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Identifying Gene Disruptions in Novel Balanced de novo Constitutional Translocations in Childhood Cancer Patients by Whole Genome Sequencing

PURPOSE: We applied whole genome sequencing to children diagnosed with neoplasms and found to carry apparently balanced constitutional translocations, to discover novel genic disruptions. METHODS: We applied SV calling programs CREST, Break Dancer, SV-STAT and CGAP-CNV, and developed an annotative f...

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Detalles Bibliográficos
Autores principales: Ritter, Deborah I., Haines, Katherine, Cheung, Hannah, Davis, Caleb F., Lau, Ching C., Berg, Jonathan S., Brown, Chester W., Thompson, Patrick A., Gibbs, Richard, Wheeler, David A., Plon, Sharon E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4496310/
https://www.ncbi.nlm.nih.gov/pubmed/25569436
http://dx.doi.org/10.1038/gim.2014.189
Descripción
Sumario:PURPOSE: We applied whole genome sequencing to children diagnosed with neoplasms and found to carry apparently balanced constitutional translocations, to discover novel genic disruptions. METHODS: We applied SV calling programs CREST, Break Dancer, SV-STAT and CGAP-CNV, and developed an annotative filtering strategy to achieve nucleotide resolution at the translocations. RESULTS: We identified the breakpoints for t(6;12) (p21.1;q24.31) disrupting HNF1A in a patient diagnosed with hepatic adenomas and Maturity Onset Diabetes of the Young (MODY). Translocation as the disruptive event of HNF1A, a gene known to be involved in MODY3, has not been previously reported. In a subject with Hodgkin’s lymphoma and subsequent low-grade glioma, we identified t(5;18) (q35.1;q21.2), disrupting both SLIT3 and DCC, genes previously implicated in both glioma and lymphoma. CONCLUSIONS: These examples suggest that implementing clinical whole genome sequencing in the diagnostic work-up of patients with novel but apparently balanced translocations may reveal unanticipated disruption of disease-associated genes and aid in prediction of the clinical phenotype.