Abstract PR01: A DNA methylation-based classifier for accurate molecular diagnosis of bone sarcomas
Authors: Shengyang Wu, Benjamin Cooper, Fang Bu, Christopher Bowman, Jonathan K. Killian, Shiyang Wang, Twana Jackson, Daniel Gorovets, Richard Gorlick, Kristen Thomas, Matthias Karajannis, Matija Snuderl
Journal: Clinical Cancer Research (2018)

Abstract Background: 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 sarcoma samples we developed a random forest classifier from the 400 most differentially methylated CpG sites (FDR q value &amp;lt;0.001). This classifier was then validated on 10 synovial sarcoma samples from The Cancer Genome Atlas (TCGA), 86 osteosarcoma samples from TARGET-OS, and 15 Ewing's sarcoma from a recently published series. (Huertas-Martinez et al., Cancer Lett 2016) Results: Methylation profiling revealed three distinct molecular clusters, 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 all but one sample from the Ewing's sarcoma series was classified as Ewing's (14/15, sensitivity 93%, specificity 100%). The single misclassified osteosarcoma sample was classified as a Ewing's sarcoma, and later determined to be a misdiagnosed Ewing's sarcoma based on RNA-seq data demonstrating high EWRS1 and ETV1 expression. An additional clinical sample that was misdiagnosed as a synovial sarcoma based on initial histopathology was accurately recognized as osteosarcoma by the methylation classifier. Pathway analysis with MSigDB (Broad Institute) identified targets of polycomb group proteins SUZ12 and EED, possessing the H3K27 trimethylated mark, as highly enriched within classifier genes Conclusions: Osteosarcoma, Ewing's sarcoma, and synovial sarcoma have distinct epigenetic profiles. Our validated methylation-based classifier provides increased diagnostic accuracy, including in cases where standard histopathology is inconclusive. This abstract is also being presented as Poster A01. Citation Format: Shengyang Wu, Benjamin Cooper, Fang Bu, Christopher Bowman, Jonathan K. Killian, Shiyang Wang, Twana Jackson, Daniel Gorovets, Richard Gorlick, Kristen Thomas, Matthias Karajannis, Matija Snuderl. A DNA methylation-based classifier for accurate molecular diagnosis of bone sarcomas [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr PR01.