Pediatric and Adolescent Osteosarcoma pp 459-465 | Cite as
Molecular Classification of Osteosarcoma
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Abstract
Genomic technologies are now being used to identify new molecular markers or signatures for both diagnostic and prognostic purposes. Recently, we reported the molecular classification of pediatric osteosarcoma by expression profiling in an attempt to identify a signature that could predict the chemoresistance of a tumor before treatment is initiated. We identified a 45-gene signature that discriminates between good and poor responders to chemotherapy in osteosarcoma. Using this classifier, we can predict with 100% accuracy the chemoresponse of osteosarcoma patients prior to the initiation of treatment. These encouraging results suggest that the genomic approach will revolutionize the diagnosis and prognostication of osteosarcoma patients and improve their outcome through predictive, personalized care.
Keywords
Support Vector Machine Linear Discriminant Analysis Resistant Cell Support Vector Machine Classifier Poor ResponderReferences
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