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Protein co-expression networks identified from HOT lesions of ER+HER2–Ki-67high luminal breast carcinomas
Patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative/Ki-67-high (ER+HER2–Ki-67high) luminal breast cancer have a worse prognosis and do not respond to hormonal treatment and chemotherapy. This study sought to identify disease-related protein networks significant...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814020/ https://www.ncbi.nlm.nih.gov/pubmed/33462336 http://dx.doi.org/10.1038/s41598-021-81509-9 |
Sumario: | Patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative/Ki-67-high (ER+HER2–Ki-67high) luminal breast cancer have a worse prognosis and do not respond to hormonal treatment and chemotherapy. This study sought to identify disease-related protein networks significantly associated with this subtype, by assessing in-depth proteomes of 10 lesions of high and low Ki-67 values (HOT, five; COLD, five) microdissected from the five tumors. Weighted correlation network analysis screened by over-representative analysis identified the five modules significantly associated with the HOT lesions. Pathway enrichment analysis, together with causal network analysis, revealed pathways of ribosome-associated quality controls, heat shock response by oxidative stress and hypoxia, angiogenesis, and oxidative phosphorylation. A semi-quantitative correlation of key-protein expressions, protein co-regulation analysis, and multivariate correlation analysis suggested co-regulations via network-network interaction among the four HOT-characteristic modules. Predicted highly activated master and upstream regulators were most characteristic to ER-positive breast cancer and associated with oncogenic transformation, as well as resistance to chemotherapy and endocrine therapy. Interestingly, inhibited intervention causal networks of numerous chemical inhibitors were predicted within the top 10 lists for the WM2 and WM5 modules, suggesting involvement of potential therapeutic targets in those data-driven networks. Our findings may help develop therapeutic strategies to benefit patients. |
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