Improved relapse-free survival on aromatase inhibitors in breast cancer is associated with interaction between oestrogen receptor-α and progesterone receptor-b
Files
(Published version)
Date
2018
Authors
Snell, C.
Gough, M.
Liu, C.
Middleton, K.
Pyke, C.
Shannon, C.
Woodward, N.
Hickey, T.
Armes, J.
Tilley, W.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
British Journal of Cancer, 2018; 119(11):1316-1325
Statement of Responsibility
Cameron E. Snell, Madeline Gough, Cheng Liu, Kathryn Middleton, Christopher Pyke, Catherine Shannon, Natasha Woodward, Theresa E. Hickey, Jane E. Armes and Wayne D. Tilley
Conference Name
Abstract
Background: Recent pre-clinical studies indicate that activated progesterone receptor (PR) (particularly the PR-B isoform) binds to oestrogen receptor-α (ER) and reprogrammes transcription toward better breast cancer outcomes. We investigated whether ER and PR-B interactions were present in breast tumours and associated with clinical parameters including response to aromatase inhibitors. Methods: We developed a proximity ligation assay to detect ER and PR-B (ER:PR-B) interactions in formalin-fixed paraffin-embedded tissues. The assay was validated in a cell line and patient-derived breast cancer explants and applied to a cohort of 229 patients with ER-positive and HER2-negative breast cancer with axillary nodal disease. Results: Higher frequency of ER:PR-B interaction correlated with increasing patient age, lower tumour grade and mitotic index. A low frequency of ER:PR-B interaction was associated with higher risk of relapse. In multivariate analysis, ER:PR-B interaction frequency was an independent predictive factor for relapse, whereas PR expression was not. In subset analysis, low frequency of ER:PR-B interaction was predictive of relapse on adjuvant aromatase inhibitor (HR 4.831, p = 0.001), but not on tamoxifen (HR 1.043, p = 0.939). Conclusions: This study demonstrates that ER:PR-B interactions have utility in predicting patient response to adjuvant AI therapy.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
© Cancer Research UK 2018 Note: This work is published under the standard license to publish agreement. After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution 4.0 International (CC BY 4.0).