LAUSR

11034Background: Bone sarcomas present a unique diagnostic challenge because of the considerable morphologic overlap between different entities. The choice of optimal treatment, however, is dependent upon accurate diagnosis. Genome-wide DNA methylation profiling has emerged as a new approach to aid in the diagnosis of brain tumors, with diagnostic accuracy exceeding standard histopathology. In this work we developed and validated a methylation based classifier to differentiate between osteosarcoma, Ewing’s sarcoma, and synovial sarcoma. Methods: DNA methylation status of 482,421 CpG sites in 15 osteosarcoma, 10 Ewing’s sarcoma, and 11 synovial sarcoma samples were measured using the Illumina HumanMethylation450 array. From this training set of 36 samples we developed a random forest classifier using the 400 most differentially methylated CpG sites (FDR q value < 0.001). This classifier was then validated on 10 synovial sarcoma samples from TCGA, 86 osteosarcoma samples from TARGET-OS, and 15 Ewing’s sarco...