Abstract
The BRCA1 gene from individuals at risk of breast and ovarian cancers can be screened for the presence of mutations. However, the cancer association of most alleles carrying missense mutations is unknown, thus creating significant problems for genetic counseling. To increase our ability to identify cancer-associated mutations in BRCA1, we set out to use the principles of protein three-dimensional structure as well as the correlation between the cancer-associated mutations and those that abolish transcriptional activation. Thirty-one of 37 missense mutations of known impact on the transcriptional activation function of BRCA1 are readily rationalized in structural terms. Loss-of-function mutations involve nonconservative changes in the core of the BRCA1 C-terminus (BRCT) fold or are localized in a groove that presumably forms a binding site involved in the transcriptional activation by BRCA1; mutations that do not abolish transcriptional activation are either conservative changes in the core or are on the surface outside of the putative binding site. Next, structure-based rules for predicting functional consequences of a given missense mutation were applied to 57 germ-line BRCA1 variants of unknown cancer association. Such a structure-based approach may be helpful in an integrated effort to identify mutations that predispose individuals to cancer.
Highlights
Many germ-line mutations in the human BRCA1 gene are associated with inherited breast and ovarian cancers [1, 2]
According to PSI-BLAST [23], the latter six sequences are the only sequences in the nonredundant protein sequence database at National Center for Biotechnology Information that have between 30% and 90% sequence identity to the human BRCA1 BRCA1 C-terminus (BRCT) domains
We tabulated a total of 94 missense mutations in the human BRCA1 BRCT domains (Tables 1 and 2; Fig. 1)
Summary
Many germ-line mutations in the human BRCA1 gene are associated with inherited breast and ovarian cancers [1, 2]. The disease association of over 350 missense mutations remains unclear, primarily because their relatively low frequency and ethnic specificity limit the usefulness of the population-based statistical approaches to identifying cancer-causing mutations. To address this problem, we use here the threedimensional structure of the human BRCA1 BRCT domains to assess the transcriptional activation functions of BRCA1 mutants. Cancer-associated mutations in the BRCT domains, but not benign polymorphisms, inactivate transcriptional activation and binding to RNA polymerase II (18 –21) These observations suggest that abolishing the transcriptional activation function of BRCA1 leads to tumor development and provides a genetic framework for characterization of BRCA1 BRCT variants
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