Stratifying Risk for Early Detection

Stratifying Risk for Early Detection in Hereditary Breast and Ovarian Cancer

Lead 1: Prof Marc Tischkowitz, University of Cambridge

Lead 2: Prof Allison Kurian, Stanford University

Lead 3: Prof. Gareth Evans, University of Manchester

Collaborators:

University of Cambridge: Prof. Antonis Antoniou

University of Southampton: Prof. Diana Eccles

Stanford University: Dr Alice Fan, Prof. James Ford

Project Summary

Women with inherited mutations in cancer genes such as BRCA1 and BRCA2 have a greatly increased risk of developing breast and ovarian cancers. Mutations in other genes such as PALB2, ATM and CHEK2 also increase risk. Early detection of cancer is of paramount importance in these women but the risks for each woman with a mutation can vary considerably. This means that the range of cancer risk estimates for women with mutations in these genes are wide and not personalised, so all women are given the same figures. This makes it particularly challenging for a woman to decide what level of early detection uptake they should seek and whether to opt for surveillance over life-changing surgeries such as risk reducing mastectomy.

We have developed a new tool, CanRisk which gives each woman with a mutation her own personal risk estimate based on factors that are known to modify the risk. One of the most important factors is the combined effect of hundreds of small genetic alterations scattered throughout the genome that act together to increase or decrease a woman’s cancer risk, and which will be different for each person. Other factors include hormonal (e.g. age at first period, number of pregnancies) and lifestyle (weight, alcohol consumption). The CanRisk personalised risk estimate has been validated and we know it correctly identifies those at higher risk. This study will examine how we can best use it in the clinic and how it influences women’s uptake of early detection and risk reduction.