Li Zheng, Xu Dan, Jing Jing, Wang Jing, Jiang Min, Li Fengsen
The Traditional Chinese Medicine Hospital Affiliated with Xinjiang Medical University, Urumqi, China.
National Clinical Research Base of Traditional Chinese Medicine, Urumqi, China.
J Oncol. 2022 Aug 17;2022:4254195. doi: 10.1155/2022/4254195. eCollection 2022.
Globally, the incidence and associated mortality of chronic obstructive pulmonary disease (COPD) and lung carcinoma are showing a worsening trend. There is increasing evidence that COPD is an independent risk factor for the occurrence and progression of lung carcinoma. This study aimed to identify and validate the gene signatures associated with COPD, which may serve as potential new biomarkers for the prediction of prognosis in patients with lung carcinoma.
A total of 111 COPD patient samples and 40 control samples were obtained from the GSE76925 cohort, and a total of 4933 genes were included in the study. The weighted gene coexpression network analysis (WGCNA) was performed to identify the modular genes that were significantly associated with COPD. The KEGG pathway and GO functional enrichment analyses were also performed. The RNAseq and clinicopathological data of 490 lung squamous cell carcinoma patients were obtained from the TCGA database. Further, univariate Cox regression and Lasso analyses were performed to screen for marker genes and construct a survival analysis model. Finally, the Human Protein Atlas (HPA) database was used to assess the gene expression in normal and tumor tissues of the lungs.
A 6-gene signature (DVL1, MRPL4, NRTN, NSUN3, RPH3A, and SNX32) was identified based on the Cox proportional risk analysis to construct the prognostic RiskScore survival model associated with COPD. Kaplan-Meier survival analysis indicated that the model could significantly differentiate between the prognoses of patients with lung carcinoma, wherein higher RiskScore samples were associated with a worse prognosis. Additionally, the model had a good predictive performance and reliability, as indicated by a high AUC, and these were validated in both internal and external sets. The 6-gene signature had a good predictive ability across clinical signs and could be considered an independent factor of prognostic risk. Finally, the protein expressions of the six genes were analyzed based on the HPA database. The expressions of DVL1, MRPL4, and NSUN3 were relatively higher, while that of RPH3A was relatively lower in the tumor tissues. The expression of SNX32 was high in both the tumor and paracarcinoma tissues. Results of the analyses using TCGA and GSE31446 databases were consistent with the expressions reported in the HPA database.
Novel COPD-associated gene markers for lung carcinoma were identified and validated in this study. The genes may be considered potential biomarkers to evaluate the prognostic risk of patients with lung carcinoma. Furthermore, some of these genes may have implications as new therapeutic targets and can be used to guide clinical applications.
在全球范围内，慢性阻塞性肺疾病（COPD）和肺癌的发病率及相关死亡率呈上升趋势。越来越多的证据表明，COPD是肺癌发生和发展的独立危险因素。本研究旨在识别并验证与COPD相关的基因特征，这些特征可能作为预测肺癌患者预后的潜在新生物标志物。
从GSE76925队列中获取了111份COPD患者样本和40份对照样本，共纳入4933个基因进行研究。进行加权基因共表达网络分析（WGCNA）以识别与COPD显著相关的模块基因。还进行了KEGG通路和GO功能富集分析。从TCGA数据库中获取了490例肺鳞状细胞癌患者的RNAseq和临床病理数据。此外，进行单变量Cox回归和Lasso分析以筛选标记基因并构建生存分析模型。最后，使用人类蛋白质图谱（HPA）数据库评估肺正常组织和肿瘤组织中的基因表达。
基于Cox比例风险分析确定了一个6基因特征（DVL1、MRPL4、NRTN、NSUN3、RPH3A和SNX32），以构建与COPD相关的预后风险评分生存模型。Kaplan-Meier生存分析表明，该模型可显著区分肺癌患者的预后，其中风险评分较高的样本预后较差。此外，该模型具有良好的预测性能和可靠性，AUC较高，在内部和外部数据集均得到验证。该6基因特征在临床体征方面具有良好的预测能力，可被视为预后风险的独立因素。最后，基于HPA数据库分析了这六个基因的蛋白表达。在肿瘤组织中，DVL1、MRPL4和NSUN3的表达相对较高，而RPH3A的表达相对较低。SNX32在肿瘤组织和癌旁组织中的表达均较高。使用TCGA和GSE31446数据库的分析结果与HPA数据库报道的表达一致。
本研究识别并验证了与肺癌相关的新型COPD相关基因标志物。这些基因可被视为评估肺癌患者预后风险的潜在生物标志物。此外，其中一些基因可能具有作为新治疗靶点的意义，可用于指导临床应用。
