Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Aging (Albany NY). 2022 May 12;14(9):4069-4084. doi: 10.18632/aging.204073.
Hepatocellular Carcinoma (HCC) is a highly heterogeneous malignant tumor, and its prognostic prediction is extremely challenging. Ferroptosis is a cell mechanism dependent on iron, which is very significant for HCC development. Long non-coding RNA (lncRNA) is also linked to HCC progression. This work aimed to establish a prognosis risk model for HCC and to discover a possible biomarker and therapeutic target.
The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq transcriptome data and clinic information of HCC patients. Firstly, univariate Cox was utilized to identify 66 prognostic ferroptosis-related lncRNAs. Then, the identified lncRNAs were further included in the multivariate Cox analysis to construct the prognostic model. Eventually, we performed quantitative polymerase chain reaction (q-PCR) to validate the risk model.
We established a prognostic seventeen-ferroptosis-related lncRNA signature model. The signature could categorize patients into two risk subgroups, with the low-risk subgroup associated with a better prognosis. Additionally, the area under the curve (AUC) of the lncRNAs signature was 0.801, indicating their reliability in forecasting HCC prognosis. Risk score was an independent prognostic factor by regression analyses. Gene set enrichment analysis (GSEA) analyses demonstrated a remarkable enrichment of cancer-related and immune-related pathways in the high-risk group. Besides, the immune status was decreased in the high-risk group. Eventually, three prognostic lncRNAs were validated in human HCCLM3 cell lines.
The risk model based on seventeen-ferroptosis-related lncRNA has significant prognostic value for HCC and may be therapeutic targets associated with ferroptosis in clinical ways.
肝细胞癌（HCC）是一种高度异质性的恶性肿瘤，其预后预测极具挑战性。铁死亡是一种依赖铁的细胞机制，对 HCC 的发展非常重要。长链非编码 RNA（lncRNA）也与 HCC 的进展有关。本研究旨在建立 HCC 的预后风险模型，并发现可能的生物标志物和治疗靶点。
利用癌症基因组图谱（TCGA）数据库获取 HCC 患者的 RNA-seq 转录组数据和临床信息。首先，采用单因素 Cox 分析筛选出 66 个与铁死亡相关的预后 lncRNA。然后，将鉴定出的 lncRNA 进一步纳入多因素 Cox 分析，构建预后模型。最后，通过定量聚合酶链反应（q-PCR）验证风险模型。
我们建立了一个由十七个与铁死亡相关的 lncRNA 组成的预后签名模型。该模型可将患者分为两个风险亚组，低风险组的预后较好。此外，lncRNAs 签名的曲线下面积（AUC）为 0.801，表明其在预测 HCC 预后方面具有较高的可靠性。通过回归分析，风险评分是一个独立的预后因素。基因集富集分析（GSEA）分析表明，高风险组中存在显著富集的癌症相关和免疫相关通路。此外，高风险组的免疫状态降低。最后，在人 HCCLM3 细胞系中验证了三个预后 lncRNA。
基于十七个与铁死亡相关的 lncRNA 的风险模型对 HCC 具有显著的预后价值，并且可能是临床相关铁死亡的治疗靶点。
