Imperial College London
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DR JAMES M. FLANAGAN

Faculty of Medicine, Department of Surgery & Cancer

Reader in Epigenetics
 
 
 
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Contact

 

+44 (0)20 7594 2127j.flanagan

 
 
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Location

 

Institute of Reproductive and Developmental BiologyHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Flower:2016:10.1080/15592294.2015.1111504,
author = {Flower, KJ and Shenker, NS and el-Bahrawy, M and Goldgar, DE and Parsons, MT and KConFab and AFFECT and Spurdle, AB and Morris, JR and Brown, R and Flanagan, JM},
doi = {10.1080/15592294.2015.1111504},
journal = {Epigenetics},
pages = {1121--1132},
title = {DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer},
url = {http://dx.doi.org/10.1080/15592294.2015.1111504},
volume = {10},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set).  Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity.
AU  - Flower,KJ
AU  - Shenker,NS
AU  - el-Bahrawy,M
AU  - Goldgar,DE
AU  - Parsons,MT
AU  - KConFab
AU  - AFFECT
AU  - Spurdle,AB
AU  - Morris,JR
AU  - Brown,R
AU  - Flanagan,JM
DO  - 10.1080/15592294.2015.1111504
EP  - 1132
PY  - 2016///
SN  - 1559-2308
SP  - 1121
TI  - DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer
T2  - Epigenetics
UR  - http://dx.doi.org/10.1080/15592294.2015.1111504
UR  - https://www.tandfonline.com/doi/full/10.1080/15592294.2015.1111504
UR  - http://hdl.handle.net/10044/1/27744
VL  - 10
ER  -
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