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Precision medicine and survivorship

Our work spans the themes of precision medicine and survivorship. Our focus is on early detection and prevention of breast cancer and breast cancer recurrence; specifically, we aim to investigate germline genetic variants for their role in breast cancer subtype development and outcome. We strive to translate and implement our findings in models and tools to facilitate shared decision-making by patients and physicians with overarching goals to prevent breast cancer and recurrence of cancer, to reduce overtreatment, and to improve outcome. We also investigate and strive to implement the best Ethical, Legal, and Societal (ESLI) practices related to the (secondary) use of human data and materials.


Identification of hereditary variants relevant for breast cancer subtypes and prognostication
We are actives members of the Breast Cancer Association Consortium (BCAC), which identified many novel breast cancer susceptibility loci. However, the genetic determinants of specific breast cancer subtypes and breast cancer outcome or prognosis are still largely unexplained. We are trying to identify those through a number of national and international large studies, among others within this large BCAC consortium. The BCAC clinico-pathological database including tumour characteristics and clinical diagnostic and treatment information as well as follow-up from >70 studies comprising >110,000 patients is maintained by our group. We aim to identify germline variants that are important in the aetiology of breast cancer subtypes as well as variants that affect prognosis through treatment response or other mechanisms.  Genetic germline or tumour genetic variants or molecular tumour markers will need to be included in (online) prediction models. Therefore, we are also working in collaborative efforts to improve outcome predictions of online models such as PREDICT in order to assist fine-tuning of these prediction models for individualized treatment and follow-up decision for breast cancer patients.

Understanding and predicting risk of contralateral breast cancer
Contralateral breast cancer (CBC), a new primary tumour in the opposite breast, is a rare event (10-year cumulative incidence 4%) with potential for poor outcome. We need improved risk prediction and understanding of the disease aetiology to identify high and low risk to develop CBC and to optimize the decision making around contralateral preventive mastectomy or tailored follow up strategy. Therefore, we developed and validated a CBC risk prediction model, PredictCBC, using multiple studies including patients, oncogenetics and tumour and treatment information. Although in breast cancer patients with BRCA1/2 germline mutations, PredictCBC is potentially useful for clinical decision making, CBC in the general breast cancer population remains challenging. To address this remaining challenge, we are expanding the model with additional informative factors, such as a polygenic risk score (PRS).

More transparency and facilitating research by improving information procedures
We made a significant contribution towards improving consent procedures for the (secondary) use of residual tissue, images, and data, for scientific research. Although most patients agree with the use of their materials and data for research, previous research of our group shows that patients felt that transparency around this topic should be improved. Moreover, changing societal norms increased the number of research studies for which the opt-out procedure did not suffice anymore. Since mid-2018, the Netherlands Cancer Institute therefore informs all patients about this use, and asks their consent. Our national ‘ELSI servicedesk’ provides information and advice on legal, ethical and social issues in precision medicine and health research in general to researchers and other interested stakeholders. We have several applied research projects on topics such as informed consent, patient information, return of results, big data, genomic data, and legal issues related to use of patient data and materials.

 

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