Gene Expression Profile of Glioblastoma Multiforme Invasive Phenotype Points to New Therapeutic Targets

Abstract

The invasive phenotype of glioblastoma multiforme (GBM) is a hallmark of malignant process, yet molecular mechanisms that dictate this locally invasive behavior remain poorly understood. Gene expression profiles of human glioma cells were assessed from laser capture-microdissected GBM cells collected from paired patient tumor cores and white matter-invading cell populations. Changes in gene expression in invading GBM cells were validated by quantitative reverse transcription polymerase chain reaction (QRT-PCR) and immunohistochemistry in an independent sample set. QRT-PCR confirmed the differential expression in 19 of 21 genes tested. Immunohistochemical analyses of autotaxin (ATX), ephrin B3, B-cell lymphoma-w (BCLW), and protein tyrosine kinase 2 beta showed them to be expressed in invasive glioma cells. The known GBM markers, insulin-like growth factor binding protein 2 and vimentin, were robustly expressed in the tumor core. A glioma invasion tissue microarray confirmed the expression of ATX and BCLW in invasive cells of tumors of various grades. GBM phenotypic and genotypic heterogeneity is well documented. In this study, we show an additional layer of complexity: transcriptional differences between cells of tumor core and invasive cells located in the brain parenchyma. Gene products supporting invasion may be novel targets for manipulation of brain tumor behavior with consequences on treatment outcome.

Identification of expressed genes characterizing long-term survival in malignant glioma patients

“…Several works (Sallinen et al, 2000;Khan et al, 2001;Ramaswamy et al, 2001;Rickman et al, 2001;Agrawal et al, 2002;Kim et al, 2002;Veer et al, 2002;Vijver et al, 2002;Boom et al, 2003;Godard et al, 2003;Hunter et al, 2003;Mischel et al, 2003;Nutt et al, 2003;Shai et al, 2003;Sorlie et al, 2003;Freije et al, 2004;Mischel et al, 2004;Hoelzinger et al, 2005;Liang et al, 2005;Nigro et al, 2005;Rich et al, 2005;Somasundaram et al, 2005;Wong et al, 2005) showed the usefulness of utilizing methods of analysis of multiple forms of data including both clinical and multiple genes, to achieve a more precise discrimination of outcomes for individual patients. The same logical use of multiple forms of data and methods of analysis has been applied in the present study to accurately achieve better classification and prediction of glioma patients.…”

“…Recently, developed microarray technology has permitted development of multi-organ cancer classification including gliomas (Ramaswamy et al, 2001;Rickman et al, 2001;Kim et al, 2002;Hunter et al, 2003;Mischel et al, 2004), identification of tumor subclasses (Khan et al, 2001;Mischel et al, 2003;Shai et al, 2003;Sorlie et al, 2003;Liang et al, 2005;Nigro et al, 2005;Wong et al, 2005), discovery of progression markers (Sallinen et al, 2000;Agrawal et al, 2002;van de Boom et al, 2003;Godard et al, 2003;Hoelzinger et al, 2005;Rich et al, 2005;Somasundaram et al, 2005) and prediction of disease outcomes (van't Veer et al, 2002;van de Vijver et al, 2002;Nutt et al, 2003;Freije et al, 2004). Unlike clinicopathological staging, molecular staging can predict long-term outcomes of any individual based on gene expression profile of the tumor at diagnosis.…”

Assessment of angiogenesis by CD105 and nestin expression in peritumor tissue of glioblastoma

“…Neoplastic cells were identified by their nuclear atypia and heteropycnotic staining. Reactive astrocytes were recognized by dendritic morphology of their abundant eosinophilic cytoplasm and large eccentric nuclei (26). Tumors were classified according to the World Health Organization (WHO) criteria (27).…”

Les tumeurs gliales diffuses de l’adulte

“…À l'intérieur même d'une sous-population tumorale, les cellules présentent de façon hétérogène des altérations moléculaires, telles que l'amplification de l'EGFR (points oranges), de la MET (points jaunes), du PDGFR (points verts) ou la méthylation du promoteur de MGMT (points bleus). B. Les différentes sous-populations tumorales expriment des gènes différents en faveur d'un comportement biologique différent [19][20][21][22][23][24][25][26][27][28][29] (voir Glossaire pour définition des abréviations).…”

“…GFAP et pERK [20] Nestine et pAKT [20] ASPHD2, NFE2L2, LAMC1, CD133 [24] ET-1, IL-8 [26] CD133 [19] IGFBP2 et vimentine [21] Autotaxine, éphrine B3, Bcl-w, PTK 2 [21] Hif1, IL-8 [25] E-sélectine [27] Nestine [28] Stéphine B [22] Cathepsines S et L [22] Gènes de la voie Notch [29] …”