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Development of an exosomal gene signature to detect residual disease in dogs with osteosarcoma using a novel xenograft platform and machine learning [mouse data]

ABSTRACT: We developed a method using canine osteosarcoma in mouse xenografts to distinguish tumor-derived from host-response exosomal mRNAs. The model allows for the identification of canine osteosarcoma-specific gene signatures by RNA sequencing and a species-differentiating bioinformatics pipeline. An osteosarcoma-associated signature consisting of five gene transcripts was validated in dogs with osteosarcoma. Serum/plasma exosomes were isolated from 53 dogs in distinct clinical groups (“healthy”, “osteosarcoma”, “other bone tumor”, or “non-neoplastic disease”). Pre-treatment samples from osteosarcoma cases were used as the training set and a validation set from post-treatment samples was used for testing, classifying as “osteosarcoma–detected” or “osteosarcoma–NOT detected”. Dogs in a validation set whose post-treatment samples were classified as “osteosarcoma–NOT detected” had longer remissions, up to 15 months after treatment. In conclusion, we identified a gene signature predictive of molecular remissions with potential applications in the early detection and minimal residual disease settings. These results provide proof-of-concept for our discovery platform and its utilization in future studies to inform cancer risk, diagnosis, prognosis, and therapeutic response.

ORGANISM(S): Mus musculus

PROVIDER: GSE183190 | GEO | 2021/09/03

REPOSITORIES: GEO

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Project description:T-cells play a crucial role in canine immunoregulation and defence against invading pathogens. Proliferation is fundamental to T-cell differentiation, homeostasis and immune response. Initiation of proliferation following receptor mediated stimuli requires a temporally programmed gene response that can be identified as immediate-early, mid- and late phases. The immediate-early response genes in T-cell activation engage the cell cycle machinery and promote subsequent gene activation events. Genes involved in this immediate-early response in dogs are yet to be identified. The present study was undertaken to characterize the early T-cell gene response in dogs to improve understanding of the genetic mechanisms regulating immune function. Gene expression profiles were characterized using canine gene expression microarrays and quantitative reverse transcription PCR (qRT-PCR), and paired samples from eleven dogs. Significant functional annotation clusters were identified following stimulation with phytohemagluttinin (PHA) (5μg/ml), including the Toll-like receptor signaling pathway and phosphorylation pathways. Using strict statistical criteria, 13 individual genes were found to be differentially expressed, nine of which have ontologies that relate to proliferation and cell cycle control. These included, prostaglandin-endoperoxide synthase 2 (PTGS2/COX2), early growth response 1 (EGR1), growth arrest and DNA damage-inducible gene (GADD45B), phorbol-12-myristate-13-acetate-induced protein 1 (PMAIP1), V-FOS FBJ murine osteosarcoma viral oncogene homolog (FOS), early growth response 2 (EGR2), hemogen (HEMGN), polo-like kinase 2 (PLK2) and polo-like kinase 3 (PLK3). Differential gene expression was re-examined using qRT-PCR, which confirmed that EGR1, EGR2, PMAIP1, PTGS2, FOS and GADD45B were significantly upregulated in stimulated cells and ALAS2 downregulated. PTGS2 and EGR1 showed the highest levels of response in these dogs. Both of these genes are involved in cell cycle regulation. This study provides a comprehensive analysis of the early T-cell gene response to activation in dogs.

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Development of an exosomal gene signature to detect residual disease in dogs with osteosarcoma using a novel xenograft platform and machine learning [mouse data]

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