Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer

Md Tanvir Hasan; Md Rakibul Islam; Md Rezwan Islam; Baraa Riyadh Altahan; Kawsar Ahmed; Francis M Bui; Sami Azam; Mohammad Ali Moni

doi:10.1186/s43141-023-00469-x

Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer

J Genet Eng Biotechnol. 2023 Feb 1;21(1):10. doi: 10.1186/s43141-023-00469-x.

Authors

Md Tanvir Hasan¹, Md Rakibul Islam², Md Rezwan Islam², Baraa Riyadh Altahan³, Kawsar Ahmed^{4

5}, Francis M Bui⁶, Sami Azam⁷, Mohammad Ali Moni⁸

Affiliations

¹ Department of Business Engineering, Ghent University, 9000 Gent, Belgium.
² Department of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka, 1342, Bangladesh.
³ Department of Medical Instrumentation Engineering Techniques, Al-Mustaqbal University College, Hilla, Babil, 51001, Iraq.
⁴ Department of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada. kawsar.ict@mbstu.ac.bd.
⁵ Group of Bio-photomatiχ, Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh. kawsar.ict@mbstu.ac.bd.
⁶ Department of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada.
⁷ College of Engineering, IT and Environment, Charles Darwin University, Casuarina, NT, 0909, Australia.
⁸ Faculty of Health and Behavioural Sciences, School of Health and Rehabilitation Sciences, The University of Queensland, St. Lucia, QLD, 4072, Australia. m.moni@uq.edu.au.

Abstract

Background: In today's society, cancer has become a big concern. The most common cancers in women are breast cancer (BC), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). CC is a type of cervix cancer that is the fourth most common cancer in women and the fourth major cause of death.

Results: This research uses a network approach to discover genetic connections, functional enrichment, pathways analysis, microRNAs transcription factors (miRNA-TF) co-regulatory network, gene-disease associations, and therapeutic targets for CC. Three datasets from the NCBI's GEO collection were considered for this investigation. Then, using a comparison approach between the datasets, 315 common DEGs were discovered. The PPI network was built using a variety of combinatorial statistical approaches and bioinformatics tools, and the PPI network was then utilized to identify hub genes and critical modules.

Conclusion: Furthermore, we discovered that CC has specific similar links with the progression of different tumors using Gene Ontology terminology and pathway analysis. Transcription factors-gene linkages, gene-disease correlations, and the miRNA-TF co-regulatory network were revealed to have functional enrichments. We believe the candidate drugs identified in this study could be effective for advanced CC treatment.