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Co-expression network analysis of gene expression profiles of HER2(+) breast cancer-associated brain metastasis

Brain metastasis occurs in ~30% of patients with breast cancer, and patients with human epidermal growth factor receptor 2 (HER2)(+) breast cancer have a particularly high frequency of brain metastasis. Weighted gene co-expression network analysis was conducted to identify the hub differentially exp...

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Detalles Bibliográficos
Autores principales: Yuan, Feng, Wang, Wei, Cheng, Hongtao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6256326/
https://www.ncbi.nlm.nih.gov/pubmed/30546434
http://dx.doi.org/10.3892/ol.2018.9562
Descripción
Sumario:Brain metastasis occurs in ~30% of patients with breast cancer, and patients with human epidermal growth factor receptor 2 (HER2)(+) breast cancer have a particularly high frequency of brain metastasis. Weighted gene co-expression network analysis was conducted to identify the hub differentially expressed genes from patients with HER2(+) breast cancer between brain metastases and primary tumors. The potential candidate genes were investigated in another set of patient samples to confirm their relevance. The results indicated that a number of pathways altered significantly when breast cancer metastasized to the brain. Cyclophilin A (CypA) and ribosomal protein L17 (RPL17) were overexpressed in breast cancer-associated brain metastases, whereas tumor protein 63 (TP63) and von Willebrand factor A domain-containing 8 (VWA8) were significantly downregulated in breast cancer brain metastases. Furthermore, the expression of CypA and RPL17 in brain metastases were significantly increased compared with that in primary breast tumors, and the expression of TP63 and VWA8 in brain metastases were significantly decreased. This result indicated that the significant differences in expression observed between primary breast tumors and brain metastases were derived from significantly altered systems, including gene modules rather than single genes.