Subtyping glioblastoma by combining miRNA and mRNA expression data using compressed sensing-based approach

In the clinical practice, many diseases such as glioblastoma, leukemia, diabetes, and prostates have multiple subtypes. Classifying subtypes accurately using genomic data will provide individualized treatments to target-specific disease subtypes. However, it is often difficult to obtain satisfactory classification accuracy using only one type of data, because the subtypes of a disease can exhibit similar patterns in one data type. Fortunately, multiple types of genomic data are often available due to the rapid development of genomic techniques. This raises the question on whether the classification performance can significantly be improved by combining multiple types of genomic data. In this article, we classified four subtypes of glioblastoma multiforme (GBM) with multiple types of genome-wide data (e.g., mRNA and miRNA expression) from The Cancer Genome Atlas (TCGA) project. We proposed a multi-class compressed sensing-based detector (MCSD) for this study. The MCSD was trained with data from TCGA and then applied to subtype GBM patients using an independent testing data. We performed the classification on the same patient subjects with three data types, i.e., miRNA expression data, mRNA (or gene expression) data, and their combinations. The classification accuracy is 69.1% with the miRNA expression data, 52.7% with mRNA expression data, and 90.9% with the combination of both mRNA and miRNA expression data. In addition, some biomarkers identified by the integrated approaches have been confirmed with results from the published literatures. These results indicate that the combined analysis can significantly improve the accuracy of classifying GBM subtypes and identify potential biomarkers for disease diagnosis.     

Systematic Genetic Analysis Identifies Cis-eQTL Target Genes Associated with Glioblastoma Patient Survival

Prior expression quantitative trait locus (eQTL) studies have demonstrated heritable variation determining differences in gene expression. The majority of eQTL studies were based on cell lines and normal tissues. We performed cis-eQTL analysis using glioblastoma multiforme (GBM) data sets obtained from The Cancer Genome Atlas (TCGA) to systematically investigate germline variation’s contribution to tumor gene expression levels. We identified 985 significant cis-eQTL associations (FDR<0.05) mapped to 978 SNP loci and 159 unique genes. Approximately 57% of these eQTLs have been previously linked to the gene expression in cell lines and normal tissues; 43% of these share cis associations known to be associated with functional annotations. About 25% of these cis-eQTL associations are also common to those identified in Breast Cancer from a recent study. Further investigation of the relationship between gene expression and patient clinical information identified 13 eQTL genes whose expression level significantly correlates with GBM patient survival (p<0.05). Most of these genes are also differentially expressed in tumor samples and organ-specific controls (p<0.05). Our results demonstrated a significant relationship of germline variation with gene expression levels in GBM. The identification of eQTLs-based expression associated survival might be important to the understanding of genetic contribution to GBM cancer prognosis.     

Construction of lncRNA-associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

Long noncoding RNAs (lncRNAs) serve as competitive endogenous RNAs (ceRNAs) that play significant regulatory roles in the pathogenesis of tumors. However, the role of lncRNAs, especially the lncRNA-related ceRNA regulatory network, in glioblastoma (GBM) has not been fully elucidated. The goal of the current study was to construct lncRNA-microRNA-mRNA-related ceRNA networks for further investigation of their mechanism of action in GBM. We downloaded data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases and identified differential lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) associated with GBM. A ceRNA network was constructed and analyzed to examine the relationship between lncRNAs and patients’ overall survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) were used to analyze the related mRNAs to indirectly explain the mechanism of action of lncRNAs. The potential effective drugs for the treatment of GBM were identified using the connectivity map (CMap). After integrated analysis, we obtained a total of 210 differentially expressed lncRNAs, 90 differentially expressed miRNAs, and 2508 differentially expressed mRNAs (DEmRNAs) from the TCGA and GEO databases. Using these differential genes, we constructed a lncRNA-associated ceRNA network. Six lncRNAs in the ceRNA network were associated with the overall survival of patients with GBM. Through KEGG analysis, it was found that the DEmRNAs involved in the network are related to cancer-associated pathways, for instance, mitogen-activated protein kinase and Ras signaling pathways. CMap analysis revealed four small-molecule compounds that could be used as drugs for the treatment of GBM. In this study, a multi-database joint analysis was used to construct a lncRNA-related ceRNA network to help identify the regulatory functions of lncRNAs in the pathogenesis of GBM.     

Suppression of tumorigenicity by MicroRNA-138 through inhibition of EZH2-CDK4/6-pRb-E2F1 signal loop in glioblastoma multiforme

Deregulation of microRNAs (miRNAs) is implicated in tumor progression. We attempt to indentify the tumor suppressive miRNA not only down-regulated in glioblastoma multiforme (GBM) but also potent to inhibit the oncogene EZH2, and then investigate the biological function and pathophysiologic role of the candidate miRNA in GBM. In this study, we show that miRNA-138 is reduced in both GBM clinical specimens and cell lines, and is effective to inhibit EZH2 expression. Moreover, high levels of miR-138 are associated with long overall and progression-free survival of GBM patients from The Cancer Genome Atlas dataset (TCGA) data portal. Ectopic expression of miRNA-138 effectively inhibits GBM cell proliferation in vitro and tumorigenicity in vivo through inducing cell cycles G1/S arrest. Mechanism investigation reveals that miRNA-138 acquires tumor inhibition through directly targeting EZH2, CDK6, E2F2 and E2F3. Moreover, an EZH2-mediated signal loop, EZH2-CDK4/6-pRb-E2F1, is probably involved in GBM tumorigenicity, and this loop can be blocked by miRNA-138. Additionally, miRNA-138 negatively correlates to mRNA levels of EZH2 and CDK6 among GBM clinical samples from both TCGA and our small amount datasets. In conclusion, our data demonstrate a tumor suppressive role of miRNA-138 in GBM tumorigenicity, suggesting a potential application in GBM therapy.     

Cancer Association Study of Aminoacyl-tRNA Synthetase Signaling Network in Glioblastoma

Aminoacyl-tRNA synthetases (ARSs) and ARS-interacting multifunctional proteins (AIMPs) exhibit remarkable functional versatility beyond their catalytic activities in protein synthesis. Their non-canonical functions have been pathologically linked to cancers. Here we described our integrative genome-wide analysis of ARSs to show cancer-associated activities in glioblastoma multiforme (GBM), the most aggressive malignant primary brain tumor. We first selected 23 ARS/AIMPs (together referred to as ARSN), 124 cancer-associated druggable target genes (DTGs) and 404 protein-protein interactors (PPIs) of ARSs using NCI's cancer gene index. 254 GBM affymetrix microarray data in The Cancer Genome Atlas (TCGA) were used to identify the probe sets whose expression were most strongly correlated with survival (Kaplan-Meier plots versus survival times, log-rank t-test <0.05). The analysis identified 122 probe sets as survival signatures, including 5 of ARSN (VARS, QARS, CARS, NARS, FARS), and 115 of DTGs and PPIs (PARD3, RXRB, ATP5C1, HSP90AA1, CD44, THRA, TRAF2, KRT10, MED12, etc). Of note, 61 survival-related probes were differentially expressed in three different prognosis subgroups in GBM patients and showed correlation with established prognosis markers such as age and phenotypic molecular signatures. CARS and FARS also showed significantly higher association with different molecular networks in GBM patients. Taken together, our findings demonstrate evidence for an ARSN biology-dominant contribution in the biology of GBM.     

Altered Expression of Polycomb Group Genes in Glioblastoma Multiforme

The Polycomb group (PcG) proteins play a critical role in histone mediated epigenetics which has been implicated in the malignant evolution of glioblastoma multiforme (GBM). By systematically interrogating The Cancer Genome Atlas (TCGA), we discovered widespread aberrant expression of the PcG members in GBM samples compared to normal brain. The most striking differences were upregulation of EZH2, PHF19, CBX8 and PHC2 and downregulation of CBX7, CBX6, EZH1 and RYBP. Interestingly, changes in EZH2, PHF19, CBX7, CBX6 and EZH1 occurred progressively as astrocytoma grade increased. We validated the aberrant expression of CBX6, CBX7, CBX8 and EZH2 in GBM cell lines by Western blotting and qRT-PCR, and further the aberrant expression of CBX6 in GBM tissue samples by immunohistochemical staining. To determine if there was functional significance to the diminished CBX6 levels in GBM, CBX6 was overexpressed in GBM cells resulting in decreased proliferative capacity. In conclusion, aberrant expression of PcG proteins in GBMs may play a role in the development or maintenance of the malignancy.     

Overexpression of CD97 Confers an Invasive Phenotype in Glioblastoma Cells and Is Associated with Decreased Survival of Glioblastoma Patients

Mechanisms of invasion in glioblastoma (GBM) relate to differential expression of proteins conferring increased motility and penetration of the extracellular matrix. CD97 is a member of the epidermal growth factor seven-span transmembrane family of adhesion G-protein coupled receptors. These proteins facilitate mobility of leukocytes into tissue. In this study we show that CD97 is expressed in glioma, has functional effects on invasion, and is associated with poor overall survival. Glioma cell lines and low passage primary cultures were analyzed. Functional significance was assessed by transient knockdown using siRNA targeting CD97 or a non-target control sequence. Invasion was assessed 48 hours after siRNA-mediated knockdown using a Matrigel-coated invasion chamber. Migration was quantified using a scratch assay over 12 hours. Proliferation was measured 24 and 48 hours after confirmed protein knockdown. GBM cell lines and primary cultures were found to express CD97. Knockdown of CD97 decreased invasion and migration in GBM cell lines, with no difference in proliferation. Gene-expression based Kaplan-Meier analysis was performed using The Cancer Genome Atlas, demonstrating an inverse relationship between CD97 expression and survival. GBMs expressing high levels of CD97 were associated with decreased survival compared to those with low CD97 (p = 0.007). CD97 promotes invasion and migration in GBM, but has no effect on tumor proliferation. This phenotype may explain the discrepancy in survival between high and low CD97-expressing tumors. This data provides impetus for further studies to determine its viability as a therapeutic target in the treatment of GBM.     

Glioblastoma cell secretome: analysis of three glioblastoma cell lines reveal 148 non-redundant proteins

Glioblastoma multiforme (GBM) is the most aggressive among human gliomas with poor prognosis. Study of tumor cell secretome - proteins secreted by cancer cell lines, is a powerful approach to discover potential diagnostic or prognostic biomarkers. Here we report, for the first time, proteins secreted by three GBM cell lines, HNGC2, LN229 and U87MG. Analysis of the conditioned media of these cell lines by LC-MS/MS using ESI-IT mass spectrometer (LTQ) resulted in the confident identification of 102, 119 and 64 proteins, respectively. Integration of the results from all the three cell lines lead to a dataset of 148 non-redundant proteins. Subcellular classification using Genome Ontology indicated that 42% of the proteins identified belonged to extracellular or membrane proteins, viz. Vinculin, Tenascin XB, SERPIN F1 and TIMP-1. 52 proteins matched with the secretomes of 11 major cancer types reported earlier whereas remaining 96 are unique to our study. 25 protein identifications from the dataset represent proteins related to GBM or other cancer tissues as per Human Protein Atlas; at least 22 are detectable in plasma, 11 of them being reported even in cerebrospinal fluid. Our study thus provides a valuable resource of GBM cell secretome with potential for further investigation as GBM biomarkers.     

自噬基因CTSL表达与胶质母细胞瘤患者预后相关

本研究旨在探讨自噬基因CTSL对胶质母细胞瘤(GBM)患者的预后影响。利用癌症基因组图谱(TCGA)、人类自噬数据库(HADB)、中国脑胶质瘤基因组图谱(CGGA)数据库、基因表达谱分析(GEPIA)获取数据信息,通过筛选差异表达基因及单因素和多因素COX分析确定GBM的独立预后危险因素,同时通过基因本体论(GO)、基因组百科全书途径(KEGG)、临床病理相关性、基因集富集分析(GSEA)、自噬基因网络分析CTSL的相关作用机制。结果显示:(1)富集分析显示胶质母细胞瘤中差异自噬基因(ARG)与自噬体的形成、细胞凋亡、血管生成、细胞化疗等相关;(2)GBM中CTSL的mRNA水平明显高于正常组织样本;(3)多因素COX回归分析显示自噬基因CTSL的高表达为GBM预后的独立危险因素,STUPP治疗(术后替莫唑胺[Tmz]同步放化疗+Tmz辅助化疗)为独立保护因素;(4)自噬基因CTSL在非GCIMP(CpG岛甲基化)型、间质型、IDH野生型、1p/19q无缺失型胶质母细胞瘤及化疗后表达量更高。综上所述,本研究分析了自噬基因在GBM中的作用,并表明自噬基因CTSL的过表达预示胶质母细胞瘤患者不良预后,显示自噬基因CTSL有作为有效靶标的潜质。     

IKBIP,a novel glioblastoma biomarker,maintains abnormal proliferation of tumor cells by inhibiting the ubiquitination and degradation of CDK4

Sustained proliferative signaling is a crucial hallmark and therapeutic target in glioblastoma (GBM); however, new intrinsic regulators and their underlying mechanisms remain to be elucidated. In this study, I kappa B kinase interacting protein (IKBIP) was identified to be correlated with the progression of GBM by analysis of The Cancer Genome Atlas (TCGA) data. TCGA database analysis indicated that higher IKBIP expression was associated with high tumor grade and poor prognosis in GBM patients, and these correlations were subsequently validated in clinical samples. IKBIP knockdown induced G1/S arrest by blocking the Cyclin D1/CDK4/CDK6/CDK2 pathway. Our results showed that IKBIP may bind directly to CDK4, a key cell cycle checkpoint protein, and prevent its ubiquitination-mediated degradation in GBM cells. An in vivo study confirmed that IKBIP knockdown strongly suppressed cell proliferation and tumor growth and prolonged survival in a mouse xenograft model established with human GBM cells. In conclusion, IKBIP functions as a novel driver of GBM by binding and stabilizing the CDK4 protein. IKBIP could be a potential therapeutic target in GBM.     

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.     

Prognostic power of a lipid metabolism gene panel for diffuse gliomas

Lipid metabolism reprogramming plays important role in cell growth, proliferation, angiogenesis and invasion in cancers. However, the diverse lipid metabolism programmes and prognostic value during glioma progression remain unclear. Here, the lipid metabolism‐related genes were profiled using RNA sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database. Gene ontology (GO) and gene set enrichment analysis (GSEA) found that glioblastoma (GBM) mainly exhibited enrichment of glycosphingolipid metabolic progress, whereas lower grade gliomas (LGGs) showed enrichment of phosphatidylinositol metabolic progress. According to the differential genes of lipid metabolism between LGG and GBM, we developed a nine‐gene set using Cox proportional hazards model with elastic net penalty, and the CGGA cohort was used for validation data set. Survival analysis revealed that the obtained gene set could differentiate the outcome of low‐ and high‐risk patients in both cohorts. Meanwhile, multivariate Cox regression analysis indicated that this signature was a significantly independent prognostic factor in diffuse gliomas. Gene ontology and GSEA showed that high‐risk cases were associated with phenotypes of cell division and immune response. Collectively, our findings provided a new sight on lipid metabolism in diffuse gliomas.