4.5 Article

Predisposition gene identification in common cancers by exome sequencing: insights from familial breast cancer

Journal

BREAST CANCER RESEARCH AND TREATMENT
Volume 134, Issue 1, Pages 429-433

Publisher

SPRINGER
DOI: 10.1007/s10549-012-2057-x

Keywords

Breast cancer predisposition; Exome sequencing; Common disease genetics; Missing heritability

Categories

Funding

  1. US Military Acquisition (ACQ) Activity
  2. Era of Hope Award [W81XWH-05-1-0204]
  3. Cancer Research UK [C8620/A8372, C8620/A8857]
  4. Institute of Cancer Research (UK)
  5. National Health Service
  6. Michael and Betty Kadoorie Cancer Genetics Research Programme
  7. MRC [G0700491] Funding Source: UKRI
  8. Cancer Research UK [15106] Funding Source: researchfish
  9. Medical Research Council [G0700491] Funding Source: researchfish

Ask authors/readers for more resources

The genetic component of breast cancer predisposition remains largely unexplained. Candidate gene case-control resequencing has identified predisposition genes characterised by rare, protein truncating mutations that confer moderate risks of disease. In theory, exome sequencing should yield additional genes of this class. Here, we explore the feasibility and design considerations of this approach. We performed exome sequencing in 50 individuals with familial breast cancer, applying frequency and protein function filters to identify variants most likely to be pathogenic. We identified 867,378 variants that passed the call quality filters of which 1,296 variants passed the frequency and protein truncation filters. The median number of validated, rare, protein truncating variants was 10 in individuals with, and without, mutations in known genes. The functional candidacy of mutated genes was similar in both groups. Without prior knowledge, the known genes would not have been recognisable as breast cancer predisposition genes. Everyone carries multiple rare mutations that are plausibly related to disease. Exome sequencing in common conditions will therefore require intelligent sample and variant prioritisation strategies in large case-control studies to deliver robust genetic evidence of disease association.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available