Construction and validation of a metabolism-associated gene signature for predicting the prognosis, immune landscape, and drug sensitivity in bladder cancer

BMC Medical Genomics

Research

Fei Peng¹  Zhenqian Fan²  Yuejiao Liu³  Shaobo Yang⁴  Zhe Zhang⁴  Yuxin Bi⁴  Wang Chai⁴  Hailong Hu⁴  Chong Shen⁴  Zhouliang Wu⁴ 

[1] Department of Critical Care Medicine, the Peoples Hospital of Yuxi City, Yunnan, China;Department of Endocrinology, The Second Hospital of Tianjin Medical University, 23 Pingjiang Road, Jianshan Street, Hexi, 300211, Tianjin, People’s Republic of China;Department of Pharmacy, Zhu Xianyi Memorial Hospital of Tianjin Medical University, Tianjin, China;Department of Urology, The Second Hospital of Tianjin Medical University, 23 Pingjiang Road, Jianshan Street, Hexi, 300211, Tianjin, People’s Republic of China;Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, 300211, Tianjin, China;

关键词: Bladder cancer;    Metabolism;    Prognostic model;    Tumor microenvironment;    Immune therapy;   

DOI  :  10.1186/s12920-023-01678-6

 received in 2023-06-06, accepted in 2023-09-30,  发布年份 2023

来源: Springer

【 摘 要 】

Tumor Metabolism is strongly correlated with prognosis. Nevertheless, the prognostic and therapeutic value of metabolic-associated genes in BCa patients has not been fully elucidated. First, in this study, metabolism-related differential expressed genes DEGs with prognostic value in BCa were determined. Through the consensus clustering algorithm, we identified two molecular clusters with significantly different clinicopathological features and survival prognosis. Next, a novel metabolism-related prognostic model was established. Its reliable predictive performance in BCa was verified by multiple external datasets. Multivariate Cox analysis exhibited that risk score were independent prognostic factors. Interestingly, GSEA enrichment analysis of GO, KEGG, and Hallmark gene sets showed that the biological processes and pathways associated with ECM and collagen binding in the high-risk group were significantly enriched. Notely, the model was also significantly correlated with drug sensitivity, immune cell infiltration, and immunotherapy efficacy prediction by the wilcox rank test and chi-square test. Based on the 7 immune infiltration algorithm, we found that Neutrophils, Myeloid dendritic cells, M2 macrophages, Cancer-associated fibroblasts, etc., were more concentrated in the high-risk group. Additionally, in the IMvigor210, GSE111636, GSE176307, or our Truce01 (registration number NCT04730219) cohorts, the expression levels of multiple model genes were significantly correlated with objective responses to anti-PD-1/anti-PD-L1 immunotherapy. Finally, the expression of interested model genes were verified in 10 pairs of BCa tissues and para-carcinoma tissues by the HPA and real-time fluorescent quantitative PCR. Altogether, the signature established and validated by us has high predictive power for the prognosis, immunotherapy responsiveness, and chemotherapy sensitivity of BCa.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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