Large-Scale Comparative Analysis of Canine and Human Osteosarcomas Uncovers Conserved Clinically Relevant Tumor Microenvironment Subtypes

犬和人类骨肉瘤的大规模比较分析揭示了保守的临床相关肿瘤微环境亚型

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作者:Sushant Patkar, Joshua Mannheimer, Stephanie A Harmon, Christina J Ramirez, Christina N Mazcko, Peter L Choyke, Gregory Thomas Brown, Baris Turkbey, Amy K LeBlanc, Jessica A Beck

Conclusions

These findings demonstrate the potential of leveraging data from naturally occurring cancers in canines to model the complexity of the human osteosarcoma TME, offering a promising avenue for the discovery of novel biomarkers and developing more effective precision oncology treatments.

Purpose

Osteosarcoma is an aggressive bone cancer lacking robust biomarkers for personalized treatment. Despite its scarcity in humans, it is relatively common in adult pet dogs. This study aimed to analyze clinically annotated bulk tumor transcriptomic datasets of canine and patients with human osteosarcoma to identify potentially conserved patterns of disease progression. Experimental design: Bulk transcriptomic data from 245 pet dogs with treatment-naïve appendicular osteosarcoma were analyzed using deconvolution to characterize the tumor microenvironment (TME). The TME of both primary and metastatic tumors derived from the same dog was compared, and its impact on canine survival was assessed. A machine learning model was developed to classify the TME based on its inferred composition using canine tumor data. This model was applied to eight independent human osteosarcoma datasets to assess its generalizability and prognostic value.

Results

This study found three distinct TME subtypes of canine osteosarcoma based on cell type composition of bulk tumor samples: immune enriched, immune enriched dense extracellular matrix-like, and immune desert. These three TME-based subtypes of canine osteosarcomas were conserved in humans and could predict progression-free survival outcomes of human patients, independent of conventional prognostic factors such as percent tumor necrosis post standard of care chemotherapy treatment and disease stage at diagnosis. Conclusions: These findings demonstrate the potential of leveraging data from naturally occurring cancers in canines to model the complexity of the human osteosarcoma TME, offering a promising avenue for the discovery of novel biomarkers and developing more effective precision oncology treatments.

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