Molecular Subtypes Of Glioblastoma Multiforme Research Articles

Identification of a novel glioblastoma multiforme molecular subtype with poor prognosis and high immune infiltration based on oxidative stress-related genes.

Glioblastoma multiforme (GBM) is a highly malignant primary brain tumor with a poor prognosis. Reactive oxygen species that accumulate during tumorigenesis can cause oxidative stress (OS), which plays a crucial role in cancer cell survival. Clinical and transcriptome data of TCGA-GBM dataset from UCSC Xena database were analyzed. Consensus clustering analysis was conducted to identify OS-related molecular subtypes for GBM. The immune infiltrate level between subtypes were characterized by ESTIMATE algorithm. Differentially expressed genes (DEGs) between subtypes were screened by DESeq2 package. Two OS-related molecular subtypes of GBM were identified, and cluster 2 had poorer overall survival and higher immune infiltration levels than cluster 1. Enrichment analysis showed that 54 DEGs in cluster 2 were significantly enriched in cytokine/chemokine-related functions or pathways. Ten hub genes (CSF2, CSF3, CCL7, LCN2, CXCL6, MMP8, CCR8, TNFSF11, IL22RA2, and ORM1) were identified in GBM subtype 2 through protein-protein interaction network, most of which were positively correlated with immune factors and immune checkpoints. A total of 55 small molecule drugs obtained from drug gene interaction database (DGIdb) may have potential therapeutic effects in GBM subtype 2 patients. Our study identified 10 hub genes as potential therapeutic targets in GBM subtype 2 patients, who have poorer overall survival and higher immune infiltration levels. These findings could pave the way for new treatments for this aggressive form of brain cancer.

Targeting GBM with an Oncolytic Picornavirus SVV-001 alone and in combination with fractionated Radiation in a Novel Panel of Orthotopic PDX models

BackgroundAnimal models representing different molecular subtypes of glioblastoma multiforme (GBM) is desired for developing new therapies. SVV-001 is an oncolytic virus selectively targeting cancer cells. It’s capacity of passing through the blood brain barrier makes is an attractive novel approach for GBM.Materials and methods23 patient tumor samples were implanted into the brains of NOD/SCID mice (1 × 105 cells/mouse). Tumor histology, gene expression (RNAseq), and growth rate of the developed patient-derived orthotopic xenograft (PDOX) models were compared with the originating patient tumors during serial subtransplantations. Anti-tumor activities of SVV-001 were examined in vivo; and therapeutic efficacy validated in vivo via single i.v. injection (1 × 1011 viral particle) with or without fractionated (2 Gy/day x 5 days) radiation followed by analysis of animal survival times, viral infection, and DNA damage.ResultsPDOX formation was confirmed in 17/23 (73.9%) GBMs while maintaining key histopathological features and diffuse invasion of the patient tumors. Using differentially expressed genes, we subclassified PDOX models into proneural, classic and mesenchymal groups. Animal survival times were inversely correlated with the implanted tumor cells. SVV-001 was active in vitro by killing primary monolayer culture (4/13 models), 3D neurospheres (7/13 models) and glioma stem cells. In 2/2 models, SVV-001 infected PDOX cells in vivo without harming normal brain cells and significantly prolonged survival times in 2/2 models. When combined with radiation, SVV-001 enhanced DNA damages and further prolonged animal survival times.ConclusionA panel of 17 clinically relevant and molecularly annotated PDOX modes of GBM is developed, and SVV-001 exhibited strong anti-tumor activities in vitro and in vivo.

Construction of Molecular Subtypes and Related Prognostic and Immune Response Models Based on M2 Macrophages in Glioblastoma.

ObjectivesTo identify the molecular subtypes of glioblastoma multiforme (GBM) related to M2 macrophage-based prognostic genes, then to preliminarily explore their biological functions and construct immunotherapy response gene models.Material and MethodsWe used R language to analyze GBM microarray data, and other tools, including xCell and CIBERSORTx, to identify subtypes of GBM that related to M2 macrophages. The process started with the exploration of biological functions of the two subtypes by pathway analyses and GSEA, and continued with a combined procedure of constructing an M2 macrophage-related prognostic gene model and exploring the immune treatment response for GBM.ResultsA high abundance of M2 macrophages in GBM was associated with poor prognosis. According to M2 macrophage-related prognostic genes, GBM was divided into two subtypes (cluster A and cluster B). The differential gene enrichment analysis of the two clusters showed that cluster A was less enriched in M2 macrophages and had immunopotential. The M2score, which was constructed based on M2 macrophage-related prognostic genes, was not only related to the survival and prognosis of patients with GBM, but also predictive of the effectiveness of immunotherapy in these patients. This result has been effectively verified in an external data set.ConclusionGBM was successfully divided into two subtypes according to M2-macrophage-related prognostic genes. In GBM, a high M2score may indicate better clinical outcome and enhancement of the immunotherapy response.

Case of multifocal glioblastoma with four fusion transcripts of ALK, FGFR2, NTRK2, and NTRK3 genes stresses the need for tumor tissue multisampling for transcriptomic analysis

Glioblastoma multiforme (GBM) is the most malignant brain tumor with patient mortality rate close to 100%, 5-yr survival rate of ∼5%, and a median survival of 14 mo. GBMs have notorious histomorphologic and molecular heterogeneities thus giving hope for development of future personalized therapies. We describe here a case of a 48-yr-old male patient with three-nodular GBM. To address the question of intratumoral molecular heterogeneity, a comparative analysis of gene expression was performed by using multiple samples collected from different tumor sites with the aid of intraoperative magnetic resonance imaging (MRI). Sixteen GBM biosamples from parietal, temporal, and temporo-polar localizations were collected from primary, recurrent, and second recurrent tumors and were obtained and investigated by RNA sequencing. Our investigations revealed that biosamples derived from different tumor sites differ in their gene expression profiles with classical or mesenchymal signatures associated with clinically distinct molecular subtypes of GBM found within the same tumor. The results also showed significant differences in the expression of genes specific for targeted therapeutics. Our investigations have enabled the identification of four novel fusion transcripts—KIF5C-NTRK3, AC016907.2-ALK, CNTNAP3-NTRK2, and ZNF135-FGFR2—each present in only one sample. We found no differences between untreated and recurrent stages in the expression levels of genes involved in fusion transcripts, suggesting the lack of association between fusion transcript and treatment response. In contrast, longitudinal changes in the expression of VEGF and MGMT genes were concordant with the tumor response to bevacizumab and temozolomide. Our study underscores the importance of integrating a multisampling approach and RNA sequencing and demonstrates the predictive merit of an integrated approach for differentiating genomic aberrations associated with untreated or post-treatment recurrent GBMs.

Molecular profile of glioblastoma

Glioblastoma multiforme (GBM) is one of the most devastating primary intracranial tumors in case of adults. The intricacy of GBM is contemplated at both the inter- and intra-tumoral levels by cellular and sub-molecular heterogeneity. Subsequently, various expected diagnostic, prognostic, and prescient biomarkers have been reflected. The current methodology and understanding of biomarkers of GBM are discussed here. We have also highlighted the molecular subtypes of GBM, genetic aberrations, and how the microRNAs are involved in glioblastoma.

Rapid 3D Bioprinting of Glioblastoma Model Mimicking Native Biophysical Heterogeneity.

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor characterized by high cellular and molecular heterogeneity, hypervascularization, and innate drug resistance. Cellular components and extracellular matrix (ECM) are the two primary sources of heterogeneity in GBM. Here, biomimetic tri-regional GBM models with tumor regions, acellular ECM regions, and an endothelial region with regional stiffnesses patterned corresponding to the GBM stroma, pathological or normal brain parenchyma, and brain capillaries, are developed. Patient-derived GBM cells, human endothelial cells, and hyaluronic acid derivatives are used to generate a species-matched and biochemically relevant microenvironment. This in vitro study demonstrates that biophysical cues are involved in various tumor cell behaviors and angiogenic potentials and promote different molecular subtypes of GBM. The stiff models are enriched in the mesenchymal subtype, exhibit diffuse invasion of tumor cells, and induce protruding angiogenesis and higher drug resistance to temozolomide. Meanwhile, the soft models demonstrate enrichment in the classical subtype and support expansive cell growth. The three-dimensional bioprinting technology utilized in this study enables rapid, flexible, and reproducible patient-specific GBM modeling with biophysical heterogeneity that can be employed by future studies as a tunable system to interrogate GBM disease mechanisms and screen drug compounds.

The landscape of the mesenchymal signature in brain tumours.

The complexity of glioblastoma multiforme, the most common and lethal variant of gliomas, is reflected by cellular and molecular heterogeneity at both the inter- and intra-tumoural levels. Molecular subtyping has arisen in the past two decades as a promising strategy to give better predictions of glioblastoma multiforme evolution, common disease pathways, and rational treatment options. The Cancer Genome Atlas network initially identified four molecular subtypes of glioblastoma multiforme: proneural, neural, mesenchymal and classical. However, further studies, also investigated glioma stem cells, have only identified two to three subtypes: proneural, mesenchymal and classical. The proneural-mesenchymal transition upon tumour recurrence has been suggested as a mechanism of tumour resistance to radiation and chemotherapy treatment. Glioblastoma multiforme patients with the mesenchymal subtype tend to survive shorter than other subtypes when analysis is restricted to samples with low transcriptional heterogeneity. Although the mesenchymal signature in malignant glioma may seem at odds with the common idea of the ectodermal origin of neural-glial lineages, the presence of the mesenchymal signature in glioma is supported by several studies suggesting that it can result from: (i) intrinsic expression of tumour cells affected with accumulated genetic mutations and cell of origin; (ii) tumour micro-environments with recruited macrophages or microglia, mesenchymal stem cells or pericytes, and other progenitors; (iii) resistance to tumour treatment, including radiotherapy, antiangiogenic therapy and possibly chemotherapy. Genetic abnormalities, mainly NF1 mutations, together with NF-κB transcriptional programs, are the main driver of acquiring mesenchymal-signature. This signature is far from being simply tissue artefacts, as it has been identified in single cell glioma, circulating tumour cells, and glioma stem cells that are released from the tumour micro-environment. All these together suggest that the mesenchymal signature in glioblastoma multiforme is induced and sustained via cell intrinsic mechanisms and tumour micro-environment factors. Although patients with the mesenchymal subtype tend to have poorer prognosis, they may have favourable response to immunotherapy and intensive radio- and chemotherapy.

Molecular subtypes and differentiation programmes of glioma stem cells as determinants of extracellular vesicle profiles and endothelial cell-stimulating activities

ABSTRACTWe have previously uncovered the impact of oncogenic and differentiation processes on extracellular vesicles (EVs) in cancer. This is of interested in the context of glioma stem cells (GSC) that are responsible for recurrent nature of glioblastoma multiforme (GBM), while retaining the potential to undergo differentiation and self renewal. GSCs reside in vascular niches where they interact with endothelial cells through a number of mediators including bioactive cargo of EVs. GSCs can be classified as proneural (PN) or mesenchymal (MES) subtypes on the basis of their gene expression profiles and distinct biological characteristics. In the present study we investigated how GSC diversity and differentiation programmes influence their EV-mediated communication potentials. Indeed, molecular subtypes of GBMs and GSCs differ with respect to their expression of EV-related genes (vesiculome) and GSCs with PN or MES phenotypes produce EVs with markedly different characteristics, marker profiles, proteomes and endothelial stimulating activities. For example, while EVs of PN GSC are largely devoid of exosomal markers their counterparts from MES GSCs express ample CD9, CD63 and CD81 tetraspanins. In both GSC subtypes serum-induced differentiation results in profound, but distinct changes of cellular phenotypes including the enhanced EV production, reconfiguration of their proteomes and the related functional pathways. Notably, the EV uptake was a function of both subtype and differentiation state of donor cells. Thus, while, EVs produced by differentiated MES GSCs were internalized less efficiently than those from undifferentiated cells they exhibited an increased stimulatory potential for human brain endothelial cells. Such stimulating activity was also observed for EVs derived from differentiated PN GSCs, despite their even weaker uptake by endothelial cells. These findings suggest that the role of EVs as biological mediators and biomarkers in GBM may depend on the molecular subtype and functional state of donor cancer cells, including cancer stem cells.Abbreviations: CryoTEM: cryo-transmission electron microscopy; DIFF: differentiated GSCs; EGF: epidermal growth factor; DUC: differential ultracentrifugation; EV: extracellular vesicle; FGF: fibroblast growth factor; GBM: glioblastoma multiforme; GFAP: glial fibrillary acidic protein; GO: gene ontology; GSC: glioma stem cells; HBEC-5i: human brain endothelial cells; MES: mesenchymal cells; MTS - [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt; PMT1: proneural-to-mesenchyman transition cell line 1; PN: proneural cells; TEM: transmission electron microscopy; WB: western blotting

Experimental studies on correlation between nucleolus spindle-related protein 1 and the malignant progression and prognosis of human glioblastoma multiforme

Objective: To investigate the correlation between nucleolus spindle-related protein 1 (NUSAP1) and malignant progression and prognosis of human glioblastoma multiforme (GBM). Methods: RT-PCR and immunohistochemical technique were applied to analyze NUSAP1 expression level in GBM surgical specimens. Correlations between NUSAP1 expression and molecular classification and survival of patients with GBM were also investigated in TCGA database. The gene silencing technique was used to silence NUSAP1 expression in U87 cells, CCK-8 assay was used to detect cell proliferation, flow cytometry was used to detect cell cycle changes, and in vivo tumorigenicity was evaluated after NUSAP1 silencing in tumor-bearing mice. Results: NUSAP1 expression level in GBM was higher than that in non-tumor brain tissue. Survival curve analysis showed that the survival time of GBM patients with high NUSAP1 expression decreased significantly (P<0.01). NUSAP1 expression was relatively lower in mesenchymal and neural molecular subtypes of GBM, when compared with the other two molecular subtypes. And it was closely related with specific genetic aberrations (such as PTEN loss and IDH1 mutation). Silencing NUSAP1 inhibited G2/M cell cycle progression of GBM cells, and inhibited cell proliferation both in vitro and in vivo. Conclusion: Expression of NUSAP1 is closely related to progress and prognosis of GBM, and can be a biomarker reflecting GBM prognosis and act as a therapeutic target with potential clinical application value.

Glioblastoma update: molecular biology, diagnosis, treatment, response assessment, and translational clinical trials.

This is an exciting time in neuro-oncology. Discoveries elucidating the molecular mechanisms of oncogenesis and the molecular subtypes of glioblastoma multiforme (GBM) have led to new diagnostic and classification schemes with more prognostic power than histology alone. Molecular profiling has become part of the standard neuropathological evaluation of GBM. Chemoradiation followed by adjuvant temozolomide remains the standard therapy for newly diagnosed GBM, but survival remains unsatisfactory. Patients with recurrent GBM continue to have a dismal prognosis, but neuro-oncology centers with active clinical trial programs are seeing a small but increasing cadre of patients with longer survival. Molecularly targeted therapeutics, personalized therapy based on molecular profiling of individual tumors, and immunotherapeutic strategies are all being evaluated and refined in clinical trials. Understanding of the molecular mechanisms of tumor-mediated immunosuppression, and specifically interactions between tumor cells and immune effector cells in the tumor microenvironment, has led to a new generation of immunotherapies, including vaccine and immunomodulatory strategies as well as T-cell-based treatments. Molecularly targeted therapies, chemoradiation, immunotherapies, and anti-angiogenic therapies have created the need to develop more reliable neuroimaging criteria for differentiating the effects of therapy from tumor progression and changes in blood–brain barrier physiology from treatment response. Translational clinical trials for patients with GBM now incorporate quantitative imaging using both magnetic resonance imaging and positron emission tomography techniques. This update presents a summary of the current standards for therapy for newly diagnosed and recurrent GBM and highlights promising translational research.

Biomarkers and therapeutic advances in glioblastoma multiforme.

Glioblastoma multiforme (GBM) is a malignant tumor within the brain. Generally classified as primary and secondary with several different subtypes, ample molecular biomarkers have risen throughout the years which have garnered the attention of researchers. The advancements in genomics and proteomics have allowed researchers to gather prominent molecular biomarkers. All these biomarkers are gathered by means of biopsy or bodily fluid sample collection and are quantitatively analyzed by polymerase chain reaction coupled with other computational technologies. This review highlights the significance, regulation and prevalence of molecular biomarkers such as O6 -methylguanine-DNA methyltransferase, epidermal growth factor receptor vIII, isocitrate dehydrogenase mutation and several others which expressed differently in different types and molecular subtypes of GBM. The discoveries and roles of GBM-specific microRNAs including miR-21 and miR-10b as biomarkers with promising prognostic values were also delineated. The role and mechanism of biomarkers in GBM tumorigenesis are essential in the development of therapy for patients suffering from the disease itself. Thus, this review also discusses the mechanisms, effects and limitations of therapy such as temozolomide, viral gene transfer, biomarker-based vaccines or even engineered T cells for more specific responses. Biomarkers have displayed a high value and could eventually be utilized as drug targets. It is hoped that by combining different aspects of the disease which present with different biomarkers could lead to the development of a robust, effective and innovative take on GBM therapy.

Inflammatory landscape of human brain tumors reveals an NFκB dependent cytokine pathway associated with mesenchymal glioblastoma

The tumor microenvironment is being increasingly recognized as a key factor in cancer aggressiveness. In this study, we characterized the inflammatory gene signatures altered in glioma cell lines and tumor specimens of differing histological and molecular subtypes. The results showed that glioblastoma multiforme (GBM) shows upregulation of a subset of inflammatory genes when compared to astrocytomas and oligodendrogliomas. With molecular subtypes of GBM, the expression of inflammatory genes is heterogeneous, being enriched in mesenchymal and downregulated in Proneural/GCIMP. Other inflammation-associated processes such as tumor-associated macrophage (TAM) signatures are upregulated in mesenchymal, and a subset of 33 mesenchymal-enriched inflammatory and TAM markers showed correlation with poor survival. We found that various GBM tumor-upregulated genes such as IL6, IL8 and CCL2 are also actively expressed in glioma cell lines, playing differential and cooperative roles in promoting proliferation, invasion, angiogenesis and macrophage polarization in vitro. These genes can be stimulated by pathways typically altered in GBM, including the EGFR, PDGFR, MEK1/2-ERK1/2, PI3K/Akt and NFκB cascades. Taken together, the results presented herein depict some inflammatory pathways altered in gliomas and highlight potentially relevant targets to therapy improvement.

DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer.

Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher–Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.

Abstract A16: Combinatorial drug testing using 3D microtumors derived from GBM PDX reveals cytotoxic synergisms in pharmacokinomics-informed pathway interactions

Abstract Introduction: Drug testing of Glioblastoma multiforme (GBM) has revealed that many promising preclinical therapies fail when translated to the clinic. Serious limitations in preclinical models (often monolayer, serum-treated immortalized cell models) likely contribute to this translational failure. Although patient-derived xenografts (PDX), in which patient tumors are serially passaged in immunocompromised mice, are potentially superior model systems of human disease, high throughput drug studies in GBM PDX tumors are not feasible due to time, cost and throughput. To overcome these challenges, we have developed a GBM PDX MicroTumor system in which GBM PDX cells are grown in a novel 3D extracellular matrix material (HuBiogel™, Vivo Biosciences Inc., Birmingham, AL). We hypothesized that this 3D MicroTumor system would better emulate in vivo PDX tumor growth while providing a high throughput assay system for drug combination studies that can be performed in a more rapid timeframe. Methods: Six GBM PDX tumor “xenolines” were selected from the UAB Brain Tumor Animal Model Core to represent the 4 known molecular subtypes of GBM: Classical (JX10, X1016, X1046); Proneural (XD456); Neural (JX10) and Mesenchymal (JX22P). Tumor cells were prepared as single cell suspensions from subcutaneously passaged tumors and embedded in HuBiogel™ beads to form MicroTumors using Neuro-basal media devoid of serum. Single and combinatorial drug cytotoxicity studies were performed using MTT mitochondrial viability assays and Calcein AM imaging. Small molecule inhibitors selected for drug testing were: 1) selumetinib-targeting MEK1/2; 2) crizotinib-targeting c-MET and ALK; 3) cediranib-targeting VEGFR, FLT-1, FLT-4, c-KIT, and PDGFR; and 4) WP1066-targeting JAK2/STAT3. Combinatorial interactions were determined by Chou-Talalay combination index (CI) calculation using Calcusyn software. Global kinase signaling (kinomic profiling) was assessed using paired total cell lysates of GBM-PDX from orthotopic tumors grown in athymic nu/nu mice and as 3D MicroTumors. Testing was performed on the PamStation12 high content peptide microarray platform within the UAB Kinome Core. Results: Following optimization of model system conditions, 4 drugs were tested at multiple concentrations to identify effective dose ranges. While crizotinib, cediranib and WP1066 demonstrated significant cytotoxicity in at least 1 of the GBM-PDX MicroTumors tested, selumetinib was ineffective in producing cytotoxicity as a monotherapy. However, in combinatorial drug testing, selumetinib was effective in promoting synergistic activity (CI&amp;lt;1.0) when combined with each of the other drugs in several of the GBM-PDX tested. Conversely, WP1066 demonstrated some antagonistic interactions with the other drugs in certain tumors. Overall, cediranib and crizotinib demonstrated the most consistent level of efficacy both as monotherapies and combinatorial therapies across the GBM-PDX MicroTumors. Kinomic profiles were compared between GBM-PDX MicroTumors and matched GBM-PDX tumor xenolines grown as orthotopic intracranial tumors to confirm kinase signaling fidelity between the model systems. Paired t-test of kinomic phosphopeptide probes revealed only 20 of 246 peptides significantly differed (FDR&amp;lt;0.05) between the model systems suggesting a high level of signaling preservation within the MicroTumors. Conclusions: The GBM-PDX 3D MicroTumor provides a relatively high throughput drug screening model system that displays similar kinase signaling pathway activation as compared to their in vivo intracranial counterpart. Specific synergistic drug combinations were identified through MicroTumor testing. Ongoing drug combination testing of intracranially implanted GBM-PDX will determine how robustly the MicroTumor system predicts in vivo efficacy. Citation Format: Christopher D. Willey, Ashley N. Gilbert, Rachael Shevin, Catherine P. Langford, Christine W. Duarte, Raj Singh, Joshua C. Anderson, G. Yancey Gillespie. Combinatorial drug testing using 3D microtumors derived from GBM PDX reveals cytotoxic synergisms in pharmacokinomics-informed pathway interactions. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr A16.

IM-06 * A BIOINFORMATICS EVALUATION OF TUMOR-ASSOCIATED MACROPHAGES ACROSS 2 BRAIN TUMOR TYPES

BACKGROUND: CD163, the membrane form of a M2 macrophage marker, is exclusively expressed on alternatively activated or M2 macrophages. In some tumors such as neuroblastoma, CD163+ tumor-associated macrophages (TAMs) were shown to correlate with metastatic disease, age and outcome. Recently, the presence of TAMs has been demonstrated in some brain tumors, with evidence of origins from monocyte-derived macrophages from peripheral blood, and not brain resident microglial. AIM: (1) To evaluate CD163 expression using gene expression data, in 2 brain tumor types, medulloblastoma (MB) and glioblastoma multiforme (GBM); (2) To correlate CD163 expression with prognostic outcome in MBs and GBMs. METHODS: We analyzed CD163 gene expression in MBs (n = 60, Affymetrix U133 plus 2.0 platform) from Texas Children's Cancer Center and GBMs from TCGA dataset (n = 168, RNA sequencing). RESULTS: Previously, we provided evidence that the quantitative expression of CD163, indicative of CD163+ TAMs infiltration, was distinct among molecular subtypes of MBs, Sonic-Hedgehog-activated tumors were the most enriched (p = 0.006). We further discovered that CD163 expression was also distinct among molecular subtypes of GBMs, with Mesenchymal subtype being most enriched (p = 0.0006). CONCLUSIONS: These findings highlight the therapeutic implications on the pathogenesis role and therapeutic targeting aspects of CD163+ macrophages in different molecular subtypes of 2 brain tumor types. M2 macrophages serve a greater regulatory function than effector killing function associated with classically activated macrophages. IL10 secreted by M2 macrophages are also implicated in angiogenesis necessary for tumor growth and proliferation. In addition, TAMs cross-present tumor-derived endogenous ligands and can be specifically recognized and killed by natural-killer-T-cells.

Coexpression analysis of CD133 and CD44 identifies proneural and mesenchymal subtypes of glioblastoma multiforme.

Accumulating evidence suggests that the stem cell markers CD133 and CD44 indicate molecular subtype in Glioblastoma Multiforme (GBM). Gene coexpression analysis of The Cancer Genome Atlas GBM dataset was undertaken to compare markers of the Glioblastoma Stem-Progenitor Cell (GSPC) phenotype. Pearson correlation identified genes coexpressed with stem cell markers, which were then used to build a gene signature that classifies patients based on a CD133 coexpression module signature (CD133-M) or CD44-M subtype. CD133-M tumors were enriched for the Proneural (PN) GBM subtype compared to Mesenchymal (MES) subtype for CD44-M tumors. Gene set enrichment identified DNA replication/cell cycle genes in the CD133-M and invasion/migration in CD44-M, while functional experiments showed enhanced cellular growth in CD133 expressing cells and enhanced invasion in cells expressing CD44. As with the 4 major molecular subtypes of GBM, there was no long-term survival difference between CD44-M and CD133-M patients, although CD44-M patients responded better to temozolomide while CD133-M patients benefited from radiotherapy. The use of a targeted coexpression approach to predict functional properties of surface marker expressing cells is novel, and in the context of GBM, supports accumulating evidence that CD133 and CD44 protein marker expression correlates with molecular subtype.

MiRNA Multiplayers in glioma. From bench to bedside.

Glioblastoma multiforme (GBM) is the most common type of malignant gliomas, characterized by genetic instability, intratumoral histopathological variability and unpredictable clinical behavior. Disappointing results in the treatment of gliomas with surgery, radiation and chemotherapy have fuelled a search for a new therapeutic targets and treatment modalities. A novel small non-coding RNA molecules, microRNAs (miRNAs), appear to represent one of the most attractive target molecules contributing to the pathogenesis of various types of tumors. They play crucial roles in tumorigenesis, angiogenesis, invasion and apoptosis. Some miRNAs are also associated with clinical outcome and chemo- and radiotherapy resistance. Moreover, miRNA have the potential to affect the responses to molecular-targeted therapies and they also might be associated with cancer stem cell properties, affecting tumor maintenance and progression. The expression profiles of miRNAs are also useful for subclassification of GBM, what underscores the heterogeneity of diseases that all share the same WHO histopathological grade. Importantly, molecular subtypes of GBM appear to correlate with clinical phenotypes, tumor characteristic and treatment outcomes. miRNAs are then biological markers with possible diagnostic and prognostic potential. They could also serve as one of the promising treatment targets in human glioblastoma.

Investigating the Link between Molecular Subtypes of Glioblastoma, Epithelial-Mesenchymal Transition, and CD133 Cell Surface Protein

In this manuscript, we use genetic data to provide a three-faceted analysis on the links between molecular subclasses of glioblastoma, epithelial-to-mesenchymal transition (EMT) and CD133 cell surface protein. The contribution of this paper is three-fold: First, we use a newly identified signature for epithelial-to-mesenchymal transition in human mammary epithelial cells, and demonstrate that genes in this signature have significant overlap with genes differentially expressed in all known GBM subtypes. However, the overlap between genes up regulated in the mesenchymal subtype of GBM and in the EMT signature was more significant than other GBM subtypes. Second, we provide evidence that there is a negative correlation between the genetic signature of EMT and that of CD133 cell surface protein, a putative marker for neural stem cells. Third, we study the correlation between GBM molecular subtypes and the genetic signature of CD133 cell surface protein. We demonstrate that the mesenchymal and neural subtypes of GBM have the strongest correlations with the CD133 genetic signature. While the mesenchymal subtype of GBM displays similarity with the signatures of both EMT and CD133, it also exhibits some differences with each of these signatures that are partly due to the fact that the signatures of EMT and CD133 are inversely related to each other. Taken together these data shed light on the role of the mesenchymal transition and neural stem cells, and their mutual interaction, in molecular subtypes of glioblastoma multiforme.

Unique genome-wide map of TCF4 and STAT3 targets using ChIP-seq reveals their association with new molecular subtypes of glioblastoma

Aberrant activation of beta-catenin/TCF4 and STAT3 signaling in glioblastoma multiforme (GBM) has been reported. However, the molecular mechanisms related to this process are still poorly understood. Genome-wide screening of the binding characteristics of the transcription factors TCF4 and STAT3 in GBM cells was performed by chromatin immunoprecipitation sequencing (ChIP-seq) assay. Hierarchical clustering was used to analyze the association of TCF4 and STAT3 coregulated genes with The Cancer Genome Atlas (TCGA) GBM subtypes (classical, mesenchymal, neural, and proneural). New molecular classification of GBM was proposed and validated in Western and Asian populations. We identified 1250 overlapping putative target genes that were coregulated by TCF4 and STAT3. Further, the coregulated genes had the potential to guide TCGA GBM subtypes. Finally, we proposed a new molecular classification of GBM into 2 subtypes (proneural-like and mesenchymal-like) and showed that the new classification could be applied to both Western and Asian populations. In addition, the GBM response to temozolomide therapy differed depending on its subtype; mesenchymal-like GBM benefited, while there was no benefit for proneural-like GBM. This is the first comprehensive study to combine a ChIP-seq assay of TCF4 and STAT3 and data mining of patient cohorts to derive molecular subtypes of GBM.