Transcriptomic profiling in canines and humans reveals cancer specific gene modules and biological mechanisms common to both species

• Main Authors: Braisted, J. (Author), Breen, M. (Author), Gerhold, D. (Author), Grewal, G. (Author), LeBlanc, A.K (Author), Mazcko, C. (Author), Sittampalam, G. (Author), Tawa, G.J (Author)
• Format: Article
• Language: English
• Published: Public Library of Science 2021
• Subjects: animal; animal cell; animal tissue; Animals; Article; B cell lymphoma; BACE2 gene; bioinformatics; biology; Biomarkers, Tumor; Bone Neoplasms; bone tumor; cancer model; Canis; classification; clustering algorithm; COL12A1 gene; COL5A2 gene; COL6A3 gene; Computational Biology; controlled study; CTSH gene; data classification; dog; dog disease; Dog Diseases; Dogs; EDEM1 gene; epigenetics; gene; gene activation; gene expression profiling; Gene Expression Profiling; gene expression regulation; Gene Expression Regulation, Neoplastic; gene regulatory network; Gene Regulatory Networks; genetic association; genetics; GPNMB gene; human; Humans; JAK1 gene; k nearest neighbor; LPCAT1 gene; lung carcinoma; Lung Neoplasms; lung surfactant; lung tumor; Lymphoma, B-Cell; Lymphoma, T-Cell; melanogenesis; melanoma; Melanoma; molecular fingerprinting; molecular genetics; Molecular Sequence Annotation; Molecular Targeted Therapy; molecularly targeted therapy; NAPSA gene; neoplasm; Neoplasms; nonhuman; oncogene; Oncogenes; ossification; osteosarcoma; Osteosarcoma; PMEL gene; PTK2B gene; ribosome protein; RPL8 gene; RPLP0 gene; RPS7 gene; species difference; Species Specificity; T cell lymphoma; transcriptomics; Translational Medical Research; translational research; tumor gene; tumor marker; veterinary medicine
• Online Access: View Fulltext in Publisher

 Understanding relationships between spontaneous cancer in companion (pet) canines and humans can facilitate biomarker and drug development in both species. Towards this end we developed an experimental-bioinformatic protocol that analyzes canine transcriptomics data in the context of existing human data to evaluate comparative relevance of canine to human cancer. We used this protocol to characterize five canine cancers: melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, in 60 dogs. We applied an unsupervised, iterative clustering method that yielded five co-expression modules and found that each cancer exhibited a unique module expression profile. We constructed cancer models based on the co-expression modules and used the models to successfully classify the canine data. These canine-derived models also successfully classified human tumors representing the same cancers, indicating shared cancer biology between canines and humans. Annotation of the module genes identified cancer specific pathways relevant to cells-of-origin and tumor biology. For example, annotations associated with melanin production (PMEL, GPNMB, and BACE2), synthesis of bone material (COL5A2, COL6A3, and COL12A1), synthesis of pulmonary surfactant (CTSH, LPCAT1, and NAPSA), ribosomal proteins (RPL8, RPS7, and RPLP0), and epigenetic regulation (EDEM1, PTK2B, and JAK1) were unique to melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, respectively. In total, 152 biomarker candidates were selected from highly expressing modules for each cancer type. Many of these biomarker candidates are under-explored as drug discovery targets and warrant further study. The demonstrated transferability of classification models from canines to humans enforces the idea that tumor biology, biomarker targets, and associated therapeutics, discovered in canines, may translate to human medicine. Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.