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. RNA-Seq experiments on selected canine tissue samples from these tumor classes has been completed. Using bioinformatics analysis of the RNA-Seq data the team developed diagnostic biomarker hypotheses, identified important mechanistic genes, and proposed drug combination therapies specific to each tumor type. Ongoing comparative genome hybridization and resequencing experiments will determine the copy number and mutational status of the biomarker and mechanistic genes. Ongoing screening experiments will determine the activity of proposed drug combination therapies in canine cancer cell lines. Completed tissue proteomics experiments have shown that 56 out of the 72 proposed biomarkers genes code for proteins that are expressed in the cancer tissues. Furthermore the biomarker proteins show specificity to various tumor types. Ongoing blood proteomics experiments will determine if the protein expression and tumor selectivity carries over into the blood serum of the canines. Similar analyses are ongoing using publicly available human RNA-Seq data. Biomarkers, drug combinations, and important genes that are found to be consistent across both human and canine analyses will then have the highest chance of being successful in a potential clinical trial.
|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|