Methylation-based reclassification and risk stratification of skull-base chordomas

  • Xulei Huo
  • , Tengxian Guo
  • , Ke Wang
  • , Bohan Yao
  • , Da Li
  • , Huan Li
  • , Wei Chen*
  • , Liang Wang*
  • , Zhen Wu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Skull-base chordomas are rare malignant bone cancers originating from the remnant of the notochord. Survival is variable, and clinical or molecular factors cannot reliably predict their outcomes. This study therefore identified epigenetic subtypes that defined new chordoma epigenetic profiles and their corresponding characteristics. Methods: Methylation profiles of 46 chordoma-resected neoplasms between 2008 and 2014, along with clinical information, were collected. K-means consensus clustering and principal component analysis were used to identify and validate the clusters. Single-sample gene set enrichment analysis, methylCIBERSORT algorithm, and copy number analysis were used to identify the characteristics of the clusters. Results: Unsupervised clustering analysis confirmed two clusters with a progression-free survival difference. Gene set enrichment analysis indicated that the early and late estrogen response pathways and the hypoxia pathway were activated whereas the inflammatory and interferon gamma responses were suppressed. Forty-six potential therapeutic targets corresponding to differentially methylated sites were identified from chordoma patients. Subgroups with a worse outcome were characterized by low immune cell infiltration, higher tumor purity, and higher stemness indices. Moreover, copy number amplifications mostly occurred in cluster 1 tumors and the high-risk group. Additionally, the presence of a CCNE1 deletion was exclusively found in the group of chordoma patients with better outcome, whereas RB1 and CDKN2A/2B deletions were mainly found in the group of chordoma patients with worse outcome. Conclusions: Chordoma prognostic epigenetic subtypes were identified, and their corresponding characteristics were found to be variable.

Original languageEnglish
Article number960005
JournalFrontiers in Oncology
Volume12
DOIs
StatePublished - 11 Nov 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • DNA methylation
  • copy number variation
  • infiltration immune level
  • prognostic biomarker
  • stemness indices

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