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

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.

Systematic analysis of the cuprotosis in tumor microenvironment and prognosis of gastric cancer

“…The uncontrolled death of single or mixed RCDs can lead to various human diseases, including cancer. Moreover, several cancers, including pancreatic adenocarcinoma, colon cancer, ovarian cancer, liver cancer, triple-negative breast cancer, bladder cancer, and clear-cell renal cell carcinoma, may benefit from the utilization of cuproptosis-related genes in prognosis prediction, immune response evaluation, and tumor classification [ [54] , [55] , [56] , [57] , [58] , [59] , [60] ]. We also established a risk score based on the cuprotosis signature that was able to predict the prognosis, response to ICIs and GC subtype of patients.…”

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

“…膀胱癌是起源于尿路上皮的恶性肿瘤，是我国泌尿系统肿瘤所致死亡的最常见原因 ［ 1 ］ 。膀胱癌的治疗方案包括手术切除、放化疗和免疫治疗等，尽管这些治疗方法近年来取得了显著进展，但患者治疗后复发或进展的可能性仍较高，其中约40%的患者会多次复发 ［ 2 ］ 。目前临床上膀胱癌患者的预后主要通过组织病理学诊断和肿瘤分期系统进行预测，但准确度不高。虽已有多个研究通过TCGA和GEO等公共数据库构建膀胱癌预后模型，但仍无法同时满足方便快捷和高准确率的要求 ［ 3 - 5 ］ 。因此，建立膀胱癌患者预后的高效预测模型，对于指导临床个性化治疗十分必要。…”