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Identification of a glycolysis-related lncRNA prognostic signature for clear cell renal cell carcinoma
Authors:Wei Ma  Manli Zhong  Xiaowu Liu
Affiliation:1.Department of Breast Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China;2.College of Life and Health Sciences, Northeastern University, Shenyang, China;3.Department of Urology, The First Affiliated Hospital of China Medical University, Shenyang, China
Abstract:Background: The present study investigated the independent prognostic value of glycolysis-related long noncoding (lnc)RNAs in clear cell renal cell carcinoma (ccRCC).Methods: A coexpression analysis of glycolysis-related mRNAs–long noncoding RNAs (lncRNAs) in ccRCC from The Cancer Genome Atlas (TCGA) was carried out. Clinical samples were randomly divided into training and validation sets. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to establish a glycolysis risk model with prognostic value for ccRCC, which was validated in the training and validation sets and in the whole cohort by Kaplan–Meier, univariate and multivariate Cox regression, and receiver operating characteristic (ROC) curve analyses. Principal component analysis (PCA) and functional annotation by gene set enrichment analysis (GSEA) were performed to evaluate the risk model.Results: We identified 297 glycolysis-associated lncRNAs in ccRCC; of these, 7 were found to have prognostic value in ccRCC patients by Kaplan–Meier, univariate and multivariate Cox regression, and ROC curve analyses. The results of the GSEA suggested a close association between the 7-lncRNA signature and glycolysis-related biological processes and pathways.Conclusion: The seven identified glycolysis-related lncRNAs constitute an lncRNA signature with prognostic value for ccRCC and provide potential therapeutic targets for the treatment of ccRCC patients.
Keywords:clear cell renal cell carcinoma (ccRCC)   glycolysis   long noncoding RNAs (lncRNAs)   prognosis   risk model
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