Penetrance estimates for BRCA1 and BRCA2 based on genetic testing in a Clinical Cancer Genetics service setting: Risks of breast/ovarian cancer quoted should reflect the cancer burden in the family

<p>Abstract</p> <p>Background</p> <p>The identification of a <it>BRCA1 </it>or <it>BRCA2 </it>mutation in familial breast cancer kindreds allows genetic testing of at risk relatives. However, considerable controversy exists regarding the cancer risks in women who test positive for the family mutation.</p> <p>Methods</p> <p>We reviewed 385 unrelated families (223 with <it>BRCA1 </it>and 162 with <it>BRCA2 </it>mutations) ascertained through two regional cancer genetics services. We estimated the penetrance for both breast and ovarian cancer in female mutation carriers (904 proven mutation carriers – 1442 females in total assumed to carry the mutation) and also assessed the effect on penetrance of mutation position and birth cohort.</p> <p>Results</p> <p>Breast cancer penetrance to 70 and to 80 years was 68% (95%CI 64.7–71.3%) and 79.5% (95%CI 75.5–83.5%) respectively for <it>BRCA1 </it>and 75% (95%CI 71.7–78.3%) and 88% (95%CI 85.3–91.7%) for <it>BRCA2</it>. Ovarian cancer risk to 70 and to 80 years was 60% (95%CI 65–71%) and 65% (95%CI 75–84%) for <it>BRCA1 </it>and 30% (95%CI 25.5–34.5%) and 37% (95%CI 31.5–42.5%) for <it>BRCA2</it>. These risks were borne out by a prospective study of cancer in the families and genetic testing of unaffected relatives. We also found evidence of a strong cohort effect with women born after 1940 having a cumulative risk of 22% for breast cancer by 40 years of age compared to 8% in women born before 1930 (p = 0.0005).</p> <p>Conclusion</p> <p>In high-risk families, selected in a genetics service setting, women who test positive for the familial <it>BRCA1/BRCA2 </it>mutation are likely to have cumulative breast cancer risks in keeping with the estimates obtained originally from large families. This is particularly true for women born after 1940.</p

Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers

Thomas PE, Klinger R, Furlong LI, Hofmann-Apitius M, Friedrich CM. Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers. BMC Bioinformatics. 2011;12(Suppl 4): S4

Characterization Of Large Rearrangements In Autosomal Dominant Polycystic Kidney Disease And The Pkd1/Tsc2 Contiguous Gene Syndrome

Large DNA rearrangements account for about 8% of disease mutations and are more common in duplicated genomic regions, where they are difficult to detect. Autosomal dominant polycystic kidney disease ( ADPKD) is caused by mutations in either PKD1 or PKD2. PKD1 is located in an intrachromosomally duplicated region. A tuberous sclerosis gene, TSC2, lies immediately adjacent to PKD1 and large deletions can result in the PKD1/TSC2 contiguous gene deletion syndrome. To rapidly identify large rearrangements, a multiplex ligation-dependent probe amplification assay was developed employing base-pair differences between PKD1 and the six pseudogenes to generate PKD1-specific probes. All changes in a set of 25 previously defined deletions in PKD1, PKD2 and PKD1/TSC2 were detected by this assay and we also found 14 new mutations at these loci. About 4% of the ADPKD patients in the CRISP study were found to have gross rearrangements, and these accounted for about a third of base-pair mutation negative families. Sensitivity of the assay showed that about 40% of PKD1/TSC contiguous gene deletion syndrome families contained mosaic cases. Characterization of a family found to be mosaic for a PKD1 deletion is discussed here to illustrate family risk and donor selection considerations. Our assay improves detection levels and the reliability of molecular testing of patients with ADPKD.WoSScopu

Combining accurate tumor genome simulation with crowdsourcing to benchmark somatic structural variant detection

BackgroundThe phenotypes of cancer cells are driven in part by somatic structural variants. Structural variants can initiate tumors, enhance their aggressiveness, and provide unique therapeutic opportunities. Whole-genome sequencing of tumors can allow exhaustive identification of the specific structural variants present in an individual cancer, facilitating both clinical diagnostics and the discovery of novel mutagenic mechanisms. A plethora of somatic structural variant detection algorithms have been created to enable these discoveries; however, there are no systematic benchmarks of them. Rigorous performance evaluation of somatic structural variant detection methods has been challenged by the lack of gold standards, extensive resource requirements, and difficulties arising from the need to share personal genomic information.ResultsTo facilitate structural variant detection algorithm evaluations, we create a robust simulation framework for somatic structural variants by extending the BAMSurgeon algorithm. We then organize and enable a crowdsourced benchmarking within the ICGC-TCGA DREAM Somatic Mutation Calling Challenge (SMC-DNA). We report here the results of structural variant benchmarking on three different tumors, comprising 204 submissions from 15 teams. In addition to ranking methods, we identify characteristic error profiles of individual algorithms and general trends across them. Surprisingly, we find that ensembles of analysis pipelines do not always outperform the best individual method, indicating a need for new ways to aggregate somatic structural variant detection approaches.ConclusionsThe synthetic tumors and somatic structural variant detection leaderboards remain available as a community benchmarking resource, and BAMSurgeon is available at https://github.com/adamewing/bamsurgeon