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胰腺腺癌蛋白质-蛋白质相互作用网络分析

Pancreatic adenocarcinoma protein-protein interaction network analysis.

作者信息

Rezaei-Tavirani Mostafa, Rezaei-Tavirani Sina, Ahmadi Nayebali, Naderi Nosratollah, Abdi Saeed

机构信息

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

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

出版信息

Gastroenterol Hepatol Bed Bench. 2017 Winter;10(Suppl1):S85-S92.

PMID:29511477
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5838186/
Abstract

AIM

Gene assessment of pancreatic adenocarcinoma disease via protein-protein interaction (PPI) Network Analysis.

BACKGROUND

Diagnosis, especially early detection of pancreatic adenocarcinoma as a lethal disease implies more investigation. PPI Network Analysis is a suitable tool to discover new aspects of molecular mechanism of diseases.

METHODS

In the present study the related genes to pancreatic adenocarcinoma are studied in the interactome unit and the key genes are highlighted. The significant clusters were introduced by Cluster-ONE application of Cytoscape software 3.4.0. The genes are retrieved from STRING date base and analyzed by Cytoscape software. The crucial genes based on analysis of central parameters were determined and enriched by ClueGO v2.3.5 via gene ontology.

RESULTS

The number of 24 key genes among 794 initial genes were highlighted as crucial nodes in relationship with pancreatic adenocarcinoma. All of the key genes were organized in a cluster including 216 nodes. The main related pathways and cancer diseases were determined.

CONCLUSION

It was concluded that the introduced 24 genes are possible biomarker panel of pancreatic adenocarcinoma.

摘要

目的

通过蛋白质-蛋白质相互作用（PPI）网络分析对胰腺腺癌疾病进行基因评估。

背景

作为一种致命疾病，胰腺癌的诊断，尤其是早期检测需要更多的研究。PPI网络分析是发现疾病分子机制新方面的合适工具。

方法

在本研究中，在相互作用组单元中研究与胰腺腺癌相关的基因，并突出关键基因。通过Cytoscape软件3.4.0的Cluster-ONE应用程序引入显著簇。从STRING数据库中检索基因，并通过Cytoscape软件进行分析。基于中心参数分析确定关键基因，并通过ClueGO v2.3.5通过基因本体进行富集。

结果

794个初始基因中的24个关键基因被突出显示为与胰腺腺癌相关的关键节点。所有关键基因都组织在一个包含216个节点的簇中。确定了主要相关途径和癌症疾病。

结论

得出结论，所引入的24个基因可能是胰腺腺癌的生物标志物组。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/57a2a227b619/GHFBB-10-S085-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/5f20add9f5ea/GHFBB-10-S085-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/78cffc71f200/GHFBB-10-S085-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/b78d35c4b4aa/GHFBB-10-S085-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/57a2a227b619/GHFBB-10-S085-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/5f20add9f5ea/GHFBB-10-S085-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/78cffc71f200/GHFBB-10-S085-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/b78d35c4b4aa/GHFBB-10-S085-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/5838186/57a2a227b619/GHFBB-10-S085-g004.jpg

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