Detecting differential allelic expression using high-resolution melting curve analysis: Application to the breast cancer susceptibility gene CHEK2

Tú Nguyen-Dumont, Lars P. Jordheim, Jocelyne Michelon, Nathalie Forey, Sandrine McKay-Chopin, Olga Sinilnikova, Florence Le Calvez-Kelm, Melissa C. Southey, Sean V. Tavtigian, Fabienne Lesueur

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Abstract

Background: The gene CHEK2 encodes a checkpoint kinase playing a key role in the DNA damage pathway. Though CHEK2 has been identified as an intermediate breast cancer susceptibility gene, only a small proportion of high-risk families have been explained by genetic variants located in its coding region. Alteration in gene expression regulation provides a potential mechanism for generating disease susceptibility. The detection of differential allelic expression (DAE) represents a sensitive assay to direct the search for a functional sequence variant within the transcriptional regulatory elements of a candidate gene. We aimed to assess whether CHEK2 was subject to DAE in lymphoblastoid cell lines (LCLs) from high-risk breast cancer patients for whom no mutation in BRCA1 or BRCA2 had been identified. Methods. We implemented an assay based on high-resolution melting (HRM) curve analysis and developed an analysis tool for DAE assessment. Results: We observed allelic expression imbalance in 4 of the 41 LCLs examined. All four were carriers of the truncating mutation 1100delC. We confirmed previous findings that this mutation induces non-sense mediated mRNA decay. In our series, we ruled out the possibility of a functional sequence variant located in the promoter region or in a regulatory element of CHEK2 that would lead to DAE in the transcriptional regulatory milieu of freely proliferating LCLs. Conclusions: Our results support that HRM is a sensitive and accurate method for DAE assessment. This approach would be of great interest for high-throughput mutation screening projects aiming to identify genes carrying functional regulatory polymorphisms.

Original languageEnglish
Article number39
Number of pages10
JournalBMC Medical Genomics
Volume4
DOIs
Publication statusPublished - 2011
Externally publishedYes

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