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pmid:39524749
Construction and experimental verification of a novel nine-glycosylation-related gene prognostic risk model for clear cell renal carcinoma.
Wanlei Sun · Long Guo · Jianqing Ye · Min Zhou · Cong Shu · Xin Ying · Hongliang Liu · Fei Liu
Heliyon · 2024 doi:10.1016/j.heliyon.2024.e39258
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Experiment
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Data
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Analysis
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Execution
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Complete file
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This study aimed to develop a novel signature for predicting ccRCC prognosis based on glycosylation-related genes (GRGs).\nMethods: Differentially expressed GRGs (DE_GRGs) were identified using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus and used for constructing the risk model. The function of key genes was validated.\nResults: Twenty-two DE_GRGs were intersected between GSE53757 and TCGA. Patients with ccRCC were divided into two clusters based on the expression profile of these DE_GRGs. Significant differences in the infiltration of 10 immune cell types were observed between two subclusters. Subsequently, the prognostic signatures of nine DE_GRGs (CHST9, COLGALT1, FUT3, FUT6, HS3ST2, POMGNT2, ST8SIA4, UGT3A1, and UGT8) were established. Patients in the high-risk group showed a poorer prognosis relative to the low-risk group. According to univariate and multivariate Cox regression analyses, the risk score, stage, and grade could be independent prognostic factors. A nomogram incorporating information on gender, age, risk group, TNM stage, and clinical stage showed accurate prediction in the survival probability. Except for CHST9, HS3ST2, and ST8SIA4, expression patterns of the remaining 6 DE_GRGs in Caki-1 and 786-O cells were confirmed by quantitative real-time PCR. FUT6 overexpression resulted in the inhibition of proliferation, migration, and invasion of ccRCC cells.\nConclusion: This study established a nine-DE_GRG-based prognostic signature, which independently predicted ccRCC prognosis. 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