Protein-Protein Interaction Network Analysis of Salivary Proteomic Data in Oral Cancer Cases

Document Type: Research Articles

Authors

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

2 Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Abstract

Background: Oral cancer is a frequently encountered neoplasm of the head and neck region, being the eight most
common type of human malignancy worldwide. Despite improvement in its control, morbidity and mortality rates have
improved little in the past decades. Therefore, prevention and/or early detection are a high priority. Proteomics with
network analysis have emerged as a powerful tool to identify important proteins associated with cancer development
and progression that can be potential targets for early diagnosis. In the present study, network- based protein- protein
interactions (PPI) for oral cancer were identified and then analyzed for use as key proteins/potential biomarkers.
Material and Methods: Gene expression data in articles which focused on saliva proteomics of oral cancer were
collected and 74 candidate genes or proteins were extracted. Related protein networks of differentially expressed proteins
were explored and visualized using cytoscape software. Further PPI analysis was performed by Molecular Complex
Detection (MCODE) and BiNGO methods. Results: Network analysis of genes/proteins related to oral cancer identified
kininogen-1, angiotensinogen, annexin A1, IL-8, IgG heavy variable and constant chains, CRP, collagen alpha-1 and
fibronectin as 9 hub-bottleneck proteins. In addition, based on clustering with the MCODE tool, vitronectin, collagen
alpha-2, IL-8 and integrin alpha-v were established as 5 distinct seed proteins. Conclusion: A hub-bottleneck protein
panel may offer a potential /candidate biomarker pattern for diagnosis and treatment of oral cancer disease. Further
investigation and validation of these proteins are warranted.

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