AUTHOR=Yang Sheng , Zhou Jiahui , Chen Zhihao , Sun Qingyang , Zhang Dongsheng , Feng Yifei , Wang Xiaowei , Sun Yueming 

TITLE=A novel m7G-related lncRNA risk model for predicting prognosis and evaluating the tumor immune microenvironment in colon carcinoma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.934928

DOI=10.3389/fonc.2022.934928

ISSN=2234-943X

ABSTRACT=N7-methylguanosine (m7G) modification proves to be one of the most prevalent post-transcriptional RNA modifications. Its function in the TME has garnered widespread focus in the past few years. Long non-coding RNAs (lncRNAs) played a essential part in tumor evaluation and were closely associated with the tumor immune microenvironment. Thus, we performed detailed bioinformatics to develop an m7G-associated lncRNA prognostic model analizing the colon adenocarcinoma(COAD) database from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was applied to discover m7G-related lncRNAs. Differential expression analysis was used to screen lncRNAs.Then We gained 88 differentially expressed m7G-related lncRNAs.Univariate Cox analysis and lasso regression analysis were performed to build an 8 m7G-related lncRNAs (ELFN1-AS1, GABPB1-AS1, SNHG7, GS1-124K5.4, ZEB1-AS1, PCAT6, C1RL-AS1, MCM3AP-AS1) risk model. Consensus clustering analysis was applied to identify the m7G-related lncRNAs subtypes. We also verified the risk prediction effect of a gene signature in the GSE17536 test set (177 patients). A nomogram was constructed to predict overall survival rates. Furthermore, we analyzed differentially expressed genes(DEGs) between high-risk and low-risk groups.GeneOntology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted with the analyzed DEGs.At last, single sample Gene Set Enrichment Analysis(ssGSEA), CIBERSORT, MCP-COUNTER, and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data(ESTIMATE) algorithms were utilized to discover the relationship with both risk model and tumor microenvironment(TME). Consequently, the m7G-related lncRNAs risk model for COAD patients could be a viable prognostic tool and treatment target.