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Topology-based protein–protein interaction analysis of oral cancer proteins


Affiliations
1 Department of Bioinformatics, Center for Biological Sciences (Bioinformatics), Central University of South Bihar, Panchanpur Road, Fathehpur, Tekari-Gaya 824 236, India, India
 

Oral cancer is a common type of head and neck cancer that affects majority of the population worldwide. The present study focuses on the network-based protein–protein interaction (PPI) approach for the identification of oral cancer targets and systems biology approach-based analysis. Totally 47 oral cancer gene targets were extracted from the BioXpress database, Oral Cancer Gene Database and HNC database. The related protein networks were explored and visualized using Cytoscape v3.7.2. Topology predictions were performed by Mole­cular Complex Detection tool and Biological Networks Gene Ontology tool (BiNGO) plug-in from Cytoscape v3.7.2. The comprehensive study using MCODE are three clusters of 15 common oral cancer genes. The pre­dicted proteins were GSK-3b, PKM, Catenin-b1, Tp53, SMAD-3, MYC, LDHA, HIF1-a, PDPK-1, AKT3, PIK3CA, ILK, UBC, E2F1 and SKP. The 15 oral cancer genes with their significant P-value < 0.05 are responsible for the development of oral cancer. These 15 proteins obtained from network-based interaction analysis can be a potential solution of anti-cancer drug molecules against multiple targets of oral cancer

Keywords

Cluster analysis, gene ontology, oral cancer, protein–protein networks, topology analysis.
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  • Topology-based protein–protein interaction analysis of oral cancer proteins

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Authors

Keerti Kumar Yadav
Department of Bioinformatics, Center for Biological Sciences (Bioinformatics), Central University of South Bihar, Panchanpur Road, Fathehpur, Tekari-Gaya 824 236, India, India
Ajay Kumar Singh
Department of Bioinformatics, Center for Biological Sciences (Bioinformatics), Central University of South Bihar, Panchanpur Road, Fathehpur, Tekari-Gaya 824 236, India, India

Abstract


Oral cancer is a common type of head and neck cancer that affects majority of the population worldwide. The present study focuses on the network-based protein–protein interaction (PPI) approach for the identification of oral cancer targets and systems biology approach-based analysis. Totally 47 oral cancer gene targets were extracted from the BioXpress database, Oral Cancer Gene Database and HNC database. The related protein networks were explored and visualized using Cytoscape v3.7.2. Topology predictions were performed by Mole­cular Complex Detection tool and Biological Networks Gene Ontology tool (BiNGO) plug-in from Cytoscape v3.7.2. The comprehensive study using MCODE are three clusters of 15 common oral cancer genes. The pre­dicted proteins were GSK-3b, PKM, Catenin-b1, Tp53, SMAD-3, MYC, LDHA, HIF1-a, PDPK-1, AKT3, PIK3CA, ILK, UBC, E2F1 and SKP. The 15 oral cancer genes with their significant P-value < 0.05 are responsible for the development of oral cancer. These 15 proteins obtained from network-based interaction analysis can be a potential solution of anti-cancer drug molecules against multiple targets of oral cancer

Keywords


Cluster analysis, gene ontology, oral cancer, protein–protein networks, topology analysis.

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DOI: https://doi.org/10.18520/cs%2Fv123%2Fi10%2F1216-1224