Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Accurate prediction and validation of response to endocrine therapy in breast cancer


ABSTRACT: Purpose Aromatase inhibitors (AIs) have an established role in breast cancer treatment. Response rates are only 50-70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Participants and Methods Pre- and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 post-menopausal women with ER+ breast cancer receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed by three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterised and a four gene classifier of clinical response was established (accuracy of 96%) based upon the level of two genes prior to treatment (one associated with immune signalling, IL6ST and the other with apoptosis, NGFRAP1) and two proliferation genes (ASPM, MCM4) at 2 weeks of therapy. The four gene signature was found to be 91% accurate in a blinded, completely independent validation dataset of patients treated with anastrozole. Matched 2 week on-treatment biopsies improved predictive power over pre-treatment biopsies alone. This signature also significantly predicted recurrence free survival (p=0.029) and breast cancer specific survival (p=0.009). We demonstrate that the test can also be performed using quantitative PCR or immunohistochemistry. Conclusion A four gene predictive model of clinical response to AIs by two weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and a failure to reduce proliferation by 2 weeks are functional characteristics of breast tumours that do not respond to AIs. 25 Pre treatment, 25 two week and 25 three month on-treatment primary breast tumour samples from the same patients. Data was analysed with two previously generated datasets, GSE55374 which was also processed on Illumina HT-12v4 BeadChips (GPL10558) and GSE20181 on Affymetrix U133A GeneChips (GPL96)

ORGANISM(S): Homo sapiens

SUBMITTER: Andrew Sims 

PROVIDER: E-GEOD-59515 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

altmetric image

Publications

Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer.

Turnbull Arran K AK   Arthur Laura M LM   Renshaw Lorna L   Larionov Alexey A AA   Kay Charlene C   Dunbier Anita K AK   Thomas Jeremy S JS   Dowsett Mitch M   Sims Andrew H AH   Dixon J Michael JM  

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20150601 20


<h4>Purpose</h4>Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy.<h4>Patients and methods</h4>Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estro  ...[more]

Similar Datasets

2014-08-11 | E-GEOD-55374 | biostudies-arrayexpress
2015-07-06 | GSE59515 | GEO
2014-08-11 | GSE55374 | GEO
2007-12-10 | GSE5462 | GEO
2010-07-28 | GSE20181 | GEO
2008-06-13 | E-GEOD-5462 | biostudies-arrayexpress
2010-07-28 | E-GEOD-20181 | biostudies-arrayexpress
2012-07-16 | E-GEOD-39387 | biostudies-arrayexpress
2011-04-22 | GSE28796 | GEO
2021-02-09 | GSE158724 | GEO