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构建并多组学验证基于五个铁死亡相关基因的模型,用于预测胰腺导管腺癌的预后和治疗反应,并进行免疫景观分析

英文原题:Construction and multi-omics validation of a five-gene ferroptosis-based model for predicting prognosis and therapy response in pancreatic ductal adenocarcinoma with immune landscape analysis.

查看英文原题

Construction and multi-omics validation of a five-gene ferroptosis-based model for predicting prognosis and therapy response in pancreatic ductal adenocarcinoma with immune landscape analysis.

PubMed 2026/07/13(内容时间) Discov Oncol Q3 · IF 2.8(JCR 2025)

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研究思路按摘要原文分段

铁死亡是一种铁依赖性程序性细胞死亡,在胰腺导管腺癌(PDAC)中发挥复杂作用,既调控肿瘤发展,也调控免疫相互作用。然而,铁死亡在PDAC中的临床意义和潜在分子机制尚未完全阐明,这限制了其在治疗中的应用。

为了识别铁死亡相关基因(FRGs),我们整合了来自 TCGA-PDAC 和 GTEx 数据库的转录组数据,以及来自三个 GEO 数据集(GSE62452、GSE78229 和 GSE183795)的补充数据。我们通过序贯分析构建了预后风险模型,其中包括单因素 Cox 回归、LASSO 回归和多因素 Cox 回归。通过 Kaplan-Meier 生存曲线、时间特异性 ROC 曲线分析以及与临床病理特征的相关性研究,我们严格评估了该模型的预测准确性和临床相关性。多组学分析包括 GO/KEGG/GSEA/GSVA 通路富集、CIBERSORT 免疫解卷积、ESTIMATE 评分、TIDE/ICB 反应预测、肿瘤突变负荷(TMB)分析、oncoPredict 药物敏感性估计、单细胞 RNA-seq(GSE212966)、空间转录组(GSM8452850)、拟时序轨迹以及 HPA 免疫组化验证。

建立了一个稳健的五基因铁死亡相关预后特征(BCAR3、GSK3B、STAT1、MAGED2、MYEOV)。在TCGA队列(5年AUC = 0.87)和三个外部验证队列(5年AUC 0.804-0.833)中,被归为高风险组的患者总生存期显著劣于低风险组。高风险肿瘤显示有丝分裂纺锤体、PI3K-AKT-mTOR、G2M检查点、糖酵解和p53通路富集,KRAS/TP53突变率显著升高,TMB更高,呈现“炎症但免疫抑制”的微环境(静息NK细胞/浆细胞增加,活化NK细胞减少,检查点CD44/HHLA2/LGALS9上调),以及化疗敏感性差异(高风险组对吉西他滨、厄洛替尼、吉非替尼、曲美替尼更敏感)。单细胞和空间分析证实其主要在恶性导管细胞中表达,具有动态的拟时序依赖模式(尤其是GSK3B在晚期细胞中上调),以及高评分亚群中MIF信号介导的串扰增强。蛋白质水平异质性经HPA-IHC验证。

本研究开发了一个简洁且经过外部验证的五基因铁死亡相关预后特征,该特征能有效对PDAC患者的生存结局进行分层,并反映肿瘤增殖、代谢重编程、免疫逃逸和药物反应中与铁死亡相关的改变。该模型为机制指导的精准治疗策略提供了框架,例如铁死亡诱导联合免疫治疗或风险适应性化疗,并可能为改善这种高度致死性恶性肿瘤的结局提供新见解。

展开英文摘要原文

Ferroptosis is an iron-dependent programmed cell death, which plays a complex role in pancreatic ductal adenocarcinoma (PDAC), regulating both tumor development and immune interaction. However, the clinical significance and potential molecular mechanism of ferroptosis in PDAC have not been fully clarified, which limits its application in treatment.

In order to identify ferroptosis-related genes (FRGs), we integrated transcriptome data from TCGA-PDAC and GTEx databases, as well as supplementary data from three GEO datasets (GSE62452, GSE78229 and GSE183795). We constructed a prognostic risk model by sequential analysis, which included univariate Cox regression, LASSO regression and multivariate Cox regression. Through Kaplan-Meier survival curve, time-specific ROC curve analysis and correlation study with clinicopathological features, we strictly evaluated the prediction accuracy and clinical relevance of this model. Multi-omics analyses included GO/KEGG/GSEA/GSVA pathway enrichment, CIBERSORT immune deconvolution, ESTIMATE scores, TIDE/ICB response prediction, tumor mutational burden (TMB) profiling, oncoPredict drug sensitivity estimation, single-cell RNA-seq (GSE212966), spatial transcriptome (GSM8452850), pseudotime trajectory, and HPA immunohistochemistry validation.

A robust five-gene ferroptosis-related prognostic signature (BCAR3, GSK3B, STAT1, MAGED2, MYEOV) was established. Patients categorized into the high-risk group demonstrated a markedly inferior overall survival compared to those in the low-risk group across both the TCGA cohort (5-year AUC = 0.87) and three external validation cohorts (5-year AUC 0.804-0.833). High-risk tumors showed enrichment in mitotic spindle, PI3K-AKT-mTOR, G2M checkpoint, glycolysis, and p53 pathways, markedly elevated KRAS/TP53 mutation rates, higher TMB, an "inflammatory yet immunosuppressive" microenvironment (increased resting NK cells/plasma cells, decreased activated NK cells, upregulated checkpoints including CD44/HHLA2/LGALS9), and differential chemotherapy sensitivity (greater sensitivity to gemcitabine, erlotinib, gefitinib, trametinib in high-risk group). Single-cell and spatial analyses confirmed predominant expression in malignant ductal cells, with dynamic pseudotime-dependent patterns (especially GSK3B upregulation in late-stage cells) and enhanced MIF signaling-mediated crosstalk in high-score subpopulations. Protein-level heterogeneity was verified by HPA-IHC.

In this study, a concise and externally validated five-gene ferroptosis-related prognostic signature was developed, which effectively stratifies survival outcomes in PDAC patients and reflects ferroptosis-associated alterations in tumor proliferation, metabolic reprogramming, immune evasion, and drug response. This model provides a framework for mechanism-informed precision treatment strategies, such as ferroptosis induction combined with immunotherapy or risk-adapted chemotherapy, and may offer new insights into improving outcomes in this highly lethal malignancy.

论文信息

作者
Liu W、Shen Y、Rao L、Qiao Z、Ling X、Cheng L、Shen G
第一作者单位
Department of Minimally Invasive Common Surgery, Suzhou Ninth People's Hospital, Xuzhou Medical University Suzhou Bay Clinical College, Suzhou, Jiangsu, China.China
通讯作者单位
Department of Minimally Invasive Common Surgery, Suzhou Ninth People's Hospital, Xuzhou Medical University Suzhou Bay Clinical College, Suzhou, Jiangsu, China. wjshengenhai@163.com.China
期刊
Discover oncology2026 Jul 13
原文标识
PubMed 42440056 · DOI 10.1007/s12672-026-05566-0