Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes.

Guo X, Shi J, Cai Q, Shu XO, He J, Wen W, Allen J, Pharoah P, Dunning A, Hunter DJ, Kraft P, Easton DF, Zheng W, Long J
Hum Mol Genet. 2018 27 (5): 853-859

PMID: 29325031 · PMCID: PMC6454518 · DOI:10.1093/hmg/ddy005

Functional disruptions of susceptibility genes by large genomic structure variant (SV) deletions in germlines are known to be associated with cancer risk. However, few studies have been conducted to systematically search for SV deletions in breast cancer susceptibility genes. We analysed deep (> 30x) whole-genome sequencing (WGS) data generated in blood samples from 128 breast cancer patients of Asian and European descent with either a strong family history of breast cancer or early cancer onset disease. To identify SV deletions in known or suspected breast cancer susceptibility genes, we used multiple SV calling tools including Genome STRiP, Delly, Manta, BreakDancer and Pindel. SV deletions were detected by at least three of these bioinformatics tools in five genes. Specifically, we identified heterozygous deletions covering a fraction of the coding regions of BRCA1 (with approximately 80kb in two patients), and TP53 genes (with ∼1.6 kb in two patients), and of intronic regions (∼1 kb) of the PALB2 (one patient), PTEN (three patients) and RAD51C genes (one patient). We confirmed the presence of these deletions using real-time quantitative PCR (qPCR). Our study identified novel SV deletions in breast cancer susceptibility genes and the identification of such SV deletions may improve clinical testing.

MeSH Terms (13)

BRCA1 Protein Breast Neoplasms Fanconi Anemia Complementation Group N Protein Female Genetic Predisposition to Disease Genome, Human High-Throughput Nucleotide Sequencing Humans Membrane Proteins PTEN Phosphohydrolase Rad51 Recombinase Sequence Deletion Tumor Suppressor Protein p53

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