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鉴定预测胰腺癌预后和治疗反应的铁死亡相关特征

Identification of ferroptosis-related signature predicting prognosis and therapeutic responses in pancreatic cancer.

作者信息

Chung Ting Ting, Piao Zanyue, Lee Seung Jin

机构信息

College of Pharmacy, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, Republic of Korea.

出版信息

Sci Rep. 2025 Jan 2;15(1):75. doi: 10.1038/s41598-024-84607-6.

Abstract

Ferroptosis plays a role in tumorigenesis by affecting lipid peroxidation and metabolic pathways; however, its prognostic or therapeutic relevance in pancreatic adenocarcinoma (PAAD) remains poorly understood. In this study, we developed a prognostic ferroptosis-related gene (FRG)-based risk model using cohorts of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), proposing plausible therapeutics. Differentially expressed FRGs between tumors from TCGA-PAAD and normal pancreatic tissues from Genotype-Tissue Expression were analyzed to construct a prognostic risk model using univariate and multivariate Cox regression and LASSO analyses. A model incorporating AURKA, CAV1, and PML gene expression effectively distinguished survival differences between high- and low-risk groups among TCGA-PAAD patients, with validation in two ICGC cohorts. The high-risk group was enriched in gene sets involving mTOR, MAPK, and E2F signaling. The immune and stromal cells infiltration score did not differ between the groups. Analysis of PRISM datasets using our risk model to classify pancreatic cell lines suggested the dasatinib's efficacy in the high-risk group, which was experimentally confirmed in four cell lines with a high- or low-risk signature. In conclusion, this study proposed a robust FRG-based prognostic model that may help stratify PAAD patients with poor prognoses and select potential therapeutic avenues.

摘要

铁死亡通过影响脂质过氧化和代谢途径在肿瘤发生中发挥作用;然而,其在胰腺腺癌(PAAD)中的预后或治疗相关性仍知之甚少。在本研究中,我们利用癌症基因组图谱(TCGA)和国际癌症基因组联盟(ICGC)的队列开发了一种基于铁死亡相关基因(FRG)的预后风险模型,并提出了合理的治疗方法。分析了TCGA-PAAD肿瘤与基因型-组织表达中的正常胰腺组织之间差异表达的FRG,使用单变量和多变量Cox回归以及LASSO分析构建预后风险模型。一个包含极光激酶A(AURKA)、小窝蛋白1(CAV1)和早幼粒细胞白血病蛋白(PML)基因表达的模型有效地区分了TCGA-PAAD患者中高风险组和低风险组之间的生存差异,并在两个ICGC队列中得到验证。高风险组在涉及雷帕霉素靶蛋白(mTOR)、丝裂原活化蛋白激酶(MAPK)和E2F信号通路的基因集中富集。两组之间的免疫和基质细胞浸润评分没有差异。使用我们的风险模型对胰腺细胞系进行分类的PRISM数据集分析表明达沙替尼在高风险组中有效,这在四个具有高风险或低风险特征的细胞系中得到了实验证实。总之,本研究提出了一种强大的基于FRG的预后模型,可能有助于对预后不良的PAAD患者进行分层,并选择潜在的治疗途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c077/11695983/44eb26811455/41598_2024_84607_Fig1_HTML.jpg

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