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

Abstract

Abstract 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.