Spontaneous cancers in dogs and cats are an underused group of naturally occurring malignancies that share many features with human cancers such as osteosarcoma, prostate and breast cancers, non-Hodgkin's lymphoma, melanoma, soft tissue sarcoma, head and neck carcinoma, and virally induced lymphomas. Treatment of pet animals - primarily dogs - with naturally occurring cancer helps researchers better understand the biology of cancer and to improve the assessment of novel treatments for humans. The National Cancer Institute (NCI) Comparative Oncology Program has a collection of cancer tissue samples from dogs that span five different histologies (mast cell tumor, hemangiosarcoma, soft tissue sarcoma, pulmonary tumor, osteosarcoma, lymphoma, and melanoma) with anywhere from 100-500 patients (dogs) per histology. Each patient has tumor and normal tissue, serum, plasma, whole blood, and urine. All patients are enrolled while treatment-nave and have clinical outcome data. The biological material needs to be supplemented with transcriptomic data from RNA sequencing (RNA-Seq) experiments, which will provide information on underlying molecular level details associated with the various canine cancers. Additional bioinformatics analysis will add focused information on gene groups (modules), biochemical pathways, and controlling transcription factors relevant to each canine cancer state. Similar analysis on publically available human data will allow us to find gene modules common to both canine and human cancers. This comparative mechanism-based information then provides a means for identifying cancer diagnostic biomarkers and drug repurposing hypotheses that can be used to guide future validation experiments in canines and humans. This research will enable complete characterization of the common elements of five types of canine and human cancer in the form of transcription factors, the gene modules they control, and resultant biochemical pathways. This knowledge will support the generation of new hypotheses for drug repurposing, aid in the identification and validation of relevant cancer biomarkers, and increase the likelihood that the results of hypothesis testing in animals (dogs) will be predictive of what happens in humans.
|Grimm, Fabian A; Iwata, Yasuhiro; Sirenko, Oksana et al. (2016) A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives. Green Chem 18:4407-4419|