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

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.

Keywords: Breast cancer; drug repurposing; early diagnosis and prognosis; hub of the hub-genes (hHubGs); molecular docking; regulatory factors.

Figure 1.

The workflow of this study.

Figure 2.

The PPI network based on 259 unique HubGs, where large size indicates hHubGs with the highest degree of connectivity (degree >90).

Figure 3.

(A) Analysis of expression levels of hHubGs between the normal group and 4-stage group (stage 1, stage 2, stage 3, and stage 4) of BC, and (B) ROC curves to investigate the prognostic power of hHubGs by the RF and SVN-based BC prediction models with 3 gene-expression profile data sets in NCBI-GEO database.

Figure 4.

hHubGs-regulatory networks, where pink indicates hHubGs (diamond shape hHubGs indicate TFs themselves): (A) hHubGs-TFs interaction network, where large green indicates key transcription factors; (B) hHubG-miRNA interaction network, where large green indicates key posttranscriptional factors; and (C) upstream and downstream analysis of TFs (I) differential expressions for TFs of hHubGs (II) upstream and downstream regulation by hHubGs that are also TFs (JUN, TP53, and ESR1), where pink diamond indicates core TFs, red rectangle indicates upstream TFs, and blue rectangle indicates downstream TFs.

Figure 5.

Molecular docking analysis results for screening candidate drugs against BC: (A) presented interaction binding affinity scores between hHubGs and drug agents; (B) visualization of interaction between 10 candidate drugs and hHubGs by zooming; (C) overlap between the top-ranked HubGs and hHubGs; and (D) cross-validation of the candidate drugs by top-ranked HubGs.

Figure 6.

MD simulation analysis of the top 3 interactions, where blue, red, and green indicate SORAFENIB-ESR1, CHEMBL1765740-EGFR, and AMG900-TOP2A interactions, respectively: (A) time evolution of RMSDs of backbone atoms (C, Cα, and N) for protein for each docked complex, and (B) represented binding free energy of each snapshot for the top 3 interactions.

Figure 7.

Agreement of the proposed BC-related hHubGs with other independent studies.