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Review
. 2019 Jul;15(7):405-417.
doi: 10.1038/s41582-019-0220-2. Epub 2019 Jun 21.

Genetic and molecular epidemiology of adult diffuse glioma

Annette M Molinaro  1   2 , Jennie W Taylor  3   4 , John K Wiencke  3   5 , Margaret R Wrensch  3   6   5
Affiliations
Review

Genetic and molecular epidemiology of adult diffuse glioma

Annette M Molinaro et al. Nat Rev Neurol. 2019 Jul.

Abstract

The WHO 2007 glioma classification system (based primarily on tumour histology) resulted in considerable interobserver variability and substantial variation in patient survival within grades. Furthermore, few risk factors for glioma were known. Discoveries over the past decade have deepened our understanding of the molecular alterations underlying glioma and have led to the identification of numerous genetic risk factors. The advances in molecular characterization of glioma have reframed our understanding of its biology and led to the development of a new classification system for glioma. The WHO 2016 classification system comprises five glioma subtypes, categorized by both tumour morphology and molecular genetic information, which led to reduced misclassification and improved consistency of outcomes within glioma subtypes. To date, 25 risk loci for glioma have been identified and several rare inherited mutations that might cause glioma in some families have been discovered. This Review focuses on the two dominant trends in glioma science: the characterization of diagnostic and prognostic tumour markers and the identification of genetic and other risk factors. An overview of the many challenges still facing glioma researchers is also included.

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Conflict of interest statement

Competing interests

The authors declare no competing interests.

Figures

Figure 1.
Figure 1.. Overview of key molecular subtypes in the WHO 2016 classification of newly diagnosed adult diffuse glioma.
a | Histological assessment integrated with molecular diagnosis based on IDH mutation and 1p19q co-deletion status defines the five subtypes of adult diffuse glioma included in the WHO 2016 classification,. Kaplan–Meier survival curves for each type are based on data from 1989–2012. b | For each WHO 2016 disease subtype, telomerase-related mutation frequencies are depicted in pie charts showing the proportion of tumours with mutations in TERT and/or ATRX (green, TERT mutations only; blue, ATRX mutations only; purple, mutations in both TERT and ATRX; light blue, wild type TERT and wild type ATRX). Waffle plots show the relative proportions of IDH-mutant, TERT-mutant and 1p19q co-deleted tumours in each WHO 2016 disease subtype. c | Graphs showing methylation classifications for each WHO 2016 subtype. The methylation categories depicted overlap to a great extent with those identified in a subsequent study (pink, LGm1 and A IDH HG; purple, LGm2 and A IDH; light blue, LGm3 and O IDH; black, LGm4 and GBM RTK II; gray, LGm5 and GBM MES/GBM RTK I; brown-grey, LGm6 and DMG K27/GBM MID/GBM MYCN). WHO 2016 classification from REFS.,. Survival data and telomerase mutation data from REF. with additional mutation data from REF.. Methylation profile data from REFS.,.
Figure 2.
Figure 2.. Annual average age-adjusted incidence and relative survival data for non-glioblastoma and glioblastoma CNS tumours.
The Central Brain Tumor Registry of the United States (CBTRUS) and other global reporting registries have not yet published glioma statistics based on the WHO 2016 classification system. Accordingly, this Figure presents the latest available published CBTRUS statistics from 2011–2015 as well as data accessed directly from CBTRUS, both based on the WHO 2007 classification system. Data from REF. Note that different axes are used for incidences of glioblastoma versus the other types of glioma.
Figure 3
Figure 3. Heritable germline risk factors for the WHO 2016 subtypes of adult glioma.
Summary of the relationship between heritable germline risk factors and WHO 2016 classification. Overlapping boxes contain alterations shared by different diffuse glioma tumour subtypes. Involved genes are known to be relevant to the indicated biological pathways, but with a few exceptions the functional consequences of individual single-nucleotide polymorphisms (SNPs) are unknown. SNPs and gene names in bold were strongly associated with more than one WHO 2016 glioma subgroup in multivariant analyses. Data from REFS.,.
Figure 4
Figure 4. Hypothesized pathways of glioma development.
Our current understanding of gliomagenesis involves an interplay of inherited risk variants and acquired alterations. Additional SNPs associated with glioma not included in the figure are: 1p31 (RAVER2); 10q25 (VTI1A); 11q14 (11p14); 16p13 (near MPG); and 16p13 (LMF1). Data from REFS.,,,,.
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