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Background  Therapeutic outcomes of osteosarcoma treatment have not significantly improved in several decades. Therefore, strong prognostic biomarkers are urgently needed.    Methods  We first extracted the tRNA-derived small RNA (tsRNA) expression profiles of osteosarcoma from the GEO database. Then, we performed a unique module analysis and use the LASSO-Cox model to select survival-associated tsRNAs. Model effectiveness was further verified using an independent validation dataset. Target genes with selected tsRNAs were predicted using RNAhybrid.    Results  A LASSO-Cox model was established to select six prognostic tsRNA biomarkers: tRF-33-6SXMSL73VL4YDN, tRF-32-6SXMSL73VL4YK, tRF-32-M1M3WD8S746D2, tRF-35-RPM830MMUKLY5Z, tRF-33-K768WP9N1EWJDW, and tRF-32-MIF91SS2P46I3. We developed a prognostic panel for osteosarcoma patients concerning their overall survival by high-low risk. Patients with a low-risk profile had improved survival rates in training and validation dataset.    Conclusions  The suggested prognostic panel can be utilized as a reliable biomarker to predict osteosarcoma patient survival rates.

Development of a tRNA-Derived Small RNA Prognostic Panel and Their Potential Functions in Osteosarcoma