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Deregulation of microRNA (miRNA) transcript levels has been observed in many types of tumors including osteosarcoma. Molecular pathways regulated by differentially expressed miRNAs may contribute to the heterogeneous tumor behaviors observed in naturally occurring cancers. Thus, tumor-associated miRNA expression may provide informative biomarkers for disease outcome and metastatic potential in osteosarcoma patients. We showed previously that clusters of miRNAs at the 14q32 locus are downregulated in human osteosarcoma. Human and canine osteosarcoma patient's samples with clinical follow-up data were used in this study. We used bioinformatics and comparative genomics approaches to identify miRNA based prognostic biomarkers in osteosarcoma. Kaplan-Meier survival curves and Whitney Mann U tests were conducted for validating the statistical significance. Here we show that an inverse correlation exists between aggressive tumor behavior (increased metastatic potential and accelerated time to death) and the residual expression of 14q32 miRNAs (using miR-382 as a representative of 14q32 miRNAs) in a series of clinically annotated samples from human osteosarcoma patients. We also show a comparable decrease in expression of orthologous 14q32 miRNAs in canine osteosarcoma samples, with conservation of the inverse correlation between aggressive behavior and expression of orthologous miRNA miR-134 and miR-544. We conclude that downregulation of 14q32 miRNA expression is an evolutionarily conserved mechanism that contributes to the biological behavior of osteosarcoma, and that quantification of representative transcripts from this family, such as miR-382, miR-134, and miR-544, provide prognostic and predictive markers that can assist in the management of patients with this disease.
Bibliographical noteFunding Information:
This study was supported by grant P30 CA077598 from the National Cancer Institute, by a Faculty Research and Development grant from the University of Minnesota Academic Health Center, by a translational research grant from the Masonic Cancer Center, University of Minnesota, by grants from the Wyckoff Rein in Sarcoma and by grants 2254 and 947 from the AKC Canine Health Foundation to JFM and SS. The authors also wish to thank Drs. Reena Kartha, David Largaespada, Denis Clohisy and Jennie Walker for their support and helpful discussions. Finally, we wish to acknowledge the Minnesota Supercomputing Institute for providing access to computational resources.