Abstract
BackgroundBladder carcinoma (BC) is one of the most prevalent and malignant tumors. Multiple gene signatures based on BC metabolism, especially regarding glycolysis, remain unclear. Thus, we developed a glycolysis-related gene signature to be used for BC prognosis prediction.MethodsTranscriptomic and clinical data were divided into a training set and a validation set after they were downloaded and analyzed from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Gene-set enrichment analysis (GSEA) and differential analysis were used to screen differentially expressed genes (DEGs), while univariate Cox regression and lasso-penalized Cox regression were employed for signature establishment. To evaluate the prognostic power of the signature, receiver operating characteristic (ROC) curve and Kaplan–Meier (KM) survival analysis were also used. Additionally, we developed a nomogram to predict patients’ survival chances using the identified prognostic gene signature. Further, gene mutation and protein expression, as well as the independence of signature genes, were also analyzed. Finally, we also performed qPCR and western blot to detect the expression and potential pathways of signature genes in BC samples.ResultsTen genes were selected for signature construction among 71 DEGs, including nine risk genes and one protection gene. KM survival analysis revealed that the high-risk group had poor survival and the low-risk group had increased survival. ROC curve analysis and the nomogram validated the accurate prediction of survival using a gene signature composed of 10 glycolysis-related genes. Western blot and qPCR analysis demonstrated that the expression trend of signature genes was basically consistent with previous results. These 10 glycolysis-related genes were independent and suitable for a signature.ConclusionOur current study indicated that we successfully built and validated a novel 10-gene glycolysis-related signature for BC prognosis.
Highlights
MATERIALS AND METHODSBladder carcinoma (BC), a highly aggressive malignant lesion, accounted for more than one million new diagnoses and approximately 200,000 eventual deaths in 2018 (Bray et al, 2018)
receiver operating characteristic (ROC) curve analysis and the nomogram validated the accurate prediction of survival using a gene signature composed of 10 glycolysis-related genes
Glucose is metabolized through the tricarboxylic acid (TCA) cycle, during which the metabolic intermediate pyruvic acid is oxidized into carbon dioxide, water, and releases adenosine triphosphate (ATP) to provide energy (Koppenol et al, 2011)
Summary
Bladder carcinoma (BC), a highly aggressive malignant lesion, accounted for more than one million new diagnoses and approximately 200,000 eventual deaths in 2018 (Bray et al, 2018). Two determinative risk factors affecting the survival of patients with BC are tumor relapse and metastasis (Nadal and Bellmunt, 2019). Glycolysis is a major and crucial component of metabolism whose malignant changes represent carcinogenesis (Hanahan and Weinberg, 2011). Bladder carcinoma (BC) is one of the most prevalent and malignant tumors. Multiple gene signatures based on BC metabolism, especially regarding glycolysis, remain unclear. We developed a glycolysis-related gene signature to be used for BC prognosis prediction
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