Exploring bacterial key genes and therapeutic agents for breast cancer among the Ghanaian female population: Insights from In Silico analyses
Breast cancer (BC) is yet a significant global health challenge across various populations including Ghana, though several studies on host-genome associated with BC have been investigated molecular mechanisms of BC development and progression, and candidate therapeutic agents. However, a little atte...
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Veröffentlicht in: | PloS one 2024-11, Vol.19 (11), p.e0312493 |
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Zusammenfassung: | Breast cancer (BC) is yet a significant global health challenge across various populations including Ghana, though several studies on host-genome associated with BC have been investigated molecular mechanisms of BC development and progression, and candidate therapeutic agents. However, a little attention has been given on microbial genome in this regard, although alterations in microbiota and epigenetic modifications are recognized as substantial risk factors for BC. This study focused on identifying bacterial key genes (bKGs) associated with BC infections in the Ghanaian population and exploring potential drug molecules by targeting these bKGs through in silico analyses. At first, 16S rRNA bacterial sequence data were downloaded from NCBI database comprising 520 samples from BC patients and 442 from healthy controls. Analysis of 16S rRNA-Seq data showed significant differences in bacterial abundance between BC and healthy groups and identified 26 differential genera with the threshold values at |log2FC|>2.0 and p-value≤0.05. It was observed that two genera Prevotella and Anaerovibria are significantly upregulated in BC patients and others are downregulated. Functional analysis based on all differential genera identified 19 MetaCyc signaling pathways, twelve of which were significantly enriched in BC patients by containing 165 genes Top-ranked 10 genes mdh, pykF, gapA, zwf, pgi, tpiA, pgk, pfkA, ppsA, and pykA were identified as BC-causing bacterial key genes (bKGs) through protein-protein interaction network analysis. Subsequently, the bKG-guided top ranked 10 drug molecules Digitoxin, Digoxin, Ledipasvir, Suramin, Ergotamine, Venetoclax, Nilotinib, Conivaptan, Dihydroergotamine, and Elbasvir were identified using molecular docking analysis. The stability of top-ranked three drug-target complexes (Digitoxin-pykA, Digoxin-mdh, and Ledipasvir-pgi) were confirmed through the molecular dynamics simulation studies. Therefore, these findings might be useful resources to the wet-lab researchers for further experimental validation on bacterial therapies against BC. |
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ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0312493 |