Peng Bo, Lou Han, Chen Chen, Wang Lei, Li Huawei, Lu Tong, Na Ruisi, Xu Ran, Xin Tong, Yao Lingqi, Xu Henghui, Wang Kaiyu, Liu Xin, Zhang Linyou
Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China and Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, China.
Front Genet. 2022 Jun 13;13:870302. doi: 10.3389/fgene.2022.870302. eCollection 2022.
The prognosis of the most common histological subtype of lung cancer, lung adenocarcinoma (LUAD), is relatively poor. Mitochondrial homeostasis depends to a great extent on the coordination between mitophagy and mitochondrial biogenesis, the deregulation of which causes various human diseases, including cancer. There is accumulating evidence that long noncoding RNAs (lncRNAs) are critical in predicting the prognosis and immune response in carcinoma. Therefore, it is critical to discern lncRNAs related to mitochondrial homeostasis in LUAD patients. In this study, we identified mitochondrial homeostasis-related lncRNAs (MHRlncRNAs) by coexpression analysis. In order to construct a prognostic signature composed of three MHRlncRNAs, univariate and multivariate Cox regression analyses were performed. Kaplan-Meier analysis, stratification analysis, principal component analysis (PCA), receiver operating characteristic (ROC) curve, gene set enrichment analysis (GSEA), and nomogram were applied to evaluate and optimize the risk model. Subsequently, we identified the mitochondrial homeostasis-related lncRNA signature (MHLncSig) as an independent predictive factor of prognosis. Based on the LUAD subtypes regrouped by this risk model, we further investigated the underlying tumor microenvironment, tumor mutation burden, and immune landscape behind different risk groups. Likewise, individualized immunotherapeutic strategies and candidate compounds were screened to aim at different risk subtypes of LUAD patients. Finally, we validated the expression trends of lncRNAs included in the risk model using quantitative real-time polymerase chain reaction (qRT-PCR) assays. The established MHLncSig may be a promising tool for predicting the prognosis and guiding individualized treatment in LUAD.
肺癌最常见的组织学亚型——肺腺癌（LUAD）的预后相对较差。线粒体稳态在很大程度上依赖于线粒体自噬与线粒体生物发生之间的协调，其失调会导致包括癌症在内的各种人类疾病。越来越多的证据表明，长链非编码RNA（lncRNA）在预测癌症的预后和免疫反应方面至关重要。因此，识别LUAD患者中与线粒体稳态相关的lncRNA至关重要。在本研究中，我们通过共表达分析鉴定了与线粒体稳态相关的lncRNA（MHRlncRNA）。为了构建一个由三个MHRlncRNA组成的预后特征，我们进行了单变量和多变量Cox回归分析。应用Kaplan-Meier分析、分层分析、主成分分析（PCA）、受试者工作特征（ROC）曲线、基因集富集分析（GSEA）和列线图来评估和优化风险模型。随后，我们将与线粒体稳态相关的lncRNA特征（MHLncSig）确定为预后的独立预测因素。基于此风险模型重新分组的LUAD亚型，我们进一步研究了不同风险组背后潜在的肿瘤微环境、肿瘤突变负担和免疫格局。同样，针对LUAD患者的不同风险亚型筛选了个性化的免疫治疗策略和候选化合物。最后，我们使用定量实时聚合酶链反应（qRT-PCR）分析验证了风险模型中包含的lncRNA的表达趋势。所建立的MHLncSig可能是预测LUAD预后和指导个体化治疗的一个有前景的工具。
