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胰腺癌中自噬预后特征的全基因组鉴定

Genome-Wide Identification of Autophagy Prognostic Signature in Pancreatic Cancer.

作者信息

Yu Jianfa, Lang Qi, Zhong Chongli, Wang Shuang, Tian Yu

机构信息

Department of General Surgery, Shengjing Hospital Affiliated to China Medical University, Shenyang, Liaoning, China.

Key Laboratory of Higher Education of Liaoning Province, Shenyang, Liaoning, China.

出版信息

Dose Response. 2021 Jun 30;19(2):15593258211023260. doi: 10.1177/15593258211023260. eCollection 2021 Apr-Jun.

Abstract

BACKGROUND

Autophagy plays a vital role in cancer development. However, there is currently no comprehensive study regarding the effects of autophagy-related genes (ARGs) on pancreatic cancer prognosis. Thus, this study aimed to establish an autophagy-related signature for predicting the prognosis of patients with pancreatic cancer.

METHODS

We identified and validated differentially-expressed ARGs using data from The Cancer Genome Atlas (TCGA) database, Genotype-Tissue Expression project (GTEx) and Expression Omnibus (GEO) database. We performed Cox proportional hazards regression analysis on the differentially-expressed ARGs to develop an autophagy-related signature. We tested the expression of these genes through western blotting and verified their prognostic values through gene expression profiling and interactive analyses (GEPIA).

RESULTS

We identified a total of 21 differentially-expressed ARGs and screened 4 OS-related ARGs (TP63, RAB24, APOL1, and PTK6). Both the training and validation sets showed that the autophagy-related signature was more accurate than the Tumor Node Metastasis (TNM) staging system. Moreover, the western blotting result showed that the expression of TP63, APOL1, and PTK6 was high, whereas that of RAB24 was low in cancer tissues.

CONCLUSION

This 4-ARG signature might potentially help in providing personalized therapy to patients with cancer.

摘要

背景

自噬在癌症发展中起着至关重要的作用。然而,目前尚无关于自噬相关基因(ARGs)对胰腺癌预后影响的全面研究。因此,本研究旨在建立一种自噬相关特征以预测胰腺癌患者的预后。

方法

我们使用来自癌症基因组图谱(TCGA)数据库、基因型-组织表达项目(GTEx)和基因表达综合数据库(GEO)的数据,鉴定并验证了差异表达的ARGs。我们对差异表达的ARGs进行Cox比例风险回归分析,以建立一种自噬相关特征。我们通过蛋白质免疫印迹法检测了这些基因的表达,并通过基因表达谱分析和交互式分析(GEPIA)验证了它们的预后价值。

结果

我们共鉴定出21个差异表达的ARGs,并筛选出4个与总生存期(OS)相关的ARGs(TP63、RAB24、APOL1和PTK6)。训练集和验证集均显示,自噬相关特征比肿瘤-淋巴结-转移(TNM)分期系统更准确。此外,蛋白质免疫印迹结果显示,在癌组织中TP63、APOL1和PTK6的表达较高,而RAB24的表达较低。

结论

这种4-ARG特征可能有助于为癌症患者提供个性化治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc1/8252352/98eaff8c8376/10.1177_15593258211023260-fig1.jpg

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