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

Background: Lung adenocarcinoma (LUAD) is the most common malignant tumor that seriously affects a huge number of human health. It is reported that abnormal levels of glycosylation promote the progression and poor prognosis of lung cancer. Hence, we aimed to explore the prognostic signature related to glycosyltransferases (GTs) for LUAD. Method: Based on the data of gene expression profiles obtained from The Cancer Genome Atlas (TCGA) database and GTs obtained from the GlycomeDB database, we identified differentially expressed GTs-related genes (DGTs) between control and LUAD samples. The latent functions and pathways of DGTs were detected by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ingenuity pathway analysis (IPA) methods. Univariate and multivariate Cox regression analyses were then performed to screen the candidate prognostic genes to conduct a prognostic risk model for LUAD. Kaplan-Meier(K-M) curve was operated to assess the overall survival (OS) of LUAD patients. The accuracy and specificity of the constructed risk model were evaluated by receiver operating characteristic analysis (ROC). In addition, the infiltrating immune cells in the tumor environment were analyzed using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Results: A total of 48 DGTs were identified, contained 37 upregulated and 11 downregulated DGTs, which 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 screeded as prognostic genes to construct a risk model for LUAD that divided patients into a high-and low-risk group. K-M curve analysis suggested that high-risk patients showed shorter OS compared with low-risk patients. ROC analysis demonstrated the risk model presented a better ability for diagnosing LUAD. Additionally, the portion of infiltrating aDC and Tgd were higher in the high-risk group than the low-risk group. Spearman correlation analysis manifested that the prognostic genes (MFNG and ALG3) were significantly correlated with infiltrating immune cells. Conclusion: We established a novel GTs-related risk model for the prognosis of LUAD patients, providing new therapeutic targets for LUAD.