生物信息数据挖掘影响癌症患者双膦酸盐相关性颌骨骨坏死（BRONJ）风险的候选药物。

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

机构信息

Department of Orthopaedic Surgery, The 2nd Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Harbin 150081, China.

出版信息

Dis Markers. 2022 Sep 14;2022:3348480. doi: 10.1155/2022/3348480. eCollection 2022.

DOI:10.1155/2022/3348480

PMID:36157219

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9492334/

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, < 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.

摘要

背景

双膦酸盐相关性下颌骨坏死（BRONJ）会导致严重的发病率。其他同时使用的药物可能会调节 BRONJ 的风险。本研究旨在利用生物信息学数据挖掘来识别可能调节癌症患者 BRONJ 风险的药物。

方法

下载与多发性骨髓瘤患者 BRONJ 相关的外周血单个核细胞的 GEO 基因表达数据集，并鉴定 BRONJ 患者与无 BRONJ 患者之间的差异表达基因（DEGs）。使用 STRING 数据库中验证的实验相互作用构建 DEGs 的蛋白质-蛋白质相互作用网络。分析网络中过度表达的基因本体（GO）分子功能术语和 KEGG 途径。确定网络拓扑结构，并识别网络中度数≥2 的“枢纽基因”。从“药物基因相互作用数据库”（DGIdb）中挖掘枢纽基因的已知药物靶点，并标记为影响 BRONJ 风险的候选药物。

结果

从微阵列基因表达数据集 GSE7116 中获得 751 个注释的 DEGs（logFC≥1.5， <0.05）。构建了一个包含 633 个节点和 168 个边的 PPI 网络。对与 49 个基因节点相互作用的药物进行了数据挖掘。发现 9 个枢纽基因中有 37 个药物相互作用，包括 TBP、TAF1、PPP2CA、PRPF31、CASP8、UQCRB、ACTR2、CFLAR 和 FAS。发现了几种已建立和新型的抗癌化疗药物、激酶抑制剂、半胱氨酸蛋白酶抑制剂、抗血管生成药物、免疫调节剂以及阿司匹林、二甲双胍、阿托伐他汀、凝血酶、雄激素和抗雄激素药物、孕激素、维生素 D 和人参皂苷 20(S)-原人参二醇。