Abstract：
Hepatocellular carcinoma (HCC) is the most common type of liver cancer, characterized by a high morbidity rate. Long non-coding RNAs (lncRNAs) play an important role in regulating various cellular processes and diseases, including cancer. However, their specific roles and mechanisms in HCC are not fully understood. This study used a multi-cohort design to investigate necroptosis-related lncRNAs (NRLs) in patients with HCC. We curated a list of 1095 NRLs and 838 genes showing differential expression between tumor and normal tissues. Among them, we found 105 NRLs closely associated with the prognosis of HCC patients. The 10 lncRNAs (AC100803.3, AC027237.2, AL158166.1, LINC02870, AC026412.3, LINC02159, AC027097.1, AC139887.4, AC007405.1, AL023583.1) generated by LASSO-Cox regression analysis were used to create a prognostic risk model for HCC and group patients into groups based on risk. The KEGG analysis revealed distinct pathway enrichments in high-risk (H-R) and low-risk (L-R) subgroups. According to GO analysis, this study identified 230 differentially expressed genes (DEGs) that were significantly enriched in specific biological processes. Comparison of immune checkpoint-related genes (MCPGs) between H-R and L-R patients revealed significant differences. Moreover, we established a correlation between the risk scores of patients with liver cancer and their sensitivity to 16 chemotherapeutic agents. Employing protein-protein interaction (PPI) analysis, we identified 10 hub genes that potentially regulate the molecular networks involved in HCC development. This study is a pioneering effort to investigate the roles of NRLs in HCC. It opens a new avenue for potential targeted therapies and provides insights into the molecular mechanisms of HCC.
摘要：
肝细胞癌（HCC）是肝癌的最常见类型，其特点是发病率高。长链非编码RNA(lncRNAs)在调节各种细胞过程和疾病中起着重要作用。包括癌症.然而,它们在HCC中的具体作用和机制尚不完全清楚。本研究使用多队列设计来研究HCC患者中与坏死相关的lncRNAs（NRL）。我们整理了1095个NRL和838个基因的列表，这些基因显示了肿瘤和正常组织之间的差异表达。其中,我们发现105个NRLs与HCC患者的预后密切相关。LASSO-Cox回归分析产生的10个lncRNAs（AC100803.3，AC027237.2，AL158166.1，LINC02870，AC026412.3，LINC02159，AC027097.1，AC139887.4，AC007405.1，AL023583.1）用于创建HCC的预后风险模型，并根据风险将患者分组。KEGG分析揭示了高风险（H-R）和低风险（L-R）亚组中不同的途径富集。根据GO分析，这项研究确定了230个差异表达基因（DEGs），这些基因在特定的生物过程中显著富集。H-R和L-R患者之间免疫检查点相关基因（MCPG）的比较显示出显着差异。此外，我们建立了肝癌患者的风险评分与其对16种化疗药物的敏感性之间的相关性.采用蛋白质-蛋白质相互作用(PPI)分析，我们确定了10个hub基因,这些hub基因可能调控HCC发生的分子网络.这项研究是研究NRLs在HCC中的作用的开创性工作。它为潜在的靶向治疗开辟了一条新途径，并提供了对HCC分子机制的见解。
