Identification of a novel metabolism-related gene signature associated with the survival of bladder cancer

BMC Cancer

Xiaotao Li¹  Shi Fu¹  Yinglong Huang¹  Jiansong Wang¹  Ting Luan¹  Haifeng Wang¹ 

[1] Department of Urology, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian street, Wuhua District, 650101, Kunming, Yunnan, People’s Republic of China;Urological disease clinical medical center of yunnan province, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian street, Wuhua District, 650101, Kunming, Yunnan, People’s Republic of China;Scientific and Technological Innovation Team of Basic and Clinical Research of Bladder Cancer in Yunnan Universities, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian street, Wuhua District, 650101, Kunming, Yunnan, People’s Republic of China;

关键词: Bladder cancer;    Metabolism-related gene;    TCGA;    GEO;    Prognosis;   

DOI  :  10.1186/s12885-021-09006-w

来源: Springer

【 摘 要 】

BackgroundBladder cancer (BC) is one of the most common malignancies and has a relatively poor outcome worldwide. In this study, we attempted to construct a novel metabolism-related gene (MRG) signature for predicting the survival probability of BC patients.MethodsFirst, differentially expressed MRGs between BC and normal samples were identified and used to construct a protein-protein interaction (PPI) network and perform mutation analysis. Next, univariate Cox regression analysis was utilized to select prognostic genes, and multivariate Cox regression analysis was applied to establish an MRG signature for predicting the survival probability of BC patients. Moreover, Kaplan-Meier (KM) survival analysis and receiver operating characteristic (ROC) analysis were performed to evaluate the predictive capability of the MRG signature. Finally, a nomogram based on the MRG signature was established to better predict the survival of BC.ResultsIn the present study, 27 differentially expressed MRGs were identified, most of which presented mutations in BC patients, and LRP1 showed the highest mutation rate. Next, an MRG signature, including MAOB, FASN and LRP1, was established by using univariate and multivariate Cox regression analysis. Furthermore, survival analysis indicated that BC patients in the high-risk group had a dramatically lower survival probability than those in the low-risk group. Finally, Cox regression analysis showed that the risk score was an independent prognostic factor, and a nomogram integrating age, pathological tumor stage and risk score was established and presented good predictive ability.ConclusionWe successfully constructed a novel MRG signature to predict the prognosis of BC patients, which might contribute to the clinical treatment of BC.

【 授权许可】

CC BY