Chen Dongjie, Gao Wenzhe, Zang Longjun, Zhang Xianlin, Li Zheng, Zhu Hongwei, Yu Xiao
Department of Hepatopancreatobiliary Surgery, The Third Xiangya Hospital, Central South University, Changsha, China.
Department of General Surgery, Affiliated Renhe Hospital of China Three Gorges University, Yichang, China.
Front Cell Dev Biol. 2022 Feb 10;10:819724. doi: 10.3389/fcell.2022.819724. eCollection 2022.
Pancreatic cancer (PC) is one of the most lethal malignancies, the mortality and morbidity of which have been increasing over the past decade. Ferroptosis, a newly identified iron-dependent cell death pattern, can be induced by iron chelators and small lipophilic antioxidants. Nonetheless, the prognostic significance of ferroptosis-related lncRNAs in PC remains to be clarified. We obtained the lncRNA expression matrix and clinicopathological information of PC patients from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) datasets in the current study. Firstly, we conducted Pearson correlation analysis to delve into the ferroptosis-related lncRNAs, and univariate Cox analysis was implemented to examine the prognostic values in PC patients. Twenty-three prognostic ferroptosis-related lncRNAs were confirmed and loaded into the least absolute shrinkage and selection operator Cox (LASSO-Cox) analysis, then a ferroptosis-related lncRNA prognostic marker (Fe-LPM) was established in the TCGA dataset. Risk scores of patients were calculated and segregated PC patients into low-risk and high-risk subgroups in each dataset. The prognostic capability of Fe-LPM was also confirmed in the ICGC dataset. Gene set enrichment analysis (GSEA) revealed that several ferroptosis-related pathways were enriched in low-risk subgroups. Furthermore, we adopted a multivariate Cox regression to establish a nomogram based on risk score, age, pathological T stage and primary therapy outcome. A competing endogenous RNA (ceRNA) network was also created relied on four of the twenty-three ferroptosis-related lncRNAs. In conclusion, the eight Fe-LPM can be utilized to anticipate the overall survival (OS) of PC patients, which are meaningful to guiding clinical strategies in PC.
胰腺癌(PC)是最致命的恶性肿瘤之一,在过去十年中其死亡率和发病率一直在上升。铁死亡是一种新发现的铁依赖性细胞死亡模式,可由铁螯合剂和小的亲脂性抗氧化剂诱导。然而,铁死亡相关lncRNAs在PC中的预后意义仍有待阐明。在本研究中,我们从癌症基因组图谱(TCGA)和国际癌症基因组联盟(ICGC)数据集中获得了PC患者的lncRNA表达矩阵和临床病理信息。首先,我们进行Pearson相关性分析以深入研究铁死亡相关lncRNAs,并进行单变量Cox分析以检验PC患者的预后价值。确认了23个与预后相关的铁死亡lncRNAs,并将其纳入最小绝对收缩和选择算子Cox(LASSO-Cox)分析,然后在TCGA数据集中建立了一个铁死亡相关lncRNA预后标志物(Fe-LPM)。计算患者的风险评分,并将每个数据集中的PC患者分为低风险和高风险亚组。Fe-LPM的预后能力也在ICGC数据集中得到证实。基因集富集分析(GSEA)显示,几个铁死亡相关通路在低风险亚组中富集。此外,我们采用多变量Cox回归,基于风险评分、年龄、病理T分期和初始治疗结果建立了一个列线图。还基于23个铁死亡相关lncRNAs中的4个创建了一个竞争性内源性RNA(ceRNA)网络。总之,这八个Fe-LPM可用于预测PC患者的总生存期(OS),这对于指导PC的临床策略具有重要意义。