Gene expression analysis and identification of key pathways in cervical cancer using RNA-Seq data
Keywords:
Cervical cancer, Gene expression analysis, Biological pathways, Enrichment analysisAbstract
Cervical cancer is one of the most prevalent cancers in women globally and typically predominates in countries that lack sufficient resources. Identifying distinct molecular pathways of the cancer will enable researchers to better understand the pathophysiology of cervical cancer as well as develop targeted therapies. The main goal of the project was to identify differentially expressed genes and any underlying pathways associated with cervical cancer via gene expression analysis.
The genomic expression of cervical cancer RNA-Seq data was acquired from the GEO data and then analyzed. After performing normalization and filtering (logFC>2, p<.05), differentially expressed genes (DEGs) were found. Pathway enrichment analysis was then performed using the KEGG and Gene Ontology databases.
A total of 4667 DEGs were identified. KEGG analysis identified significantly enriched pathways, including ECM-receptor interaction, PI3K-Akt signaling pathway, focal adhesion, cell cycle, and calcium signaling pathway (p.adjust < 0.05). GO analysis found enriched processes such as extracellular matrix organization, muscle processes, and cell adhesion.
Based on the results of this study, changes in ECM, PI3K-Akt signaling, and malignant cell adhesion pathways are significant in the pathology of cervical cancer and may be potential targets for future targeted therapy.
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