NCI Data Jamboree (Project Abstract Submission): Submission #63

Presenter Information
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First Name: Avani
Middle Initial: {Empty}
Last Name: Patel
Degree(s): N.A.
Position/Title/Career Status: {Empty}
Organization: Animal Genome Institute
Organization Address:
Palmyra

Email: info@animalgenomeinstitute.org

Additional Authors
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List of Additional Authors:
- First Name: Yuka
  Last Name: Imamura
  Affiliation: Animal Genome Institute


Abstract Information
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Abstract Category: Employing statistical, computational, and informatics tools, algorithms, and methods to integrate or analyze data
Abstract Keywords: {Empty}
Abstract Title: Cross-Species Signature Scoring and Risk Assessment Modeling for Human and Canine Osteosarcoma
Abstract:
Osteosarcoma is a genetically complex malignancy. While human and canine osteosarcomas share significant molecular similarities, integrating datasets across species and sequencing platforms remains a technical challenge. Overcoming these hurdles is crucial for identifying conserved oncological targets and improving the AI-readiness of comparative genomic data for the broader research community. We aim to develop and validate a robust computational framework for cross-species data integration, specifically focusing on continuous signature scoring models for human and canine osteosarcoma. By utilizing publicly available human osteosarcoma datasets (such as TARGET-OS) and public canine cohorts (such as NCI's DOG² cohort), we will employ expression data scaling techniques, cross-platform normalization, and continuous signature scoring algorithms to harmonize the disparate matrices. Ultimately, we aim to leverage these validated models to develop a cross-species risk assessment application to support clinical decision-making.