Identification and validation of a novel cuproptosis-related lncRNA gene signature to predict prognosis and immune response in bladder cancer

Author:

Chen Jia,Guan Yu,Li Chun,Du Hexi,Liang Chaozhao

Abstract

Abstract Purpose Bladder cancer (BCa) is one of the most common malignant tumors in the urogenital system, characterized by the high recurrence rate, mortality rate and poor prognosis. Based on cuproptosis-related long noncoding RNAs (CRLs), this study set out to create a prediction signature to evaluate the prognosis of patients with BCa. Methods RNA-seq data including CRLs and related clinicopathological data were gathered from The Cancer Genome Atlas (TCGA) database (n = 428). The predictive signature was constructed after correlation analysis. Subsequently, relying on the analyzed data from the TCGA database and our sample collection, we examined and verified the connections between CRLs model and important indexes included prognosis, route and functional enrichment, tumor immune evasion, tumor mutation, and treatment sensitivity. Results Patients in the high-risk group had lower overall survival (OS) than that of low-risk group. Compared with clinicopathological variables, CRLs features have better predictive value according to receiver operating characteristic (ROC) curve. The expression level of CRLs was highly associated with the tumor progress, tumor microenvironment and tumor immune escape. Additionally, we identified that the mutation of TP53, TTN, KMT2D and MUC16 gene were founded in patients with BCa. Lapatinib, pazopanib, saracatinib, gemcitabine, paclitaxel and palenolactone had good antitumor effects for BCa patients in the high-risk group (all P < 0.001). Conclusion This study revealed the effects of CRLs on BCa and further established CRLs model, which can be used in clinic for predicting prognosis, immunological response and treatment sensitivity inpatient with BCa.

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Endocrine and Autonomic Systems,Endocrinology,Oncology,Endocrinology, Diabetes and Metabolism

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