Identification and Characterization of Metastasis-Associated Individualized Gene Expression Signature in Osteosarcoma

Background: Osteosarcoma (OS) patients with surgical resection still relapse with poor prognosis due to the inability to detect distant metastasis. It’s essential to identify metastasis-related biomarkers for OS. Methods: Here, a computational pipeline follow relative expression orderings (REOs) using gene expression was constructed in metastases and non-metastases OS patients. Results: 138 metastasis-associated gene pair signatures (MGPSs) were identified follow two independent datasets. A metastases-specific co-expressed MGPS network was constructed for extracting biomarker for clinical application. MGPS such as MYL5 and RPL27A showed strong positive correlation (Cor =0.75, P <0.001). There were thirteen prognostic MGPSs in above network. These prognostic MGPSs could become as a specific classifier to distinguish metastases and non-metastases OS patients. MGPSs were associated with cancer metastasis-related functions. Drug and MGPS network could provide some drug candidates for treatment of OS. Conclusions: Collectively, the roles of the MGPSs in OS were elucidated, which could be beneficial for understanding OS pathogenesis and treatment.

Identification and characterization of metastasis-associated individualized gene expression signature in osteosarcoma

Introduction: Osteosarcoma (OS) patients with complete surgical resection still relapse with poor prognosis. Part of this is due to the inability to accurately detect distant metastasis. Thus it’s enssential to identify metastasis-related biomarkers for OS.Methods: In present study, a computational pipeline based on relative expression orderings (REOs) using gene expression proles was constructed in metastases and non-metastases OS patients. Results: 138 metastasis-associated gene pair signature (MGPS) were identified follow two independent datasets. In order to further extract metastasis-associated biomarker for clinical application, a metastases-specific co-expressed MGPS network was constructed and analyzed. MGPS such as MYL5 and RPL27A showed strong positive correlation (Cor =0.75, P <0.001) in metastatic OS patients. There were thirteen MGPSs in above network were associated with prognosis. These prognostic MGPSs could become as a specific classifier to distinguish metastases and non-metastases OS patients. Functional analysis showed MGPSs were associated with cancer metastasis-related functions. Drug and MGPS network could provide some drug candidates for treatment of OS. Conclusions: Collectively, the roles of the MGPSs in OS were elucidated, which could be beneficial for understanding OS pathogenesis and treatment.