Translational Validation of Personalized Treatment Strategy Based on Genetic Characteristics of Glioblastoma

Glioblastoma (GBM) heterogeneity in the genomic and phenotypic properties has potentiated personalized approach against specific therapeutic targets of each GBM patient. The Cancer Genome Atlas (TCGA) Research Network has been established the comprehensive genomic abnormalities of GBM, which sub-classified GBMs into 4 different molecular subtypes. The molecular subtypes could be utilized to develop personalized treatment strategy for each subtype. We applied a classifying method, NTP (Nearest Template Prediction) method to determine molecular subtype of each GBM patient and corresponding orthotopic xenograft animal model. The models were derived from GBM cells dissociated from patient''s surgical sample. Specific drug candidates for each subtype were selected using an integrated pharmacological network database (PharmDB), which link drugs with subtype specific genes. Treatment effects of the drug candidates were determined by in vitro limiting dilution assay using patient-derived GBM cells primarily cultured from orthotopic xenograft tumors. The consistent identification of molecular subtype by the NTP method was validated using TCGA database. When subtypes were determined by the NTP method, orthotopic xenograft animal models faithfully maintained the molecular subtypes of parental tumors. Subtype specific drugs not only showed significant inhibition effects on the in vitro clonogenicity of patient-derived GBM cells but also synergistically reversed temozolomide resistance of MGMT-unmethylated patient-derived GBM cells. However, inhibitory effects on the clonogenicity were not totally subtype-specific. Personalized treatment approach based on genetic characteristics of each GBM could make better treatment outcomes of GBMs, although more sophisticated classifying techniques and subtype specific drugs need to be further elucidated.     

A Simplified Approach for the Molecular Classification of Glioblastomas

Glioblastoma (GBM) is the most common malignant primary brain tumors in adults and exhibit striking aggressiveness. Although GBM constitute a single histological entity, they exhibit considerable variability in biological behavior, resulting in significant differences in terms of prognosis and response to treatment. In an attempt to better understand the biology of GBM, many groups have performed high-scale profiling studies based on gene or protein expression. These studies have revealed the existence of several GBM subtypes. Although there remains to be a clear consensus, two to four major subtypes have been identified. Interestingly, these different subtypes are associated with both differential prognoses and responses to therapy. In the present study, we investigated an alternative immunohistochemistry (IHC)-based approach to achieve a molecular classification for GBM. For this purpose, a cohort of 100 surgical GBM samples was retrospectively evaluated by immunohistochemical analysis of EGFR, PDGFRA and p53. The quantitative analysis of these immunostainings allowed us to identify the following two GBM subtypes: the “Classical-like” (CL) subtype, characterized by EGFR-positive and p53- and PDGFRA-negative staining and the “Proneural-like” (PNL) subtype, characterized by p53- and/or PDGFRA-positive staining. This classification represents an independent prognostic factor in terms of overall survival compared to age, extent of resection and adjuvant treatment, with a significantly longer survival associated with the PNL subtype. Moreover, these two GBM subtypes exhibited different responses to chemotherapy. The addition of temozolomide to conventional radiotherapy significantly improved the survival of patients belonging to the CL subtype, but it did not affect the survival of patients belonging to the PNL subtype. We have thus shown that it is possible to differentiate between different clinically relevant subtypes of GBM by using IHC-based profiling, a method that is advantageous in its ease of daily implementation and in large-scale clinical application.     

G-Cimp Status Prediction Of Glioblastoma Samples Using mRNA Expression Data

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.     

Increased microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas

Glioblastoma (GBM) is a highly malignant brain tumor with a dismal prognosis. Gene expression profiling of GBM has revealed clinically relevant tumor subtypes, and this provides exciting opportunities to better understand disease pathogenesis. Results from an increasing number of studies demonstrate a role for the immune response in cancer progression, yet it is unclear how the immune response differs across tumor subtypes and how it affects outcome. Utilizing gene expression data from The Cancer Genome Atlas Project and the Gene Expression Omnibus database, we demonstrate an enrichment of immune response-related gene expression in the mesenchymal subtype of adult GBM (n = 173) and pediatric high-grade gliomas (n = 53). In an independent cohort of pediatric astrocytomas (n = 24) from UCSF, we stratified tumors into subtypes and confirmed these findings. Using novel immune cell-specific gene signatures we demonstrate selective enrichment of microglia/macrophage-related genes in adult and pediatric GBM tumors of the mesenchymal subtype. Furthermore, immunostaining of adult GBM tumors showed significantly higher cell numbers of microglia/macrophages in mesenchymal versus non-mesenchymal tumors (p = 0.04). Interestingly, adult GBM tumors with the shortest survival had significant enrichment of microglia/macrophage-related genes but this was not true for pediatric GBMs. Consistent with an association with poor outcome, immune response-related genes were highly represented in an adult poor prognosis gene signature, with the expression of genes related to macrophage recruitment and activation being most strongly associated with survival (p<0.05) using CoxBoost multivariate modeling. Using a microglia/macrophage high gene signature derived from quantification of tumor-infiltrating cells in adult GBM, we identified enrichment of genes characteristic of CD4 T cells, granulocytes, and microglia/macrophages (n = 573). These studies support a role for the immune response, particularly the microglia/macrophage response, in the biology of an important subset of GBM. Identification of this subset may be important for future therapeutic stratification.     

AKT Pathway Genes Define 5 Prognostic Subgroups in Glioblastoma

Activity of GFR/PI3K/AKT pathway inhibitors in glioblastoma clinical trials has not been robust. We hypothesized variations in the pathway between tumors contribute to poor response. We clustered GBM based on AKT pathway genes and discovered new subtypes then characterized their clinical and molecular features. There are at least 5 GBM AKT subtypes having distinct DNA copy number alterations, enrichment in oncogenes and tumor suppressor genes and patterns of expression for PI3K/AKT/mTOR signaling components. Gene Ontology terms indicate a different cell of origin or dominant phenotype for each subgroup. Evidence suggests one subtype is very sensitive to BCNU or CCNU (median survival 5.8 vs. 1.5 years; BCNU/CCNU vs other treatments; respectively). AKT subtyping advances previous approaches by revealing additional subgroups with unique clinical and molecular features. Evidence indicates it is a predictive marker for response to BCNU or CCNU and PI3K/AKT/mTOR pathway inhibitors. We anticipate Akt subtyping may help stratify patients for clinical trials and augment discovery of class-specific therapeutic targets.     

Prognosis of Glioblastoma With Oligodendroglioma Component is Associated With the IDH1 Mutation and MGMT Methylation Status

Glioblastoma (GBM) with oligodendroglioma component (GBMO) is a newly described GBM subtype in the 2007 World Health Organization classification. However, its biological and genetic characteristics are largely unknown. We investigated the clinicopathological and molecular features of 34 GBMOs and compared the survival rate of these patients with those of patients with astrocytoma, oligodendroglioma, anaplastic oligoastrocytoma (AOA), and conventional GBMs in our hospital. GBMO could be divided into two groups based on the presence of an IDH1 mutation. The IDH1 mutation was more frequently found in secondary GBMO, which had lower frequencies of EGFR amplification but higher MGMT methylation than the wild type IDH1 group, and patients with mutant IDH1 GBMO were on average younger than those with wild-type IDH1. Therefore, GBMO is a clinically and molecularly heterogeneous subtype, largely belonging to a proneural and classical subtype of GBM. The survival rate of GBMO patients itself was worse than that of AOA patients but not significantly better than that of conventional GBM patients. GBMO survival was independent of the dominant histopathological subtype i.e., astrocyte-dominant or oligodendroglioma -dominant, but it was significantly associated with the IDH1 mutation and MGMT methylation status. Therefore, GBMO should be regarded as a separate entity from AOA and must be classified as a subtype of GBM. However, further study is needed to determine whether it is a pathologic variant or a pattern of GBM because GBMO has a similar prognosis to conventional GBMs.     

Identification of Variants in Primary and Recurrent Glioblastoma Using a Cancer-Specific Gene Panel and Whole Exome Sequencing

Glioblastoma (GBM) is an aggressive, malignant brain tumor typically resulting in death of the patient within one year following diagnosis; and those who survive beyond this point usually present with tumor recurrence within two years (5-year survival is 5%). The genetic heterogeneity of GBM has made the molecular characterization of these tumors an area of great interest and has led to identification of molecular subtypes in GBM. The availability of sequencing platforms that are both fast and economical can further the adoption of tumor sequencing in the clinical environment, potentially leading to identification of clinically actionable genetic targets. In this pilot study, comprised of triplet samples of normal blood, primary tumor, and recurrent tumor samples from three patients; we compared the ability of Illumina whole exome sequencing (ExomeSeq) and the Ion AmpliSeq Comprehensive Cancer Panel (CCP) to identify somatic variants in patient-paired primary and recurrent tumor samples. Thirteen genes were found to harbor variants, the majority of which were exclusive to the ExomeSeq data. Surprisingly, only two variants were identified by both platforms and they were located within the PTCH1 and NF1 genes. Although preliminary in nature, this work highlights major differences in variant identification in data generated from the two platforms. Additional studies with larger samples sizes are needed to further explore the differences between these technologies and to enhance our understanding of the clinical utility of panel based platforms in genomic profiling of brain tumors.     

FOXO1 associated with sensitivity to chemotherapy drugs and glial-mesenchymal transition in glioma

Mesenchymal subtype of glioblastoma (GBM), identified as one of four clinically relevant molecular subtypes, has worst prognosis because of its close relation with the malignant biological properties induced by glial-mesenchymal transition (GMT). However, the molecular mechanism of GMT and its characterized molecule of GBM have not been studied. Forkhead box protein O1 (FOXO1) is at a convergence point of receptor tyrosine kinase signaling as one of the three core pathways implicated in GBM. Our previous study indicated that the inactivation of FOXO1 involved in the inhibition of GMT is an independent prognosis factor of GBM. In this study, we will further confirm the role of FOXO1 in GMT through cytological experiments to clarify how FOXO1 regulates GMT and its clinical significance. We established virus-infected FOXO1 overexpression and FOXO1 knockdown cells of U373 MG and U251 mediated by lentivirus, based on the effect of which FOXO1-correlated-GMT experiments were performed in vitro and in vivo. Our data suggested that FOXO1 played a crucial role in resistance to TMZ, BCNU, and CDDP; migration and invasion; and stem cell properties of glioma cells. FOXO1 may serve as a targeted biomarker for prediction of sensitivity to chemotherapy drugs, metastasis, and prognosis, which provides a new idea for mesenchymal GBM treatment.     

Genome wide DNA copy number analysis of serous type ovarian carcinomas identifies genetic markers predictive of clinical outcome

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups.     

Glioblastoma models reveal the connection between adult glial progenitors and the proneural phenotype

Background

Tumor heterogeneity is a major obstacle for finding effective treatment of Glioblastoma (GBM). Based on global expression analysis, GBM can be classified into distinct subtypes: Proneural, Neural, Classical and Mesenchymal. The signatures of these different tumor subtypes may reflect the phenotypes of cells giving rise to them. However, the experimental evidence connecting any specific subtype of GBM to particular cells of origin is lacking. In addition, it is unclear how different genetic alterations interact with cells of origin in determining tumor heterogeneity. This issue cannot be addressed by studying end-stage human tumors.

Methodology/Principal Findings

To address this issue, we used retroviruses to deliver transforming genetic lesions to glial progenitors in adult mouse brain. We compared the resulting tumors to human GBM. We found that different initiating genetic lesions gave rise to tumors with different growth rates. However all mouse tumors closely resembled the human Proneural GBM. Comparative analysis of these mouse tumors allowed us to identify a set of genes whose expression in humans with Proneural GBM correlates with survival.

Conclusions/Significance

This study offers insights into the relationship between adult glial progenitors and Proneural GBM, and allows us to identify molecular alterations that lead to more aggressive tumor growth. In addition, we present a new preclinical model that can be used to test treatments directed at a specific type of GBM in future studies.     

Small sample issues for microarray-based classification

In order to study the molecular biological differences between normal and diseased tissues, it is desirable to perform classification among diseases and stages of disease using microarray-based gene-expression values. Owing to the limited number of microarrays typically used in these studies, serious issues arise with respect to the design, performance and analysis of classifiers based on microarray data. This paper reviews some fundamental issues facing small-sample classification: classification rules, constrained classifiers, error estimation and feature selection. It discusses both unconstrained and constrained classifier design from sample data, and the contributions to classifier error from constrained optimization and lack of optimality owing to design from sample data. The difficulty with estimating classifier error when confined to small samples is addressed, particularly estimating the error from training data. The impact of small samples on the ability to include more than a few variables as classifier features is explained.     

A mathematical methodology for determining the temporal order of pathway alterations arising during gliomagenesis

Human cancer is caused by the accumulation of genetic alterations in cells. Of special importance are changes that occur early during malignant transformation because they may result in oncogene addiction and thus represent promising targets for therapeutic intervention. We have previously described a computational approach, called Retracing the Evolutionary Steps in Cancer (RESIC), to determine the temporal sequence of genetic alterations during tumorigenesis from cross-sectional genomic data of tumors at their fully transformed stage. Since alterations within a set of genes belonging to a particular signaling pathway may have similar or equivalent effects, we applied a pathway-based systems biology approach to the RESIC methodology. This method was used to determine whether alterations of specific pathways develop early or late during malignant transformation. When applied to primary glioblastoma (GBM) copy number data from The Cancer Genome Atlas (TCGA) project, RESIC identified a temporal order of pathway alterations consistent with the order of events in secondary GBMs. We then further subdivided the samples into the four main GBM subtypes and determined the relative contributions of each subtype to the overall results: we found that the overall ordering applied for the proneural subtype but differed for mesenchymal samples. The temporal sequence of events could not be identified for neural and classical subtypes, possibly due to a limited number of samples. Moreover, for samples of the proneural subtype, we detected two distinct temporal sequences of events: (i) RAS pathway activation was followed by TP53 inactivation and finally PI3K2 activation, and (ii) RAS activation preceded only AKT activation. This extension of the RESIC methodology provides an evolutionary mathematical approach to identify the temporal sequence of pathway changes driving tumorigenesis and may be useful in guiding the understanding of signaling rearrangements in cancer development.     

A glycolysis-based ten-gene signature correlates with the clinical outcome,molecular subtype and IDH1 mutation in glioblastoma

Reprogrammed metabolism is a hallmark of cancer. Glioblastoma (GBM) tumor cells predominantly utilize aerobic glycolysis for the biogenesis of energy and intermediate nutrients. However, in GBM, the clinical significance of glycolysis and its underlying relations with the molecular features such as IDH1 mutation and subtype have not been elucidated yet. Herein, based on glioma datasets including TCGA (The Cancer Genome Atlas), REMBRANDT (Repository for Molecular Brain Neoplasia Data) and GSE16011, we established a glycolytic gene expression signature score (GGESS) by incorporating ten glycolytic genes. Then we performed survival analyses and investigated the correlations between GGESS and IDH1 mutation as well as the molecular subtypes in GBMs. The results showed that GGESS independently predicted unfavorable prognosis and poor response to chemotherapy of GBM patients. Notably, GGESS was high in GBMs of mesenchymal subtype but low in IDH1-mutant GBMs. Furthermore, we found that the promoter regions of tumor-promoting glycolytic genes were hypermethylated in IDH1-mutant GBMs. Finally, we found that high GGESS also predicted poor prognosis and poor response to chemotherapy when investigating IDH1-wildtype GBM patients only. Collectively, glycolysis represented by GGESS predicts unfavorable clinical outcome of GBM patients and is closely associated with mesenchymal subtype and IDH1 mutation in GBMs.     

GBP5 drives malignancy of glioblastoma via the Src/ERK1/2/MMP3 pathway

Guanylate binding proteins (GBPs), a family of interferon-inducible large GTPase, play a pivotal role in cell-autonomous immunity and tumor malignant transformation. Glioblastoma (GBM) is the most prevalent and lethal primary brain tumor in adults. Here we show that GBP5 was highly expressed in GBM cell lines and in clinical samples, especially in the mesenchymal subtype. The expression levels of GBP5 were negatively correlated with the prognosis of GBM patients. Overexpression of GBP5 promoted the proliferation, migration, and invasion of GBM cells in vitro and in vivo. In contrast, silencing GBP5 by RNA interference exhibited the opposite effects. Consequently, targeting GBP5 in GBM cells resulted in impaired tumor growth and prolonged survival time of mice with GBM tumors. We further identified that the Src/ERK1/2/MMP3 axis was essential for GBP5-promoted GBM aggressiveness. These findings suggest that GBP5 may represent a novel target for GBM intervention.Subject terms: CNS cancer, Oncogenes     

<Emphasis Type="Italic">Ficus carica</Emphasis> Latex Prevents Invasion Through Induction of Let-7d Expression in GBM Cell Lines

Glioblastoma multiforme (GBM) is one of the deadliest human malignancies. A cure for GBM remains elusive, and the overall survival time is less than 1 year. Thus, the development of more efficient therapeutic approaches for the treatment of these patients is required. Induction of tumor cell death by certain phytochemicals derived from medicinal herbs and dietary plants has become a new frontier for cancer therapy research. Although the cancer suppressive effect of Ficus carica (fig) latex (FCL) has been determined in a few cancer types, the effect of this latex on GBM tumors has not been investigated. Therefore, in the current study, the anti-proliferative activity of FCL and the effect of the FCL–temozolomide (TMZ) combination were tested in the T98G, U-138 MG, and U-87 MG GBM cell lines using the WST-1 assay. The mechanism of cell death was analyzed using Annexin-V/FITC and TUNEL assays, and the effect of FCL on invasion was tested using the chick chorioallantoic membrane assay. To determine the effect of FCL on GBM progression, the expression levels of 40 GBM associated miRNAs were analyzed in T98G cells using RT-qPCR. According to the obtained data, FCL causes cell death in GBM cells with different responses to TMZ, and this effect is synergistically increased in combination with TMZ. In addition, the current study is the first to demonstrate the effect of FCL on modulation of let-7d expression, which may be an important underlying mechanism of the anti-invasive effect of this extract.     

Establishment and Characterization of Primary Glioblastoma Cell Lines from Fresh and Frozen Material: A Detailed Comparison

Background

Development of clinically relevant tumor model systems for glioblastoma multiforme (GBM) is important for advancement of basic and translational biology. High molecular heterogeneity of GBM tumors is well recognized, forming the rationale for molecular tests required before administration of several of the novel therapeutics rapidly entering the clinics. One model that has gained wide acceptance is the primary cell culture model. The laborious and time consuming process is rewarded with a relative high success rate (about 60%). We here describe and evaluate a very simple cryopreservation procedure for GBM tissue prior to model establishment that will considerably reduce the logistic complexity.

Methods

Twenty-seven GBM samples collected ad hoc were prepared for primary cell culture freshly from surgery (#1) and after cryopreservation (#2).

Results

Take rates after cryopreservation (59%) were as satisfactory as from fresh tissue (63%; p = 1.000). We did not observe any relevant molecular or phenotypic differences between cell lines established from fresh or vitally frozen tissue. Further, sensitivity both towards standard chemotherapeutic agents (Temozolomide, BCNU and Vincristine) and novel agents like the receptor tyrosine kinase inhibitor Imatinib did not differ.

Conclusions

Our simple cryopreservation procedure facilitates collection, long-time storage and propagation (modeling) of clinical GBM specimens (potentially also from distant centers) for basic research, (pre-) clinical studies of novel therapies and individual response prediction.