Plasma microRNA signatures predict prognosis in canine osteosarcoma patients

Area of Science:

• Veterinary Oncology
• Molecular Diagnostics
• Canine Cancer Research

Background:

• Appendicular central osteosarcoma (OSA) in dogs is aggressive with a poor prognosis, often involving lung metastasis.
• Current prognostic methods for canine OSA, like histologic grading, have limitations in predicting clinical outcomes.
• MicroRNAs (miRNAs) are implicated in cancer and show potential for diagnosing and predicting canine OSA.

Purpose of the Study:

• To investigate the diagnostic and prognostic potential of multiple microRNAs (miRNAs) in canine osteosarcoma (OSA) using plasma samples.
• To evaluate single and multiple miRNA models, as well as multiple variable models, for predicting clinical outcomes in canine OSA.
• To identify specific miRNAs that can serve as reliable biomarkers for canine OSA diagnosis and prognosis.

Main Methods:

• Analysis of 56 miRNAs in plasma samples from three dog populations using real-time quantitative polymerase chain reaction.
• Development of decision tree and multiple variable models incorporating miRNA expression and clinical parameters.
• Comparison of predictive accuracy between single miRNA, multiple miRNA, and multiple variable models.

Main Results:

• MiR-214-3p showed increased expression in all canine OSA populations compared to controls and was a primary diagnostic indicator.
• High miR-214-3p expression alone predicted shorter overall survival and disease-free interval in canine OSA.
• Multiple miRNA models, especially those combining miR-214-3p with other miRNAs, demonstrated superior prediction of clinical outcomes compared to single miRNA or clinical variable models.

Conclusions:

• MiR-214-3p is a significant prognostic predictor in canine osteosarcoma plasma, consistent across multiple populations.
• Multi-miRNA models offer enhanced predictive accuracy for canine OSA outcomes compared to single miRNAs or traditional clinical variables.
• Plasma-based miRNA analysis presents a promising avenue for improving the diagnosis and prognosis of canine osteosarcoma.