Chen Min, Wu Guang-Bo, Hua Shan, Zhao Zhi-Feng, Li Hong-Jie, Luo Meng
Department of General Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Front Genet. 2022 Sep 29;13:907859. doi: 10.3389/fgene.2022.907859. eCollection 2022.
The study focused on establishing a prognostic survival model with six necroptosis-related lncRNAs to predict overall survival (OS) in patients with hepatocellular carcinoma (HCC). The data of gene expression and clinical information of HCC patients were obtained from The Cancer Genome Atlas (TCGA). Cox regression with LASSO was used for constructing a necroptosis-related lncRNA survival model, which we further validated with qRT-PCR . The relative bioinformatics analysis and consensus cluster analysis were performed based on six differentially expressed lncRNAs. The survival prognostic model was constructed by using data from TCGA. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. GSEA showed that several signaling pathways were related to HCC progression. Immune-related functional analysis showed that aDCs, macrophages, Th2 cells, and Tregs have stronger correlation with the high-risk group. The consensus cluster analysis further validated the 6-lncRNA prognostic model. A novel 6-lncRNA (AL606489.1, NRAV, LINC02870, DUXAP8, "ZFPM2-AS1," and AL031985.3) prognostic model had an accurately predictive power in HCC prognosis, which might be worthy of clinical application.
该研究聚焦于建立一个包含六种坏死性凋亡相关长链非编码RNA（lncRNA）的预后生存模型，以预测肝细胞癌（HCC）患者的总生存期（OS）。HCC患者的基因表达数据和临床信息来自癌症基因组图谱（TCGA）。采用LASSO Cox回归构建坏死性凋亡相关lncRNA生存模型，并通过qRT-PCR进一步验证。基于六种差异表达的lncRNA进行了相关生物信息学分析和一致性聚类分析。利用TCGA的数据构建了生存预后模型。受试者工作特征（ROC）曲线显示该模型具有良好的生存预测能力。基因集富集分析（GSEA）表明，几种信号通路与HCC进展相关。免疫相关功能分析表明，活化树突状细胞（aDCs）、巨噬细胞、辅助性T细胞2（Th2细胞）和调节性T细胞（Tregs）与高危组的相关性更强。一致性聚类分析进一步验证了6-lncRNA预后模型。一种新的6-lncRNA（AL606489.1、NRAV、LINC02870、DUXAP8、“ZFPM2-AS1”和AL031985.3）预后模型在HCC预后方面具有准确的预测能力，可能值得临床应用。
