Amandine Etcheverry

DNA methylation in glioblastoma: impact on gene expression and clinical outcome

BackgroundChanges in promoter DNA methylation pattern of genes involved in key biological pathways have been reported in glioblastoma. Genome-wide assessments of DNA methylation levels are now required to decipher the epigenetic events involved in the aggressive phenotype of glioblastoma, and to guide new treatment strategies.ResultsWe performed a whole-genome integrative analysis of methylation and gene expression profiles in 40 newly diagnosed glioblastoma patients. We also screened for associations between the level of methylation of CpG sites and overall survival in a cohort of 50 patients uniformly treated by surgery, radiotherapy and chemotherapy with concomitant and adjuvant temozolomide (STUPP protocol). The methylation analysis identified 616 CpG sites differentially methylated between glioblastoma and control brain, a quarter of which was differentially expressed in a concordant way. Thirteen of the genes with concordant CpG sites displayed an inverse correlation between promoter methylation and expression level in glioblastomas: B3GNT5, FABP7, ZNF217, BST2, OAS1, SLC13A5, GSTM5, ME1, UBXD3, TSPYL5, FAAH, C7orf13, and C3orf14. Survival analysis identified six CpG sites associated with overall survival. SOX10 promoter methylation status (two CpG sites) stratified patients similarly to MGMT status, but with a higher Area Under the Curve (0.78 vs. 0.71, p- value < 5e-04). The methylation status of the FNDC3B, TBX3, DGKI, and FSD1 promoters identified patients with MGMT-methylated tumors that did not respond to STUPP treatment (p- value < 1e-04).ConclusionsThis study provides the first genome-wide integrative analysis of DNA methylation and gene expression profiles obtained from the same GBM cohort. We also present a methylome-based survival analysis for one of the largest uniformly treated GBM cohort ever studied, for more than 27,000 CpG sites. We have identified genes whose expression may be tightly regulated by epigenetic mechanisms and markers that may guide treatment decisions.

Integrative genome‐wide analysis reveals a robust genomic glioblastoma signature associated with copy number driving changes in gene expression

Glioblastoma multiforme shows multiple chromosomal aberrations, the impact of which on gene expression remains unclear. To investigate this relationship and to identify putative initiating genomic events, we integrated a paired copy number and gene expression survey in glioblastoma using whole human genome arrays. Loci of recurrent copy number alterations were combined with gene expression profiles obtained on the same tumor samples. We identified a set of 406 “cis‐acting DNA targeted genes” corresponding to genomic aberrations with direct copy‐number‐driving changes in gene expression, defined as genes with either significantly concordant or correlated changes in DNA copy number and expression. Functional annotation revealed that these genes participate in key processes of cancer cell biology, providing insights into the genetic mechanisms driving glioblastoma. The robustness of the gene selection was validated on an external microarray data set including 81 glioblastomas and 23 non‐neoplastic brain samples. The integration of array CGH and gene expression data highlights a robust cis‐acting DNA targeted genes signature that may be critical for glioblastoma progression, with two tumor suppressor genes PCDH9 and STARD13 that could be involved in tumor invasiveness and resistance to etoposide.

A 4-Gene Signature Associated with Clinical Outcome in High-Grade Gliomas

Purpose: Gene expression studies provide molecular insights improving the classification of patients with high-grade gliomas. We have developed a risk estimation strategy based on a combined analysis of gene expression data to search for robust biomarkers associated with outcome in these tumors. Experimental Design: We performed a meta-analysis using 3 publicly available malignant gliomas microarray data sets (267 patients) to define the genes related to both glioma malignancy and patient outcome. These biomarkers were used to construct a risk-score equation based on a Cox proportional hazards model on a subset of 144 patients. External validations were performed on microarray data (59 patients) and on RT-qPCR data (194 patients). The risk-score model performances (discrimination and calibration) were evaluated and compared with that of clinical risk factors, MGMT promoter methylation status, and IDH1 mutational status. Results: This interstudy cross-validation approach allowed the identification of a 4-gene signature highly correlated to survival (CHAF1B, PDLIM4, EDNRB, and HJURP), from which an optimal survival model was built (P < 0.001 in training and validation sets). Multivariate analysis showed that the 4-gene risk score was strongly and independently associated with survival (hazard ratio = 0.46; 95% CI, 0.26–0.81; P = 0.007). Performance estimations indicated that this score added beyond standard clinical parameters and beyond both the MGMT methylation status and the IDH1 mutational status in terms of discrimination (C statistics, 0.827 versus 0.835; P < 0.001). Conclusion: The 4-gene signature provides an independent risk score strongly associated with outcome of patients with high-grade gliomas. Clin Cancer Res; 17(2); 317–27. ©2011 AACR.

Human Glioblastoma Stem-Like Cells are More Sensitive to Allogeneic NK and T Cell-Mediated Killing Compared with Serum-Cultured Glioblastoma Cells.

Glioblastoma multiforme (GBM) is the most dramatic primary brain cancer with a very poor prognosis because of inevitable disease recurrence. The median overall survival is less than 1 year after diagnosis. Cancer stem cells have recently been disclosed in GBM. GBM stem‐like cells (GSCs) exhibit resistance to radio/chemotherapeutic treatments and are therefore considered to play an important role in disease recurrence. GSCs are thus appealing targets for new treatments for GBM patients. In this study, we show that GBM cells with stem cell characteristics are resistant to lysis mediated by resting natural killer (NK) cells because of the expression of MHC class I molecules. However, GSCs are killed by lectin‐activated NK cells. Furthermore, in experiments using the therapeutic antibody CetuximAb, we show that GSCs are sensitive to antibody‐mediated cytotoxicity. We confirm the sensitivity of GSC to cytotoxicity carried out by IL2‐activated NK cells and tumor‐specific T cells. More importantly, we show that GSCs are more sensitive to NK and T cell‐mediated lysis relatively to their corresponding serum‐cultured GBM cells obtained from the same initial tumor specimen. Altogether, these results demonstrate the sensitivity of GSC to immune cell cytotoxicity and, therefore, strongly suggest that GSCs are suitable target cells for immunotherapy of GBM patients.

Identification of gene copy number variations in patients with mental retardation using array-CGH: Novel syndromes in a large French series

Array-CGH has revealed a large number of copy number variations (CNVs) in patients with multiple congenital anomalies and/or mental retardation (MCA/MR). According to criteria recently listed, pathogenicity was clearly suspected for some CNVs but benign CNVs, considered as polymorphisms, have complicated the interpretation of the results. In this study, genomic DNAs from 132 French patients with unexplained mental retardation were analysed by genome wide high-resolution Agilent 44K oligonucleotide arrays. The results were in accordance with those observed in previous studies: the detection rate of pathogenic CNVs was 14.4%. A non-random involvement of several chromosomal regions was observed. Some of the microimbalances recurrently involved regions (1q21.1, 2q23.1, 2q32q33, 7p13, 17p13.3, 17p11.2, 17q21.31) corresponding to known or novel syndromes. For all the pathogenic CNVs, further cases are needed to allow more accurate genotype-phenotype correlations underscoring the importance of databases to group patients with similar molecular data.

Immune genes are associated with human glioblastoma pathology and patient survival

BackgroundGlioblastoma (GBM) is the most common and lethal primary brain tumor in adults. Several recent transcriptomic studies in GBM have identified different signatures involving immune genes associated with GBM pathology, overall survival (OS) or response to treatment.MethodsIn order to clarify the immune signatures found in GBM, we performed a co-expression network analysis that grouped 791 immune-associated genes (IA genes) in large clusters using a combined dataset of 161 GBM specimens from published databases. We next studied IA genes associated with patient survival using 3 different statistical methods. We then developed a 6-IA gene risk predictor which stratified patients into two groups with statistically significantly different survivals. We validated this risk predictor on two other Affymetrix data series, on a local Agilent data series, and using RT-Q-PCR on a local series of GBM patients treated by standard chemo-radiation therapy.ResultsThe co-expression network analysis of the immune genes disclosed 6 powerful modules identifying innate immune system and natural killer cells, myeloid cells and cytokine signatures. Two of these modules were significantly enriched in genes associated with OS. We also found 108 IA genes linked to the immune system significantly associated with OS in GBM patients. The 6-IA gene risk predictor successfully distinguished two groups of GBM patients with significantly different survival (OS low risk: 22.3 months versus high risk: 7.3 months; p < 0.001). Patients with significantly different OS could even be identified among those with known good prognosis (methylated MGMT promoter-bearing tumor) using Agilent (OS 25 versus 8.1 months; p < 0.01) and RT-PCR (OS 21.8 versus 13.9 months; p < 0.05) technologies. Interestingly, the 6-IA gene risk could also distinguish proneural GBM subtypes.ConclusionsThis study demonstrates the immune signatures found in previous GBM genomic analyses and suggests the involvement of immune cells in GBM biology. The robust 6-IA gene risk predictor should be helpful in establishing prognosis in GBM patients, in particular in those with a proneural GBM subtype, and even in the well-known good prognosis group of patients with methylated MGMT promoter-bearing tumors.

Dual IRE1 RNase functions dictate glioblastoma development

Proteostasis imbalance is emerging as a major hallmark of cancer, driving tumor aggressiveness. Evidence suggests that the endoplasmic reticulum (ER), a major site for protein folding and quality control, plays a critical role in cancer development. This concept is valid in glioblastoma multiform (GBM), the most lethal primary brain cancer with no effective treatment. We previously demonstrated that the ER stress sensor IRE1α (referred to as IRE1) contributes to GBM progression, through XBP1 mRNA splicing and regulated IRE1‐dependent decay (RIDD) of RNA. Here, we first demonstrated IRE1 signaling significance to human GBM and defined specific IRE1‐dependent gene expression signatures that were confronted to human GBM transcriptomes. This approach allowed us to demonstrate the antagonistic roles of XBP1 mRNA splicing and RIDD on tumor outcomes, mainly through selective remodeling of the tumor stroma. This study provides the first demonstration of a dual role of IRE1 downstream signaling in cancer and opens a new therapeutic window to abrogate tumor progression.

DGKI Methylation Status Modulates the Prognostic Value of MGMT in Glioblastoma Patients Treated with Combined Radio-Chemotherapy with Temozolomide

Background Consistently reported prognostic factors for glioblastoma (GBM) are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors that responded poorly to the standard regimen. We further evaluated the potential prognostic value of DGKI methylation status. Methods 399 patients with newly diagnosed GBM and treated with a standard regimen were retrospectively included in this study. Survival modelling was performed on two patient populations: intention-to-treat population of all included patients (population 1) and MGMT-methylated patients (population 2). Cox proportional hazard models were fitted to identify the main prognostic factors. A nomogram was developed for population 1. The prognostic value of DGKI promoter methylation status was evaluated on population 1 and population 2. Results The nomogram-based stratification of the cohort identified two risk groups (high/low) with significantly different median survival. We validated the prognostic value of DGKI methylation status for MGMT-methylated patients. We also demonstrated that the DGKI methylation status identified 22% of poorly responding patients in the low-risk group defined by the nomogram. Conclusions Our results improve the conventional MGMT stratification of GBM patients receiving standard treatment. These results could help the interpretation of published or ongoing clinical trial outcomes and refine patient recruitment in the future.

Intérêt de la MGMT dans les gliomes

MGMT status is now regarded as a strong predictive factor of response to standard treatment of newly diagnosed glioblastomas involving temozolomide (TMZ) and radiotherapy. MGMT promoter methylation is also a prognostic factor - independent of treatment - in anaplastic gliomas. The predictive function can be explained by the role of the DNA repair enzyme MGMT, which antagonizes the effects of alkylating agents such as TMZ. MGMT promoter methylation could also reflect a particular molecular phenotype with its own specific prognostic significance. Since MGMT status determination is becoming a crucial biological marker in new clinical glioma trials, and is beginning to be used in day-to-day clinical practice, there is currently a strong need to determine the best technique for MGMT analysis. A French multicenter study has been set up for this purpose.

MGMT analysis in gliomas

MGMT status is now regarded as a strong predictive factor of response to standard treatment of newly diagnosed glioblastomas involving temozolomide (TMZ) and radiotherapy. MGMT promoter methylation is also a prognostic factor - independent of treatment - in anaplastic gliomas. The predictive function can be explained by the role of the DNA repair enzyme MGMT, which antagonizes the effects of alkylating agents such as TMZ. MGMT promoter methylation could also reflect a particular molecular phenotype with its own specific prognostic significance. Since MGMT status determination is becoming a crucial biological marker in new clinical glioma trials, and is beginning to be used in day-to-day clinical practice, there is currently a strong need to determine the best technique for MGMT analysis. A French multicenter study has been set up for this purpose.