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Background Reproductive and lifestyle factors influence both breast cancer risk and prognosis; this might be through breast cancer subtype. Subtypes defined by immunohistochemical hormone receptor markers and gene expression signatures are used to predict prognosis of breast cancer patients based on their tumour biology. We investigated the association between established breast cancer risk factors and the 70-gene prognostication signature in breast cancer patients. Patients and methods Standardised questionnaires were used to obtain information on established risk factors of breast cancer from the Dutch patients of the MINDACT trial. Clinical-pathological and genomic information were obtained from the trial database. Logistic regression analyses were used to estimate the associations between lifestyle risk factors and tumour prognostic subtypes, measured by the 70-gene MammaPrint ® signature (i.e. low-risk or high-risk tumours). Results Of the 1555 breast cancer patients included, 910 had low-risk and 645 had high-risk tumours. Current body mass index (BMI), age at menarche, age at first birth, age at menopause, hormonal contraceptive use and hormone replacement therapy use were not associated with MammaPrint ® . In parous women, higher parity was associated with a lower risk (OR: 0.75, [95% confidence interval {CI}: 0.59–0.95] P = 0.018) and longer breastfeeding duration with a higher risk (OR: 1.03, [95% CI: 1.01–1.05] P = 0.005) of developing high-risk tumours; risk estimates were similar within oestrogen receptor–positive disease. After stratifying by menopausal status, the associations remained present in post-menopausal women. Conclusion Using prognostic gene expression profiles, we have indications that specific reproductive factors may be associated with prognostic tumour subtypes beyond hormone receptor status. [ABSTRACT FROM AUTHOR]

Aim: To evaluate the use of the MammaPrint assay, a 70-gene risk signature for early breast cancers, and to correlate genomic risk stratification with individual clinicopathological parameters and clinical risk as assessed by Adjuvant! Online., Methods: A Dutch Pathology Registry (PALGA)-based cohort study consisting of 1916 patients for which 1946 MammaPrint assay results were synoptically reported from 2013 to 2016. We could retrospectively assess clinical risk for 1146 tumors (58.9%) using Adjuvant! Online (version 8.0 with HER2 status) and for 1155 tumors (59.4%) using PREDICT (version 2.0)., Results: Adjuvant! Online classified 718 tumors (62.7%) as clinical low risk and 428 tumors (37.3%) as clinical high risk. MammaPrint classified 1206 tumors (62.0%) as genomic low risk and 740 tumors (38.0%) as genomic high risk. Genomic risk stratification was significantly associated with histological subtype and grade (P < .001), hormonal receptor status (P < .001), presence of lymphovascular invasion (P = .001) and nodal status (P = .002), whereas no association was found with tumor size (P = .541). MammaPrint classified 52.6% of clinical high risk tumors (N = 428) as genomic low risk. This percentage was highest (67.3%) in clinical high risk ER-positive/HER2-negative grade 1-2 tumors (N = 282). Correlation between predicted overall survival benefit from adjuvant chemotherapy (PREDICT V2.0) and genomic risk distribution was almost linear., Conclusions: This study showed that MammaPrint classified 52.6% of clinical high risk tumors as genomic low risk. In the Netherlands, 62.7% of the MammaPrint assays from 2013 to 2016 were performed on clinical low risk tumors, although recent International Guidelines recommend its use in clinical high and intermediate risk tumors., (Copyright © 2017 Elsevier Ltd. All rights reserved.)