Mapping the genomic landscape of canine lung cancers
Lung cancer is the lead cause of cancer mortality. While smoking is a common cause of lung cancer, about 30,000 never-smoker lung cancer (NS-LC) diagnoses are made each year in the U.S. NS-LC is relatively understudied and a great need exists for new NS-LC treatments and accelerated clinical trials. The canine is a powerful model for comparative oncology that can help meet the need for accelerated clinical trials of candidate treatments. Compared to transgenic mouse models in which tumors are artificially induced, canine cancers arise naturally and are histopathologically similar to human cancers. To better understand the role that dogs with naturally occurring lung cancer may play as a model NS-LC, we sought to characterize its genomic landscape. In order to chart this landscape, we have pursued a multi-platform approach that includes implementation of a novel, internally developed canine cancer amplicon panel (CCAP). The CCAP amplifies targeted regions of the canine genome that correspond to known somatic cancer mutation regions in humans and provides a rapid, affordable approach to sequencing potentially important cancer genes in dogs. Notably, the data revealed that nearly half (45%) of these tumors bore somatic ERBB2 V659E mutations. We also found mutations in TP53 and KRAS in 12.5% and 8.1% of the samples, respectively. EGFR, PIK2CA, FACD2, RB1, ATM, and PTEN each had a mutation frequency of 2.7%. I have now analyzed an additional 12 normal and matched lung tumors along with two canine tumor derived cell lines. Briefly, the extracted genomic DNA was amplified using the RainDance digital droplet PCR platform and next generation sequencing was performed on the Illumina MiSeq. The data generated was analyzed with an internally developed canine analysis pipeline for single nucleotide and copy number variations. By expanding the view of the canine lung cancer landscape, we may advance cancer treatment in both the human and canine.