Identification of hub genes and small molecule therapeutic drugs related to breast cancer with comprehensive bioinformatics analysis.

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This research aimed to identify hub genes and small molecule drugs for breast cancer by integrated bioinformatics analysis. After downloading multiple gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, 283 overlapping differentially expressed genes (DEGs) significantly enriched in different cancer-related functions and pathways were obtained using LIMMA, VennDiagram and ClusterProfiler packages of R. We then analyzed the topology of protein-protein interaction (PPI) network with overlapping DEGs and further obtained six hub genes (RRM2, CDC20, CCNB2, BUB1B, CDK1, and CCNA2) from the network via STRING and Cytoscape. Subsequently, we conducted genes expression verification, genetic alterations evaluation, immune infiltration prediction, clinicopathological parameters analysis, identification of transcriptional and post-transcriptional regulatory molecules, and survival analysis for these hub genes. Meanwhile, 29 possible drug candidates (e.g., Cladribine, Gallium nitrate, Alvocidib, 1β-hydroxyalantolactone, Berberine hydrochloride, Nitidine chloride) were identified from the DGIdb database and the GSE85871 dataset. In addition, some transcription factors and miRNAs (e.g., E2F1, PTTG1, TP53, ZBTB16, hsa-miR-130a-3p, hsa-miR-204-5p) targeting hub genes were identified as key regulators in the progression of breast cancer. In conclusion, our study identified six hub genes and 29 potential drug candidates for breast cancer. These findings may advance understanding regarding the diagnosis, prognosis and treatment of breast cancer.", "claims": [{"id": "claim-method", "statement": "In this section, we applied the Kaplan–Meier Plotter (http://kmplot.com/analysis/) to evaluate prognostic information of previously identified hub genes and important reporter regulatory molecules (Nagy et al., 2018).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33083112", "locator": "sections[10] \"Survival analysis\" paragraph 2", "quote": "In this section, we applied the Kaplan–Meier Plotter (http://kmplot.com/analysis/) to evaluate prognostic information of previously identified hub genes and important reporter regulatory molecules (Nagy et al., 2018)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:The differentially expressed genes data of datasets GSE3744, GSE21422, GSE42568, GSE61304, GSE65194, TCGA BRCA and GSE97811 are available in Tables S1–S6 and Tables S11, respectively. The PPI network data in this article is available in Tables S7. The GO functional enrichment and KEGG pathway analysis data are available in Tables S8–S10. The results of the reversal effects of 8 traditional Chinese medicine ingredients on breast cancer from the GSE85871 dataset are available in Tables S12.The raw data of gene and miRNA expression are available at NCBI GEO (GSE42568, GSE3744, GSE21422, GSE61304, GSE65194, GSE97811 and GSE85871) and GEPIA 2 (http://gepia2.cancer-pku.cn/#degenes).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33083112", "locator": "sections[26] \"Additional Information and Declarations\" paragraph 4", "quote": "The following information was supplied regarding data availability:The differentially expressed genes data of datasets GSE3744, GSE21422, GSE42568, GSE61304, GSE65194, TCGA BRCA and GSE97811 are available in Tables S1–S6 and Tables S11, respectively. The PPI network data in this article is available in Tables S7. The GO functional enrichment and KEGG pathway analysis data are available in Tables S8–S10. The results of the reversal effects of 8 traditional Chinese medicine ingredients on breast cancer from the GSE85871 dataset are available in Tables S12.The raw data of gene and miRNA expression are available at NCBI GEO (GSE42568, GSE3744, GSE21422, GSE61304, GSE65194, GSE97811 and GSE85871) and GEPIA 2 (http://gepia2.cancer-pku.cn/#degenes)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33083112"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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