Dataset Information

Identification of differentially expressed genes and fusion genes associated with malignant progression of spinal cord gliomas by transcriptome analysis.

ABSTRACT: Glioma, the most common histological subtype of primary spinal cord tumors, is considered as a rare central nervous system neoplasm. In this study, 9 glioma samples (4 of grade II and 5 of grade IV with H3K27M positive) were analyzed to examine the molecular mechanisms underlying the malignant progression of gliomas, transcriptome sequencing. Differentially expressed genes (DEGs) in grade IV vs. grade II were analyzed by using the Limma package in R. Enrichment analysis was performed for the individual DEGs through VennPlex software and the Database for Annotation. Gene mutations and fusions were analyzed using the Genome Analysis Toolkit and STAR-Fusion. A total of 416 DEGs were identified in grade IV vs. grade II. Functional analysis of the DEGs showed that GALR1 and GRM5 of neuroactive ligand-receptor interactions signaling pathways may be relaed to malignant progression of gliomas. Further systematic transcriptional profiling identified 11 in-frame/frameshift gene fusions in the tumors. Notably, one novel gene fusions, GATSL2-GTF2I was detected in all of the grade II samples. In summary, the molecular alterations observed in glioma progression may improve the characterization of different human spinal cord glioma grades. The transcriptome analysis of intramedullary spinal cord glioma will provide a new candidate gene list for further mechanism research.

SUBMITTER: Liu DK

PROVIDER: S-EPMC6753211 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of differentially expressed genes and fusion genes associated with malignant progression of spinal cord gliomas by transcriptome analysis.

Liu Dong-Kang DK Wang Jin J Guo Yi Y Sun Zhen-Xing ZX Wang Gui-Huai GH

Scientific reports 20190919 1

Glioma, the most common histological subtype of primary spinal cord tumors, is considered as a rare central nervous system neoplasm. In this study, 9 glioma samples (4 of grade II and 5 of grade IV with H3K27M positive) were analyzed to examine the molecular mechanisms underlying the malignant progression of gliomas, transcriptome sequencing. Differentially expressed genes (DEGs) in grade IV vs. grade II were analyzed by using the Limma package in R. Enrichment analysis was performed for the ind ...[more]

PMID: 31537867

Similar Datasets

Project description:In the search for a therapeutic schedule for spinal cord injury, it is necessary to understand key genes and their corresponding regulatory networks involved in the spinal cord injury process. However, ad hoc selection and analysis of one or two genes cannot fully reveal the complex molecular biological mechanisms of spinal cord injury. The emergence of second-generation sequencing technology (RNA sequencing) has provided a better method. In this study, RNA sequencing technology was used to analyze differentially expressed genes at different time points after spinal cord injury in rat models established by contusion of the eighth thoracic segment. The numbers of genes that changed significantly were 944, 1362 and 1421 at 1, 4 and 7 days after spinal cord injury respectively. After gene ontology analysis and temporal expression analysis of the differentially expressed genes, C5ar1, Socs3 and CCL6 genes were then selected and identified by real-time polymerase chain reaction and western blot assay. The mRNA expression trends of C5ar1, Socs3 and CCL6 genes were consistent with the RNA sequencing results. Further verification and analysis of C5ar1 indicate that the level of protein expression of C5ar1 was consistent with its nucleic acid level after spinal cord injury. C5ar1 was mainly expressed in neurons and astrocytes. Finally, the gene Itgb2, which may be related to C5ar1, was found by Chilibot database and literature search. Immunofluorescence histochemical results showed that the expression of Itgb2 was highly consistent with that of C5ar1. Itgb2 was expressed in astrocytes. RNA sequencing technology can screen differentially expressed genes at different time points after spinal cord injury. Through analysis and verification, genes strongly associated with spinal cord injury can be screened. This can provide experimental data for further determining the molecular mechanism of spinal cord injury, and also provide possible targets for the treatment of spinal cord injury. This study was approved ethically by the Laboratory Animal Ethics Committee of Jiangsu Province, China (approval No. 2018-0306-001) on March 6, 2018.

Project description:Analyses of Expressed Sequence Tags (ESTs) databases suggest that most human genes have multiple alternative splice variants. The alternative splicing of pre-mRNA is tightly regulated during development and in different tissue types. Changes in splicing patterns have been described in disease states. Recently, we used whole-transcriptome shotgun pryrosequencing to characterize 4 malignant pleural mesothelioma (MPM) tumors, 1 lung adenocarcinoma and 1 normal lung. We hypothesized that alternative splicing profiles might be detected in the sequencing data for the expressed genes in these samples.We developed a software pipeline to map the transcriptome read sequences of the 4 MPM samples and 1 normal lung sample onto known exon junction sequences in the comprehensive AceView database of expressed sequences and to count how many reads map to each junction. 13,274,187 transcriptome reads generated by the Roche/454 sequencing platform for 5 samples were compared with 151,486 exon junctions from the AceView database. The exon junction expression index (EJEI) was calculated for each exon junction in each sample to measure the differential expression of alternative splicing events. Top ten exon junctions with the largest EJEI difference between the 4 mesothelioma and the normal lung sample were then examined for differential expression using Quantitative Real Time PCR (qRT-PCR) in the 5 sequenced samples. Two of the differentially expressed exon junctions (ACTG2.aAug05 and CDK4.aAug05) were further examined with qRT-PCR in additional 18 MPM and 18 normal lung specimens.We found 70,953 exon junctions covered by at least one sequence read in at least one of the 5 samples. All 10 identified most differentially expressed exon junctions were validated as present by RT-PCR, and 8 were differentially expressed exactly as predicted by the sequence analysis. The differential expression of the AceView exon junctions for the ACTG2 and CDK4 genes were also observed to be statistically significant in an additional 18 MPM and 18 normal lung samples examined using qRT-PCR. The differential expression of these two junctions was shown to successfully classify these mesothelioma and normal lung specimens with high sensitivity (89% and 78%, respectively).Whole-transcriptome shotgun sequencing, combined with a downstream bioinformatics pipeline, provides powerful tools for the identification of differentially expressed exon junctions resulting from alternative splice variants. The alternatively spliced genes discovered in the study could serve as useful diagnostic markers as well as potential therapeutic targets for MPM.

Project description:Complex pathological changes occur during the development of spinal cord injury (SCI), and determining the underlying molecular events that occur during SCI is necessary for the development of promising molecular targets and therapeutic strategies. This study was designed to explore differentially expressed genes (DEGs) associated with the acute and chronic stages of SCI using bioinformatics analysis. Gene expression profiles (GSE45006, GSE93249, and GSE45550) were downloaded from the Gene Expression Omnibus database. SCI-associated DEGs from rat samples were identified, and Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. In addition, a protein-protein interaction network was constructed. Approximately 66 DEGs were identified in GSE45550 between 3-14 days after SCI, whereas 2418 DEGs were identified in GSE45006 1-56 days after SCI. Moreover, 1263, 195, and 75 overlapping DEGs were identified between these two expression profiles, 3, 7/8, and 14 days after SCI, respectively. Additionally, 16 overlapping DEGs were obtained in GSE45006 1-14 days after SCI, including Pank1, Hn1, Tmem150c, Rgd1309676, Lpl, Mdh1, Nnt, Loc100912219, Large1, Baiap2, Slc24a2, Fundc2, Mrps14, Slc16a7, Obfc1, and Alpk3. Importantly, 3882 overlapping DEGs were identified in GSE93249 1-6 months after SCI, including 3316 protein-coding genes and 567 long non-coding RNA genes. A comparative analysis between GSE93249 and GSE45006 resulted in the enrichment of 1135 overlapping DEGs. The significant functions of these 1135 genes were correlated with the response to the immune effector process, the innate immune response, and cytokine production. Moreover, the biological processes and KEGG pathways of the overlapping DEGs were significantly enriched in immune system-related pathways, osteoclast differentiation, the nuclear factor-κB signaling pathway, and the chemokine signaling pathway. Finally, an analysis of the overlapping DEGs associated with both acute and chronic SCI, assessed using the expression profiles GSE93249 and GSE45006, identified four overlapping DEGs: Slc16a7, Alpk3, Lpl and Nnt. These findings may be useful for revealing the biological processes associated with SCI and the development of targeted intervention strategies.

Project description:Gene spectrum analysis has shown that gene expression and signaling pathways change dramatically after spinal cord injury, which may affect the microenvironment of the damaged site. Microarray analysis provides a new opportunity for investigating diagnosis, treatment, and prognosis of spinal cord injury. However, differentially expressed genes are not consistent among studies, and many key genes and signaling pathways have not yet been accurately studied. GSE5296 was retrieved from the Gene Expression Omnibus DataSet. Differentially expressed genes were obtained using R/Bioconductor software (expression changed at least two-fold; P < 0.05). Database for Annotation, Visualization and Integrated Discovery was used for functional annotation of differentially expressed genes and Animal Transcription Factor Database for predicting potential transcription factors. The resulting transcription regulatory protein interaction network was mapped to screen representative genes and investigate their diagnostic and therapeutic value for disease. In total, this study identified 109 genes that were upregulated and 30 that were downregulated at 0.5, 4, and 24 hours, and 3, 7, and 28 days after spinal cord injury. The number of downregulated genes was smaller than the number of upregulated genes at each time point. Database for Annotation, Visualization and Integrated Discovery analysis found that many inflammation-related pathways were upregulated in injured spinal cord. Additionally, expression levels of these inflammation-related genes were maintained for at least 28 days. Moreover, 399 regulation modes and 77 nodes were shown in the protein-protein interaction network of upregulated differentially expressed genes. Among the 10 upregulated differentially expressed genes with the highest degrees of distribution, six genes were transcription factors. Among these transcription factors, ATF3 showed the greatest change. ATF3 was upregulated within 30 minutes, and its expression levels remained high at 28 days after spinal cord injury. These key genes screened by bioinformatics tools can be used as biological markers to diagnose diseases and provide a reference for identifying therapeutic targets.

Project description:Intramedullary spinal cord tumors are a rare and understudied cancer with poor treatment options and prognosis. Our prior study used a combination of PDGF-B, HRAS, and p53 knockdown to induce the development of high-grade glioma in the spinal cords of minipigs. In this study, we evaluate the ability of each vector alone and combinations of vectors to produce high-grade spinal cord gliomas. Eight groups of rats (n = 8/group) underwent thoracolumbar laminectomy and injection of lentiviral vector in the lateral white matter of the spinal cord. Each group received a different combination of lentiviral vectors expressing PDGF-B, a constitutively active HRAS mutant, or shRNA targeting p53, or a control vector. All animals were monitored once per week for clinical deficits for 98 days. Tissues were harvested and analyzed using hematoxylin and eosin (H&E) and immunohistochemical (IHC) staining. Rats injected with PDGF-B+HRAS+sh-p53 (triple cocktail) exhibited statistically significant declines in all behavioral measures (Basso Beattie Bresnahan scoring, Tarlov scoring, weight, and survival rate) over time when compared to the control. Histologically, all groups except the control and those injected with sh-p53 displayed the development of tumors at the injection site, although there were differences in the rate of tumor growth and the histopathological features of the lesions between groups. Examination of immunohistochemistry revealed rats receiving triple cocktail displayed the largest and most significant increase in the Ki67 proliferation index and GFAP positivity than any other group. PDGF-B+HRAS also displayed a significant increase in the Ki67 proliferation index. Rats receiving PDGF-B alone and PDGF-B+ sh-p53 displayed more a significant increase in SOX2-positive staining than in any other group. We found that different vector combinations produced differing high-grade glioma models in rodents. The combination of all three vectors produced a model of high-grade glioma more efficiently and aggressively with respect to behavioral, physiological, and histological characteristics than the rest of the vector combinations. Thus, the present rat model of spinal cord glioma may potentially be used to evaluate therapeutic strategies in the future.

Dataset Information

Identification of differentially expressed genes and fusion genes associated with malignant progression of spinal cord gliomas by transcriptome analysis.

Publications

Identification of differentially expressed genes and fusion genes associated with malignant progression of spinal cord gliomas by transcriptome analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets