ArticleBreast cancer research : BCR2015
Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer.
Article in Breast cancer research : BCR, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Clinical and microarray analysis of breast cancers of all subtypes from two prospective preoperative chemotherapy studies.British journal of cancer · 2016Trial
- Clinical relevance of total choline (tCho) quantification in suspicious lesions on multiparametric breast MRI.European radiology · 2020Article
- Increased Expression of FosB through Reactive Oxygen Species Accumulation Functions as Pro-Apoptotic Protein in Piperlongumine Treated MCF7 Breast Cancer Cells.Molecules and cells · 2019Article
- Beyond 5 years: enduring risk of recurrence in oestrogen receptor-positive breast cancer.Nature reviews. Clinical oncology · 2019Review
- Genomic Instability andJCO precision oncology · 2019Article
- Molecular changes in premenopausal oestrogen receptor-positive primary breast cancer in Vietnamese women after oophorectomy.NPJ breast cancer · 2017Article
- A Delphic consensus assessment: imaging and biomarkers in gastroenteropancreatic neuroendocrine tumor disease management.Endocrine connections · 2016Article
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Authors and funding
17 authors at 4 institutions in 3 countries.
Funding
Abstract
introductionAromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach.
methodsSamples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n=84), gene expression profiling (n=47), matched pre- and post-AI aCGH (n=19 pairs) and Ki67-based AI-response analysis (n=39).
resultsIntegrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1).
conclusionsThese data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response.
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