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基于整合生物信息学分析鉴定胰腺腺癌免疫微环境中的预后基因。

Identification of prognostic genes in the pancreatic adenocarcinoma immune microenvironment by integrated bioinformatics analysis.

机构信息

NHC Key Laboratory of Cancer Proteomics, Laboratory of Structural Biology, Department of Oncology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.

National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.

出版信息

Cancer Immunol Immunother. 2022 Jul;71(7):1757-1769. doi: 10.1007/s00262-021-03110-3. Epub 2021 Dec 2.


DOI:10.1007/s00262-021-03110-3
PMID:34854950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10992807/
Abstract

PURPOSE: Pancreatic adenocarcinoma (PAAD) is one of the most common causes of death among solid tumors, and its pathogenesis remains to be clarified. This study aims to elucidate the value of immune/stromal-related genes in the prognosis of PAAD through comprehensive bioinformatics analysis based on the immune microenvironment and validated in Chinese pancreatic cancer patients. METHODS: Gene expression profiles of pancreatic cancer patients were obtained from TCGA database. Differentially expressed genes (DEGs) were identified based on the ESTIMATE algorithm. Gene co-expression networks were constructed using WGCNA. In the key module, survival analysis was used to reveal the prognostic value. Subsequently, we performed functional enrichment analysis to construct a protein-protein interaction (PPI) network. The relationship between tumor immune infiltration and hub genes was analyzed by TIMER and CIBERSORT. Finally, it was validated in the GEO database and in tissues of Chinese pancreatic cancer patients. RESULTS: In the TCGA pancreatic cancer cohort, a low immune/stromal score was associated with a good prognosis. After bioinformatic analysis, 57 genes were identified to be significantly associated with pancreatic cancer prognosis. Among them, up-regulation of four genes (COL6A3, PLAU, MMP11 and MMP14) indicated poor prognosis and was associated with multiple immune cell infiltration. IHC results showed that PLAU protein levels from Chinese pancreatic cancer tissues were significantly higher than those from adjacent non-tumor tissues and were also associated with tumor TNM stage and lymph node metastasis. CONCLUSION: In conclusion, this study demonstrates that PLAU may serve as a new diagnostic and therapeutic target, which is highly expressed in Chinese pancreatic cancer tissues and associated with lymph node metastasis.

摘要

目的:胰腺导管腺癌(PAAD)是实体瘤死亡的最常见原因之一,其发病机制仍有待阐明。本研究旨在通过基于免疫微环境的综合生物信息学分析,阐明免疫/基质相关基因在 PAAD 预后中的价值,并在中国胰腺癌患者中进行验证。

方法:从 TCGA 数据库中获取胰腺癌患者的基因表达谱。基于 ESTIMATE 算法鉴定差异表达基因(DEGs)。使用 WGCNA 构建基因共表达网络。在关键模块中,进行生存分析以揭示预后价值。随后,进行功能富集分析以构建蛋白质-蛋白质相互作用(PPI)网络。通过 TIMER 和 CIBERSORT 分析肿瘤免疫浸润与枢纽基因的关系。最后,在 GEO 数据库和中国胰腺癌组织中进行验证。

结果:在 TCGA 胰腺癌队列中,低免疫/基质评分与预后良好相关。经过生物信息学分析,鉴定出 57 个与胰腺癌预后显著相关的基因。其中,四个基因(COL6A3、PLAU、MMP11 和 MMP14)的上调提示预后不良,并与多种免疫细胞浸润有关。免疫组化结果表明,来自中国胰腺癌组织的 PLAU 蛋白水平明显高于相邻非肿瘤组织,且与肿瘤 TNM 分期和淋巴结转移有关。

结论:总之,本研究表明 PLAU 可能作为一个新的诊断和治疗靶点,在中国胰腺癌组织中高表达,并与淋巴结转移有关。

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[5]
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[6]
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[8]
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[9]
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[10]
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本文引用的文献

[1]
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Nat Immunol. 2021-9

[2]
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Signal Transduct Target Ther. 2020-10-30

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