Liu Ze-Kun, Wu Ke-Fei, Zhang Ren-Yu, Kong Ling-Min, Shang Run-Ze, Lv Jian-Jun, Li Can, Lu Meng, Yong Yu-Le, Zhang Cong, Zheng Nai-Shan, Li Yan-Hong, Chen Zhi-Nan, Bian Huijie, Wei Ding
National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China.
Department of General Surgery, Affiliated Haixia Hospital of Huaqiao University (The 910 Hospital of the Joint Logistics Team), Quanzhou, China.
Front Oncol. 2022 Mar 3;12:794034. doi: 10.3389/fonc.2022.794034. eCollection 2022.
Pyroptosis is an inflammatory form of programmed cell death that is involved in various cancers, including hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) were recently verified as crucial mediators in the regulation of pyroptosis. However, the role of pyroptosis-related lncRNAs in HCC and their associations with prognosis have not been reported. In this study, we constructed a prognostic signature based on pyroptosis-related differentially expressed lncRNAs in HCC. A co-expression network of pyroptosis-related mRNAs-lncRNAs was constructed based on HCC data from The Cancer Genome Atlas. Cox regression analyses were performed to construct a pyroptosis-related lncRNA signature (PRlncSig) in a training cohort, which was subsequently validated in a testing cohort and a combination of the two cohorts. Kaplan-Meier analyses revealed that patients in the high-risk group had poorer survival times. Receiver operating characteristic curve and principal component analyses further verified the accuracy of the PRlncSig model. Besides, the external cohort validation confirmed the robustness of PRlncSig. Furthermore, a nomogram based on the PRlncSig score and clinical characteristics was established and shown to have robust prediction ability. In addition, gene set enrichment analysis revealed that the RNA degradation, the cell cycle, the WNT signaling pathway, and numerous immune processes were significantly enriched in the high-risk group compared to the low-risk group. Moreover, the immune cell subpopulations, the expression of immune checkpoint genes, and response to chemotherapy and immunotherapy differed significantly between the high- and low-risk groups. Finally, the expression levels of the five lncRNAs in the signature were validated by quantitative real-time PCR. In summary, our PRlncSig model shows significant predictive value with respect to prognosis of HCC patients and could provide clinical guidance for individualized immunotherapy.
细胞焦亡是一种程序性细胞死亡的炎症形式,参与包括肝细胞癌(HCC)在内的多种癌症。长链非编码RNA(lncRNA)最近被证实是细胞焦亡调控中的关键介质。然而,细胞焦亡相关lncRNA在HCC中的作用及其与预后的关系尚未见报道。在本研究中,我们基于HCC中细胞焦亡相关差异表达lncRNA构建了一个预后特征。基于来自癌症基因组图谱的HCC数据构建了细胞焦亡相关mRNA-lncRNA的共表达网络。在训练队列中进行Cox回归分析以构建细胞焦亡相关lncRNA特征(PRlncSig),随后在测试队列以及两个队列的组合中进行验证。Kaplan-Meier分析显示,高风险组患者的生存时间较差。受试者工作特征曲线和主成分分析进一步验证了PRlncSig模型的准确性。此外,外部队列验证证实了PRlncSig的稳健性。此外,建立了基于PRlncSig评分和临床特征的列线图,并显示具有强大的预测能力。此外,基因集富集分析显示,与低风险组相比,高风险组中RNA降解、细胞周期、WNT信号通路和许多免疫过程显著富集。此外,高风险组和低风险组之间的免疫细胞亚群、免疫检查点基因的表达以及对化疗和免疫治疗的反应存在显著差异。最后,通过定量实时PCR验证了特征中五个lncRNA的表达水平。总之,我们的PRlncSig模型对HCC患者的预后具有显著的预测价值,并可为个体化免疫治疗提供临床指导。