Medical School of Chinese People's Liberation Army (PLA), Beijing, China.
Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, Beijing, China.
Front Immunol. 2022 Jun 24;13:836576. doi: 10.3389/fimmu.2022.836576. eCollection 2022.
Worldwide, hepatocellular carcinoma (HCC) is the most common subtype of liver cancer. However, the survival rate of patients with HCC continues to be poor. The recent literature has revealed that long non-coding RNAs (lncRNAs) and the occurrence of pyroptosis can perform a substantial task in predicting the prognosis of the respective condition along with the response to immunotherapy among HCC patients. Thus, screening and identifying lncRNAs corelated with pyroptosis in HCC patients are critical. In the current study, pyroptosis-related lncRNAs (PR-lncRNAs) have been obtained by co-expression analysis. The Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regression assessments have been performed to develop a PR-lncRNA prognostic model. The risk model was analysed using Kaplan-Meier analysis, principal component analysis (PCA), functional enrichment annotation, and a nomogram. The risk model composed of five PR-lncRNAs was identified as an independent prognostic factor. The tumour immune microenvironment (TIME) was assessed using model groupings. Finally, we validated the five PR-lncRNAs using a quantitative real-time polymerase chain reaction (qRT-PCR).
在全球范围内,肝细胞癌 (HCC) 是最常见的肝癌亚型。然而,HCC 患者的生存率仍然很差。最近的文献表明,长链非编码 RNA (lncRNA) 和细胞焦亡的发生可以在预测 HCC 患者的预后以及对免疫治疗的反应方面发挥重要作用。因此,筛选和鉴定与 HCC 患者细胞焦亡相关的 lncRNA 至关重要。在本研究中,通过共表达分析获得了与细胞焦亡相关的 lncRNA (PR-lncRNA)。采用最小绝对收缩和选择算子 (LASSO) 以及单因素和多因素 Cox 回归评估构建了 PR-lncRNA 预后模型。采用 Kaplan-Meier 分析、主成分分析 (PCA)、功能富集注释和列线图对风险模型进行了分析。确定了由五个 PR-lncRNA 组成的风险模型是一个独立的预后因素。使用模型分组评估肿瘤免疫微环境 (TIME)。最后,我们使用实时定量聚合酶链反应 (qRT-PCR) 验证了这五个 PR-lncRNA。