A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma

BMC Bioinformatics

Research

Jin-xiao Liang¹  Jin-shi Liu¹  Qian Chen¹  Da Chen¹  Xing-chen Lin²  Jin-qiao Bi²  Bing-bing Han²  Wei Gao²  Xin-yu Qian² 

[1] Department of Oncological Surgery, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), No. 1 of Banshan East Road, 310022, Hangzhou, Zhejiang Province, Republic of China;Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, People’s Republic of China;School of Medicine, Zhejiang University City College, Hangzhou, People’s Republic of China;

关键词: Lung adenocarcinoma (LUAD);    Glycosyltransferases (GTs);    Prognosis;    Immune cells;   

DOI  :  10.1186/s12859-022-05109-8

 received in 2022-06-20, accepted in 2022-12-12,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundLung adenocarcinoma (LUAD) is the most common malignant tumor that seriously affects human health. Previous studies have indicated that abnormal levels of glycosylation promote progression and poor prognosis of lung cancer. Thus, the present study aimed to explore the prognostic signature related to glycosyltransferases (GTs) for LUAD.MethodsThe gene expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and GTs were obtained from the GlycomeDB database. Differentially expressed GTs-related genes (DGTs) were identified using edge package and Venn diagram. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ingenuity pathway analysis (IPA) methods were used to investigate the biological processes of DGTs. Subsequently, Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct a prognostic model for LUAD. Kaplan–Meier (K–M) analysis was adopted to explore the overall survival (OS) of LUAD patients. The accuracy and specificity of the prognostic model were evaluated by receiver operating characteristic analysis (ROC). In addition, single-sample gene set enrichment analysis (ssGSEA) algorithm was used to analyze the infiltrating immune cells in the tumor environment.ResultsA total of 48 DGTs were mainly enriched in the processes of glycosylation, glycoprotein biosynthetic process, glycosphingolipid biosynthesis-lacto and neolacto series, and cell-mediated immune response. Furthermore, B3GNT3, MFNG, GYLTL1B, ALG3, and GALNT13 were screened as prognostic genes to construct a risk model for LUAD, and the LUAD patients were divided into high- and low-risk groups. K–M curve suggested that patients with a high-risk score had shorter OS than those with a low-risk score. The ROC analysis demonstrated that the risk model efficiently diagnoses LUAD. Additionally, the proportion of infiltrating aDCs (p < 0.05) and Tgds (p < 0.01) was higher in the high-risk group than in the low-risk group. Spearman’s correlation analysis manifested that the prognostic genes (MFNG and ALG3) were significantly correlated with infiltrating immune cells.ConclusionIn summary, this study established a novel GTs-related risk model for the prognosis of LUAD patients, providing new therapeutic targets for LUAD. However, the biological role of glycosylation-related genes in LUAD needs to be explored further.

【 授权许可】

CC BY   
© The Author(s) 2022

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