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Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon arrays

ABSTRACT: Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histological subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was performed on 26 glioblastomas, 22 oligodendrogliomas and 6 control brain samples. Our results demonstrate that Human Exon arrays can identify subgroups of gliomas based on their histological appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas a subset of which (47% and 33%) were confirmed by RT-PCR. In addition, exon-level expression profiling also identified >700 novel exons. Expression of ~67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon-level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants and can identify novel exons. The splice variants identified by exon-level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets. Keywords: cell type comparison

ORGANISM(S): Homo sapiens

PROVIDER: GSE9385 | GEO | 2008/01/29

SECONDARY ACCESSION(S): PRJNA103101

REPOSITORIES: GEO

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Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon arrays

Project description:Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histological subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was performed on 26 glioblastomas, 22 oligodendrogliomas and 6 control brain samples. Our results demonstrate that Human Exon arrays can identify subgroups of gliomas based on their histological appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas a subset of which (47% and 33%) were confirmed by RT-PCR. In addition, exon-level expression profiling also identified >700 novel exons. Expression of ~67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon-level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants and can identify novel exons. The splice variants identified by exon-level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets. Keywords: cell type comparison 6 adult non diseased brain, 26 glioblastomas, 21 oligodendrogliomas

2008-01-28 | E-GEOD-9385 | biostudies-arrayexpress

Disease-specific sequence change DSC3 in TAF1/DYT3 affects genes in vesicular transport and dopamine metabolism

Project description:The X-chromosomal dystonia parkinsonism syndrome (XDP) is associated with sequence changes within the TAF1/DYT3 multiple transcript system. While most sequence changes are intronic, one, DSC3, is located within an exon (d4). Transcribed exon d4 occurs as part of multiple splice variants. These variants include exons d3 and d4 spliced to exons of TAF1, and an independent transcript composed of exons d2-d4. Location of DSC3 in an exon (d4) and utilization of this exon in multiple splice variants suggests an important role of DSC3 in the pathogenesis of XDP. To test this hypothesis we transfected neuroblastoma cells with four expression constructs, including exons d2-d4 (d2-d4/wild-type (wt) and d2-d4/DSC3) and d3-d4 (d3-d4/wt and d3-d4/DSC3). Expression profiling revealed a dramatic effect of DSC3 on overall gene expression. 362 genes differ between cells containing d2-d4/wt and d2-d4/DSC3. Annotation clustering revealed high enrichment of genes related to dopamine metabolism, vesicular transport, synapse function, Ca++ metabolism, and oxidative stress. 211 genes were differentially expressed in d3-d4/wt vs. d3-d4/DSC3. Annotation clustering highlighted genes in signal transduction and cell-cell interaction. The data shows an important role of physiologically occurring transcript d2-d4 in normal brain function. Interference with this role by DSC3 is a likely pathological mechanism in XDP. Disturbance of dopamine function and of Ca++ metabolism can explain abnormal movement; loss of protection against reactive oxygen species may account for the neurodegenerative changes in XDP. Although d3-d4 also affect genes potentially related to neurodegenerative processes their physiologic role as splice variants of TAF1 awaits further exploration. We transfected neuroblastoma cells with four expression constructs, including exons d2-d4 (d2-d4/wild-type (wt) and d2-d4/DSC3) and d3-d4 (d3-d4/wt and d3-d4/DSC3).

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Homo sapiens

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Project description:Microarray analysis was used to determine the expression of 12,000 genes in a set of 50 gliomas, 28 glioblastomas and 22 anaplastic oligodendrogliomas. Supervised learning approaches were used to build a two-class prediction model based on a subset of 14 glioblastomas and 7 anaplastic oligodendrogliomas with classic histology. A 20-feature k-nearest neighbor model correctly classified 18 of the 21 classic cases in leave-one-out cross-validation when compared with pathological diagnoses. This model was then used to predict the classification of clinically common, histologically nonclassic samples. When tumors were classified according to pathology, the survival of patients with nonclassic glioblastoma and nonclassic anaplastic oligodendroglioma was not significantly different (P = 0.19). However, class distinctions according to the model were significantly associated with survival outcome (P = 0.05). This class prediction model was capable of classifying high-grade, nonclassic glial tumors objectively and reproducibly. Moreover, the model provided a more accurate predictor of prognosis in these nonclassic lesions than did pathological classification. These data suggest that class prediction models, based on defined molecular profiles, classify diagnostically challenging malignant gliomas in a manner that better correlates with clinical outcome than does standard pathology.

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SPLICER: A Highly Efficient Base Editing Toolbox That Enables in vivo Exon Skipping For Targeting Alzheimer’s Disease [RNA-seq]

Project description:Exon skipping technologies enable exclusion of targeted exons from mature mRNA transcripts, which has broad applications in molecular and cellular biology, medicine and biotechnology. Existing exon skipping techniques include antisense oligonucleotides, targetable nucleases and base editors, which, while effective for specific applications at some target exons, remain hindered by shortcomings preventing their broader implementation including transient effects in the case of oligonucleotides or limiting PAM motifs, sequence context preferences for deaminases, and undesirable cryptic splicing in the case of gene editing tools. To overcome these limitations, we created SPLICER, a toolbox of next-generation base editors consisting of near-PAMless Cas9 nickase variants fused with different deaminases for simultaneous editing of splice acceptor (SA) and splice donor (SD) sequences. Synchronized SA and SD editing not only improves exon skipping rates but also reduces aberrant outcomes such as cryptic splicing and intron retention. SPLICER enables editing of exon splice sites with high efficiency, including many exons refractory to splicing reprogramming by the native SpCas9 BEs. To demonstrate the therapeutic potential of SPLICER, we targeted APP exon 17, which contains the amino acid residues responsible for the formation of Aβ plaques in Alzheimer’s disease. SPLICER enabled precise and highly efficient exon skipping, which reduced the formation of Aβ42 peptides in vitro while inducing DNA editing and exon skipping in vivo within a humanized mouse model of Alzheimer’s disease. Overall, SPLICER is a widely applicable and highly efficient toolbox for exon skipping with broad therapeutic applications.

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2016-05-28 | E-GEOD-82009 | biostudies-arrayexpress

Quantitative Analysis of Alternative Spliced Variants in HNSCC

Project description:Alternative splicing of pre-mRNA generates protein diversity and has been linked to cancer progression and drug response. Exon microarray technology enables genome-wide quantication of expression levels for the majority of exons and facilitates the discovery of alternative splicing events. Analysis of exon array data is more challenging than gene expression data and there is a need for reliable quantication of exons and alternative spliced variants. We introduce a novel, computationally efficient methodology, MEAP, for exon array data preprocessing, analysis and visualization. We compared MEAP with other preprocessing methods, and validation of the results show that MEAP produces reliable quantication of exons and alternative spliced variants. Analysis of data from head and neck squamous cell carcinoma (HNSCC) cell lines revealed several variants associated with 11q13 amplication, which is a predictive marker of metastasis and decreased survival in HNSCC patients. Together these results demonstrate the utility of MEAP in suggesting novel experimentally testable predictions. Thus, in addition to novel methodology to process large-scale exon array data sets, our results provide several HNSCC candidate genes for further studies. We analyzed 15 samples using the Affymetrix Human Exon 1.0 ST platform, of which 7 samples have 11q13 amplification. Array data was preprocessed by using Multiple Exon Array Processing (MEAP).

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