Zhao Jie, Li Guangjian, Zhao Guangqiang, Wang Wei, Shen Zhenghai, Yang Yantao, Huang Yunchao, Ye Lianhua
Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China.
Department of Thoracic Surgery, Taihe Hospital (Hubei University of Medicine), Shiyan, China.
Front Oncol. 2022 Nov 1;12:986367. doi: 10.3389/fonc.2022.986367. eCollection 2022.
Lung adenocarcinoma (LUAD) is the most predominant histological subtype of lung cancer. Abnormal lipid metabolism is closely related to the development of LUAD. LncRNAs are involved in the regulation of various lipid metabolism-related genes in various cancer cells including LUAD. Here, we aimed to identify lipid metabolism-related lncRNAs associated with LUAD prognosis and to propose a new prognostic signature.
First, differentially expressed lncRNAs (DE-lncRNAs) from the TCGA-LUAD and the GSE31210 dataset were identified. Then the correlation analysis between DE-lncRNAs and lipid metabolism genes was performed to screen lipid metabolism-related lncRNAs. Cox regression analyses were performed in the training set to establish a prognostic model and the model was validated in the testing set and the validation set. Moreover, The role of this model in the underlying molecular mechanisms, immunotherapy, and chemotherapeutic drug sensitivity analysis was predicted by methods such as Gene Set Enrichment Analysis, immune infiltration, tumor mutational burden (TMB), neoantigen, Tumor Immune Dysfunction and Exclusion, chemosensitivity analysis between the high- and low-risk groups. The diagnostic ability of prognostic lncRNAs has also been validated. Finally, we validated the expression levels of selected prognostic lncRNAs by quantitative real-time polymerase chain reaction (qRT-PCR).
The prognostic model was constructed based on four prognostic lncRNAs (LINC00857, EP300-AS1, TBX5-AS1, SNHG3) related to lipid metabolism. The receiver operating characteristic curve (ROC) and Kaplan Meier (KM) curves of the risk model showed their validity. The results of Gene Set Enrichment Analysis suggested that differentially expressed genes in high- and low-risk groups were mainly enriched in immune response and cell cycle. There statistical differences in TMB and neoantigen between high- and low-risk groups. Drug sensitivity analysis suggested that patients with low risk scores may have better chemotherapy outcomes. The results of qRT-PCR were suggesting that compared with the normal group, the expressions of EP300-AS1 and TBX5-AS1 were down-regulated in the tumor group, while the expressions of LINC00857 and SNHG3 were up-regulated. The four prognostic lncRNAs had good diagnostic capabilities, and the overall diagnostic model of the four prognostic lncRNAs was more effective.
A total of 4 prognostic lncRNAs related to lipid metabolism were obtained and an effective risk model was constructed.
肺腺癌（LUAD）是肺癌最主要的组织学亚型。脂质代谢异常与肺腺癌的发生发展密切相关。长链非编码RNA（lncRNAs）参与包括肺腺癌在内的多种癌细胞中各种脂质代谢相关基因的调控。在此，我们旨在鉴定与肺腺癌预后相关的脂质代谢相关lncRNAs，并提出一种新的预后特征。
首先，从TCGA-LUAD和GSE31210数据集中鉴定出差异表达的lncRNAs（DE-lncRNAs）。然后进行DE-lncRNAs与脂质代谢基因之间的相关性分析，以筛选脂质代谢相关的lncRNAs。在训练集中进行Cox回归分析以建立预后模型，并在测试集和验证集中对该模型进行验证。此外，通过基因集富集分析、免疫浸润、肿瘤突变负荷（TMB）、新抗原、肿瘤免疫功能障碍与排除、高低风险组之间的化疗敏感性分析等方法，预测该模型在潜在分子机制、免疫治疗和化疗药物敏感性分析中的作用。还验证了预后lncRNAs的诊断能力。最后，我们通过定量实时聚合酶链反应（qRT-PCR）验证了所选预后lncRNAs的表达水平。
基于与脂质代谢相关的4个预后lncRNAs（LINC00857、EP300-AS1、TBX5-AS1、SNHG3）构建了预后模型。风险模型的受试者工作特征曲线（ROC）和Kaplan Meier（KM）曲线显示了其有效性。基因集富集分析结果表明，高低风险组中的差异表达基因主要富集于免疫反应和细胞周期。高低风险组之间的TMB和新抗原有统计学差异。药物敏感性分析表明，低风险评分的患者可能有更好的化疗效果。qRT-PCR结果表明，与正常组相比，肿瘤组中EP300-AS1和TBX5-AS1的表达下调，而LINC00857和SNHG3的表达上调。这4个预后lncRNAs具有良好的诊断能力，4个预后lncRNAs的整体诊断模型更有效。
共获得4个与脂质代谢相关的预后lncRNAs，并构建了有效的风险模型。
