Immune cell deconvolution of bulk DNA methylation data reveals an association with methylation class, key somatic alterations, and cell state in glial/glioneuronal tumors

Acta Neuropathol Commun. 2021 Sep 8;9(1):148. doi: 10.1186/s40478-021-01249-9.

Abstract

It is recognized that the tumor microenvironment (TME) plays a critical role in the biology of cancer. To better understand the role of immune cell components in CNS tumors, we applied a deconvolution approach to bulk DNA methylation array data in a large set of newly profiled samples (n = 741) as well as samples from external data sources (n = 3311) of methylation-defined glial and glioneuronal tumors. Using the cell-type proportion data as input, we used dimensionality reduction to visualize sample-wise patterns that emerge from the cell type proportion estimations. In IDH-wildtype glioblastomas (n = 2,072), we identified distinct tumor clusters based on immune cell proportion and demonstrated an association with oncogenic alterations such as EGFR amplification and CDKN2A/B homozygous deletion. We also investigated the immune cluster-specific distribution of four malignant cellular states (AC-like, OPC-like, MES-like and NPC-like) in the IDH-wildtype cohort. We identified two major immune-based subgroups of IDH-mutant gliomas, which largely aligned with 1p/19q co-deletion status. Non-codeleted gliomas showed distinct proportions of a key genomic aberration (CDKN2A/B loss) among immune cell-based groups. We also observed significant positive correlations between monocyte proportion and expression of PD-L1 and PD-L2 (R = 0.54 and 0.68, respectively). Overall, the findings highlight specific roles of the TME in biology and classification of CNS tumors, where specific immune cell admixtures correlate with tumor types and genomic alterations.

Keywords: Deconvolution; Genomic aberrations; Immunotherapy; Tumor microenvironment.

Publication types

  • Research Support, N.I.H., Intramural

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / immunology*
  • Biomarkers, Tumor / metabolism
  • Brain Neoplasms / immunology*
  • Brain Neoplasms / metabolism
  • Brain Neoplasms / pathology
  • Cohort Studies
  • DNA Copy Number Variations / physiology
  • DNA Methylation / physiology*
  • Data Analysis
  • Glioma / genetics
  • Glioma / immunology*
  • Glioma / metabolism
  • Humans
  • Immunity, Cellular / physiology*
  • Monocytes / immunology
  • Monocytes / metabolism
  • Tumor Microenvironment / physiology*

Substances

  • Biomarkers, Tumor