ArticleComputational and mathematical methods in medicine2022
Study on the Expression Profile of Autophagy-Related Genes in Colon Adenocarcinoma.
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- First metagenomic analysis of age-associated changes in the gut microbiome among healthy Saudi adults: SAMS pilot study.Frontiers in aging · 2026Article
- miR-124 and VAMP3 Act Antagonistically in Human Neuroblastoma.International journal of molecular sciences · 2023Article
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Authors and funding
3 authors.
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Abstract
Colon adenocarcinoma (COAD) is a common digestive tract tumor. Autophagy-related genes (ARGs) may play an obbligato role in the biological processes of COAD. This study was aimed at exploring the role of ARGs in COAD. Clinical data and RNA sequencing data of tumor and healthy samples were obtained from The Cancer Genome Atlas (TCGA), and discrepantly expressed ARGs were screened. Statistical differences of ARGs were performed with Gene Ontology (GO) functional annotation and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Eight ARGs were selected by univariate Cox and multivariate Cox regression. Kaplan-Meier (K-M) and multivariate receiver operating characteristic (multi-ROC) were used to check the fitness of the model. Among 398 COAD samples and 39 normal samples obtained from the TCGA database, 37 differentially expressed ARGs were screened. In the training group, eight prognostics-related ARGs (MTMR14, VAMP3, HSPA8, TSC1, DAPK1, CX3CL1, ATG13, and MAP1LC3C) were identified by Cox regression. A gene signature risk prediction model was constructed base on 8 autophagy-related genes. The survival time of the low-risk group was longer than the high-risk group, and the AUC of the model was 0.794. Univariate and multivariate Cox regression analysis showed that age and riskscore were the independent predictor. In conclusion, the prognosis model we built based one ARGs of COAD patients can estimate the prognosis of patients in clinical treatment.
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