Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma

Xin Hu, Emmanuel Martinez-Ledesma, Siyuan Zheng, Hoon Kim, Floris Barthel, Tao Jiang, Kenneth R. Hess, Roel G.W. Verhaak

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

Abstract

Background. Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category. Methods. We assembled gene expression profles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A frst cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profles. An elastic-net penalized Cox proportional hazards model was applied to build a classifer model through cross-validation within the training dataset. Results. The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed signifcantly different overall survival (P =.00058, log-rank test). For time-to-death events, the highrisk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confdence interval, 1.02-3.11). The signature was also signifcantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDHmutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be signifcantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas. Conclusion. We identifed a 35-gene signature that identifes high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratifcation.

Original languageEnglish (US)
Pages (from-to)786-795
Number of pages10
JournalNeuro-oncology
Volume19
Issue number6
DOIs
StatePublished - Jun 2017

Keywords

  • 1p/19q co-deletion
  • Glioma
  • Prognostic factor
  • elastic net Cox regression model

ASJC Scopus subject areas

  • Oncology
  • Clinical Neurology
  • Cancer Research

MD Anderson CCSG core facilities

  • Bioinformatics Shared Resource
  • Biostatistics Resource Group

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