Breast and ovarian cancer patients harboring BRCA1/2 germline mutations have clinically benefitted from therapy with PARP inhibitor (PARPi) or platinum compounds, but acquired resistance limits clinical impact. In this study, we investigated the impact of mutations on BRCA1 isoform expression and therapeutic response. Cancer cell lines and tumors harboring mutations in exon 11 of BRCA1 express a BRCA1-Δ11q splice variant lacking the majority of exon 11. The introduction of frameshift mutations to exon 11 resulted in nonsense-mediated mRNA decay of full-length, but not the BRCA1-Δ11q isoform. CRISPR/Cas9 gene editing as well as overexpression experiments revealed that the BRCA1-Δ11q protein was capable of promoting partial PARPi and cisplatin resistance relative to full-length BRCA1, both in vitro and in vivo. Furthermore, spliceosome inhibitors reduced BRCA1-Δ11q levels and sensitized cells carrying exon 11 mutations to PARPi treatment. Taken together, our results provided evidence that cancer cells employ a strategy to remove deleterious germline BRCA1 mutations through alternative mRNA splicing, giving rise to isoforms that retain residual activity and contribute to therapeutic resistance.

BackgroundPREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in ‘step’ changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status.MethodsMultivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT.ResultsIn the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease.The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40.ConclusionsThe PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-017-0852-3) contains supplementary material, which is available to authorized users.

In view of this association, we emphasise the importance of a specific approach to the treatment of anxiety and depression together with clinical treatment to improve the quality of life of these patients.

Purpose To analyse the effect of germline mutations in BRCA1 and BRCA2 on mortality in ovarian cancer patients up to ten years after diagnosis. Experimental Design We used unpublished survival time data for 2,242 patients from two case-control studies and extended survival-time data for 4,314 patients from previously reported studies. All participants had been screened for deleterious germline mutations in BRCA1 and BRCA2. Survival time was analysed for the combined data using Cox proportional hazard models with BRCA1 and BRCA2 as time-varying covariates. Competing risks were analysed using Fine and Gray model. Results The combined 10-year overall survival was 30% (95% CI, 28%-31%) for non-carriers, 25% (95% CI, 22%-28%) for BRCA1 carriers, and 35% (95% CI, 30%-41%) for BRCA2 carriers. The hazard ratio for BRCA1 was 0.53 at time zero and increased over time becoming greater than one at ·4.8 years. For BRCA2, the hazard ratio was 0.42 at time zero and increased over time (predicted to become greater than one at 10.5 years). The results were similar when restricted to 3,202 patients with high-grade serous tumors, and to ovarian cancer specific mortality. Conclusions BRCA1/2 mutations are associated with better short-term survival, but this advantage decreases over time and, in BRCA1 carriers is eventually reversed. This may have important implications for therapy of both primary and relapsed disease and for analysis of long-term survival in clinical trials of new agents, particularly those that are effective in BRCA1/2 mutation carriers.