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. 2025 Jan 1;21(1):63-73.
doi: 10.4274/ejbh.galenos.2024.2024-11-2.

Bioinformatics Based Drug Repurposing Approach for Breast and Gynecological Cancers: RECQL4/FAM13C Genes Address Common Hub Genes and Drugs

Gizem Ayna Duran  1
Affiliations

Bioinformatics Based Drug Repurposing Approach for Breast and Gynecological Cancers: RECQL4/FAM13C Genes Address Common Hub Genes and Drugs

Gizem Ayna Duran. Eur J Breast Health. .

Abstract

Objective: The prevalence of breast cancer and gynaecological cancers is high, and these cancer types can occur consecutively as secondary cancers. The aim of our study is to determine the genes commonly expressed in these cancers and to identify the common hub genes and drug components.

Materials and methods: Gene intensity values of breast cancer, gynaecological cancers such as cervical, ovarian and endometrial cancers were used from the Gene Expression Omnibus database Affymetrix Human Genome U133 Plus 2.0 Array project. Using the linear modelling method included in the R LIMMA package, genes that differ between healthy individuals and cancer patients were identified. Hub genes were determined using cytoHubba in Cytoscape program. "ShinyGo 0.80" tool was used to determine the disease-specific biological KEGG pathways. Drug.MATADOR from the ShinyGo 0.80 tool was used to predict drug-target relationships.

Results: The RecQ Like Helicase 4 and Family with Sequence Similarity 13 Member C genes were found to be similarly expressed in breast cancer and gynaecological cancers. Upon KEGG pathway analyses with hub genes, Drug.MATADOR analysis with hub genes related to cancer related pathways was performed. We have determined these gene/drug interactions: NBN (targeted by Hydroxyurea), EP300 (targeted by Acetylcarnitine) and MAPK14 (targeted by Salicylate and Dibutyryl cyclic AMP).

Conclusion: The drugs associated with hub genes determined in our study are not routinely used in cancer treatment. Our study offers the opportunity to identify the target genes of drugs used in breast and gynaecological cancers with the drug repurposing approach.

Keywords: Breast cancer; DEGs; RECQL4/FAM13C; drug repurposing; gynaecological cancers; hub genes.

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Figures

Figure 1
Figure 1
Outline of the study has been shown to clarify the setup of the research
Figure 2
Figure 2
Volcano plot of breast and gynecological cancers. Blue dots indicate p-value 10e-6, green dots indicate Log2FC ≤ -1 and ≥1, and red dots show those that are below the p-value of 0.05 and Log2FC thresholds. Gray dots indicate insignificant genes. (a) breast cancer (GSE20685), (b) breast cancer (GSE42568), (c) breast cancer (GSE54002), (d) cervical cancer (GSE5787), (e) cervical cancer (GSE63514), (f) cervical cancer (GSE54388), (g) ovarian cancer (GSE27651), (H) ovarian cancer (GSE14407), (i) endometrial cancer (GSE17025)
Figure 3
Figure 3
Network of hub-genes identified by closeness (a) and degree (b) in Cytoscape according to PPI network analysis done with CytoHubba plugins of the Cytoscape program, hub genes were determined based on closeness (a) and degree (b). The top 20 nodes were used according to both closeness and degree PPI: Protein-protein interactions
Figure 4
Figure 4
The lollipop chart (a) and network (b) of KEGG pathways in ShinyGO 0.80 According to KEGG pathway analysis from ShinyGO 0.80 online tool, biological pathways related commonly with breast and gynecological cancers are shown with lollipop chart (a) and network (b)
Figure 5
Figure 5
Predicted drug components commonly related to both breast and gynecological cancers. Using Drug.MATADOR analysis from ShinyGO 0.80 online tool, drug-gene target prediction has been made by using common hub genes determined for both breast cancer and gynecological cancers
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