ArticleBioMed research international2021
Identification and Verification of a 17 Immune-Related Gene Pair Prognostic Signature for Colon Cancer.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Comprehensive analysis of the correlation between GSTM1 and tumor immunity in colon cancer.Journal of gastrointestinal oncology · 2022Article
- Identification of microsatellite instability and immune-related prognostic biomarkers in colon adenocarcinoma.Frontiers in immunology · 2022Article
- Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer.Journal of inflammation research · 2021Article
- A Comprehensive Prognostic Model for Colon Adenocarcinoma Depending on Nuclear-Mitochondrial-Related Genes.Technology in cancer research & treatmentArticle
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColon cancer (CC) is a malignant tumor with a high incidence and poor prognosis. Accumulating evidence shows that the immune signature plays an important role in the tumorigenesis, progression, and prognosis of CC. Our study is aimed at establishing a novel robust immune-related gene pair signature for predicting the prognosis of CC.
methodsGene expression profiles and corresponding clinical information are obtained from two public data sets: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO, GSE39582). We screened out immune-related gene pairs (IRGPs) associated with prognosis in the discovery cohort. Lasso-Cox proportional hazard regression was used to develop the best prognostic signature model. According to this, the patients in the validation cohort were divided into high immune-risk group and low immune-risk group, and the prediction ability of the signature model was verified by survival analysis and independent prognostic analysis.
resultsA total of 17 IRGPs composed of 26 IRGs were used to construct a prognostic-related risk scoring model. This model accurately predicted the prognosis of CC patients, and the patients in the high immune-risk group indicated poor prognosis in the discovery cohort and validation cohort. Besides, whether in univariate or multivariate analysis, the IRGP signature was an independent prognostic factor. T cell CD4 memory resting in the low-risk group was significantly higher than that in the high-risk group. Functional analysis showed that the biological processes of the low-risk group included "TCA cycle" and "RNA degradation," while the high-risk group was enriched in the "CAMs" and "focal adhesion" pathways.
conclusionWe have successfully established a signature model composed of 17 IRGPs, which provides a novel idea to predict the prognosis of CC patients.
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