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

Author:

Alam Md Shahin123ORCID,Sultana Adiba34,Kibria Md Kaderi3,Khanam Alima5,Wang Guanghui1,Mollah Md Nurul Haque3

Affiliation:

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

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

3. Bioinformatics Laboratory (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh

4. Medical Big Data Center, Guangdong Provincial People’s Hospital/Guangdong Academy of Medical Sciences, Guangzhou, China

5. Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, Bangladesh

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.

Funder

the Interdisciplinary Basic Frontier Innovation Program of Suzhou Medical College of Soochow University

the National Natural Science Foundation of China

the Talent Program of Taicang Health Commission

Publisher

SAGE Publications

Reference120 articles.

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