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PMID: 14583454 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

Cancer research ·Vol. 63 ·No. 20 ·2003-10-15 ·Pages 6613-25

Godard S, Getz G, Delorenzi M, Farmer P, Kobayashi H, Desbaillets I, Nozaki M, Diserens AC, Hamou MF, Dietrich PY, Regli L, Janzer RC, Bucher P, Stupp R, de Tribolet N, Domany E, Hegi ME

Abstract

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

MeSH Terms
Adolescent Adult Aged Astrocytoma/blood supply,genetics,metabolism,pathology Brain Neoplasms/blood supply,genetics,metabolism,pathology Cell Hypoxia/physiology Child, Preschool Female Gene Expression Profiling Gene Expression Regulation, Neoplastic Glioblastoma/genetics,metabolism,pathology Humans Insulin-Like Growth Factor Binding Protein 2/biosynthesis,genetics Male Middle Aged Multigene Family Neovascularization, Pathologic/genetics Oligonucleotide Array Sequence Analysis Reproducibility of Results
Chemicals
Insulin-Like Growth Factor Binding Protein 2
Authors & Affiliations
17 authors, click to expand affiliations / ORCID
Godard Sophie
Laboratory of Tumor Biology and Genetics,University Hospital (CHUV), 1011 Lausanne, Switzerland.
Getz Gad
Delorenzi Mauro
Farmer Pierre
Kobayashi Hiroyuki
Desbaillets Isabelle
Nozaki Michimasa
Diserens Annie-Claire
Hamou Marie-France
Dietrich Pierre-Yves
Regli Luca
Janzer Robert C
Bucher Philipp
Stupp Roger
de Tribolet Nicolas
Domany Eytan
Hegi Monika E
Article Info
Journal
Cancer research
Abbr.
Cancer Res
ISSN
0008-5472
Published
2003-10-15
Pages
6613-25
Language
English
Region
United States
NLM ID
2984705R
Subset
IM
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