malignant pleural effusion.Frontiers in oncology · 2026Article
- Comprehensive analysis of cellular senescence and immune microenvironment in papillary thyroid carcinoma.Aging · 2024Article
- Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents.BMC medical genomics · 2023Article
- Construction and verification of a novel prognostic risk model for kidney renal clear cell carcinoma based on immunity-related genes.Frontiers in genetics · 2023Article
- The role of fibroblast growth factor 18 in cancers: functions and signaling pathways.Frontiers in oncology · 2023Review
- Prognosis prediction of stage IV colorectal cancer patients by mRNA transcriptional profile.Cancer medicine · 2022Article
- Article
- Integrated Analysis of Necroptosis-Related Genes for Prognosis, Immune Microenvironment Infiltration, and Drug Sensitivity in Colon Cancer.Frontiers in medicine · 2022Article
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6 authors.
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Abstract
purposeThe aims of the present study were to explore immune-related genes (IRGs) in stage IV colorectal cancer (CRC) and construct a prognostic risk score model to predict patient overall survival (OS), providing a reference for individualized clinical treatment.
methodsHigh-throughput RNA-sequencing, phenotype, and survival data from patients with stage IV CRC were downloaded from TCGA. Candidate genes were identified by screening for differentially expressed IRGs (DE-IRGs). Univariate Cox regression, LASSO, and multivariate Cox regression analyses were used to determine the final variables for construction of the prognostic risk score model. GSE17536 from the GEO database was used as an external validation dataset to evaluate the predictive power of the model.
resultsA total of 770 candidate DE-IRGs were obtained, and a prognostic risk score model was constructed by variable screening using the following 12 genes: FGFR4, LGR6, TRBV12-3, NUDT6, MET, PDIA2, ORM1, IGKV3D-20, THRB, WNT5A, FGF18, and CCR8. In the external validation set, the survival prediction C-index was 0.685, and the AUC values were 0.583, 0.731, and 0.837 for 1-, 2- and 3-year OS, respectively. Univariate and multivariate Cox regression analyses demonstrated that the risk score model was an independent prognostic factor for patients with stage IV CRC. High- and low-risk patient groups had significant differences in the expression of checkpoint coding genes (ICGs).
conclusionThe prognostic risk score model for stage IV CRC developed in the present study based on immune-related genes has acceptable predictive power, and is closely related to the expression of ICGs.
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