ArticleInternational journal of clinical and experimental pathology2018
Bioinformatic analysis of differential expression and core GENEs in breast cancer.
Article in International journal of clinical and experimental pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Bioinformatic Characterization of Genes That Are Correlated to the Progression of Breast Cancer to Breast Cancer Brain Metastasis.Cancer reports (Hoboken, N.J.) · 2025Article
- Identification and prognostic significance of Ki-67-related genes in triple negative breast cancer.Discover oncology · 2025Article
- Disrupted circadian control promotes oncogenesis in breast cancer.Bioinformation · 2025Article
- Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.Bioinformatics and biology insights · 2024Article
- Expression profiling of luminal B breast tumor in Indian women.Journal of cancer research and clinical oncology · 2023Article
- Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer.Medicina (Kaunas, Lithuania) · 2023Article
- Article
- An in-silico method leads to recognition of hub genes and crucial pathways in survival of patients with breast cancer.Scientific reports · 2020Article
- Leveraging User-Friendly Network Approaches to Extract Knowledge From High-ThroughputFrontiers in genetics · 2019Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer (BRCA) is one of the most common malignancies in women. The gene expression profile of GSE103512 from the GEO database was downloaded in order to find key genes involved in the occurrence and development of BRCA. 75 samples, including 65 cancer and 10 normal samples, were included in this analysis. Differentially expressed genes (DEGs) between BRCA patients and health people were chosen using R tool. We next performed gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) was utilized to visualize protein-protein interaction (PPI) of these DEGs. The related genes and medicines specific to hub genes were predicted by CBioportal. We screened a total of 357 DEGs including 77 up-regulated and 280 down-regulated. A series of BRCA related GO terms and pathways were identified by analysis of these DEGs. Insulin-like growth factor 1 (IGF1); epidermal growth factor receptor (EGFR); v-jun avian sarcoma virus 17 oncogene homolog (JUN) and Estrogen Receptor 1 (ESR1) of the DEGs were screened by construction of the PPI network and the degree of connectivity. IGF1 and ESR1 were finally selected as potential hub genes and treatment targets of BRCA. In conclusion, this bioinformatics analysis demonstrated that DEGs and hub genes, such as IGF1, might regulate the development of gastric cancer. These DEGs could be used as new biomarkers for diagnosis and to guide the combination medicine of BRCA.
Indexed as
Identifiers
31938209PMC6958129W3026685967What OpenQuestion holds
Registered trials
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