Combining functional information relating to genetic variation in BRCA1 and BRCA2 to evaluate its clinical significance 

Background of research project:

Mutations in the BRCA1 and BRCA2 genes strongly predispose to the development of breast and ovarian cancer. For this reason, DNA-testing is offered to women at high familial risk for breast cancer. However, in many cases, a genetic variant is being detected of which the clinical significance is not clear. These include missense mutations and intronic changes with unknown effect on mRNA-processing. 

Research questions:

To derive and combine information from the literature and genetic databases that may help to functionally understand the relevance of genetic variants of uncertain clinical significance (VUCS), and to make this information available to the BRCA mutation scanning community through a dedicated web-site.

Project description:

In this project we want to find evidence that either supports or refutes the possibility that an unclassified sequence variant is causally related to disease outcome in carriers. A genetic variant in BRCA1 or BRCA2 could either be an irrelevant polymorphism, a low-risk variant, or a previously unrecognized high-risk variant. It is impossible to distinguish between these possibilities on the basis of a single test-result. Only a comprehensive approach, incorporating data on mutation type, clinical validation, population genetics, and functional consequences of the DNA change on the protein, can provide a meaningful classification of genetic variation.

Experimental design:

Through literature searching, and database mining, we will collect all relevant information on a set of VUCSs. This data will come from diverse sources, such as SNP-databases, molecular biology publications on BRCA1/2 function, sequence alignments for evolutionary conservation, etc. A limited amount of unpublished data might also be available directly from the laboratory from related projects. All information will be collected in a relational database, allowing various combinations of output. Brief reports on each VUCS will be produced and made available through the web.

Techniques to be applied:

Database mining; literature search (PubMed).

Statistical methods:

Fishers's exact test

Plan of work and time schedule:

The length of the project (12 weeks) allows the analysis of several VUCS in parallel. Depending on the amount of information collected, statistical analyses can be attempted to weigh the different types of evidence collected on a variant to arrive at a quantitative probability that it is truly pathogenic. 

Equipment to be used:

None

Updated:  19-02-2003
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