Int J Med Sci 2020; 17(13):1879-1896. doi:10.7150/ijms.45813

Research Paper

A Prognostic Model Based on the Immune-related Genes in Colon Adenocarcinoma

Yuan-Lin Sun, Yang Zhang, Yu-Chen Guo, Zi-Hao Yang, Yue-Chao Xu

Department of Gastrointestinal Surgery, The First Hospital, Jilin University, Changchun 130021, Jilin Province, China.

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Citation:
Sun YL, Zhang Y, Guo YC, Yang ZH, Xu YC. A Prognostic Model Based on the Immune-related Genes in Colon Adenocarcinoma. Int J Med Sci 2020; 17(13):1879-1896. doi:10.7150/ijms.45813. Available from http://www.medsci.org/v17p1879.htm

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Abstract

Background: Immune-related genes (IRGs) are critically involved in the tumor microenvironment (TME) of colon adenocarcinoma (COAD). Here, the study was mainly designed to establish a prognostic model of IRGs to predict the survival of COAD patients.

Methods: The Cancer Genome Atlas (TCGA), Immunology Database and Analysis Portal (ImmPort) database, and Cistrome database were utilized for extracting data regarding the expression of immune gene- and tumor-related transcription factors (TFs), aimed at the identification of differentially expressed genes (DEGs), differentially expressed IRGs (DEIRGs), and differentially expressed TFs (DETFs). Univariate Cox regression analysis was subsequently performed for the acquisition of prognosis-related IRGs, followed by establishment of TF regulatory network for uncovering the possible molecular regulatory association in COAD. Subsequently, multivariate Cox regression analysis was conducted to further determine the role of prognosis-related IRGs for prognostic prediction in COAD. Finally, the feasibility of a prognostic model with immunocytes was explored by immunocyte infiltration analysis.

Results: A total of 2450 DEGs, 8 DETFs, and 79 DEIRGs were extracted from the corresponding databases. Univariate Cox regression analysis revealed 11 prognosis-related IRGs, followed by establishment of a regulatory network on prognosis-related IRGs at transcriptional levels. Functionally, IRG GLP2R was negatively modulated by TF MYH11, whereas IRG TDGF1 was positively modulated by TF TFAP2A. Multivariate Cox regression analysis was subsequently performed to establish a prognostic model on the basis of seven prognosis-related IRGs (GLP2R, ESM1, TDGF1, SLC10A2, INHBA, STC2, and CXCL1). Moreover, correlation analysis of immunocyte infiltration also revealed that the seven-IRG prognostic model was positively associated with five types of immunocytes (dendritic cell, macrophage, CD4 T cell, CD8 T cell, and neutrophil), which may directly reflect tumor immune state in COAD.

Conclusions: Our present findings indicate that the prognostic model based on prognosis-related IRGs plays a crucial role in the clinical supervision and prognostic prediction of COAD patients at both molecular and cellular levels.

Keywords: immune-related genes (IRGs), differential expressed analysis, prognostic model, Cox regression analysis, colon adenocarcinoma (COAD)