Literature DB >> 16433698

Evaluation of two different models to predict BRCA1 and BRCA2 mutations in a cohort of Danish hereditary breast and/or ovarian cancer families.

A-M Gerdes1, D G Cruger, M Thomassen, T A Kruse.   

Abstract

To meet the increasing demand for BRCA1 and BRCA2 mutation analysis, a robust system for selecting families who have a higher chance of a mutation has become important. Several models have been developed to help predict which samples are more likely to be mutation positive than others. We have undertaken a complete BRCA1 and BRCA2 mutation analysis in 267 Danish families with high-risk family history. We found deleterious mutations in 28% (76) of the families, 68% (52) of those in BRCA1 and 32% (24) in BRCA2. We compared our results with two popular manual models developed to estimate the chance of a positive result. One is the recently published Manchester model and the other is the Frank 2 model updated by Myriad Genetic Laboratories, Inc. Neither of the models would have suggested screening all mutation-positive samples. The Manchester model would have suggested screening 124 of the families in the cohort, thereby detecting 54 of 76 mutations (sensitivity 71%; specificity 63%), whereas the Frank 2/Myriad model would have found 60 of 76 mutations by screening 169 samples if a 10% likelihood was adapted (sensitivity 79%; specificity 43%). The updated Manchester model suggested screening 172 families whereby 64 mutations would have been detected (sensitivity 84%; specificity 44%). We conclude that although both models would have reduced the number of samples screened significantly, up to 28% of the mutations would not have been found by applying these models to this Danish cohort of families. This raises the question whether models designed for specific populations can be used in a wider setting.

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Year:  2006        PMID: 16433698     DOI: 10.1111/j.1399-0004.2006.00568.x

Source DB:  PubMed          Journal:  Clin Genet        ISSN: 0009-9163            Impact factor:   4.438


  11 in total

1.  Population frequencies of pathogenic alleles of BRCA1 and BRCA2: analysis of 173 Danish breast cancer pedigrees using the BOADICEA model.

Authors:  Thorkild Terkelsen; Lise-Lotte Christensen; Deirdre Cronin Fenton; Uffe Birk Jensen; Lone Sunde; Mads Thomassen; Anne-Bine Skytte
Journal:  Fam Cancer       Date:  2019-10       Impact factor: 2.375

Review 2.  Genotype/Phenotype correlations in patients with hereditary breast cancer.

Authors:  Maike Wittersheim; Reinhard Büttner; Birgid Markiefka
Journal:  Breast Care (Basel)       Date:  2015-02       Impact factor: 2.860

3.  Evaluation of BRCA1 and BRCA2 mutation prevalence, risk prediction models and a multistep testing approach in French-Canadian families with high risk of breast and ovarian cancer.

Authors:  Jacques Simard; Martine Dumont; Anne-Marie Moisan; Valérie Gaborieau; Hélène Malouin; Francine Durocher; Jocelyne Chiquette; Marie Plante; Denise Avard; Paul Bessette; Claire Brousseau; Michel Dorval; Béatrice Godard; Louis Houde; Yann Joly; Marie-Andrée Lajoie; Gilles Leblanc; Jean Lépine; Bernard Lespérance; Hélène Vézina; Jillian Parboosingh; Roxane Pichette; Louise Provencher; Josée Rhéaume; Daniel Sinnett; Carolle Samson; Jean-Claude Simard; Martine Tranchant; Patricia Voyer; Douglas Easton; Sean V Tavtigian; Bartha-Maria Knoppers; Rachel Laframboise; Peter Bridge; David Goldgar
Journal:  J Med Genet       Date:  2006-08-11       Impact factor: 6.318

Review 4.  The contribution of BRCA1 and BRCA2 to ovarian cancer.

Authors:  Susan J Ramus; Simon A Gayther
Journal:  Mol Oncol       Date:  2009-02-10       Impact factor: 6.603

5.  Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models.

Authors:  Noralane M Lindor; Rachel A Lindor; Carmel Apicella; James G Dowty; Amanda Ashley; Katherine Hunt; Betty A Mincey; Marcia Wilson; M Cathie Smith; John L Hopper
Journal:  Fam Cancer       Date:  2007-07-17       Impact factor: 2.375

6.  Association of FTO Mutations with Risk and Survival of Breast Cancer in a Chinese Population.

Authors:  Xianxu Zeng; Zhenying Ban; Jing Cao; Wei Zhang; Tianjiao Chu; Dongmei Lei; Yanmin Du
Journal:  Dis Markers       Date:  2015-06-04       Impact factor: 3.434

7.  Classifications within molecular subtypes enables identification of BRCA1/BRCA2 mutation carriers by RNA tumor profiling.

Authors:  Martin J Larsen; Torben A Kruse; Qihua Tan; Anne-Vibeke Lænkholm; Martin Bak; Anne E Lykkesfeldt; Kristina P Sørensen; Thomas V O Hansen; Bent Ejlertsen; Anne-Marie Gerdes; Mads Thomassen
Journal:  PLoS One       Date:  2013-05-21       Impact factor: 3.240

8.  Tumour-infiltrating CD4-, CD8- and FOXP3-positive immune cells as predictive markers of mortality in BRCA1- and BRCA2-associated breast cancer.

Authors:  Nanna Jørgensen; Thomas Vauvert F Hviid; Lise B Nielsen; Ida M H Sønderstrup; Jens Ole Eriksen; Bent Ejlertsen; Anne-Marie Gerdes; Torben A Kruse; Mads Thomassen; Maj-Britt Jensen; Anne-Vibeke Lænkholm
Journal:  Br J Cancer       Date:  2021-08-07       Impact factor: 9.075

9.  Evaluation of BRCA1 and BRCA2 mutations and risk-prediction models in a typical Asian country (Malaysia) with a relatively low incidence of breast cancer.

Authors:  E Thirthagiri; S Y Lee; P Kang; D S Lee; G T Toh; S Selamat; S-Y Yoon; N A Mohd Taib; M K Thong; C H Yip; S H Teo
Journal:  Breast Cancer Res       Date:  2008-07-16       Impact factor: 6.466

10.  RNA profiling reveals familial aggregation of molecular subtypes in non-BRCA1/2 breast cancer families.

Authors:  Martin J Larsen; Mads Thomassen; Qihua Tan; Anne-Vibeke Lænkholm; Martin Bak; Kristina P Sørensen; Mette Klarskov Andersen; Torben A Kruse; Anne-Marie Gerdes
Journal:  BMC Med Genomics       Date:  2014-01-31       Impact factor: 3.063

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