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构建并验证一个与细胞坏死性凋亡相关的基因签名,用于预测胰腺癌的预后和肿瘤微环境。

Construction and Validation of a Necroptosis-Related Gene Signature for Predicting Prognosis and Tumor Microenvironment of Pancreatic Cancer.

机构信息

Department of Hepatobiliary Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Dis Markers. 2022 Jun 14;2022:9737587. doi: 10.1155/2022/9737587. eCollection 2022.

Abstract

Pancreatic cancer (PC) is notorious for its parallel morbidity and mortality rates. Recently, necroptosis, a form of programmed cell necrosis, has gained popularity for its role in tumorigenesis and metastasis. In this study, we explored the expression of necroptosis-related genes in PC and normal pancreatic tissues and identified 52 differentially expressed genes (DEGs). The Cox regression analysis was applied to construct the prognostic risk model, which divided patients into high- and low-risk groups. PC patients in the low-risk group showed a significantly better overall survival (OS) than those in the high-risk group. We further validated the prognostic role in ICGC cohort. Further, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and tumor microenvironment (TME) analysis were used to explore the underlying mechanisms. Notably, based on the gene signature, we revealed that the risk score was strongly related to the sensitivity of chemotherapy. In conclusion, necroptosis-related genes serve as an important immune mediator, and the risk model could be used to predict the survival and to guide the development of precision drugs for patients with PC.

摘要

胰腺癌(PC)以其平行的发病率和死亡率而臭名昭著。最近,程序性细胞坏死的一种形式——坏死性凋亡,因其在肿瘤发生和转移中的作用而受到关注。在这项研究中,我们探讨了 PC 和正常胰腺组织中坏死性凋亡相关基因的表达,并鉴定了 52 个差异表达基因(DEGs)。Cox 回归分析用于构建预后风险模型,将患者分为高风险组和低风险组。低风险组的 PC 患者的总生存期(OS)明显优于高风险组。我们在 ICGC 队列中进一步验证了其预后作用。此外,还进行了基因本体(GO)、京都基因与基因组百科全书(KEGG)、基因集富集分析(GSEA)和肿瘤微环境(TME)分析,以探讨潜在的机制。值得注意的是,基于基因特征,我们揭示了风险评分与化疗敏感性密切相关。总之,坏死性凋亡相关基因是一种重要的免疫调节剂,风险模型可用于预测 PC 患者的生存情况,并指导精准药物的开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d345/9214653/b6120c380f70/DM2022-9737587.001.jpg

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