Deciphering breast cancer HER2-negativity with regard to HER2-targeted therapy
Breast cancer (BC) has the highest incidence (24,400 new cases in 2014), representing the second cause of death in Canadian women (5,000). The Human Epidermal Growth Factor Receptor 2, HER2, is a prognostic marker of clinical outcomes in BC. Overexpression and/or amplification of HER2 occur in 20-25% of breast tumours and have been associated with a more aggressive clinical behaviour. The great majority of breast tumours are therefore HER2-negative (HER2-). Anti-HER2 agents are administered only to patients with a HER2-positive (HER2+) tumour, and recent data suggest that a sub-group of patients presenting with HER2- tumours could benefit from anti-HER2 treatments. Studies have demonstrated than in up to 30 percent of breast recurrences/metastases, ER/PR/HER2 status will change, including a change from HER2 negative to positive. Hence identifying genes that would signal a switch to HER2+ status in HER2- tumours undergoing a change in their HER2 status after a breast recurrence would be of great benefit to patients. These patients could be administered an anti-HER2 treatment in prevention thus preventing possible recurrences.
Accordingly, we propose an innovative strategy in which the methylation signature present in HER2- primary breast tumours that will become HER2+ at recurrence may be predictive as it would be present before a HER2+ phenotype occurs. Indeed, changes in methylation occurring in HER2- breast tumours that will become HER2+ following recurrences could be used as predictive biomarkers, indicating whether these patients will respond to anti-HER2 treatment. Such methylation changes affecting specific gene expression could in turn be applicable to all HER2- tumours.
Using machine learning, the methylation signature of these breast tissues will be correlated with the expression profile to further confirm the identification of preventive biomarkers. Highlighting changes in methylation early enough so that these could be used as a tool for targeted treatment is clearly a novel and understudied areas which likely has the huge potential of identifying predictive biomarkers associated with a sensitivity to anti-HER2 agents. Hence, we hypothesize that there are methylation changes in a primary HER2-negative breast tumour that can predict a change from HER2-negative to HER2-positive at recurrence, and that this predictive methylation signature can be used to offer preventive anti-HER2 treatment in HER2-negative breast tumours.
This project will be achieved through the following objectives:
Objective 1: To establish the whole genome methylation and transcription profiles of a series of HER2-/HER2+ and HER2-/HER2- tumours following recurrences or second cancer.
Objective 2: To identify genes and functional pathways to pinpoint biomarkers predictive of a change from HER2- to HER2+ status.
Identifying a predictive methylation signature in primary HER2-negative breast tumours that are HER2-positive at time of recurrence is highly innovative and critically important as it would provide deeply needed biomarkers that will help in identifying women affected with primary HER2-negative tumours in whom an anti-HER2 treatment would be beneficial at time of diagnosis. This is clinically relevant as for 20-25% of all BC patients who currently do not receive anti-HER2 agents and whose prognosis is particularly poor (the so-called triple-negative BC patients, i.e. ER-, PR-, HER2-) still require an adequate therapy.
Université Laval. Département de médecine sociale et préventive
Universtié de Montréal