4.6 Article

DNA methylation-based prognostic subtypes of chordoma tumors in tissue and plasma

Journal

NEURO-ONCOLOGY
Volume 24, Issue 3, Pages 442-454

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/neuonc/noab235

Keywords

bone cancer; central nervous system cancer; DNA methylation analysis; noninvasive diagnosis; prognostic biomarkers

Funding

  1. Canadian Institute of Health Research Canada Graduate Scholarship Doctoral Award
  2. Strategic Training in Transdisciplinary Radiation Science for the 21st Century Program Scholarship
  3. Princess Margaret Cancer Foundation PostDoctoral Fellowship Award
  4. Canadian Institute of Health Research New Investigator salary award [201512MSH360794-228629]
  5. Princess Margaret Cancer Foundation
  6. Canada Research Chair
  7. Canadian Institute of Health Research Foundation Grant [FDN 148430]
  8. Canadian Institute of Health Research Project Grant [PJT 165986]
  9. Natural Sciences and Engineering Research Council of Canada [489073]
  10. Terry Fox Research Institute Program Projects Grant [1106]
  11. Ontario Institute for Cancer Research (Province of Ontario)
  12. Canadian Cancer Society Operating Grant [706135]

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This study identifies prognostic epigenetic chordoma subtypes using plasma methylomes and may transform patient management by balancing treatment aggressiveness with patient risk according to prognosis. Plasma methylomes can distinguish chordomas from other clinical diagnoses and accurately classify tumors based on plasma methylation data.
Background Chordomas are rare malignant bone cancers of the skull-base and spine. Patient survival is variable and not reliably predicted using clinical factors or molecular features. This study identifies prognostic epigenetic chordoma subtypes that are detected noninvasively using plasma methylomes. Methods Methylation profiles of 68 chordoma surgical samples were obtained between 1996 and 2018 across three international centers along with matched plasma methylomes where available. Results Consensus clustering identified two stable tissue clusters with a disease-specific survival difference that was independent of clinical factors in a multivariate Cox analysis (HR = 14.2, 95%CI: 2.1-94.8, P = 0.0063). Immune-related pathways with genes hypomethylated at promoters and increased immune cell abundance were observed in the poor-performing Immune-infiltrated subtype. Cell-to-cell interaction plus extracellular matrix pathway hypomethylation and higher tumor purity were observed in the better-performing Cellular subtype. The findings were validated in additional DNA methylation and RNA sequencing datasets as well as with immunohistochemical staining. Plasma methylomes distinguished chordomas from other clinical differential diagnoses by applying fifty chordoma-versus-other binomial generalized linear models in random 20% testing sets (mean AUROC = 0.84, 95%CI: 0.52-1.00). Tissue-based and plasma-based methylation signals were highly correlated in both prognostic clusters. Additionally, leave-one-out models accurately classified all tumors into their correct cluster based on plasma methylation data. Conclusions Here, we show the first identification of prognostic epigenetic chordoma subtypes and first use of plasma methylome-based biomarkers to noninvasively diagnose and subtype chordomas. These results may transform patient management by allowing treatment aggressiveness to be balanced with patient risk according to prognosis.

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