Dataset Information

Toward classification of BRCA1 missense variants using a biophysical approach.

ABSTRACT: Carriers of germ line mutations in breast cancer susceptibility gene BRCA1 have an increased risk of developing breast and ovarian cancers; missense mutations have, however, been difficult to assess for disease association. Here we have used a biophysical approach to classify these variants. We established an assay for measuring the thermodynamic stability of the BRCA1 BRCT domains and investigated the effects of 36 missense mutations. The mutations show a range of effects. Some do not change the stability, whereas others destabilize the protein by as much as 6 kcal mol(-1); one-third of the mutants could not be expressed in soluble form in Escherichia coli, and we conclude that these destabilize the protein by an even greater amount. We tested several computer algorithms for their ability to predict the mutant effects and found that by grouping them into two classes (destabilizing by less than or more than 2.2 kcal mol(-1)), the algorithms could predict the stability changes. Importantly, with the exception of the few mutants located in the binding site, none showed a significant reduction in affinity for phosphorylated substrate. These results indicate that despite very large losses in stability, the integrity of the structure is not compromised by the mutations. Thus, the majority of mutations cause loss of function by reducing the proportion of BRCA1 molecules that are in the folded state and increasing the proportion of molecules that are unfolded. Consequently, small molecule stabilization of the structure could be a generally applicable preventative therapeutic strategy for rescuing many BRCA1 mutations.

SUBMITTER: Rowling PJ

PROVIDER: S-EPMC2888420 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Toward classification of BRCA1 missense variants using a biophysical approach.

Rowling Pamela J E PJ Cook Rebecca R Itzhaki Laura S LS

The Journal of biological chemistry 20100408 26

Carriers of germ line mutations in breast cancer susceptibility gene BRCA1 have an increased risk of developing breast and ovarian cancers; missense mutations have, however, been difficult to assess for disease association. Here we have used a biophysical approach to classify these variants. We established an assay for measuring the thermodynamic stability of the BRCA1 BRCT domains and investigated the effects of 36 missense mutations. The mutations show a range of effects. Some do not change th ...[more]

PMID: 20378548

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Project description:BACKGROUND:The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. METHODS:We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. RESULTS:PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. CONCLUSION:We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

Dataset Information

Toward classification of BRCA1 missense variants using a biophysical approach.

Publications

Toward classification of BRCA1 missense variants using a biophysical approach.

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