Bioinformatic analysis of RNA-seq data from TCGA database reveals prognostic significance of immune-related genes in colon cancer. Issue 31 (5th August 2022)

• Record Type: Journal Article
• Authors: Ouyang, Yan; Huang, Jiangtao; Wang, Yun; Tang, Fuzhou; Hu, Zuquan; Zeng, Zhu; Zhang, Shichao
• Is Part Of: Medicine. Volume 101:Issue 31(2022)
• Page Start: e29962
• Publication Date: 2022-08-05
• Subjects: colon cancer -- differentially expressed genes -- immune-related genes -- prognostic value -- tumor microenvironment; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000029962
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : The tumor immune microenvironment is of crucial importance in cancer progression and anticancer immune responses. Thus, systematic exploration of the expression landscape and prognostic significance of immune-related genes (IRGs) to assist in the prognosis of colon cancer is valuable and significant. The transcriptomic data of 470 colon cancer patients were obtained from The Cancer Genome Atlas database and the differentially expressed genes were analyzed. After an intersection analysis, the hub IRGs were identified and a prognostic index was further developed using multivariable Cox analysis. In addition, the discriminatory ability and prognostic significance of the constructed model were validated and the characteristics of IRGs associated overall survival were analyzed to elucidate the underlying molecular mechanisms. A total of 465 differentially expressed IRGs and 130 survival-associated IRGs were screened. Then, 46 hub IRGs were identified by an intersection analysis. A regulatory network displayed that most of these genes were unfavorable for the prognosis of colon cancer and were regulated by transcription factors. After a least absolute shrinkage and selection operator regression analysis, 14 hub IRGs were ultimately chose to construct a prognostic index. The validation results illustrated that this model could act as an independent indicator to moderately separate colon cancer patients into low- and high-risk groups. This study ascertained the prognostic significance of IRGs in colon cancer and successfully constructed an IRG-based prognostic signature for clinical prediction. Our results provide promising insight for the exploration of diagnostic markers and immunotherapeutic targets in colon cancer.