Comprehensive analysis of cuproptosis-related lncRNAs in the prognosis and therapy response of patients with bladder cancer

Abstract

Background: Cuproptosis is the recently defined regulatory cell death (RCD) that plays essential roles in tumorigenesis and progression. Long noncoding RNAs (lncRNAs) regulate the gene expression through various means. However, the clinical value of cuproptosis-related lncRNAs in bladder cancer (BLCA) remains poorly described. Methods:We downloaded the transcriptome sequencing data and clinical information from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and lasso Cox regression analyses were performed to construct the prognostic risk signature, the predictive accuracy of which was validated in the subsequent independence and stratification analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore the underlying molecular mechanisms involved in the signature to explore therapeutic vulnerabilities and potential targets in BLCA. Tumor mutational burden (TMB) and tumor immune dysfunction and exclusion (TIDE) were used to estimate the response to immune checkpoint inhibitors (ICIs). We further explored the potential new drug-target candidates based on the half maximal inhibitory concentration for this patient population.Results: Fifteen cuproptosis-related lncRNAs significantly associated with survival were identified to construct the risk signature based on the normalized expression level and regression coefficient of each gene.The patients with BLCA and high-risk scores defined by the signature were associated with worse survival outcomes. The differentially expressed genes (DEGs) between the 2 risk groups had different biological activity. Furthermore, the patients in the low-risk group exhibited a higher TMB index and a lower TIDE score. The sensitivity of multiple antitumor drugs was negatively related to risk score, including AR-42, AS605240, FK866, TAK-715, and tubastatin A, while the sensitivity of some antitumor drugs, such as AMG-706, BX-795, and RO-3306, were positively correlated with risk score.Conclusions: Our study established and verified a novel clinical risk signature with cuproptosis-related lncRNAs that may predict therapy response and prognosis with robust and stable accuracy in patients with BLCA and enhance the personalized management of this patient population.

A comprehensive analysis of FBN2 in bladder cancer: A risk factor and the tumour microenvironment influencer

“…A potential predictive biomarker of clinical response to immune checkpoint inhibitor treatment is TMB, or the amount of somatic missense mutations per million bases (MB) in a tumour's genes [ 62 ]. Neoantigens are produced as a result of the slow accumulation of somatic mutations, which activate T cell immunogenicity and suppress tumour cells [ 63 ]. High TMB tumours produce many antigens, making them immunogenic and triggering an anticancer response [ 64 ].…”

Research progress of N1-methyladenosine RNA modification in cancer

“…In 2022, BC emerged as the second most common malignant tumor within the urinary system, accounting for 17,100 out of the 81,180 new cases reported. Despite the availability of a wide array of treatment modalities, the prognosis for BC remains unsatisfactory [53][54][55][56]. Glioma-ABCC3, ALKBH1, ALKBH3, TRMT61B, TRMT6, TRMT10C, TRMT61A -Proliferation and resistance [88][89][90][91][92] Bladder-cancer-TRMT6/TRMT61A, ALKBH3 tRF-3-UPR, NOX-ROS signaling Tumorigenesis, tumor angiogenesis and invasiveness [97,98] In recent years, the advancement of our understanding of BC has been significantly augmented by increased research into RNA modification.…”

基于铜死亡相关的 lncRNA的膀胱癌预后模型的构建及免疫浸润分析

“…铜死亡是一种铜依赖性的新型细胞程序性死亡，由脂酰化蛋白介导且与细胞线粒体代谢高度相关 ［ 10 ］ 。目前，已有铜死亡相关lncRNA用于建立肾透明细胞癌、肝细胞癌及胃癌预后模型的报道 ［ 6 ， 16 - 17 ］ 。可见铜死亡相关lncRNA与肿瘤的预后有非常紧密的联系，但铜死亡相关lncRNA在膀胱癌预后预测中的应用至今少有探讨。Cai等 ［ 18 ］ 基于铜死亡相关lncRNA构建了膀胱癌患者预后评估模型，但模型预测患者预后的AUC均不理想；Li等 ［ 19 ］ 选用15个铜死亡相关lncRNA构建了膀胱癌患者预后评估模型，虽然AUC较高，但由于选用的lncRNA数过多，临床应用中检验难度较大。本研究基于TCGA数据库建立铜死亡相关lncRNA模型来预测膀胱癌患者的预后，旨在为膀胱癌患者的预后风险评估提供新的工具。…”