ABSTRACT
A genomic understanding of the oncogenic processes and individual variability of human cancer has steadily fueled improvement in patient outcomes over the past 20 years. Mutations within tumour tissues are routinely assessed through clinical genomic diagnostic assays by academic and commercial laboratories to facilitate diagnosis, prognosis and effective treatment stratification. The application of genomics has unveiled a wealth of mutation-based biomarkers in canine cancers, suggesting that the transformative principles that have revolutionized human cancer medicine can be brought to bear in veterinary oncology. To advance clinical genomics and genomics-guided medicine in canine oncology, we have developed and validated a canine cancer next-generation sequencing gene panel for the identification of multiple mutation types in clinical specimens. With this panel, we examined the genomic landscapes of 828 tumours from 813 dogs, spanning 53 cancer types. We identified 7856 alterations, encompassing copy number variants, single nucleotide variants, indels and internal tandem duplications. Additionally, we evaluated the clinical utility of these alterations by incorporating a biomarker framework from comprehensive curation of primary canine literature and inferences from human cancer genomic biomarker literature and clinical diagnostics. Remarkably, nearly 90% of the cases exhibited mutations with diagnostic, prognostic or therapeutic implications. Our work represents a thorough assessment of genomic landscapes in a large cohort of canine cancers, the first of its kind for its comprehensive inclusion of multiple mutation types and structured annotation of biomarkers, demonstrating the clinical potential of leveraging mutation-based biomarkers in veterinary oncology.
Subject(s)
Dog Diseases , Neoplasms , Dogs , Humans , Animals , Dog Diseases/genetics , Neoplasms/genetics , Neoplasms/veterinary , Genomics , Mutation , Biomarkers, Tumor/geneticsABSTRACT
While long-term survival rates for early-stage lung cancer are high, most cases are diagnosed in later stages that can negatively impact survival rates. We aim to design a simple, single biomarker blood test for early-stage lung cancer that is robust to preclinical variables and can be readily implemented in the clinic. Whole blood was collected in PAXgene tubes from a training set of 29 patients, and a validation set of 260 patients, of which samples from 58 patients were prospectively collected in a clinical trial specifically for our study. After RNA was extracted, the expressions of FPR1 and a reference gene were quantified by an automated one-step Taqman RT-PCR assay. Elevated levels of FPR1 mRNA in whole blood predicted lung cancer status with a sensitivity of 55% and a specificity of 87% on all validation specimens. The prospectively collected specimens had a significantly higher 68% sensitivity and 89% specificity. Results from patients with benign nodules were similar to healthy volunteers. No meaningful correlation was present between our test results and any clinical characteristic other than lung cancer diagnosis. FPR1 mRNA levels in whole blood can predict the presence of lung cancer. Using this as a reflex test for positive lung cancer screening computed tomography scans has the potential to increase the positive predictive value. This marker can be easily measured in an automated process utilizing off-the-shelf equipment and reagents. Further work is justified to explain the source of this biomarker.