Prognostic Stratification of GBMs Using Combinatorial Assessment of IDH1 Mutation,MGMT Promoter Methylation,and TERT Mutation Status: Experience from a Tertiary Care Center in India

This study aims to establish the best and simplified panel of molecular markers for prognostic stratification of glioblastomas (GBMs). One hundred fourteen cases of GBMs were studied for IDH1, TP53, and TERT mutation by Sanger sequencing; EGFR and PDGFRA amplification by fluorescence in situ hybridization; NF1expression by quantitative real time polymerase chain reaction (qRT-PCR); and MGMT promoter methylation by methylation-specific PCR. IDH1 mutant cases had significantly longer progression-free survival (PFS) and overall survival (OS) as compared to IDH1 wild-type cases. Combinatorial assessment of MGMT and TERT emerged as independent prognostic markers, especially in the IDH1 wild-type GBMs. Thus, within the IDH1 wild-type group, cases with only MGMT methylation (group 1) had the best outcome (median PFS: 83.3 weeks; OS: not reached), whereas GBMs with only TERT mutation (group 3) had the worst outcome (PFS: 19.7 weeks; OS: 32.8 weeks). Cases with both or none of these alterations (group 2) had intermediate prognosis (PFS: 47.6 weeks; OS: 89.2 weeks). Majority of the IDH1 mutant GBMs belonged to group 1 (75%), whereas only 18.7% and 6.2% showed group 2 and 3 signatures, respectively. Interestingly, none of the other genetic alterations were significantly associated with survival in IDH1 mutant or wild-type GBMs.Based on above findings, we recommend assessment of three markers, viz., IDH1, MGMT, and TERT, for GBM prognostication in routine practice. We show for the first time that IDH1 wild-type GBMs which constitute majority of the GBMs can be effectively stratified into three distinct prognostic subgroups based on MGMT and TERT status, irrespective of other genetic alterations.     

Network Signatures of Survival in Glioblastoma Multiforme

To determine a molecular basis for prognostic differences in glioblastoma multiforme (GBM), we employed a combinatorial network analysis framework to exhaustively search for molecular patterns in protein-protein interaction (PPI) networks. We identified a dysregulated molecular signature distinguishing short-term (survival<225 days) from long-term (survival>635 days) survivors of GBM using whole genome expression data from The Cancer Genome Atlas (TCGA). A 50-gene subnetwork signature achieved 80% prediction accuracy when tested against an independent gene expression dataset. Functional annotations for the subnetwork signature included “protein kinase cascade,” “IκB kinase/NFκB cascade,” and “regulation of programmed cell death” – all of which were not significant in signatures of existing subtypes. Finally, we used label-free proteomics to examine how our subnetwork signature predicted protein level expression differences in an independent GBM cohort of 16 patients. We found that the genes discovered using network biology had a higher probability of dysregulated protein expression than either genes exhibiting individual differential expression or genes derived from known GBM subtypes. In particular, the long-term survivor subtype was characterized by increased protein expression of DNM1 and MAPK1 and decreased expression of HSPA9, PSMD3, and CANX. Overall, we demonstrate that the combinatorial analysis of gene expression data constrained by PPIs outlines an approach for the discovery of robust and translatable molecular signatures in GBM.     

Using AI-Based Evolutionary Algorithms to Elucidate Adult Brain Tumor (Glioma) Etiology Associated with IDH1 for Therapeutic Target Identification

Adult brain tumors (glioma) represent a cancer of unmet need where standard-of-care is non-curative; thus, new therapies are urgently needed. It is unclear whether isocitrate dehydrogenases (IDH1/2) when not mutated have any role in gliomagenesis or tumor growth. Nevertheless, IDH1 is overexpressed in glioblastoma (GBM), which could impact upon cellular metabolism and epigenetic reprogramming. This study characterizes IDH1 expression and associated genes and pathways. A novel biomarker discovery pipeline using artificial intelligence (evolutionary algorithms) was employed to analyze IDH-wildtype adult gliomas from the TCGA LGG-GBM cohort. Ninety genes whose expression correlated with IDH1 expression were identified from: (1) All gliomas, (2) primary GBM, and (3) recurrent GBM tumors. Genes were overrepresented in ubiquitin-mediated proteolysis, focal adhesion, mTOR signaling, and pyruvate metabolism pathways. Other non-enriched pathways included O-glycan biosynthesis, notch signaling, and signaling regulating stem cell pluripotency (PCGF3). Potential prognostic (TSPYL2, JAKMIP1, CIT, TMTC1) and two diagnostic (MINK1, PLEKHM3) biomarkers were downregulated in GBM. Their gene expression and methylation were negatively and positively correlated with IDH1 expression, respectively. Two diagnostic biomarkers (BZW1, RCF2) showed the opposite trend. Prognostic genes were not impacted by high frequencies of molecular alterations and only one (TMTC1) could be validated in another cohort. Genes with mechanistic links to IDH1 were involved in brain neuronal development, cell proliferation, cytokinesis, and O-mannosylation as well as tumor suppression and anaplerosis. Results highlight metabolic vulnerabilities and therapeutic targets for use in future clinical trials.     

The global DNA methylation surrogate LINE-1 methylation is correlated with MGMT promoter methylation and is a better prognostic factor for glioma

Gliomas are the most frequently occurring primary brain tumor in the central nervous system of adults. Glioblastoma multiformes (GBMs, WHO grade 4) have a dismal prognosis despite the use of the alkylating agent, temozolomide (TMZ), and even low grade gliomas (LGGs, WHO grade 2) eventually transform to malignant secondary GBMs. Although GBM patients benefit from promoter hypermethylation of the O(6)-methylguanine-DNA methyltransferase (MGMT) that is the main determinant of resistance to TMZ, recent studies suggested that MGMT promoter methylation is of prognostic as well as predictive significance for the efficacy of TMZ. Glioma-CpG island methylator phenotype (G-CIMP) in the global genome was shown to be a significant predictor of improved survival in patients with GBM. Collectively, we hypothesized that MGMT promoter methylation might reflect global DNA methylation. Additionally in LGGs, the significance of MGMT promoter methylation is still undetermined. In the current study, we aimed to determine the correlation between clinical, genetic, and epigenetic profiles including LINE-1 and different cancer-related genes and the clinical outcome in newly diagnosed 57 LGG and 54 GBM patients. Here, we demonstrated that (1) IDH1/2 mutation is closely correlated with MGMT promoter methylation and 1p/19q codeletion in LGGs, (2) LINE-1 methylation levels in primary and secondary GBMs are lower than those in LGGs and normal brain tissues, (3) LINE-1 methylation is proportional to MGMT promoter methylation in gliomas, and (4) higher LINE-1 methylation is a favorable prognostic factor in primary GBMs, even compared to MGMT promoter methylation. As a global DNA methylation marker, LINE-1 may be a promising marker in gliomas.     

MGMT 甲基化影响替莫唑胺对胶质母细胞瘤疗效的研究

目的:探讨MGMT甲基化如何影响替莫唑胺对胶质母细胞瘤的治疗效果。方法:选取41个胶质母细胞瘤患者(根据相同替莫唑胺化疗方案治疗下临床结局的不同分为两组)的肿瘤组织,采用甲基化特异性聚合酶链反应分析胶质瘤组织中MGMT基因启动子区过甲基化状态,同时采用免疫组织化学法分析胶质瘤组织中MGMT蛋白表达情况。结果:临床结局不佳组中,以MGMT蛋白表达阳性的肿瘤为主(72.2%),而在结局相对良好组中,MGMT蛋白表达的阳性率仅为39.1%;在MGMT蛋白表达阳性的22例胶质母细胞瘤组织中,7例MGMT启动子甲基化,阳性率为31.8%,在MGMGT蛋白表达阴性的19例中,14例MGMT启动子甲基化,阳性率为73.7%(P<0.05)。结论:MGMT基因启动子区的甲基化状态与MGMT蛋白的表达相关。MGMT基因启动子过甲基化,MGMT蛋白表达较低;MGMT基因启动子去甲基化,MGMT蛋白表达较高。MGMT启动子过甲基化通过抑制MGMT基因的表达而增加替莫唑胺的疗效。     

Identification of Global DNA Methylation Signatures in Glioblastoma-Derived Cancer Stem Cells

Glioblastoma(GBM)is the most common and most aggressive primary brain tumor in adults.The existence of a small population of stem-like tumor cells that efficiently propagate tumors and resist cytotoxic therapy is one proposed mechanism leading to the resilient behavior of tumor cells and poor prognosis.In this study,we performed an in-depth analysis of the DNA methylation landscape in GBMderived cancer stem cells(GSCs).Parallel comparisons of primary tumors and GSC lines derived from these tumors with normal controls(a neural stem cell(NSC)line and normal brain tissue)identified groups of hyper- and hypomethylated genes that display a trend of either increasing or decreasing methylation levels in the order of controls,primary GBMs,and their counterpart GSC lines,respectively.Interestingly,concurrent promoter hypermethylation and gene body hypomethylation were observed in a subset of genes including MGMT,AJAP1 and PTPRN2.These unique DNA methylation signatures were also found in primary GBM-derived xenograft tumors indicating that they are not tissue culture-related epigenetic changes.Integration of GSC-specific epigenetic signatures with gene expression analysis further identified candidate tumor suppressor genes that are frequently down-regulated in GBMs such as SPINT2,NEFM and PENK.Forced re-expression of SPINT2 reduced glioma cell proliferative capacity,anchorage independent growth,cell motility,and tumor sphere formation in vitro.The results from this study demonstrate that GSCs possess unique epigenetic signatures that may play important roles in the pathogenesis of GBM.     

IDH1 mutations is prognostic marker for primary glioblastoma multiforme but MGMT hypermethylation is not prognostic for primary glioblastoma multiforme

Purpose

To establish the frequency of IDH1 mutations and MGMT methylation in primary glioblastomas.

Experimental design

We screened primary glioblastoma multiforme (GBM) in a population-based study for IDH1 mutations and MGMT methylation and correlated them with clinical data.

Results

IDH1 mutations were detected in 5 of 40 primary glioblastomas (12,5%). Primary GBM patients carrying IDH1 mutations were significantly younger, mean age of 41 ± 5.06 years, than patients with wild-type IDH1, mean age of 57 ± 2,29 years, p = 0.011. The mean survival time of all GBM patients with and without IDH1 mutations was 19 months (5 cases) and 16 months (35 cases), respectively (p > 0,05). MGMT methylation was detected in 13 of the 40 patients (32,5%). MGMT-promoter methylation did not correlate with overall survival (OS; p > 0,05).

Conclusion

In summary, our study is the first study to investigate the IDH1 mutation status and MGMT methylation in primary GBMs in Turkish population and confirmed IDH1 mutation as a genetic marker for also primary GBMs. Our data are still insufficient for definite ascertainment; and our preliminary results suggest: IDH1 status shows an association with younger age and there is a lack of association between IDH1 mutation and survival time. Furthermore MGMT promoter methylation had no prognostic value and lower frequency in primary glioblastomas.     

The Proneural Molecular Signature Is Enriched in Oligodendrogliomas and Predicts Improved Survival among Diffuse Gliomas

The Cancer Genome Atlas Project (TCGA) has produced an extensive collection of ‘-omic’ data on glioblastoma (GBM), resulting in several key insights on expression signatures. Despite the richness of TCGA GBM data, the absence of lower grade gliomas in this data set prevents analysis genes related to progression and the uncovering of predictive signatures. A complementary dataset exists in the form of the NCI Repository for Molecular Brain Neoplasia Data (Rembrandt), which contains molecular and clinical data for diffuse gliomas across the full spectrum of histologic class and grade. Here we present an investigation of the significance of the TCGA consortium''s expression classification when applied to Rembrandt gliomas. We demonstrate that the proneural signature predicts improved clinical outcome among 176 Rembrandt gliomas that includes all histologies and grades, including GBMs (log rank test p = 1.16e-6), but also among 75 grade II and grade III samples (p = 2.65e-4). This gene expression signature was enriched in tumors with oligodendroglioma histology and also predicted improved survival in this tumor type (n = 43, p = 1.25e-4). Thus, expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for lower grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy. Integrated DNA and RNA analysis of low-grade and high-grade proneural gliomas identified increased expression and gene amplification of several genes including GLIS3, TGFB2, TNC, AURKA, and VEGFA in proneural GBMs, with corresponding loss of DLL3 and HEY2. Pathway analysis highlights the importance of the Notch and Hedgehog pathways in the proneural subtype. This demonstrates that the expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for low-grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy.     

Comparative Analysis of Matrix Metalloproteinase Family Members Reveals That MMP9 Predicts Survival and Response to Temozolomide in Patients with Primary Glioblastoma

Background

Glioblastoma multiform (GBM) is the most common malignant primary brain tumor in adults. Radiotherapy plus concomitant and adjuvant TMZ chemotherapy is the current standard of care for patients with GBM. Matrix metalloproteinases (MMPs), a family of zinc-dependent endopeptidases, are key modulators of tumor invasion and metastasis due to their ECM degradation capacity. The aim of the present study was to identify the most informative MMP member in terms of prognostic and predictive ability for patients with primary GBM.

Method

The mRNA expression profiles of all MMP genes were obtained from the Chinese Glioma Genome Atlas (CGGA), the Repository for Molecular Brain Neoplasia Data (REMBRANDT) and the {"type":"entrez-geo","attrs":{"text":"GSE16011","term_id":"16011"}}GSE16011 dataset. MGMT methylation status was also examined by pyrosequencing. The correlation of MMP9 expression with tumor progression was explored in glioma specimens of all grades. Kaplan–Meier analysis and Cox proportional hazards regression models were used to investigate the association of MMP9 expression with survival and response to temozolomide.

Results

MMP9 was the only significant prognostic factor in three datasets for primary glioblastoma patients. Our results indicated that MMP9 expression is correlated with glioma grade (p<0.0001). Additionally, low expression of MMP9 was correlated with better survival outcome (OS: p = 0.0012 and PFS: p = 0.0066), and MMP9 was an independent prognostic factor in primary GBM (OS: p = 0.027 and PFS: p = 0.032). Additionally, the GBM patients with low MMP9 expression benefited from temozolomide (TMZ) chemotherapy regardless of the MGMT methylation status.

Conclusions

Patients with primary GBMs with low MMP9 expression may have longer survival and may benefit from temozolomide chemotherapy.     

Radiologically Defined Ecological Dynamics and Clinical Outcomes in Glioblastoma Multiforme: Preliminary Results

MATERIALS AND METHODS: We examined pretreatment magnetic resonance imaging (MRI) examinations from 32 patients with glioblastoma multiforme (GBM) enrolled in The Cancer Genome Atlas (TCGA). Spatial variations in T1 post-gadolinium and either T2-weighted or fluid attenuated inversion recovery sequences from each tumor MRI study were used to characterize each small region of the tumor by its local contrast enhancement and edema/cellularity (“habitat”). The patient cohort was divided into group 1 (survival < 400 days, n = 16) and group 2 (survival > 400 days, n = 16). RESULTS: Histograms of relative values in each sequence demonstrated that the tumor regions were consistently divided into high and low blood contrast enhancement, each of which could be subdivided into regions of high, low, and intermediate cell density/interstitial edema. Group 1 tumors contained greater volumes of habitats with low contrast enhancement but intermediate and high cell density (not fully necrotic) than group 2. Both leave-one-out and 10-fold cross-validation schemes demonstrated that individual patients could be correctly assigned to the short or long survival group with 81.25% accuracy. CONCLUSION: We demonstrate that novel image analytic techniques can characterize regional habitat variations in GBMs using combinations of MRI sequences. A preliminary study of 32 patients from the TCGA database found that the distribution of MRI-defined habitats varied significantly among the different survival groups. Radiologically defined ecological tumor analysis may provide valuable prognostic and predictive biomarkers in GBM and other tumors.     

Proportional Upregulation of CD97 Isoforms in Glioblastoma and Glioblastoma-Derived Brain Tumor Initiating Cells

CD97 is a novel glioma antigen that confers an invasive phenotype and poor survival in patients with glioblastoma (GBM), the most aggressive primary malignant brain tumor. The short isoform of CD97, known as EGF(1,2,5), has been shown to promote invasion and metastasis, but its role in gliomas and GBM-derived brain tumor initiating cells (BTICs) has not been studied. We sought to characterize CD97 expression among gliomas and identify the specific isoforms expressed. The short isoform of CD97 was identified in GBM and GBM-derived BTICs, but not low grade or anaplastic astrocytomas. All samples expressing the EGF(1,2,5) isoform were also found to express the EGF(1,2,3,5) isoform. These isoforms are believed to possess similar ligand binding patterns and interact with chondroitin sulfate, a component of the extracellular matrix, and the integrin α5β1. Using data acquired from the Cancer Genome Atlas (TCGA), we show that CD97 is upregulated among the classical and mesenchymal subtypes of GBM and significantly decreased among IDH1 mutant GBMs. Given its proven roles in tumor invasion, expression among aggressive genetic subtypes of GBM, and association with overall survival, CD97 is an attractive therapeutic target for patients with GBM.     

Functional temozolomide sensitivity testing of patient-specific glioblastoma stem cell cultures is predictive of clinical outcome

Serum-free culturing of patient-derived glioblastoma biopsies enrich for glioblastoma stem cells (GSCs) and is recognized as a disease-relevant model system in glioblastoma (GBM). We hypothesized that the temozolomide (TMZ) drug sensitivity of patient-derived GSC cultures correlates to clinical sensitivity patterns and has clinical predictive value in a cohort of GBM patients. To this aim, we established 51 individual GSC cultures from surgical biopsies from both treatment-naïve primary and pretreated recurrent GBM patients. The cultures were evaluated for sensitivity to TMZ over a dosing range achievable in normal clinical practice. Drug efficacy was quantified by the drug sensitivity score. MGMT-methylation status was investigated by pyrosequencing. Correlative, contingency, and survival analyses were performed for associations between experimental and clinical data. We found a heterogeneous response to temozolomide in the GSC culture cohort. There were significant differences in the sensitivity to TMZ between the newly diagnosed and the TMZ-treated recurrent disease (p <0.01). There was a moderate correlation between MGMT-status and sensitivity to TMZ (r=0.459, p=0.0009). The relationship between MGMT status and TMZ efficacy was statistically significant on multivariate analyses (p=0.0051). We found a predictive value of TMZ sensitivity in individual GSC cultures to patient survival (p=0.0089). We conclude that GSC-enriched cultures hold clinical and translational relevance by their ability to reflect the clinical heterogeneity in TMZ-sensitivity, substantiate the association between TMZ-sensitivity and MGMT-promotor methylation status and appear to have a stronger predictive value than MGMT-promotor methylation on clinical responses to TMZ.     

Molecular Predictors of Long-Term Survival in Glioblastoma Multiforme Patients

Glioblastoma multiforme (GBM) is the most common and aggressive adult primary brain cancer, with <10% of patients surviving for more than 3 years. Demographic and clinical factors (e.g. age) and individual molecular biomarkers have been associated with prolonged survival in GBM patients. However, comprehensive systems-level analyses of molecular profiles associated with long-term survival (LTS) in GBM patients are still lacking. We present an integrative study of molecular data and clinical variables in these long-term survivors (LTSs, patients surviving >3 years) to identify biomarkers associated with prolonged survival, and to assess the possible similarity of molecular characteristics between LGG and LTS GBM. We analyzed the relationship between multivariable molecular data and LTS in GBM patients from the Cancer Genome Atlas (TCGA), including germline and somatic point mutation, gene expression, DNA methylation, copy number variation (CNV) and microRNA (miRNA) expression using logistic regression models. The molecular relationship between GBM LTS and LGG tumors was examined through cluster analysis. We identified 13, 94, 43, 29, and 1 significant predictors of LTS using Lasso logistic regression from the somatic point mutation, gene expression, DNA methylation, CNV, and miRNA expression data sets, respectively. Individually, DNA methylation provided the best prediction performance (AUC = 0.84). Combining multiple classes of molecular data into joint regression models did not improve prediction accuracy, but did identify additional genes that were not significantly predictive in individual models. PCA and clustering analyses showed that GBM LTS typically had gene expression profiles similar to non-LTS GBM. Furthermore, cluster analysis did not identify a close affinity between LTS GBM and LGG, nor did we find a significant association between LTS and secondary GBM. The absence of unique LTS profiles and the lack of similarity between LTS GBM and LGG, indicates that there are multiple genetic and epigenetic pathways to LTS in GBM patients.     

Visualizing Molecular Profiles of Glioblastoma with GBM-BioDP

Validation of clinical biomarkers and response to therapy is a challenging topic in cancer research. An important source of information for virtual validation is the datasets generated from multi-center cancer research projects such as The Cancer Genome Atlas project (TCGA). These data enable investigation of genetic and epigenetic changes responsible for cancer onset and progression, response to cancer therapies, and discovery of the molecular profiles of various cancers. However, these analyses often require bulk download of data and substantial bioinformatics expertise, which can be intimidating for investigators. Here, we report on the development of a new resource available to scientists: a data base called Glioblastoma Bio Discovery Portal (GBM-BioDP). GBM-BioDP is a free web-accessible resource that hosts a subset of the glioblastoma TCGA data and enables an intuitive query and interactive display of the resultant data. This resource provides visualization tools for the exploration of gene, miRNA, and protein expression, differential expression within the subtypes of GBM, and potential associations with clinical outcome, which are useful for virtual biological validation. The tool may also enable generation of hypotheses on how therapies impact GBM molecular profiles, which can help in personalization of treatment for optimal outcome. The resource can be accessed freely at http://gbm-biodp.nci.nih.gov (a tutorial is included).     

SAMSN1 Is Highly Expressed and Associated with a Poor Survival in Glioblastoma Multiforme

Objectives

To study the expression pattern and prognostic significance of SAMSN1 in glioma.

Methods

Affymetrix and Arrystar gene microarray data in the setting of glioma was analyzed to preliminarily study the expression pattern of SAMSN1 in glioma tissues, and Hieratical clustering of gene microarray data was performed to filter out genes that have prognostic value in malignant glioma. Survival analysis by Kaplan-Meier estimates stratified by SAMSN1 expression was then made based on the data of more than 500 GBM cases provided by The Cancer Genome Atlas (TCGA) project. At last, we detected the expression of SAMSN1 in large numbers of glioma and normal brain tissue samples using Tissue Microarray (TMA). Survival analysis by Kaplan-Meier estimates in each grade of glioma was stratified by SAMSN1 expression. Multivariate survival analysis was made by Cox proportional hazards regression models in corresponding groups of glioma.

Results

With the expression data of SAMSN1 and 68 other genes, high-grade glioma could be classified into two groups with clearly different prognoses. Gene and large sample tissue microarrays showed high expression of SAMSN1 in glioma particularly in GBM. Survival analysis based on the TCGA GBM data matrix and TMA multi-grade glioma dataset found that SAMSN1 expression was closely related to the prognosis of GBM, either PFS or OS (P<0.05). Multivariate survival analysis with Cox proportional hazards regression models confirmed that high expression of SAMSN1 was a strong risk factor for PFS and OS of GBM patients.

Conclusion

SAMSN1 is over-expressed in glioma as compared with that found in normal brains, especially in GBM. High expression of SAMSN1 is a significant risk factor for the progression free and overall survival of GBM.     

Genetic variation in RPS6KA1, RPS6KA2, RPS6KB1, RPS6KB2, and PDK1 and risk of colon or rectal cancer

RPS6KA1, RPS6KA2, RPS6KB1, RPS6KB2, and PDK1 are involved in several pathways central to the carcinogenic process, including regulation of cell growth, insulin, and inflammation. We evaluated genetic variation in their candidate genes to obtain a better understanding of their association with colon and rectal cancer. We used data from two population-based case-control studies of colon (n=1574 cases, 1940 controls) and rectal (n=791 cases, 999 controls) cancer. We observed genetic variation in RPS6KA1, RPS6KA2, and PRS6KB2 were associated with risk of developing colon cancer while only genetic variation in RPS6KA2 was associated with altering risk of rectal cancer. These genes also interacted significantly with other genes operating in similar mechanisms, including Akt1, FRAP1, NFκB1, and PIK3CA. Assessment of tumor markers indicated that these genes and this pathway may importantly contributed to CIMP+ tumors and tumors with KRAS2 mutations. Our findings implicate these candidate genes in the etiology of colon and rectal cancer and provide information on how these genes operate with other genes in the pathway. Our data further suggest that this pathway may lead to CIMP+ and KRAS2-mutated tumors.     

Combined PTEN Mutation and Protein Expression Associate with Overall and Disease-Free Survival of Glioblastoma Patients

Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) is a tumor suppressor commonly inactivated in glioblastoma multiforme (GBM), but the prognostic significance of PTEN remains controversial. Here, we demon- strate significant prognostic value of combined PTEN mutation and expression for the survival of patients with GBM on the basis of analysis of large-scale cancer genomic data. PTEN nonsense mutations associated with sig- nificantly shorter disease-free survival and overexpression of PTEN protein linked to shorter disease-free and overall survival of patients with GBM. PTEN nonsense mutations correlated with decreased p53 and Gata3 protein levels and increased genomic instability in human GBM tissues. Expression of nonsense PTEN mutant decreased p53 and Gata3 levels, producing increased DNA damage both in vitro and in vivo. Mice carrying xenograft tumors with nonsense PTEN mutant displayed significantly shorter survival. Our data demonstrated the prognostic value of combined PTEN mutation and protein expression for patients with GBM and highlighted distinct biologic effects of nonsense and missense mutations of PTEN.