Integrative metabolome and transcriptome profiling reveals discordant glycolysis process between osteosarcoma and normal osteoblastic cells

Osteosarcoma (OS) is the most common primary malignant tumor of bone in children and adolescents. However, few biomarkers of diagnostic significance have been established. In recent years, high-throughput transcriptomic and metabolomic approaches make it possible for studying the levels of thousands of biomarkers simultaneously. In this study, we integrated two disparate transcriptomic and metabolomic datasets to find meaningful biomarkers and then used an independent dataset to test the sensibility and specificity of these biomarkers. By using integrated two datasets, we discovered that the biomarkers involved in the glycolysis pathway are highly enriched, including 4 genes (ENO1, TPI1, PKG1 and LDHC) and 2 metabolites (lactate and pyruvate). The 4 genes were significantly down-regulated in OS samples as well as the 2 metabolites. The mixed metabolites + genes signature also outperformed metabolites or genes alone, with recall being 0.813 and F-measure being 0.812. And the AUC value of metabolites + genes classifier was 0.825 (compared to 0.58 for metabolites and 0.821 for genes alone). Our findings establish that integrated transcriptomic and metabolomic signature can be used to distinguish OS malignant with good diagnostic accuracy superior to other methods.