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从不同个体研究中鉴定乳腺癌早期诊断、预后和治疗的核心基因枢纽

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.

作者信息

Alam Md Shahin, Sultana Adiba, Kibria Md Kaderi, Khanam Alima, Wang Guanghui, Mollah Md Nurul Haque

机构信息

Center of Translational Medicine, The First People's Hospital of Taicang, Taicang Affiliated Hospital of Soochow University, Suzhou, China.

Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, China.

出版信息

Bioinform Biol Insights. 2024 Sep 4;18:11779322241272386. doi: 10.1177/11779322241272386. eCollection 2024.

Abstract

Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (, , , , , , , , , and ) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs , AMG-900 vs , and CHEMBL1765740 vs ) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.

摘要

乳腺癌(BC)是一种复杂的疾病,是导致女性高死亡率的原因。早期诊断和治疗的改善可能会降低死亡率。文献中有超过74项独立研究提出了导致BC的枢纽基因(HubGs)。然而,我们观察到它们的HubG集彼此并不那么一致。这可能是由于样本单位的区域和环境差异所致。因此,需要探索HubG(hHubG)集的枢纽,其可能在不同国家地区及其环境中对BC的早期诊断和治疗更具代表性。在本研究中,我们基于所有74个独立的HubG集,通过蛋白质-蛋白质相互作用网络分析,选择排名前10的HubGs(、、、、、、、、和)作为hHubG集。hHubG集富集分析检测到一些与BC进展显著相关的关键生物学过程、分子功能和途径。通过BC进展不同阶段的箱线图和BC预测模型对hHubGs进行表达分析,表明所提出的hHubGs可被视为早期诊断和预后生物标志物。最后,我们通过分子对接分析,提出了hHubGs指导的排名前10的候选药物分子(索拉非尼、AMG-900、CHEMBL1765740、恩曲替尼、MK-6592、YM201636、马西替尼、GSK2126458、TG-02和帕唑帕尼)用于治疗BC。我们基于100纳秒分子动力学(MD)模拟的分子力学泊松-玻尔兹曼表面积(MM-PBSA)方法计算前3种药物-靶点复合物(索拉非尼与、AMG-900与、CHEMBL1765740与)的结合自由能,研究了它们的稳定性,发现它们具有稳定的性能。与个体研究结果相比,文献综述也更支持我们关于BC的发现。因此,本研究的结果可能是BC早期诊断、预后和治疗的有用资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60ec/11375675/3f747cbd0cf9/10.1177_11779322241272386-fig1.jpg

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