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MicroRNA-27a distinguishes glioblastoma multiforme from diffuse and anaplastic astrocytomas and has prognostic value.

ABSTRACT: MicroRNAs (miRNAs) are a class of small noncoding RNAs that bind to 3'-untranslated (UTR) regions of target messenger RNAs to regulate protein synthesis. Reports have suggested that a set of specific miRNAs may be used as diagnostic and/or prognostic markers for astrocytoma grading. However, there are few studies of the specific miRNAs differentially expressed in each astrocytoma grade. MiRNA-containing total RNA was isolated from archived formalin-fixed, paraffin-embedded (FFPE) samples from WHO grade II-IV astrocytoma patients. The RNA was labeled and hybridized to Affymetrix miRNA 2.0 arrays. Statistical analysis identified several miRNAs differentially expressed in each astrocytoma grade. In particular, miR-27a, miR-210, and miR-1225-5p expression levels were able to differentiate grade IV from grade II and III astrocytomas as confirmed by real-time PCR. Kaplan-Meier survival analysis showed that disease progression occurred faster for Glioblastoma Multiforme (GBM) patients with a lower miR-27a expression level. Transfection of CRL-1690 GBM human cancer cells with a miR-27a oligonucleotide inhibitor followed by Real-time PCR identified six potential miR-27a target genes. Furthermore, the miR-27a oligonucleotide inhibitor induced CRL-1690 cell apoptosis. Taken together, our results provide additional miRNA signatures for distinguishing GBM from lower astrocytoma grades and suggest miR-27a as a prognostic and therapeutic target for GBM.

SUBMITTER: Rivera-Diaz M

PROVIDER: S-EPMC4300691 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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MicroRNA-27a distinguishes glioblastoma multiforme from diffuse and anaplastic astrocytomas and has prognostic value.

Rivera-Díaz Mónica M Miranda-Román Miguel A MA Soto Daniel D Quintero-Aguilo Mario M Ortiz-Zuazaga Humberto H Marcos-Martinez María J MJ Vivas-Mejía Pablo E PE

American journal of cancer research 20141215 1

MicroRNAs (miRNAs) are a class of small noncoding RNAs that bind to 3'-untranslated (UTR) regions of target messenger RNAs to regulate protein synthesis. Reports have suggested that a set of specific miRNAs may be used as diagnostic and/or prognostic markers for astrocytoma grading. However, there are few studies of the specific miRNAs differentially expressed in each astrocytoma grade. MiRNA-containing total RNA was isolated from archived formalin-fixed, paraffin-embedded (FFPE) samples from WH ...[more]

PMID: 25628931

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Project description:BackgroundGliomas are the most common intracranial tumors and are classified as I-IV. Among them, glioblastoma multiforme (GBM) is the most common invasive glioma with a poor prognosis. New molecular biomarkers that can predict clinical outcomes in GBM patients must be identified, which will help comprehend their pathogenesis and supply personalized treatment. Our research revealed four powerful survival indicators in GBM by reanalyzing microarray data and genetic sequencing data in public databases. Moreover, it unraveled new potential therapeutic targets which could help improve the survival time and quality of life of GBM patients.Materials and methodsTo identify prognostic signatures in GBMs, we analyzed the gene profiling data of GBM and standard brain samples from the Gene Expression Omnibus, including four datasets and RNA sequencing data from The Cancer Genome Atlas (TCGA) containing 152 glioblastoma tissues. We performed the differential analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, weighted gene co-expression network analysis (WGCNA) and Cox regression analysis.ResultsAfter differential analysis in GSE12657, GSE15824, GSE42656 and GSE50161, overlapping differentially expressed genes were identified. We identified 110 up-regulated DEGs and 75 down-regulated DEGs in the GBM samples. Significantly enriched subclasses of the GO classification of these genes included mitotic sister chromatid separation, mitotic nuclear division and so on. In KEGG pathway analysis, the most abundant terms were ECM-receptor interaction and protein digestion and absorption. WGCNA analysis was performed on these 185 DEGs in 152 glioblastoma samples obtained from TCGA, and gene co-expression networks were constructed. We then performed a multivariate Cox analysis and established a Cox proportional hazards regression model using the top 20 genes significantly correlated with survival time. We identified a four-protein prognostic signature that could divide patients into high-risk and low-risk groups. Increased expression of SLC12A5, CCL2, IGFBP2, and PDPN was associated with increased risk scores. Finally, the K-M curves confirmed that these genes could be used as independent predictors of survival in patients with glioblastoma.ConclusionOur analytical study identified a set of potential biomarkers that could predict survival and may contribute to successful treatment of GBM patients.

Project description:Tumor growth is a spatiotemporal birth-and-death process with loss of heterotypic contact-inhibition of locomotion (CIL) of tumor cells promoting invasion and metastasis. Therefore, representing tumor cells as two-dimensional points, we can expect the tumor tissues in histology slides to reflect realizations of spatial birth-and-death process which can be mathematically modeled to reveal molecular mechanisms of CIL, provided the mathematics models the inhibitory interactions. Gibbs process as an inhibitory point process is a natural choice since it is an equilibrium process of the spatial birth-and-death process. That is if the tumor cells maintain homotypic contact inhibition, the spatial distributions of tumor cells will result in Gibbs hard core process over long time scales. In order to verify if this is the case, we applied the Gibbs process to 411 TCGA Glioblastoma multiforme patient images. Our imaging dataset included all cases for which diagnostic slide images were available. The model revealed two groups of patients, one of which - the "Gibbs group," showed the convergence of the Gibbs process with significant survival difference. Further smoothing the discretized (and noisy) inhibition metric, for both increasing and randomized survival time, we found a significant association of the patients in the Gibbs group with increasing survival time. The mean inhibition metric also revealed the point at which the homotypic CIL establishes in tumor cells. Besides, RNAseq analysis between patients with loss of heterotypic CIL and intact homotypic CIL in the Gibbs group unveiled cell movement gene signatures and differences in Actin cytoskeleton and RhoA signaling pathways as key molecular alterations. These genes and pathways have established roles in CIL. Taken together, our integrated analysis of patient images and RNAseq data provides for the first time a mathematical basis for CIL in tumors, explains survival as well as uncovers the underlying molecular landscape for this key tumor invasion and metastatic phenomenon.

Project description:Anaplastic astrocytoma (AA) and its more aggressive counterpart, glioblastoma multiforme (GBM), are the most common intrinsic brain tumors in adults and are almost universally fatal. A deeper understanding of the molecular relationship of these tumor types is necessary to derive insights into the diagnosis, prognosis, and treatment of gliomas. Although genomewide profiling of expression levels with microarrays can be used to identify differentially expressed genes between these tumor types, comparative studies so far have resulted in gene lists that show little overlap.To achieve a more accurate and stable list of the differentially expressed genes and pathways between primary GBM and AA, we performed a meta-analysis using publicly available genome-scale mRNA data sets. There were four data sets with sufficiently large sample sizes of both GBMs and AAs, all of which coincidentally used human U133 platforms from Affymetrix, allowing for easier and more precise integration of data. After scoring genes and pathways within each data set, we combined the statistics across studies using the nonparametric rank sum method to identify the features that differentiate GBMs and AAs. We found >900 statistically significant probe sets after correction for multiple testing from the >22,000 tested. We also used the rank sum approach to select >20 significant Biocarta pathways after correction for multiple testing out of >175 pathways examined. The most significant pathway was the hypoxia-inducible factor (HIF) pathway. Our analysis suggests that many of the most statistically significant genes work together in a HIF1A/VEGF-regulated network to increase angiogenesis and invasion in GBM when compared to AA.We have performed a meta-analysis of genome-scale mRNA expression data for 289 human malignant gliomas and have identified a list of >900 probe sets and >20 pathways that are significantly different between GBM and AA. These feature lists could be utilized to aid in diagnosis, prognosis, and grade reduction of high-grade gliomas and to identify genes that were not previously suspected of playing an important role in glioma biology. More generally, this approach suggests that combined analysis of existing data sets can reveal new insights and that the large amount of publicly available cancer data sets should be further utilized in a similar manner.

Project description:Purpose: Gene expression analyses comparing tumors of different behaviors have been used for the identification of genes that have a role in the growth and maintenance of tumors, with the aim of both understanding the molecular basis of tumorigenesis and identifying novel potential therapeutic targets. We have here used this approach to identify the underlying gene expression differences between highly invasive glioblastoma multiforme and typically benign pilocytic astrocytomas. Experimental Design: We performed cDNA microarray analyses comparing astrocytomas of polar grade: grade I, pilocytic astrocytoma (PA), the non-invasive and most frequent pediatric tumor, with grade IV, the highly infiltrative glioblastoma multiforme (GBM) Results: Despite the significant clinical and pathological differences between the two tumor types, only 63 genes were found to exhibit two-fold or greater over-expression in GBM as compared with PA. A functional classification of the GBM over-expressed genes indicated that more than 50% are related to the regulation of the cell cycle and mitosis. Microarray data was validated by RQ-PCR testing six over-expressed genes in GBM related to PA: MELK, AUKB, ASPM, PRC1, IL13RA2 and KIAA0101. The differential expression was confirmed for all six genes, showing at least a 5 fold increase in the average expression levels in GBM compared to PA. Of the over expressed genes, that which exhibited the most statistically significant difference is Maternal Embryonic Leucine zipper Kinase (MELK). We undertook a more detailed investigation of the expression of this serine/threonine kinase gene in astrocytomas in the light of its role in the regulation of multipotent neural progenitor proliferation and previous suggestions that this may be a oncogenic target of general importance. In an examination of more than 100 tumors of the central nervous system we found progressively higher expression of MELK in GBM with astrocytoma grade and a noteworthy uniformity of high level expression in GBM. This latter feature probably explains the lack of observed association of MELK expression with survival of GBM patients. Over-expression at a similar level to GBM was also observed in medulloblastoma. We found neither gene methylation nor amplification to be a factor in MELK expression but were able to demonstrate that MELK knockdown in malignant astrocytoma cell lines caused a reduction in proliferation and anchorage-independent growth in in vitro assays. Conclusions: Our results indicate that GBM and PA differ by the expression of surprisingly few genes. Among them, MELK may play a key role in differentiating these two tumor types and represent an important therapeutic target for the management of the most frequent brain tumors in adult and children. Keywords: Comparizon of CNS tumors of different grades.

Dataset Information

MicroRNA-27a distinguishes glioblastoma multiforme from diffuse and anaplastic astrocytomas and has prognostic value.

Publications

MicroRNA-27a distinguishes glioblastoma multiforme from diffuse and anaplastic astrocytomas and has prognostic value.

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