A Novel Assessment Model Based on Molecular Subtypes of Hypoxia-Related LncRNAs for Prognosis of Bladder Cancer

基于缺氧相关长链非编码RNA分子亚型的膀胱癌预后新型评估模型

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Abstract

Hypoxia is a common feature in various tumors that regulates aggressiveness. Previous studies have demonstrated that some dysregulated long non-coding RNAs (lncRNAs) are correlated with tumor progression, including bladder cancer (BCa). However, the prognostic effect of hypoxia-related lncRNAs (HRLs) and their clinical relevance, as well as their regulatory effect on the tumor immune microenvironment, are largely unknown in BCa. A co-expression analysis between hypoxia genes and lncRNA expression, which was downloaded from the TCGA database, was performed to identify HRLs. Univariate Cox regression analysis was performed to select the most desirable lncRNAs for molecular subtype, and further LASSO analysis was performed to develop a prognostic model. This molecular subtype based on four HRLs (AC104653, AL136084, AL139393, and LINC00892) showed good performance in the tumor microenvironment and tumor mutation burden. The prognostic risk model suggested better performance in predicting BCa patients' prognosis and obtained a close correlation with clinicopathologic features. Furthermore, four of five first-line clinical chemotherapies showed different sensitivities to this model, and nine immune checkpoints showed different expression in the molecular subtypes or the risk model. In conclusion, this study indicates that this molecular subtype and risk model based on HRLs may be useful in improving the prognostic prediction of BCa patients with different clinical situations and may help to find a useful target for tumor therapy.

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