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.
| Original language | English |
|---|---|
| Article number | 10 |
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Journal of Genetic Engineering and Biotechnology |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Dec 2023 |
Bibliographical note
Funding Information:This work was supported by Al-Mustaqbal University College and in part by funding from the Natural Sciences and Engineering Research Council of Canada (NSERC).
Funding Information:
The authors would like to thank and extend their appreciation and gratitude to Al-Mustaqbal University College in Iraq for funding this project.
Publisher Copyright:
© 2023, The Author(s).
