AUTHOR=Shi Yanlong , Wang Yizhu , Yang Rui , Zhang Wenning , Zhang Yu , Feng Kun , Lv Qingpeng , Niu Kaiyi , Chen Jiping , Li Li , Zhang Yewei TITLE=Glycosylation-related molecular subtypes and risk score of hepatocellular carcinoma: Novel insights to clinical decision-making JOURNAL=Frontiers in Endocrinology VOLUME=Volume 13 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.1090324 DOI=10.3389/fendo.2022.1090324 ISSN=1664-2392 ABSTRACT=Abstract Background: Hepatocellular Carcinoma (HCC) is the fifth most common cancer and the third leading cause of cancer deaths worldwide, seriously affecting human community health and care. Emerging evidence has shown that aberrant glycosylaiton was associated with tumor progression and metastasis. However, the role of glycosylation-related genes in HCC has not been reported. Methods: The weighted gene co-expression network analysis (WGCNA) and Non-negative matrix factorization (NMF) analysis were applied to identify molecular subtypes and functional modules in HCC. The Lasso Cox regression was used to construct the glycosylation-related signature. The independent prognostic value of the risk model was confirmed and validated by systematic techniques, including PCA, tSNE, Kaplan-Meier survival analysis, ROC curve, multivariate cox regression, nomogram and calibration curve. The ssGSEA, GSVA, GO, and KEGG analyses were evaluated by immune microenviroment and potential biological processes. The qRT-PCR and immunohistochemistry analysis were used to verify the expression of 5-gens. Results: We identified the glycosylation-related genes with bioinformatics analysis to construct and validate a 5-gene signature for the prognosis of HCC patients. Patients with HCC in the high-risk group had a worse prognosis. The risk score could be an independent factor, and was associated with clinical features, such as grade and stage. Nomogram exhibited an accurate score that included risk score and clinical parameters. The infiltration levels of anti-tumor cells were up-regulated in the low-risk group, including B_cells, Mast_cells, neutrophils, NK_cells, and T_helper_cells. Moreover, glycosylation was more sensitive to immunotherapy, and may play a critical role in the metabolic processes of HCC, such as bile acid metabolism and fatty acid metabolism. In addition, the 5-genes mRNA and protein expression were over-expressed in HCC cells and tissues. Conclusions: The glycosylation-related signature is effective for prognostic recognition, immune efficacy evaluation, and substance metabolism in HCC, providing a novel insight for therapeutic target prediction and clinical decision-making.