Models of epigenetic age capture patterns of DNA methylation in glioma associated with molecular subtype, survival, and recurrence.

Journal Article (Journal Article)

Background: Models of epigenetic aging (epigenetic clocks) have been implicated as potentially useful markers for cancer risk and prognosis. Using 2 previously published methods for modeling epigenetic age, Horvath's clock and epiTOC, we investigated epigenetic aging patterns related to World Health Organization grade and molecular subtype as well as associations of epigenetic aging with glioma survival and recurrence. Methods: Epigenetic ages were calculated using Horvath's clock and epiTOC on 516 lower-grade glioma and 141 glioblastoma cases along with 136 nontumor (normal) brain samples. Associations of tumor epigenetic age with patient chronological age at diagnosis were assessed with correlation and linear regression, and associations were validated in an independent cohort of 203 gliomas. Contribution of epigenetic age to survival prediction was assessed using Cox proportional hazards modeling. Sixty-three samples from 18 patients with primary-recurrent glioma pairs were also analyzed and epigenetic age difference and rate of epigenetic aging of primary-recurrent tumors were correlated to time to recurrence. Results: Epigenetic ages of gliomas were near-universally accelerated using both Horvath's clock and epiTOC compared with normal tissue. The 2 independent models of epigenetic aging were highly associated with each other and exhibited distinct aging patterns reflective of molecular subtype. EpiTOC was found to be a significant independent predictor of survival. Epigenetic aging of gliomas between primary and recurrent tumors was found to be highly variable and not significantly associated with time to recurrence. Conclusions: We demonstrate that epigenetic aging reflects coherent modifications of the epigenome and can potentially provide additional prognostic power for gliomas.

Full Text

Duke Authors

Cited Authors

  • Liao, P; Ostrom, QT; Stetson, L; Barnholtz-Sloan, JS

Published Date

  • June 18, 2018

Published In

Volume / Issue

  • 20 / 7

Start / End Page

  • 942 - 953

PubMed ID

  • 29432558

Pubmed Central ID

  • PMC6007761

Electronic International Standard Serial Number (EISSN)

  • 1523-5866

Digital Object Identifier (DOI)

  • 10.1093/neuonc/noy003

Language

  • eng

Conference Location

  • England