{"title":"Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.","authors":"Md Shahin Alam, Adiba Sultana, Md Kaderi Kibria, Alima Khanam, Guanghui Wang, Md Nurul Haque Mollah","doi":"10.1177/11779322241272386","DOIUrl":null,"url":null,"abstract":"<p><p>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 (<i>CCNB1</i>, <i>CDK1</i>, <i>TOP2A</i>, <i>CCNA2</i>, <i>ESR1</i>, <i>EGFR</i>, <i>JUN</i>, <i>ACTB</i>, <i>TP53</i>, and <i>CCND1</i>) 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 <i>ESR1</i>, AMG-900 vs <i>TOP2A</i>, and CHEMBL1765740 vs <i>EGFR</i>) 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.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11375675/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics and Biology Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11779322241272386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
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 (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) 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 ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) 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.
乳腺癌（BC）是一种复杂的疾病，导致妇女的高死亡率。早期诊断和改善治疗可降低死亡率。文献中有超过 74 项研究提出了导致乳腺癌的枢纽基因（HubGs）。然而，我们观察到，它们的 HubG 组合并不完全一致。这可能是由于样本单位的地区和环境差异造成的。因此，我们需要探索更能代表不同国家地区及其环境的 BC 早期诊断和治疗的 HubG（hHubG）集。在本研究中，我们基于所有74个HubG集，通过蛋白-蛋白相互作用网络分析，选择了排名前10位的HubG集（CCNB1、CDK1、TOP2A、CCNA2、ESR1、EGFR、JUN、ACTB、TP53和CCND1）作为hHubG集。hHubG集富集分析发现了一些与BC进展显著相关的关键生物学过程、分子功能和通路。通过盒图分析hHubGs在BC不同进展阶段的表达情况以及BC预测模型表明，所提出的hHubGs可被视为早期诊断和预后的生物标志物。最后，我们通过分子对接分析提出了以hHubGs为指导的排名前10位的候选药物分子（SORAFENIB、AMG-900、CHEMBL1765740、ENTRECTINIB、MK-6592、YM201636、masitinib、GSK2126458、TG-02和PAZOPANIB），用于治疗BC。我们根据基于分子力学泊松-波尔兹曼表面积（MM-PBSA）方法的 100-ns 分子动力学（MD）模拟，计算了药物与靶点复合物（SORAFENIB vs ESR1、AMG-900 vs TOP2A 和 CHEMBL1765740 vs EGFR）的结合自由能，研究了排名靠前的 3 个药物与靶点复合物（SORAFENIB vs ESR1、AMG-900 vs TOP2A 和 CHEMBL1765740 vs EGFR）的稳定性，发现它们的性能稳定。与个别研究结果相比，文献综述也更支持我们对 BC 的研究结果。因此，本研究的结果可能会成为 BC 早期诊断、预后和治疗的有用资源。
期刊介绍：
Bioinformatics and Biology Insights is an open access, peer-reviewed journal that considers articles on bioinformatics methods and their applications which must pertain to biological insights. All papers should be easily amenable to biologists and as such help bridge the gap between theories and applications.
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