ArticleOncology letters2017
Bioinformatics analysis of gene expression profiles to identify causal genes in luminal B2 breast cancer.
Article in Oncology letters, 2017. 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, 13 citations in OpenAlex.
- High NTRK2 protein expression levels may be associated with poorer prognosis of breast cancer patients.The Journal of international medical research · 2024Article
- Article
- A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer.Frontiers in oncology · 2021Article
- CBNA: A control theory based method for identifying coding and non-coding cancer drivers.PLoS computational biology · 2019Article
- Tumor suppressor MCPH1 regulates gene expression profiles related to malignant conversion and chromosomal assembly.International journal of cancer · 2019Article
- Analysis of the autophagy gene expression profile of pancreatic cancer based on autophagy-related protein microtubule-associated protein 1A/1B-light chain 3.World journal of gastroenterology · 2019Article
- Seeking for Correlative Genes and Signaling Pathways With Bone Metastasis From Breast Cancer by Integrated Analysis.Frontiers in oncology · 2019Article
- Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes.NPJ systems biology and applications · 2019Article
- Systematic identification of the key candidate genes in breast cancer stroma.Cellular & molecular biology letters · 2018Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients with the luminal B subtype of breast cancer exhibit a poor prognosis, high metastatic risk and high incidence of chemotherapy resistance. Luminal B breast cancer is sub-classified into B1 and B2. The pathophysiological mechanism of luminal B2 breast cancer (LB2BC) progression has yet to be characterized. Therefore, the present study aimed to identify the genes involved in the pathogenesis of LB2BC. The data of 117 LB2BC expression profiles were downloaded from The Cancer Genome Atlas (TCGA) and differentially expressed genes (DEGs) were identified by comparison with non-tumor tissue expression profiles. Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) networks were used to obtain insight into the functions of DEGs. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis was performed to validate the expression level of DEGs in tissue samples. A total of 2,251 DEGs, including 759 upregulated and 1,492 downregulated genes, were identified between LB2BC and non-tumor tissues. The top 15 upregulated and downregulated genes were used to construct a PPI network: Epidermal growth factor receptor (EGFR), fibronectin-1 (FN1) and Polo-like kinase-1 had the highest connectivity degrees. KEGG analysis identified that DEGs were most significantly enriched in 'focal adhesion', 'pathways in cancer' and 'ECM-receptor interaction' pathways. The results of RT-qPCR demonstrated that EGFR was significantly downregulated in LB2BC, whereas FN1 was significantly upregulated, whereas neurotrophic receptor tyrosine kinase 2 (NTRK2) trended towards downregulation. In conclusion, the DEGs identified in the present study, including NTRK2, FN1 and EGFR, may serve pivotal roles in the tumorigenesis of LB2BC by affecting the 'focal adhesion', 'pathways in cancer' and 'ECM-receptor interaction' KEGG pathways.
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