Wang Xinyi, Jing Hui, Li Hecheng
Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Transl Lung Cancer Res. 2023 Feb 28;12(2):230-246. doi: 10.21037/tlcr-22-500. Epub 2023 Feb 23.
Cuproptosis, a recently discovered type of programmed cell death (PCD), paves a new avenue for cancer treatment. It has been revealed that PCD-related lncRNAs play a critical role in various biological processes of lung adenocarcinoma (LUAD). However, the role of cuproptosis-related lncRNA (CuRLs) remains unclear. This study aimed to identify and validate a CuRLs-based signature for the prognostic prediction of patients with LUAD.
RNA sequencing data and clinical information of LUAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Pearson correlation analysis was used to identify CuRLs. Univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, and stepwise multivariate Cox analysis were applied to construct a novel prognostic CuRLs signature. A nomogram was developed for the prediction of patient survival outcomes. Gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were utilized to explore potential functions underlying the CuRLs signature. Patients were divided into low- and high-risk groups. Several algorithms, such as tumor immune estimation resource (TIMER), cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), and QuanTIseq, were combined to comprehensively investigate the differences in immune landscape between different risk groups. Sensitivity to common anticancer drugs was analyzed using the pRRophetic algorithm.
We constructed a novel prognostic signature based on 10 CuRLs, including and . This 10-CuRLs risk signature showed great diagnostic accuracy combined with traditional clinical risk factors, and a nomogram was constructed for potential clinical translation. The tumor immune microenvironment was significantly different between different risk groups. Among drugs commonly used in the treatment of lung cancer, the sensitivity of cisplatin, docetaxel, gemcitabine, gefitinib, and paclitaxel was higher in low-risk patients, and patients in the low-risk group may benefit more from imatinib.
These results revealed the outstanding contribution of the CuRLs signature to the evaluation of prognosis and treatment modalities for patients with LUAD. The differences in characteristics between different risk groups provide an opportunity for better patient stratification and to explore novel drugs in different risk groups.
铜死亡是一种最近发现的程序性细胞死亡（PCD）类型，为癌症治疗开辟了一条新途径。研究表明，与PCD相关的长链非编码RNA（lncRNA）在肺腺癌（LUAD）的各种生物学过程中起着关键作用。然而，与铜死亡相关的lncRNA（CuRLs）的作用仍不清楚。本研究旨在识别并验证一种基于CuRLs的特征，用于预测LUAD患者的预后。
从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）获取LUAD的RNA测序数据和临床信息。采用Pearson相关分析识别CuRLs。应用单因素Cox回归分析、最小绝对收缩和选择算子（LASSO）Cox回归以及逐步多因素Cox分析构建一种新的预后CuRLs特征。绘制列线图以预测患者生存结局。利用基因集变异分析（GSVA）、基因集富集分析（GSEA）、基因本体（GO）和京都基因与基因组百科全书（KEGG）通路分析来探索CuRLs特征潜在的功能。将患者分为低风险组和高风险组。结合多种算法，如肿瘤免疫估计资源（TIMER）、通过估计RNA转录本相对亚群进行细胞类型鉴定（CIBERSORT）和QuanTIseq，全面研究不同风险组之间免疫格局的差异。使用pRRophetic算法分析对常用抗癌药物的敏感性。
我们基于10个CuRLs构建了一种新的预后特征，包括[具体内容缺失]和[具体内容缺失]。这种10-CuRLs风险特征与传统临床风险因素相结合显示出很高的诊断准确性，并构建了列线图用于潜在的临床转化。不同风险组之间的肿瘤免疫微环境存在显著差异。在肺癌常用治疗药物中，低风险患者对顺铂、多西他赛、吉西他滨、吉非替尼和紫杉醇的敏感性较高，低风险组患者可能从伊马替尼中获益更多。
这些结果揭示了CuRLs特征对LUAD患者预后评估和治疗方式的突出贡献。不同风险组之间特征的差异为更好地进行患者分层以及探索不同风险组中的新药提供了机会。
