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Special issue “The advance of solid tumor research in China”: Multi-omics analysis based on 1311 clear cell renal cell carcinoma samples identifies a glycolysis signature associated with prognosis and treatment response
Authors:Xi Tian  Yue Wang  Wenhao Xu  Haidan Tang  Shuxuan Zhu  Aihetaimujiang Anwaier  Wangrui Liu  Wenfeng Wang  Wenkai Zhu  Jiaqi Su  Yuanyuan Qu  Hailiang Zhang  Dingwei Ye
Institution:1. Department of Urology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China;2. Affiliated Hospital of Youjiang Medical University for Nationalities, Guangxi, China
Abstract:In clear cell renal cell carcinoma (ccRCC), glycolysis is enhanced mainly because of the increased expression of key enzymes in glycolysis. Hence, the discovery of new molecular biomarkers for glycolysis may help guide and establish a precise system of diagnosis and treatment for ccRCC. Expression profiles of 1079 tumor samples of ccRCC patients (including 311 patients treated with everolimus or nivolumab) were downloaded from public databases. Proteomic profiles of 232 ccRCC samples were obtained from Fudan University Shanghai Cancer Center (FUSCC). Biological changes, tumor microenvironment and prognostic differences were explored between samples with various glycolysis characteristics. There were significant differences in CD8+ effector T cells, epithelial-to-mesenchymal transition and pan-fibroblast TGFb between the Low and High glyScore groups. The tumor mutation burden of the Low glyScore group was lower than that of the High glyScore group. And higher glyScore was significantly associated with worse overall survival (OS) in 768 ccRCC patients (P < .0001). External validation in FUSCC cohort also indicated that glyScore was of strong ability for predicting OS (P < .05). GlyScore may serve as a biomarker for predicting everolimus response in ccRCC patients due to its significant associations with progression-free survival (PFS). And glyScore may also predict overall survival in patients treated with nivolumab. We calculated the glyScore in ccRCC and the defined glyScore was of strong ability for predicting OS. In addition, glyScore may also serve as a biomarker for predicting PFS in patients treated with everolimus and could predict OS in patients treated with nivolumab.
Keywords:biomarker  clear cell renal cell carcinoma  everolimus  glycolysis  nivolumab  tumor microenvironment
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