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. 2022 Sep 14:2022:3348480.
doi: 10.1155/2022/3348480. eCollection 2022.

Bioinformatic Data Mining for Candidate Drugs Affecting Risk of Bisphosphonate-Related Osteonecrosis of the Jaw (BRONJ) in Cancer Patients

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Bioinformatic Data Mining for Candidate Drugs Affecting Risk of Bisphosphonate-Related Osteonecrosis of the Jaw (BRONJ) in Cancer Patients

Jinpeng Zhuang et al. Dis Markers. .

Abstract

Background: Bisphosphonate-related osteonecrosis of the jaw (BRONJ) leads to significant morbidity. Other coadministered drugs may modulate the risk for BRONJ. The present study aimed to leverage bioinformatic data mining to identify drugs that potentially modulate the risk of BRONJ in cancer.

Methods: A GEO gene expression dataset of peripheral blood mononuclear cells related to BRONJ in multiple myeloma patients was downloaded, and differentially expressed genes (DEGs) in patients with BRONJ versus those without BRONJ were identified. A protein-protein interaction network of the DEGs was constructed using experimentally validated interactions in the STRING database. Overrepresented Gene Ontology (GO) molecular function terms and KEGG pathways in the network were analysed. Network topology was determined, and 'hub genes' with degree ≥2 in the network were identified. Known drug targets of the hub genes were mined from the 'drug gene interaction database' (DGIdb) and labelled as candidate drugs affecting the risk of BRONJ.

Results: 751 annotated DEGs (log FC ≥ 1.5, p < 0.05) were obtained from the microarray gene expression dataset GSE7116. A PPI network with 633 nodes and 168 edges was constructed. Data mining for drugs interacting with 49 gene nodes was performed. 37 drug interactions were found for 9 of the hub genes including TBP, TAF1, PPP2CA, PRPF31, CASP8, UQCRB, ACTR2, CFLAR, and FAS. Interactions were found for several established and novel anticancer chemotherapeutic, kinase inhibitor, caspase inhibitor, antiangiogenic, and immunomodulatory agents. Aspirin, metformin, atrovastatin, thrombin, androgen and antiandrogen drugs, progesterone, Vitamin D, and Ginsengoside 20(S)-Protopanaxadiol were also documented.

Conclusions: A bioinformatic data mining strategy identified several anticancer, immunomodulator, and other candidate drugs that may affect the risk of BRONJ in cancer patients.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Volcano depicting differentially expressed genes (DEGs) in the dataset GSE7116, comparing multiple myeloma patients with BRONJ and those on bisphosphonate therapy without BRONJ. Red points indicate upregulated DEGs and blue points indicate downregulated DEGs (FDR adjusted p < 0.05, log FC ≥ 1.5).
Figure 2
Figure 2
Protein-protein interaction network of the DEGs consisting of 633 nodes and 168 edges clustered into 3 modules. Disconnected nodes are hidden.
Figure 3
Figure 3
Overrepresented GO molecular functions in the PPI network represented in a semantic space by multidimensional Scaling (MDS) using REVIGO. Semantically similar GO terms are projected together. The color scale represents log FDR values.

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