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胆囊癌蛋白质谱数据的综合生物信息学分析

Gallbladder cancer integrated bioinformatics analysis of protein profile data.

作者信息

Zali Mohammad Reza, Zamanian Azodi Mona, Razzaghi Zahra, Heydari Mohammad Hossain

机构信息

Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

Gastroenterol Hepatol Bed Bench. 2019;12(Suppl1):S66-S73.

Abstract

AIM

Identifying the critical genes that differentiate gall bladder cancer from a normal gall bladder and the related biological terms was the aim of this study.

BACKGROUND

The molecular mechanism underlying gall bladder cancer (GBC) trigger and development still requires investigations. Potential therapeutic biomarkers can be identified through protein-protein interaction network prediction of proteome as a complementary study.

METHODS

Here, a literature review of proteomics studies of gall bladder cancer from 2010 to 2019 was undertaken to screen differentially expressed proteins in this cancer. A network of 27 differentially expressed proteins (DEPs) via Cytoscape 3.7.1 and its plug-ins was constructed and analyzed.

RESULTS

Ten proteins were introduced as hub-bottlenecks among which four were from DEPs. The gene ontology analysis also indicated that positive regulation of multi-organism process and regulation of response to biotic stimulus are the most disrupted biological processes of GBC considering their relationships with the DEPs.

CONCLUSION

ACTG, ALB, GGH, and DYNC1H1, and relative biological terms were introduced as drug targets and possible diagnostic biomarkers.

摘要

目的

本研究旨在鉴定区分胆囊癌与正常胆囊的关键基因以及相关生物学术语。

背景

胆囊癌(GBC)触发和发展的分子机制仍需研究。蛋白质组的蛋白质-蛋白质相互作用网络预测可作为补充研究,用于识别潜在的治疗生物标志物。

方法

对2010年至2019年胆囊癌蛋白质组学研究进行文献综述,以筛选该癌症中差异表达的蛋白质。通过Cytoscape 3.7.1及其插件构建并分析了一个由27种差异表达蛋白(DEP)组成的网络。

结果

引入了10种蛋白质作为枢纽瓶颈,其中4种来自DEP。基因本体分析还表明,考虑到它们与DEP的关系,多生物体过程的正调控和对生物刺激的反应调控是GBC最受干扰的生物学过程。

结论

ACTG、ALB、GGH和DYNC1H1以及相关生物学术语被作为药物靶点和可能的诊断生物标志物引入。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e8a/7011054/10d517707d6b/GHFBB-12-S66-g001.jpg

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