1. Genomic profiling of canine mast cell tumors identifies DNA copy number aberrations associated with KIT mutations and high histological grade
- Author
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Rachael Thomas, Matthew Breen, Scott Moroff, and Hiroyuki Mochizuki
- Subjects
0301 basic medicine ,Mastocytosis, Cutaneous ,DNA Copy Number Variations ,Copy number analysis ,Biology ,Sensitivity and Specificity ,Genome ,DNA sequencing ,03 medical and health sciences ,Dogs ,Predictive Value of Tests ,Genetics ,medicine ,Animals ,Digital polymerase chain reaction ,Gene ,Comparative Genomic Hybridization ,Cancer ,medicine.disease ,Phenotype ,Proto-Oncogene Proteins c-kit ,030104 developmental biology ,Mutation ,Cancer research ,Comparative genomic hybridization - Abstract
Mast cell tumor (MCT) is the most common skin malignancy of domestic dogs and presents with a widely variable clinical behavior. Although activating KIT mutations are present in approximately 20% of canine MCTs, molecular etiology is largely unknown for the majority of this cancer. Characterization of genomic alterations in canine MCTs may identify genomic regions and/or genes responsible for their development and progression, facilitating the discovery of new therapeutic targets and improved clinical management of this heterogeneous cancer. We performed genome-wide DNA copy number analysis of 109 primary MCTs derived from three popular canine breeds (the Boxer, Labrador Retriever, and Pug) as well as nontarget breeds using oligonucleotide array comparative genomic hybridization (oaCGH). We demonstrated a stepwise accumulation of numerical DNA copy number aberrations (CNAs) as tumor grade increases. DNA sequencing analysis revealed that KIT mutations were found less frequently in the Pug tumors and were strongly associated with high histological grade. Tumors with KIT mutations showed genome-wide aberrant copy number profiles, with frequent CNAs involving genes in the p53 and RB pathways, whereas CNAs were very limited in tumors with wild-type KIT. We evaluated the presence of four CNAs to predict aggressive tumor phenotypes. This approach predicted aggressive tumors with a sensitivity of 78-94% and specificity of 88-93%, when using oaCGH and droplet digital PCR platforms. Further investigation of genome regions identified in this study may lead to the development of a molecular tool for classification and prognosis, as well as identification of therapeutic target molecules.
- Published
- 2017
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