Genome-wide DNA methylation analysis identifies potent CpG signature for temzolomide response in non-G-CIMP glioblastomas with unmethylated MGMT promoter: MGMT-dependent roles of GPR81

PURPOSES

To identify potent DNA methylation candidates that could predict response to temozolomide (TMZ) in glioblastomas (GBMs) that do not have glioma-CpGs island methylator phenotype (G-CIMP) but have an unmethylated promoter of O-6-methylguanine-DNA methyltransferase (unMGMT).

METHODS

The discovery-validation approach was planned incorporating a series of G-CIMP-/unMGMT GBM cohorts with DNA methylation microarray data and clinical information, to construct multi-CpG prediction models. Different bioinformatic and experimental analyses were performed for biological exploration.

RESULTS

By analyzing discovery sets with radiotherapy (RT) plus TMZ versus RT alone, we identified a panel of 64 TMZ efficacy-related CpGs, from which a 10-CpG risk signature was further constructed. Both the 64-CpG panel and the 10-CpG risk signature were validated showing significant correlations with overall survival of G-CIMP-/unMGMT GBMs when treated with RT/TMZ, rather than RT alone. The 10-CpG risk signature was further observed for aiding TMZ choice by distinguishing differential outcomes to RT/TMZ versus RT within each risk subgroup. Functional studies on GPR81, the gene harboring one of the 10 CpGs, indicated its distinct impacts on TMZ resistance in GBM cells, which may be dependent on the status of MGMT expression.

CONCLUSIONS

The 64 TMZ efficacy-related CpGs and in particular the 10-CpG risk signature may serve as promising predictive biomarker candidates for guiding optimal usage of TMZ in G-CIMP-/unMGMT GBMs.

Gene Editing Corrects In Vitro a G > A GLB1 Transition from a GM1 Gangliosidosis Patient

Ganglioside-monosialic acid (GM1) gangliosidosis, a rare autosomal recessive disorder, is frequently caused by deleterious single nucleotide variants (SNVs) in GLB1 gene. These variants result in reduced β-galactosidase (β-gal) activity, leading to neurodegeneration associated with premature death. Currently, no effective therapy for GM1 gangliosidosis is available. Three ongoing clinical trials aim to deliver a functional copy of the GLB1 gene to stop disease progression. In this study, we show that 41% of GLB1 pathogenic SNVs can be replaced by adenine base editors (ABEs). Our results demonstrate that ABE efficiently corrects the pathogenic allele in patient-derived fibroblasts, restoring therapeutic levels of β-gal activity. Off-target DNA analysis did not detect off-target editing activity in treated patient's cells, except a bystander edit without consequences on β-gal activity based on 3D structure bioinformatics predictions. Altogether, our results suggest that gene editing might be an alternative strategy to cure GM1 gangliosidosis.

Potent predictive CpG signature for temozolomide response in non-glioma-CpG island methylator phenotype glioblastomas with methylated MGMT promoter

Aim: We aimed to identify potent CpG signatures predicting temozolomide (TMZ) response in glioblastomas (GBMs) that do not have the glioma-CpG island methylator phenotype (G-CIMP) but have a methylated promoter of MGMT (me MGMT). Materials & methods: Different datasets of non-G-CIMP me MGMT GBMs with molecular and clinical data were analyzed. Results: A panel of 77 TMZ efficacy-related CpGs and a seven-CpG risk signature were identified and validated for distinguishing differential outcomes to radiotherapy plus TMZ versus radiotherapy alone in non-G-CIMP me MGMT GBMs. An integrated classification scheme was also proposed for refining a MGMT-based TMZ-guiding approach in all G-CIMP-GBMs. Conclusion: The CpG signatures may serve as promising predictive biomarker candidates for guiding optimal TMZ usage in non-G-CIMP me MGMT GBMs.

Aberrant DNA methylation impacts HOX genes expression in bone marrow mesenchymal stromal cells of myelodysplastic syndromes and de novo acute myeloid leukemia

DNA methylation, a major biological process regulating the transcription, contributes to the pathophysiology of hematologic malignancies, and hypomethylating agents are commonly used to treat myelodysplastic syndromes (MDS) and acute myeloid leukemias (AML). In these diseases, bone marrow mesenchymal stromal cells (MSCs) play a key supportive role through the production of various signals and interactions. The DNA methylation status of MSCs, likely to reflect their functionality, might be relevant to understand their contribution to the pathophysiology of these diseases. Consequently, the aim of our study was to analyze the modifications of DNA methylation profiles of MSCs induced by MDS or AML. MSCs from MDS/AML patients were characterized via 5-methylcytosine quantification, gene expression profiles of key regulators of DNA methylation, identification of differentially methylated regions (DMRs) by methylome array, and quantification of DMR-coupled genes expression. MDS and AML-MSCs displayed global hypomethylation and under-expression of DNMT1 and UHRF1. Methylome analysis revealed aberrant methylation profiles in all MDS and in a subgroup of AML-MSCs. This aberrant methylation was preferentially found in the sequence of homeobox genes, especially from the HOX family (HOXA1, HOXA4, HOXA5, HOXA9, HOXA10, HOXA11, HOXB5, HOXC4, and HOXC6), and impacted on their expression. These results highlight modifications of DNA methylation in MDS/AML-MSCs, both at global and focal levels dysregulating the expression of HOX genes well known for their involvement in leukemogenesis. Such DNA methylation in MSCs could be the consequence of the malignant disease or could participate in its development through defective functionality or exosomal transfer of HOX transcription factors from MSCs to hematopoietic cells.

Integration of Raman spectra with transcriptome data in glioblastoma multiforme defines tumour subtypes and predicts patient outcome

Raman spectroscopy is an imaging technique that has been applied to assess molecular compositions of living cells to characterize cell types and states. However, owing to the diverse molecular species in cells and challenges of assigning peaks to specific molecules, it has not been clear how to interpret cellular Raman spectra. Here, we provide firm evidence that cellular Raman spectra (RS) and transcriptomic profiles of glioblastoma can be computationally connected and thus interpreted. We find that the dimensions of high-dimensional RS and transcriptomes can be reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to predict global gene expression profiles by applying the calculated transformation matrix to Raman spectra and vice versa. From these analyses, we extract a minimal gene expression signature associated with specific RS profiles and predictive of disease outcome.

Integrative analysis identifies an immune-relevant epigenetic signature for prognostication of non-G-CIMP glioblastomas

The clinical and molecular implications of DNA methylation alterations remain unclear among the majority of glioblastomas (GBMs) without glioma-CpGs island methylator phenotype (G-CIMP); integrative multi-level molecular profiling may provide useful information. Independent cohorts of non-G-CIMP GBMs or IDH wild type (wt) lower-grade gliomas (LGGs) from local and public databases with DNA methylation and gene expression microarray data were included for discovery and validation of a multimarker signature, combined using a RISK score model. Bioinformatic and in vitro functional analyses were employed for biological validation. Using a strict multistep selection approach, we identified eight CpGs, each of which was significantly correlated with overall survival (OS) of non-G-CIMP GBMs, independent of age, the O-6-methylguanine-DNA methyltransferase (MGMT) methylation status, treatments and other identified CpGs. An epigenetic RISK signature of the 8 CpGs was developed and validated to robustly and independently prognosticate prognosis in different cohorts of not only non-G-GIMP GBMs, but also IDHwt LGGs. It also showed good discriminating value in stratified cohorts by current clinical and molecular factors. Bioinformatic analysis revealed consistent correlation of the epigenetic signature to distinct immune-relevant transcriptional profiles of GBM bulks. Functional experiments showed that S100A2 appeared to be epigenetically regulated by one identified CpG and was associated with GBM cell proliferation, apoptosis, invasion, migration and immunosuppression. The prognostic 8-CpGs RISK score signature may be of promising value for refining current glioma risk classification, and its potential links to distinct immune phenotypes make it a promising biomarker candidate for predicting response to anti-glioma immunotherapy.

EZH2 and KDM6B Expressions Are Associated with Specific Epigenetic Signatures during EMT in Non Small Cell Lung Carcinomas

The role of Epigenetics in Epithelial Mesenchymal Transition (EMT) has recently emerged. Two epigenetic enzymes with paradoxical roles have previously been associated to EMT, EZH2 (Enhancer of Zeste 2 Polycomb Repressive Complex 2 (PRC2) Subunit), a lysine methyltranserase able to add the H3K27me3 mark, and the histone demethylase KDM6B (Lysine Demethylase 6B), which can remove the H3K27me3 mark. Nevertheless, it still remains unclear how these enzymes, with apparent opposite activities, could both promote EMT. In this study, we evaluated the function of these two enzymes using an EMT-inducible model, the lung cancer A549 cell line. ChIP-seq coupled with transcriptomic analysis showed that EZH2 and KDM6B were able to target and modulate the expression of different genes during EMT. Based on this analysis, we described INHBB, WTN5B, and ADAMTS6 as new EMT markers regulated by epigenetic modifications and directly implicated in EMT induction.

Local intracerebral inhibition of IRE1 by MKC8866 sensitizes glioblastoma to irradiation/chemotherapy in vivo

Glioblastoma multiforme (GBM) is the most severe primary brain cancer. Despite an aggressive treatment comprising surgical resection and radio/chemotherapy, patient's survival post diagnosis remains short. A limitation for success in finding novel improved therapeutic options for such dismal disease partly lies in the lack of a relevant animal model that accurately recapitulates patient disease and standard of care. In the present study, we have developed an immunocompetent GBM model that includes tumor surgery and a radio/chemotherapy regimen resembling the Stupp protocol and we have used this model to test the impact of the pharmacological inhibition of the endoplasmic reticulum (ER) stress sensor IRE1, on treatment efficacy.

Cytosine methylation of mature microRNAs inhibits their functions and is associated with poor prognosis in glioblastoma multiforme

Background

Literature reports that mature microRNA (miRNA) can be methylated at adenosine, guanosine and cytosine. However, the molecular mechanisms involved in cytosine methylation of miRNAs have not yet been fully elucidated. Here we investigated the biological role and underlying mechanism of cytosine methylation in miRNAs in glioblastoma multiforme (GBM).

Methods

RNA immunoprecipitation with the anti-5methylcytosine (5mC) antibody followed by Array, ELISA, dot blot, incorporation of a radio-labelled methyl group in miRNA, and miRNA bisulfite sequencing were perfomred to detect the cytosine methylation in mature miRNA. Cross-Linking immunoprecipiation qPCR, transfection with methylation/unmethylated mimic miRNA, luciferase promoter reporter plasmid, Biotin-tagged 3’UTR/mRNA or miRNA experiments and in vivo assays were used to investigate the role of methylated miRNAs. Finally, the prognostic value of methylated miRNAs was analyzed in a cohorte of GBM pateints.

Results

Our study reveals that a significant fraction of miRNAs contains 5mC. Cellular experiments show that DNMT3A/AGO4 methylated miRNAs at cytosine residues inhibit the formation of miRNA/mRNA duplex and leading to the loss of their repressive function towards gene expression. In vivo experiments show that cytosine-methylation of miRNA abolishes the tumor suppressor function of miRNA-181a-5p miRNA for example. Our study also reveals that cytosine-methylation of miRNA-181a-5p results is associated a poor prognosis in GBM patients.

Conclusion

Together, our results indicate that the DNMT3A/AGO4-mediated cytosine methylation of miRNA negatively.

Graphical abstract

Novel predictive epigenetic signature for temozolomide in non-G-CIMP glioblastomas

Objective

To identify novel epigenetic signatures that could provide predictive information that is complementary to promoter methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) gene for predicting temozolomide (TMZ) response, among glioblastomas (GBMs) without glioma-CpGs island methylator phenotype (G-CIMP)

Methods

Different cohorts of primary non-G-CIMP GBMs with genome-wide DNA methylation microarray data were included for discovery and validation of a multimarker signature, combined using a RISK score model. Different statistical analyses and functional experiments were performed for clinical and biological validation.

Results

By employing discovery cohorts with radiotherapy (RT) and TMZ versus RT alone and a strict multistep selection strategy, we identified seven CpGs, each of which was significantly correlated with overall survival (OS) of non-G-CIMP GBMs with RT/TMZ, independent of age, MGMT promoter methylation status, and other identified CpGs. A RISK score signature of the 7 CpGs was developed and validated to distinguish non-G-CIMP GBMs with differential survival outcomes to RT/TMZ, but not to RT alone. The interaction analyses also showed differential outcomes to RT/TMZ versus RT alone within the RISK score-based subgroups. The signature could also improve the risk classification by age and MGMT promoter methylation status. Functional experiments showed that HSBP2 appeared to be epigenetically regulated by one identified CpG and was associated with TMZ resistance, but it was not associated with cell proliferation or apoptosis in GBM cell lines. The predictive value of the single CpG methylation of HSBP2 by pyrosequencing was observed in a local cohort of isocitrate dehydrogenase 1 (IDH1) ^R132H wild-type GBMs.

Conclusions

This novel epigenetic signature might be a promising predictive (but not a general prognostic) biomarker and be helpful for refining the MGMT-based guiding approach to TMZ usage in non-G-CIMP GBMs.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0670-9) contains supplementary material, which is available to authorized users.

A five-CpG signature of microRNA methylation in non-G-CIMP glioblastoma

AIMS

DNA methylation has been found to regulate microRNAs (miRNAs) expression, but the prognostic value of miRNA-related DNA methylation aberration remained largely elusive in cancers including glioblastomas (GBMs). This study aimed to investigate the clinical and biological feature of miRNA methylation in GBMs of non-glioma-CpG island methylator phenotype (non-G-CIMP).

METHODS

Prognostic miRNA methylation loci were analyzed, with TCGA and Rennes cohort as training sets, and independent datasets of GBMs and low-grade gliomas (LGGs) were obtained as validation sets. Different statistical and bioinformatic analysis and experimental validations were performed to clinically and biologically characterize the signature.

RESULTS

We identified and validated a risk score based on methylation status of five miRNA-associated CpGs which could predict survival of GBM patients in a series of training and validation sets. This signature was independent of age and O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. The risk subgroup was associated with angiogenesis and accordingly differential responses to bevacizumab-contained therapy. MiRNA target analysis and in vitro experiments further confirmed the accuracy of this signature.

CONCLUSION

The five-CpG signature of miRNA methylation was biologically relevant and was of potential prognostic and predictive value for GBMs. It might be of help for improving individualized treatment.

Neuro-radiological characteristics of adult diffuse grade II and III insular gliomas classified according to WHO 2016

INTRODUCTION

The phenotypic heterogeneity of diffuse gliomas is still inconsistently explained by known molecular abnormalities. Here, we report the molecular and radiological features of diffuse grade WHO II and III gliomas involving the insula and its potential impact on prognosis.

METHODS

Clinical, pathological, molecular and neuro-radiological features of 43 consecutive patients who underwent a surgical resection between 2006 and 2013 for a grade II and III gliomas involving the insula was retrospectively analyzed.

RESULTS

Median age was 44.4 years. Eight patients had oligodendrogliomas, IDH mutant (IDH^mut) and 1p/19q-codeleted (6 grade II, 2 grade III). Twenty-eight patients had diffuse astrocytomas, IDH^mut (22 grade II and 6 grade III) and seven patients had grade II diffuse astrocytomas, IDH^wt (A-IDH^wt). Vimentin staining was exclusively recorded in tumor cells from A-IDH^wt (p = 0.001). Mean cerebral blood volume (CBV) (p = 0.018), maximal value of CBV (p = 0.017) and ratio of the corrected CBV (p = 0.022) were lower for A-IDH^wt. Volumetric segmentation of ADC allowed the identification of the tumor cores, which were smaller in A-IDH^wt (p < 0.001). The tumor occurrences of A-IDH^wt were exclusively located into the temporo-insular region. Median progression-free survival (PFS) and overall survival (OS) were 50.9 months (95% CI: 26.7-75.0) and 80.9 months (60.1-101.6). By multivariate analysis, A-IDH^wt (p = 0.009; p = 0.019), 7p gain and 10q loss (p = 0.009; p = 0.016) and vimentin positive staining (p = 0.011; p = 0.029) were associated with poor PFS and OS respectively.

CONCLUSIONS

Insular low-grade A-IDH^wt presented with poor prognosis despite a smaller tumor core and no evidence of increased perfusion on MR imaging.

The expression of EMX2 lead to cell cycle arrest in glioblastoma cell line

Background

Glioblastoma (GB) is a highly invasive primary brain tumor that nearly always systematically recurs at the site of resection despite aggressive radio-chemotherapy. Previously, we reported a gene expression signature related to tumor infiltration. Within this signature, the EMX2 gene encodes a homeodomain transcription factor that we found was down regulated in glioblastoma. As EMX2 is reported to play a role in carcinogenesis, we investigated the impact of EMX2 overexpression in glioma-related cell lines.

Methods

For that purpose, we constructed tetracycline-inducible EMX2 expression lines. Transfected cell phenotypes (proliferation, cell death and cell cycle) were assessed in time-course experiments.

Results

Restoration of EMX2 expression in U87 glioblastoma cells significantly inhibited cell proliferation. This inhibition was reversible after EMX2 removal from cells. EMX2-induced proliferative inhibition was very likely due to cell cycle arrest in G1/S transition and was not accompanied by signs of cell death.

Conclusion

Our results suggest that EMX2 may constitute a putative therapeutic target for GB treatment.

Further studies are required to decipher the gene networks and transduction signals involved in EMX2’s effect on cell proliferation.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5094-y) contains supplementary material, which is available to authorized users.

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.

A novel prognostic six-CpG signature in glioblastomas

AIMS

We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM).

METHODS

A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation. An integrative analysis of multidimensional TCGA data was performed to molecularly characterize different risk tumors.

RESULTS

The six-CpG risk-score signature robustly predicted overall survival (OS) in all discovery and validation cohorts and in a treatment-independent manner. It also predicted progression-free survival (PFS) in available patients. The multimarker epigenetic signature was demonstrated as an independent prognosticator and had better performance than known molecular indicators such as glioma-CpG island methylator phenotype (G-CIMP) and proneural subtype. The defined risk subgroups were molecularly distinct; high-risk tumors were biologically more aggressive with concordant activation of proangiogenic signaling at multimolecular levels. Accordingly, we observed better OS benefits of bevacizumab-contained therapy to high-risk patients in independent sets, supporting its implication in guiding usage of antiangiogenic therapy. Finally, the six-CpG signature refined the risk classification based on G-CIMP and MGMT methylation status.

CONCLUSIONS

The novel six-CpG signature is a robust and independent prognostic indicator for GBMs and is of promising value to improve personalized management.

Integrative analysis of novel hypomethylation and gene expression signatures in glioblastomas

Molecular and clinical heterogeneity critically hinders better treatment outcome for glioblastomas (GBMs); integrative analysis of genomic and epigenomic data may provide useful information for improving personalized medicine. By applying training-validation approach, we identified a novel hypomethylation signature comprising of three CpGs at non-CpG island (CGI) open sea regions for GBMs. The hypomethylation signature consistently predicted poor prognosis of GBMs in a series of discovery and validation datasets. It was demonstrated as an independent prognostic indicator, and showed interrelationships with known molecular marks such as MGMT promoter methylation status, and glioma CpG island methylator phenotype (G-CIMP) or IDH1 mutations. Bioinformatic analysis found that the hypomethylation signature was closely associated with the transcriptional status of an EGFR/VEGFA/ANXA1-centered gene network. The integrative molecular analysis finally revealed that the gene network defined two distinct clinically relevant molecular subtypes reminiscent of different immature neuroglial lineages in GBMs. The novel hypomethylation signature and relevant gene network may provide new insights into prognostic classification, molecular characterization, and treatment development for GBMs.

From the core to beyond the margin: a genomic picture of glioblastoma intratumor heterogeneity

Glioblastoma (GB) is a highly invasive primary brain tumor that almost systematically recurs despite aggressive therapies. One of the most challenging problems in therapy of GB is its extremely complex and heterogeneous molecular biology. To explore this heterogeneity, we performed a genome-wide integrative screening of three molecular levels: genome, transcriptome, and methylome. We analyzed tumor biopsies obtained by neuro-navigation in four distinct areas for 10 GB patients (necrotic zone, tumor zone, interface, and peripheral brain zone). We classified samples and deciphered a key genes signature of intratumor heterogeneity by Principal Component Analysis and Weighted Gene Co-expression Network Analysis. At the genome level, we identified common GB copy number alterations and but a strong interindividual molecular heterogeneity. Transcriptome analysis highlighted a pronounced intratumor architecture reflecting the surgical sampling plan of the study and identified gene modules associated with hallmarks of cancer. We provide a signature of key cancer-heterogeneity genes highly associated with the intratumor spatial gradient and show that it is enriched in genes with correlation between methylation and expression levels. Our study confirms that GBs are molecularly highly diverse and that a single tumor can harbor different transcriptional GB subtypes depending on its spatial architecture.

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.

Immune genes are associated with human glioblastoma pathology and patient survival

Background

Glioblastoma (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.

Methods

In 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.

Results

The 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.

Conclusions

This 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.

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.

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.

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

Background

Changes 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.

Results

We 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).

Conclusions

This 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.

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.

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.