Department of Respiratory and Critical Care Medicine, Zhuzhou Central Hospital, Zhuzhou, 412000, Hunan, China.
Funct Integr Genomics. 2023 Oct 21;23(4):323. doi: 10.1007/s10142-023-01245-3.
Lung cancer is the most common type of malignant tumor that affects people in China and even across the globe, as it exhibits the highest rates of morbidity and mortality. Lung adenocarcinoma (LUAD) is a type of lung cancer with a very high incidence. The purpose of this study was to identify potential biomarkers that could be used to forecast the prognosis and improve the existing therapy options for treating LUAD. Clinical and RNA sequencing data of LUAD patients were retrieved from the TCGA database, while the mitochondria-associated gene sets were acquired from the MITOMAP database. Thereafter, Pearson correlation analysis was carried out to screen mitochondria-associated lncRNAs. Furthermore, univariate Cox and Lasso regression analyses were used for the initial screening of the target lncRNAs for prognostic lncRNAs before they could be incorporated into a multivariate Cox Hazard ratio model. Then, the clinical data, concordance index, Kaplan-Meier (K-M) curves, and the clinically-relevant subjects that were approved by the Characteristic Curves (ROC) were employed for assessing the model's predictive value. Additionally, the differences in immune-related functions and biological pathway enrichment between high- and low-risk LUAD groups were examined. Nomograms were developed to anticipate the OS rates of the patients within 1-, 3-, and 5 years, and the differences in drug sensitivity and immunological checkpoints were compared. In this study, 2175 mitochondria-associated lncRNAs were screened. Univariate, multivariate, and Lasso Cox regression analyses were carried out to select 13 lncRNAs with an independent prognostic significance, and a prognostic model was developed. The OS analysis of the established prognostic prediction model revealed significant variations between the high- and low-risk patients. The AUC-ROC values after 1, 3, and 5 years were seen to be 0.746, 0.692, and 0.726, respectively. The results suggested that the prognostic model riskscore could be used as an independent prognostic factor that differed from the other clinical characteristics. After analyzing the findings of the study, it was noted that both the risk groups showed significant differences in their immune functioning, immunological checkpoint genes, and drug sensitivity. The prognosis of patients with LUAD could be accurately and independently predicted using a risk prediction model that included 13 mitochondria-associated lncRNAs.
肺癌是影响中国乃至全球人群的最常见恶性肿瘤类型,其发病率和死亡率均最高。肺腺癌(LUAD)是一种发病率非常高的肺癌。本研究旨在寻找潜在的生物标志物,以预测 LUAD 的预后,并改善现有的治疗选择。从 TCGA 数据库中检索 LUAD 患者的临床和 RNA 测序数据,从 MITOMAP 数据库中获取与线粒体相关的基因集。然后,进行 Pearson 相关性分析以筛选与线粒体相关的 lncRNA。此外,使用单因素 Cox 和 Lasso 回归分析对预后 lncRNA 进行初步筛选,然后将其纳入多因素 Cox 风险比模型。然后,使用临床数据、一致性指数、Kaplan-Meier(K-M)曲线和经过特征曲线(ROC)批准的临床相关受试者来评估模型的预测价值。此外,还研究了高低风险 LUAD 组之间免疫相关功能和生物通路富集的差异。开发了列线图来预测患者在 1、3 和 5 年内的 OS 率,并比较了药物敏感性和免疫检查点的差异。在这项研究中,筛选了 2175 个与线粒体相关的 lncRNA。进行了单因素、多因素和 Lasso Cox 回归分析,以选择具有独立预后意义的 13 个 lncRNA,并建立了预后模型。建立的预后预测模型的 OS 分析显示,高低风险患者之间存在显著差异。1、3 和 5 年后的 AUC-ROC 值分别为 0.746、0.692 和 0.726。结果表明,预后模型风险评分可作为独立的预后因素,与其他临床特征不同。在分析研究结果后,发现两组在免疫功能、免疫检查点基因和药物敏感性方面均存在显著差异。使用包含 13 个与线粒体相关的 lncRNA 的风险预测模型可以准确且独立地预测 LUAD 患者的预后。