Aiguo Li

Epigenetic-Mediated Dysfunction of the Bone Morphogenetic Protein Pathway Inhibits Differentiation of Glioblastoma-Initiating Cells

Despite similarities between tumor-initiating cells with stem-like properties (TICs) and normal neural stem cells, we hypothesized that there may be differences in their differentiation potentials. We now demonstrate that both bone morphogenetic protein (BMP)-mediated and ciliary neurotrophic factor (CNTF)-mediated Jak/STAT-dependent astroglial differentiation is impaired due to EZH2-dependent epigenetic silencing of BMP receptor 1B (BMPR1B) in a subset of glioblastoma TICs. Forced expression of BMPR1B either by transgene expression or demethylation of the promoter restores their differentiation capabilities and induces loss of their tumorigenicity. We propose that deregulation of the BMP developmental pathway in a subset of glioblastoma TICs contributes to their tumorigenicity both by desensitizing TICs to normal differentiation cues and by converting otherwise cytostatic signals to proproliferative signals.

Unsupervised Analysis of Transcriptomic Profiles Reveals Six Glioma Subtypes

Gliomas are the most common type of primary brain tumors in adults and a significant cause of cancer-related mortality. Defining glioma subtypes based on objective genetic and molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications based on gene expression data have been attempted in the past with varying success and with only some concordance between studies, possibly due to inherent bias that can be introduced through the use of analytic methodologies that make a priori selection of genes before classification. To overcome this potential source of bias, we have applied two unsupervised machine learning methods to genome-wide gene expression profiles of 159 gliomas, thereby establishing a robust glioma classification model relying only on the molecular data. The model predicts for two major groups of gliomas (oligodendroglioma-rich and glioblastoma-rich groups) separable into six hierarchically nested subtypes. We then identified six sets of classifiers that can be used to assign any given glioma to the corresponding subtype and validated these classifiers using both internal (189 additional independent samples) and two external data sets (341 patients). Application of the classification system to the external glioma data sets allowed us to identify previously unrecognized prognostic groups within previously published data and within The Cancer Genome Atlas glioblastoma samples and the different biological pathways associated with the different glioma subtypes offering a potential clue to the pathogenesis and possibly therapeutic targets for tumors within each subtype.

Genomic changes and gene expression profiles reveal that established glioma cell lines are poorly representative of primary human gliomas.

Genetic aberrations, such as gene amplification, deletions, and loss of heterozygosity, are hallmarks of cancer and are thought to be major contributors to the neoplastic process. Established cancer cell lines have been the primary in vitro and in vivo models for cancer for more than 2 decades; however, few such cell lines have been extensively characterized at the genomic level. Here, we present a high-resolution genome-wide chromosomal alteration and gene expression analyses of five of the most commonly used glioma cell lines and compare the findings with those observed in 83 primary human gliomas. Although genomic alterations known to occur in primary tumors were identified in the cell lines, we also observed several novel recurrent aberrations in the glioma cell lines that are not frequently represented in primary tumors. Additionally, a global gene expression cluster distinct from primary tumors was identified in the glioma cell lines. Our results indicate that established cell lines are generally a poor representation of primary tumor biology, presenting a host of genomic and gene expression changes not observed in primary tissues, although some discrete features of glioma biology were conserved in the established cell lines. Refined maps of genetic alterations and transcriptional divergence from the original tumor type, such as the one presented here, may help serve as a guideline for a more biologically rational and clinically relevant selection of the most appropriate glioma model for a given experiment. (Mol Cancer Res 2008;6(1):21–30)

Effect of brain- and tumor-derived connective tissue growth factor on glioma invasion.

BACKGROUND Tumor cell invasion is the principal cause of treatment failure and death among patients with malignant gliomas. Connective tissue growth factor (CTGF) has been previously implicated in cancer metastasis and invasion in various tumors. We explored the mechanism of CTGF-mediated glioma cell infiltration and examined potential therapeutic targets. METHODS Highly infiltrative patient-derived glioma tumor-initiating or tumor stem cells (TIC/TSCs) were harvested and used to explore a CTGF-induced signal transduction pathway via luciferase reporter assays, chromatin immunoprecipitation (ChIP), real-time polymerase chain reaction, and immunoblotting. Treatment of TIC/TSCs with small-molecule inhibitors targeting integrin β1 (ITGB1) and the tyrosine kinase receptor type A (TrkA), and short hairpin RNAs targeting CTGF directly were used to reduce the levels of key protein components of CTGF-induced cancer infiltration. TIC/TSC infiltration was examined in real-time cell migration and invasion assays in vitro and by immunohistochemistry and in situ hybridization in TIC/TSC orthotopic xenograft mouse models (n = 30; six mice per group). All statistical tests were two-sided. RESULTS Treatment of TIC/TSCs with CTGF resulted in CTGF binding to ITGB1-TrkA receptor complexes and nuclear factor kappa B (NF-κB) transcriptional activation as measured by luciferase reporter assays (mean relative luciferase activity, untreated vs CTGF(200 ng/mL): 0.53 vs 1.87, difference = 1.34, 95% confidence interval [CI] = 0.69 to 2, P < .001). NF-κB activation resulted in binding of ZEB-1 to the E-cadherin promoter as demonstrated by ChIP analysis with subsequent E-cadherin suppression (fold increase in ZEB-1 binding to the E-cadherin promoter region: untreated + ZEB-1 antibody vs CTGF(200 ng/mL) + ZEB-1 antibody: 1.5 vs 6.4, difference = 4.9, 95% CI = 4.8 to 5.0, P < .001). Immunohistochemistry and in situ hybridization revealed that TrkA is selectively expressed in the most infiltrative glioma cells in situ and that the surrounding reactive astrocytes secrete CTGF. CONCLUSION A CTGF-rich microenvironment facilitates CTGF-ITGB1-TrkA complex activation in TIC/TSCs, thereby increasing the invasiveness of malignant gliomas.

Prediction of Associations between microRNAs and Gene Expression in Glioma Biology

Despite progress in the determination of miR interactions, their regulatory role in cancer is only beginning to be unraveled. Utilizing gene expression data from 27 glioblastoma samples we found that the mere knowledge of physical interactions between specific mRNAs and miRs can be used to determine associated regulatory interactions, allowing us to identify 626 associated interactions, involving 128 miRs that putatively modulate the expression of 246 mRNAs. Experimentally determining the expression of miRs, we found an over-representation of over(under)-expressed miRs with various predicted mRNA target sequences. Such significantly associated miRs that putatively bind over-expressed genes strongly tend to have binding sites nearby the 3′UTR of the corresponding mRNAs, suggesting that the presence of the miRs near the translation stop site may be a factor in their regulatory ability. Our analysis predicted a significant association between miR-128 and the protein kinase WEE1, which we subsequently validated experimentally by showing that the over-expression of the naturally under-expressed miR-128 in glioma cells resulted in the inhibition of WEE1 in glioblastoma cells.

Age-specific signatures of glioblastoma at the genomic, genetic, and epigenetic levels.

Age is a powerful predictor of survival in glioblastoma multiforme (GBM) yet the biological basis for the difference in clinical outcome is mostly unknown. Discovering genes and pathways that would explain age-specific survival difference could generate opportunities for novel therapeutics for GBM. Here we have integrated gene expression, exon expression, microRNA expression, copy number alteration, SNP, whole exome sequence, and DNA methylation data sets of a cohort of GBM patients in The Cancer Genome Atlas (TCGA) project to discover age-specific signatures at the transcriptional, genetic, and epigenetic levels and validated our findings on the REMBRANDT data set. We found major age-specific signatures at all levels including age-specific hypermethylation in polycomb group protein target genes and the upregulation of angiogenesis-related genes in older GBMs. These age-specific differences in GBM, which are independent of molecular subtypes, may in part explain the preferential effects of anti-angiogenic agents in older GBM and pave the way to a better understanding of the unique biology and clinical behavior of older versus younger GBMs.

Correlation Analysis between Single-Nucleotide Polymorphism and Expression Arrays in Gliomas Identifies Potentially Relevant Target Genes

Primary brain tumors are a major cause of cancer mortality in the United States. Therapy for gliomas, the most common type of primary brain tumors, remains suboptimal. The development of improved therapeutics will require greater knowledge of the biology of gliomas at both the genomic and transcriptional levels. We have previously reported whole genome profiling of chromosome copy number alterations (CNA) in gliomas, and now present our findings on how those changes may affect transcription of genes that may be involved in tumor induction and progression. By calculating correlation values of mRNA expression versus DNA copy number average in a moving window around a given RNA probe set, biologically relevant information can be gained that is obscured by the analysis of a single data type. Correlation coefficients ranged from -0.6 to 0.7, highly significant when compared with previous studies. Most correlated genes are located on chromosomes 1, 7, 9, 10, 13, 14, 19, 20, and 22, chromosomes known to have genomic alterations in gliomas. Additionally, we were able to identify CNAs whose gene expression correlation suggests possible epigenetic regulation. This analysis revealed a number of interesting candidates such as CXCL12, PTER, and LRRN6C, among others. The results have been verified using real-time PCR and methylation sequencing assays. These data will further help differentiate genes involved in the induction and/or maintenance of the tumorigenic process from those that are mere passenger mutations, thereby enriching for a population of potentially new therapeutic molecular targets.

Identification of molecular pathways facilitating glioma cell invasion in situ.

Gliomas are mostly incurable secondary to their diffuse infiltrative nature. Thus, specific therapeutic targeting of invasive glioma cells is an attractive concept. As cells exit the tumor mass and infiltrate brain parenchyma, they closely interact with a changing micro-environmental landscape that sustains tumor cell invasion. In this study, we used a unique microarray profiling approach on a human glioma stem cell (GSC) xenograft model to explore gene expression changes in situ in Invading Glioma Cells (IGCs) compared to tumor core, as well as changes in host cells residing within the infiltrated microenvironment relative to the unaffected cortex. IGCs were found to have reduced expression of genes within the extracellular matrix compartment, and genes involved in cell adhesion, cell polarity and epithelial to mesenchymal transition (EMT) processes. The infiltrated microenvironment showed activation of wound repair and tissue remodeling networks. We confirmed by protein analysis the downregulation of EMT and polarity related genes such as CD44 and PARD3 in IGCs, and EFNB3, a tissue-remodeling agent enriched at the infiltrated microenvironment. OLIG2, a proliferation regulator and glioma progenitor cell marker upregulated in IGCs was found to function in enhancing migration and stemness of GSCs. Overall, our results unveiled a more comprehensive picture of the complex and dynamic cell autonomous and tumor-host interactive pathways of glioma invasion than has been previously demonstrated. This suggests targeting of multiple pathways at the junction of invading tumor and microenvironment as a viable option for glioma therapy.

Gliomagenesis Arising from Pten- and Ink4a/Arf-Deficient Neural Progenitor Cells Is Mediated by the p53-Fbxw7/Cdc4 Pathway, Which Controls c-Myc

Glioblastoma multiforme is the most common type of primary malignant brain tumor and may arise from a cell with neural stem-like properties. Deregulation of the retinoblastoma, phosphoinositide-3 kinase (PI3K), and p53 pathways are molecular hallmarks of this disease. Recent work has shown that p53(-/-)Pten(-/-) mice form gliomas in a c-Myc-dependent manner. To explore the role of the INK4A/ARF locus and Pten deletions in gliomagenesis, we generated Pten(-/-)Ink4a/Arf(-/-) mouse neural stem cells (mNSC) and such cells were highly proliferative, self-renewing, relatively refractory to differentiation, and induced both low- and high-grade glioma formation in vivo. In contrast to p53(-/-) Pten(-/-) mNSCs, however, Pten(-/-)Ink4a/Arf(-/-) mNSCs do not express appreciable levels of c-Myc in vitro, although glioma stem cells derived from thesecells did. Sequencing of Pten(-/-)Ink4a/Arf(-/-) mNSC-derived tumors revealed spontaneous mutations in Tp53 in vivo with subsequent downregulation of Fbxw7. Expression of p53 mutants in Pten(-/-)Ink4a/Arf(-/-) mNSC or knockdown of Fbxw7 resulted in reexpression of c-Myc with enhanced Pten(-/-)Ink4a/Arf(-/-) mNSC tumorigenecity. We propose that p53 mutations contribute to gliomagenesis by both allowing the overexpression of c-Myc through downregulation of Fbxw7 and by protecting against c-Myc-induced apoptosis.

FastMEDUSA: a parallelized tool to infer gene regulatory networks.

MOTIVATION In order to construct gene regulatory networks of higher organisms from gene expression and promoter sequence data efficiently, we developed FastMEDUSA. In this parallelized version of the regulatory network-modeling tool MEDUSA, expression and sequence data are shared among a user-defined number of processors on a single multi-core machine or cluster. Our results show that FastMEDUSA allows a more efficient utilization of computational resources. While the determination of a regulatory network of brain tumor in Homo sapiens takes 12 days with MEDUSA, FastMEDUSA obtained the same results in 6 h by utilizing 100 processors. AVAILABILITY Source code and documentation of FastMEDUSA are available at https://wiki.nci.nih.gov/display/NOBbioinf/FastMEDUSA