{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["11(17)"],"submitter":["Wang S"],"pubmed_abstract":["<b>Background:</b> Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent and invasive histological subtypes among all renal cell carcinomas (RCC). Cancer cell metabolism, particularly glucose metabolism, has been reported as a hallmark of cancer. However, the characteristics of glucose metabolism-related gene sets in ccRCC have not been systematically profiled. <b>Methods:</b> In this study, we downloaded a gene expression profile and glucose metabolism-related gene set from TCGA (The Cancer Genome Altas) and MSigDB, respectively, to analyze the characteristics of glucose metabolism-related gene sets in ccRCC. We used a multivariable Cox regression analysis to develop a risk signature, which divided patients into low- and high- risk groups. In addition, a nomogram that combi"],"journal":["Journal of Cancer"],"pagination":["4996-5006"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7378912"],"repository":["biostudies-literature"],"pubmed_title":["Identification of a Glucose Metabolism-related Signature for prediction of Clinical Prognosis in Clear Cell Renal Cell Carcinoma."],"pmcid":["PMC7378912"],"pubmed_authors":["Chai K","Chen J","Wang S","Zhang L","Yu Z"],"additional_accession":[]},"is_claimable":false,"name":"Identification of a Glucose Metabolism-related Signature for prediction of Clinical Prognosis in Clear Cell Renal Cell Carcinoma.","description":"<b>Background:</b> Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent and invasive histological subtypes among all renal cell carcinomas (RCC). Cancer cell metabolism, particularly glucose metabolism, has been reported as a hallmark of cancer. However, the characteristics of glucose metabolism-related gene sets in ccRCC have not been systematically profiled. <b>Methods:</b> In this study, we downloaded a gene expression profile and glucose metabolism-related gene set from TCGA (The Cancer Genome Altas) and MSigDB, respectively, to analyze the characteristics of glucose metabolism-related gene sets in ccRCC. We used a multivariable Cox regression analysis to develop a risk signature, which divided patients into low- and high- risk groups. In addition, a nomogram that combi","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020","modification":"2025-04-05T15:18:01.62Z","creation":"2025-04-05T15:18:01.62Z"},"accession":"S-EPMC7378912","cross_references":{"pubmed":["32742447"],"doi":["10.7150/jca.45296"]}}