Literature DB >> 16818684

Accurate prediction of BRCA1 and BRCA2 heterozygous genotype using expression profiling after induced DNA damage.

Zsofia Kote-Jarai1, Lucy Matthews, Ana Osorio, Susan Shanley, Ian Giddings, Francois Moreews, Imogen Locke, D Gareth Evans, Diana Eccles, Richard D Williams, Mark Girolami, Colin Campbell, Ros Eeles.   

Abstract

PURPOSE: In this study, the differential gene expression changes following radiation-induced DNA damage in healthy cells from BRCA1/BRCA1 mutation carriers have been compared with controls using high-density microarray technology. We aimed to establish if BRCA1/BRCA2 mutation carriers could be distinguished from noncarriers based on expression profiling of normal cells. EXPERIMENTAL
DESIGN: Short-term primary fibroblast cultures were established from skin biopsies from 10 BRCA1 and 10 BRCA2 mutation carriers and 10 controls, all of whom had previously had breast cancer. The cells were subjected to 15 Gy ionizing irradiation to induce DNA damage. RNA was extracted from all cell cultures, preirradiation and at 1 hour postirradiation. For expression profiling, 15 K spotted cDNA microarrays manufactured by the Cancer Research UK DNA Microarray Facility were used. Statistical feature selection was used with a support vector machine (SVM) classifier to determine the best feature set for predicting BRCA1 or BRCA2 heterozygous genotype. To investigate prediction accuracy, a nonprobabilistic classifier (SVM) and a probabilistic Gaussian process classifier were used.
RESULTS: In the task of distinguishing BRCA1 and BRCA2 mutation carriers from noncarriers and from each other following radiation-induced DNA damage, the SVM achieved 90%, and the Gaussian process classifier achieved 100% accuracy. This effect could not be achieved without irradiation. In addition, the SVM identified a set of BRCA genotype predictor genes.
CONCLUSIONS: We conclude that after irradiation-induced DNA damage, BRCA1 and BRCA2 mutation carrier cells have a distinctive expression phenotype, and this may have a future role in predicting genotypes, with application to clinical detection and classification of mutations.

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Year:  2006        PMID: 16818684     DOI: 10.1158/1078-0432.CCR-05-2805

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  11 in total

1.  High-resolution proteome/peptidome analysis of peptides and low-molecular-weight proteins in urine.

Authors:  Harald Mischak; Bruce A Julian; Jan Novak
Journal:  Proteomics Clin Appl       Date:  2007-07-10       Impact factor: 3.494

Review 2.  A guide for functional analysis of BRCA1 variants of uncertain significance.

Authors:  Gaël A Millot; Marcelo A Carvalho; Sandrine M Caputo; Maaike P G Vreeswijk; Melissa A Brown; Michelle Webb; Etienne Rouleau; Susan L Neuhausen; Thomas v O Hansen; Alvaro Galli; Rita D Brandão; Marinus J Blok; Aneliya Velkova; Fergus J Couch; Alvaro N A Monteiro
Journal:  Hum Mutat       Date:  2012-07-16       Impact factor: 4.878

Review 3.  Functional assays for analysis of variants of uncertain significance in BRCA2.

Authors:  Lucia Guidugli; Aura Carreira; Sandrine M Caputo; Asa Ehlen; Alvaro Galli; Alvaro N A Monteiro; Susan L Neuhausen; Thomas V O Hansen; Fergus J Couch; Maaike P G Vreeswijk
Journal:  Hum Mutat       Date:  2013-12-03       Impact factor: 4.878

4.  Use of DNA-damaging agents and RNA pooling to assess expression profiles associated with BRCA1 and BRCA2 mutation status in familial breast cancer patients.

Authors:  Logan C Walker; Bryony A Thompson; Nic Waddell; Sean M Grimmond; Amanda B Spurdle
Journal:  PLoS Genet       Date:  2010-02-19       Impact factor: 5.917

5.  DepthTools: an R package for a robust analysis of gene expression data.

Authors:  Aurora Torrente; Sara López-Pintado; Juan Romo
Journal:  BMC Bioinformatics       Date:  2013-07-25       Impact factor: 3.169

6.  BRCA1 haploinsufficiency leads to altered expression of genes involved in cellular proliferation and development.

Authors:  Harriet E Feilotter; Claire Michel; Paolo Uy; Lauren Bathurst; Scott Davey
Journal:  PLoS One       Date:  2014-06-20       Impact factor: 3.240

7.  Genomic profiling of breast tumours in relation to BRCA abnormalities and phenotypes.

Authors:  Olafur Andri Stefansson; Jon Gunnlaugur Jonasson; Oskar Thor Johannsson; Kristrun Olafsdottir; Margret Steinarsdottir; Sigridur Valgeirsdottir; Jorunn Erla Eyfjord
Journal:  Breast Cancer Res       Date:  2009-07-09       Impact factor: 6.466

8.  Use of gene expression profiles of peripheral blood lymphocytes to distinguish BRCA1 mutation carriers in high risk breast cancer families.

Authors:  Marie-Laure Vuillaume; Nancy Uhrhammer; Véronique Vidal; Valérie Sylvain Vidal; Valérie Chabaud; Beline Jesson; Fabrice Kwiatkowski; Yves-Jean Bignon
Journal:  Cancer Inform       Date:  2009-03-02

9.  BRCA1 and BRCA2 missense variants of high and low clinical significance influence lymphoblastoid cell line post-irradiation gene expression.

Authors:  Nic Waddell; Anette Ten Haaf; Anna Marsh; Julie Johnson; Logan C Walker; Milena Gongora; Melissa Brown; Piyush Grover; Mark Girolami; Sean Grimmond; Georgia Chenevix-Trench; Amanda B Spurdle
Journal:  PLoS Genet       Date:  2008-05-23       Impact factor: 5.917

10.  A BRCA1 deficient-like signature is enriched in breast cancer brain metastases and predicts DNA damage-induced poly (ADP-ribose) polymerase inhibitor sensitivity.

Authors:  Ryan P McMullin; Ben S Wittner; Chuanwei Yang; Benjamin R Denton-Schneider; Daniel Hicks; Raj Singavarapu; Sharon Moulis; Jeongeun Lee; Mohammad R Akbari; Steven A Narod; Kenneth D Aldape; Patricia S Steeg; Sridhar Ramaswamy; Dennis C Sgroi
Journal:  Breast Cancer Res       Date:  2014-03-14       Impact factor: 6.466

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