Abstract:

Objective　To identify the immune-related prognostic genes that may be involved in the development and progression of colon cancer, and to screen the immune biomarkers analyzing the data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO) by weighted gene co-expression network. Methods　The study was from November to December 2022. The weighted gene coexpression network analysis was performed on immune-related genes in GSE41657 and TCGA datasets for colon cancer, and the immune-related biomarkers were screened from key modules. The gene expression data and clinical information from the TCGA database were further analyzed. Results　The most critical immune-related modules in the occurrence and development of colon cancer were obtained; their functions were enriched in chemokine signaling, migration, activation, proliferation, and migration of immune cells; their pathways were enriched in the chemokine signaling pathway, antigen processing and presentation, MAPK signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and NF-Kappa B signaling pathway. Ten genes were identified as the prognostic targets of colon cancer, including NMB, SCG2, IL1A, ULBP2, INHBB, COLEC12, F2RL1, ANGPTL1, NR3C2, and TNFRSF17. Two genes, COLEC12 and ANGPTL1, which were the most closely correlated with colon cancer immunity, were screened out through the TIMER database. They were enriched in many immune-related and cancer-related pathways, including the JAK Stat signaling pathway, Toll-like receptor signaling pathway, and MAPK signaling pathway. They may play important roles in tumor immune microenvironment. Conclusion　COLEC12 and ANGPTL1 may regulate colon cancer and its immune microenvironment through a variety of signaling pathways, and are expected to become potential immunotherapy targets.

Key words:

Colon cancer, Weighted gene coexpression network analysis, Immune related biomarkers, Cancer genome atlas, Gene Expression Omnibus database

摘要：

目的　旨在鉴定可能参与结肠癌发生发展的免疫相关预后基因，采用加权基因共表达网络对癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）联合分析，筛选免疫生物标志物。方法　2022年11月至12月，对GSE41657数据集和TCGA结肠癌数据集中免疫相关基因进行加权基因共表达网络分析，并从关键模块筛选免疫相关生物标志物，利用TCGA数据库中基因表达数据和临床信息进一步分析。结果　获得了结肠癌发生发展中与免疫相关的最关键模块，其功能富集到免疫细胞趋化、游走、活化、增殖、迁徙等，通路富集到趋化因子信号通路、抗原处理和呈递、MAPK信号通路、HIF-1信号通路、PI3K-Akt信号通路、NF-kappa B信号通路等。找到了有望作为结肠癌预后靶点的10个基因：NMB、SCG2、IL1A、ULBP2、INHBB、COLEC12、F2RL1、ANGPTL1、NR3C2、TNFRSF17。通过TIMER数据库筛选出2个与结肠癌免疫相关性最为密切的基因——COLEC12、ANGPTL1，这两个基因富集到诸多免疫相关和癌症相关通路——JAK Stat信号通路、Toll样受体信号通路、MAPK信号通路等，可能在肿瘤免疫微环境中发挥重要作用。结论　COLEC12、ANGPTL1可能通过多种信号通路对结肠癌及其免疫微环境进行调控，有望成为潜在的免疫治疗靶点。

关键词:

结肠癌, 加权基因共表达网络, 免疫相关生物标志物, 癌症基因组图谱, 基因表达综合数据库