Early identification of chemoresistant patients for improved risk-based therapy in pediatric osteosarcoma

Osteosarcoma is the most common malignant bone tumor in children. The survival rate for patients with resistance to standard chemotherapy is about 40%. The poor prognosis of chemoresistant patients indicates that new paradigms are needed to identify those patients up front, so that new treatment options can be offered initially to improve their outcome. Using a proteomic approach, we have identified two circulating biomarkers that are significantly correlated with chemoresistance. In this proposal, we plan to validate these two chemoresistant biomarkers and construct a bioinformatic model to identify chemoresistant osteosarcoma patients at initial diagnosis using sera collected in a national collaborative study.