Ren Lei, Yang Xu, Wang Weifeng, Lin Hansen, Huang Guankai, Liu Zixiong, Pan Jincheng, Mao Xiaopeng
Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
Department of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China.
Front Genet. 2023 Feb 24;14:1096783. doi: 10.3389/fgene.2023.1096783. eCollection 2023.
As a new form of regulated cell death, cuproptosis differs profoundly from apoptosis, ferroptosis, pyroptosis, and necroptosis. The correlation between cuproptosis and long non-coding RNAs (lncRNAs) has been increasingly studied recently. In this study, a novel cuproptosis-related lncRNA prognostic signature was developed to investigate biochemical recurrence (BCR) and tumor immune landscape in prostate cancer (PCa). The transcriptome data and clinicopathologic information of PCa patients were downloaded from The Cancer Genome Atlas (TCGA). Pearson's correlation analysis was applied to identify lncRNAs associated with cuproptosis. Based on Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a cuproptosis-related lncRNA prognostic model (risk score) to predict the BCR of PCa patients. Additionally, we also constructed a nomogram with the risk score and clinicopathologic features. The biological function, tumor mutation burden (TMB), immune cell infiltration, expression levels of immune checkpoint genes, and anti-cancer drug sensitivity were investigated. We constructed and validated the cuproptosis-related lncRNA signature prognostic model (risk score) by six crlncRNAs. All patients were divided into the low- and high-risk groups based on the median risk score. The Kaplan-Meier (KM) survival analysis revealed that the high-risk group had shorter BCR-free survival (BCRFS). The risk score has been proven to be an independent prognostic factor of BCR in PCa patients. In addition, a nomogram of risk scores and clinicopathologic features was established and demonstrated an excellent predictive capability of BCR. The ROC curves further validated that this nomogram had higher accuracy of predicting the BCR compared to other clinicopathologic features. We also found that the high-risk group had higher TMB levels and more infiltrated immune cells. Furthermore, patients with high TMB in the high-risk group were inclined to have the shortest BCRFS. Finally, patients in the high-risk group were more susceptible to docetaxel, gefitinib, methotrexate, paclitaxel, and vinblastine. The novel crlncRNA signature prognostic model shows a greatly prognostic prediction value of BCR for PCa patients, extends our thought on the association of cuproptosis and PCa, and provides novel insights into individual-based treatment strategies for PCa.
作为一种新的程序性细胞死亡形式,铜死亡与细胞凋亡、铁死亡、焦亡和坏死性凋亡有很大不同。近年来,铜死亡与长链非编码RNA(lncRNA)之间的相关性研究越来越多。在本研究中,我们开发了一种新的与铜死亡相关的lncRNA预后特征,以研究前列腺癌(PCa)中的生化复发(BCR)和肿瘤免疫微环境。从癌症基因组图谱(TCGA)下载了PCa患者的转录组数据和临床病理信息。应用Pearson相关分析来鉴定与铜死亡相关的lncRNA。基于Cox回归分析和最小绝对收缩和选择算子(LASSO)回归分析,我们开发了一种与铜死亡相关的lncRNA预后模型(风险评分),以预测PCa患者的BCR。此外,我们还构建了一个包含风险评分和临床病理特征的列线图。研究了其生物学功能、肿瘤突变负荷(TMB)、免疫细胞浸润、免疫检查点基因的表达水平以及抗癌药物敏感性。我们通过6个crlncRNA构建并验证了与铜死亡相关的lncRNA特征预后模型(风险评分)。根据中位风险评分将所有患者分为低风险组和高风险组。Kaplan-Meier(KM)生存分析显示,高风险组的无生化复发生存期(BCRFS)较短。风险评分已被证明是PCa患者BCR的独立预后因素。此外,建立了一个包含风险评分和临床病理特征的列线图,并证明其对BCR具有出色的预测能力。ROC曲线进一步验证,与其他临床病理特征相比,该列线图对BCR的预测准确性更高。我们还发现,高风险组的TMB水平更高,免疫细胞浸润更多。此外,高风险组中TMB高的患者倾向于具有最短的BCRFS。最后,高风险组的患者对多西他赛、吉非替尼、甲氨蝶呤、紫杉醇和长春碱更敏感。新的crlncRNA特征预后模型对PCa患者的BCR具有很大的预后预测价值,扩展了我们对铜死亡与PCa关联的认识,并为PCa的个体化治疗策略提供了新的见解。