3 PhD positions in Hereditary & Early Onset Breast Cancer Epidemiology

The Netherlands Cancer Institute (NKI) is recruiting three motivated and ambitious PhD students skilled in epidemiology, biostatistics or computational biology to contribute to the Hereditary & Early Onset Breast Cancer: Comprehensive Personalized Assessment, Early Risk Evaluation, and Clinical Management (HER-CARE) project.

HER-CARE is a Marie Skłodowska-Curie Actions-Doctoral network that brings together 9 leading academic and 3 industrial partners to train a new generation of multidisciplinary researchers with the unified goal of advancing early onset and hereditary breast cancer research. In total, the HER-CARE network will include 15 doctoral candidates across all participating institutes. In addition to conducting your primary research, you will broaden your experience through one international academic and one non-academic secondment within the HER-CARE network.

The network has three overarching aims:

1. to characterize spectrum of risk factors for early onset and hereditary breast cancer and its subtypes

2. to develop innovative approaches for risk stratification, early detection and screening of invasive breast cancer, and

3. to identify multi-modal markers of tumours and tumour environment to improve prediction of clinical outcomes and aid clinical decisions.

The Marjanka Schmidt Group is seeking PhD candidates for the following three projects within the network:

Risk and protective factors for the development of different subtypes of a second breast cancer (project 5):

Contralateral breast cancer is the most common second cancer in breast cancer survivors. Yet, there is limited understanding of hereditary and non-hereditary risk factors for contralateral breast cancer, hindering effective clinical management and informed personalized prevention strategies for breast cancer survivors. The doctoral candidate for this project will develop a multifactorial, longitudinal database and perform statistical analyses to 1) identify novel factors influencing risk of second breast cancer, including common and rare germline genetic variants, immunological markers, and mammographic density and 2) study the impact of different adjuvant treatment regimens used to treat a first breast cancer impact risk of a second breast cancer. The candidate will complete secondments at the University of Oxford (UK) and Evidencio (NL).

Risk modelling and online tool for shared decision making for risk management of second breast cancer (project 10):

Current risk models and clinical assessments are limited in their ability to distinguish which patients will develop contralateral breast cancer As a result, women at low predicted risk may still opt for preventive surgeries, such as contralateral mastectomy, despite unclear survival benefits. The doctoral candidate will develop a multifactorial predictive model and online tool to assist in the shared decision-making of second breast cancer risk management, along with a roadmap for its clinical implementation. Specifically, the candidate will 1) upgrade the CanRisk tool for risk prediction of second breast cancers using the PredictCBC model, 2) validate the upgraded CanRisk tool in relevant breast cancer populations, including hereditary breast cancer survivors, and 3) integrate CanRisk and PREDICT using the Evidencio platform for integrated second breast cancer risk assessment within context of prognostication of the first breast cancer. The candidate will complete secondments at the Cambridge Centre for Cancer Genetic Epidemiology (UK) and PHG Foundation (UK).

Genomic signatures of early onset tumours (project 12):

The distinct presentation and epidemiology of early-onset vs. late-onset breast cancer suggest biological differences between these tumours. However, the genomic determinants of these differences have not been well characterized. The doctoral candidate will characterize the unique germline and tumour genetic profiles of early-onset breast cancer to uncover their biological origins, improve detection, and identify potential treatment targets tailored to distinct genomic and immunologic profiles. Specifically, the doctoral candidate will use advanced statistical methods and programming tools (e.g., R, Python) to integrate large-scale, genomic, histological, and immunological data to identify the genomic contribution to breast cancer subtypes. The candidate will complete secondments at Centro Nacional de Análisis Genómico (Spain) and Methylomics (NL).

What are you going to do?

• Conduct innovative, interdisciplinary research to reveal novel insights about the aetiology, progression, and clinical management of early onset and hereditary breast cancer;

• Join the unique HER-CARE network that unites data-driven research with clinical translation to improve outcomes for women with hereditary and early-onset breast cancer;

• Actively collaborate with other researchers within the group, the NKI, and the HER-CARE doctoral network;

• Complete two secondments, with both (inter)national academic collaborators and non-academic partners;

• Participate in five network-wide training events and consortium meetings;

• Present your (intermediate) research results at institutional meetings, international conferences and workshops;

• Publish your results in peer-reviewed journals;

• Complete and defend a PhD thesis within the official appointment of four years.