In:
Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 111, No. 9 ( 2014-03-04), p. 3538-3543
Kurzfassung:
We hypothesized that key signaling pathways of glioma genesis might enable the molecular classification of gliomas. Gene coexpression modules around epidermal growth factor receptor ( EGFR ) (EM, 29 genes) or platelet derived growth factor receptor A ( PDGFRA ) (PM, 40 genes) in gliomas were identified. Based on EM and PM expression signatures, nonnegative matrix factorization reproducibly clustered 1,369 adult diffuse gliomas WHO grades II-IV from four independent databases generated in three continents, into the subtypes (EM, PM and EM low PM low gliomas) in a morphology-independent manner. Besides their distinct patterns of genomic alterations, EM gliomas were associated with higher age at diagnosis, poorer prognosis, and stronger expression of neural stem cell and astrogenesis genes. Both PM and EM low PM low gliomas were associated with younger age at diagnosis and better prognosis. PM gliomas were enriched in the expression of oligodendrogenesis genes, whereas EM low PM low gliomas were enriched in the signatures of mature neurons and oligodendrocytes. The EM/PM-based molecular classification scheme is applicable to adult low-grade and high-grade diffuse gliomas, and outperforms existing classification schemes in assigning diffuse gliomas to subtypes with distinct transcriptomic and genomic profiles. The majority of the EM/PM classifiers, including regulators of glial fate decisions, have not been extensively studied in glioma biology. Subsets of these classifiers were coexpressed in mouse glial precursor cells, and frequently amplified or lost in an EM/PM glioma subtype-specific manner, resulting in somatic copy number alteration-dependent gene expression that contributes to EM/PM signatures in glioma samples. EM/PM-based molecular classification provides a molecular diagnostic framework to expedite the search for new glioma therapeutic targets.
Materialart:
Online-Ressource
ISSN:
0027-8424
,
1091-6490
DOI:
10.1073/pnas.1313814111
Sprache:
Englisch
Verlag:
Proceedings of the National Academy of Sciences
Publikationsdatum:
2014
ZDB Id:
209104-5
ZDB Id:
1461794-8
SSG:
11
SSG:
12
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