DNA methylation-based classifier for accurate molecular diagnosis of bone sarcomas Journal Article
| Authors: | Wu, S. P.; Cooper, B. T.; Bu, F.; Bowman, C. J.; Killian, J. K.; Serrano, J.; Wang, S.; Jackson, T. M.; Gorovets, D.; Shukla, N.; Meyers, P. A.; Pisapia, D. J.; Gorlick, R.; Ladanyi, M.; Thomas, K.; Snuderl, M.; Karajannis, M. A. |
| Article Title: | 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-wideDNAmethylation-based classifier to differentiate between osteosarcoma, Ewing sarcoma, and synovial sarcoma. Methods DNA methylation status of 482,421 CpG sites in 10 Ewing 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 synovial sarcoma, TARGET-Osteosarcoma, and a recently published series of Ewing sarcoma. Results Methylation profiling revealed three distinct patterns, each enriched with a single sarcoma subtype. Within the validation cohorts, all samples from The Cancer Genome Atlas were accurately classified as synovial sarcoma (10 of 10; sensitivity and specificity, 100%), all but one sample from TARGET-Osteosarcoma were classified as osteosarcoma (85 of 86; sensitivity, 98%; specificity, 100%), and 14 of 15 Ewing sarcoma samples were classified correctly (sensitivity, 93%; specificity, 100%). The single misclassified osteosarcoma sample demonstrated high EWSR1 and ETV1 expression on RNA sequencing, although no fusion was found on manual curation of the transcript sequence.Twoadditional clinical samples that were difficult to classify by morphology and molecular methods were classified as osteosarcoma; one had been suspected of being a synovial sarcoma and the other of being Ewing sarcoma on initial diagnosis. Conclusion Osteosarcoma, synovial sarcoma, and Ewing sarcoma have distinct epigenetic profiles. Our validated methylation-based classifier can be used to provide diagnostic assistance when histologic and standard techniques are inconclusive. © 2018 American Society of Clinical Oncology. |
| Keywords: | osteosarcoma; adolescent; adult; child; controlled study; human tissue; preschool child; school child; aged; middle aged; young adult; major clinical study; sequence analysis; diagnostic accuracy; sensitivity and specificity; gene; gene expression; genome-wide association study; validation study; dna methylation; ewing sarcoma; microarray analysis; epigenetics; cpg island; cancer tissue; synovial sarcoma; rna sequence; genetic database; molecular diagnosis; transcription factor er81; diagnostic test accuracy study; ewsr1 gene; classifier; machine learning; the cancer genome atlas; human; male; female; priority journal; article; random forest; clinical decision support system; etv1 gene |
| Journal Title: | JCO Precision Oncology |
| Volume: | 1 |
| ISSN: | 2473-4284 |
| Publisher: | American Society of Clinical Oncology |
| Date Published: | 2017-01-01 |
| Language: | English |
| DOI: | 10.1200/po.17.00031 |
| PROVIDER: | scopus |
| PMCID: | PMC5772901 |
| PUBMED: | 29354796 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 3 February 2020 -- Source: Scopus |
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141Karajannis -
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311Meyers -
159Shukla -
7Killian
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