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. 2017 Winter;10(Suppl1):S85-S92.

Pancreatic adenocarcinoma protein-protein interaction network analysis

Mostafa Rezaei-Tavirani  1 , Sina Rezaei-Tavirani  1 , Nayebali Ahmadi  2 , Nosratollah Naderi  3 , Saeed Abdi  4
Affiliations

Pancreatic adenocarcinoma protein-protein interaction network analysis

Mostafa Rezaei-Tavirani et al. Gastroenterol Hepatol Bed Bench. 2017 Winter.

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.

Keywords: Protein-Protein Interaction; biomarker panel; cluster; gene ontology; pancreatic adenocarcinoma.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Figure 1.
Figure 1.
The three significant clusters related to the PPI network of pancreatic adenocarcinoma and their properties are presented
Figure 2
Figure 2
Degree distribution curve of PPI network of pancreatic adenocarcinoma is illustrated. The statistical parameters are determined as: fitted power law; y=74.353x-0.816, correlation; 0.910 and R-square on logarithmized value; 0.804
Figure 3
Figure 3
The sub network including 24 crucial nodes of pancreatic PPI network is represented. All of these genes are included in cluster-1.
Figure 4
Figure 4
The biological pathways related to the 24 crucial nodes of pancreatic adenocarcinoma PPI network are extracted from KEGG_01.03.2017:7194. The details and statistical parameters are presented as: final kappa score groups = 60, final group size after merging: 16, GO terms: 85, GO term connections: 471. The network was constructed by ClueGO v2.3.5. The main pathways are represented but the associated pathways are hidden. The colors are corresponded on the pathways or diseases, For example the “yellow color” refers to “pathways in cancer” and “purple color” to glioma
See this image and copyright information in PMC

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