DNA Methylation-Based Classifier for Accurate Molecular Diagnosis of Bone Sarcomas.

Abstract

PURPOSE:

Pediatric sarcomas provide a unique diagnostic challenge. There is considerable morphologic overlap between entities, increasing the importance of molecular studies in the diagnosis, treatment, and identification of therapeutic targets. We developed and validated a genome-wide DNA methylation based classifier to differentiate between osteosarcoma, Ewing's sarcoma, and synovial sarcoma.

MATERIALS AND METHODS:

DNA methylation status of 482,421 CpG sites in 10 Ewing's sarcoma, 11 synovial sarcoma, and 15 osteosarcoma samples were determined using the Illumina Infinium HumanMethylation450 array. We developed a random forest classifier trained from the 400 most differentially methylated CpG sites within the training set of 36 sarcoma samples. This classifier was validated on data drawn from The Cancer Genome Atlas (TCGA) synovial sarcoma, TARGET Osteosarcoma, and a recently published series of Ewing's sarcoma.

RESULTS:

Methylation profiling revealed three distinct patterns, each enriched with a single sarcoma subtype. Within the validation cohorts, all samples from TCGA were accurately classified as synovial sarcoma (10/10, sensitivity and specificity 100%), all but one sample from TARGET-OS were classified as osteosarcoma (85/86, sensitivity 98%, specificity 100%) and 14/15 Ewing's sarcoma samples classified correctly (sensitivity 93%, specificity 100%). The single misclassified osteosarcoma sample demonstrated high EWSR1 and ETV1 expression on RNA-seq although no fusion was found on manual curation of the transcript sequence. Two additional clinical samples, that were difficult to classify by morphology and molecular methods, were classified as osteosarcoma when previously suspected to be a synovial sarcoma and Ewing's sarcoma on initial diagnosis, respectively.

CONCLUSION:

Osteosarcoma, synovial sarcoma, and Ewing's sarcoma have distinct epigenetic profiles. Our validated methylation-based classifier can be used to provide diagnostic assistance when histological and standard techniques are inconclusive.

• Authors: S Peter Wu, Benjamin T Cooper, Fang Bu, Christopher J Bowman, J Keith Killian, Jonathan Serrano, Shiyang Wang, Twana M Jackson, Daniel Gorovets, Neerav Shukla, Paul A Meyers, David J Pisapia, Richard Gorlick, Marc Ladanyi, Kristen Thomas, Matija Snuderl, Matthias A Karajannis
• Journal: JCO precision oncology (JCO Precis Oncol) Vol. 2017 ( 2017) ISSN: 2473-4284 [Print] United States
• PMID: 29354796 (Publication Type: Journal Article)