Identifying Candidate Druggable Targets in Canine Cancer Cell Lines Using Whole-Exome Sequencing.

Mol Cancer Ther

Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado.

Published: August 2019

Cancer cell culture has been a backbone in cancer research, in which analysis of human cell line mutational profiles often correlates with oncogene addiction and drug sensitivity. We have conducted whole-exome sequence analyses on 33 canine cancer cell lines from 10 cancer types to identify somatic variants that contribute to pathogenesis and therapeutic sensitivity. A total of 66,344 somatic variants were identified. Mutational load ranged from 15.79 to 129.37 per Mb, and 13.2% of variants were located in protein-coding regions (PCR) of 5,085 genes. PCR somatic variants were identified in 232 genes listed in the Cancer Gene Census (COSMIC). Cross-referencing variants with human driving mutations on cBioPortal identified 61 variants as candidate cancer drivers in 30 cell lines. The most frequently mutated cancer driver was TP53 (15 mutations in 12 cell lines). No drivers were identified in three cell lines. We identified 501 non-COSMIC genes with PCR variants that functionally annotate with COSMIC genes. These genes frequently mapped to the KEGG MAPK and PI3K-AKT pathways. We evaluated the cell lines for ERK1/2 and AKT(S473) phosphorylation and sensitivity to the MEK1/2 inhibitor, trametinib. Twelve of the 33 cell lines were trametinib-sensitive (IC < 32 nmol/L), all 12 exhibited constitutive or serum-activated ERK1/2 phosphorylation, and 8 carried MAPK pathway cancer driver variants: NF1(2), BRAF(3), N/KRAS(3). This functionally annotated database of canine cell line variants will inform hypothesis-driven preclinical research to support the use of companion animals in clinical trials to test novel combination therapies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679748PMC
http://dx.doi.org/10.1158/1535-7163.MCT-18-1346DOI Listing

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