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Functional genomics analyses of RNA-binding proteins reveal the splicing regulator SNRPB as an oncogenic candidate in glioblastoma.

ABSTRACT: Glioblastoma (GBM) is the most common and aggressive type of brain tumor. Currently, GBM has an extremely poor outcome and there is no effective treatment. In this context, genomic and transcriptomic analyses have become important tools to identify new avenues for therapies. RNA-binding proteins (RBPs) are master regulators of co- and post-transcriptional events; however, their role in GBM remains poorly understood. To further our knowledge of novel regulatory pathways that could contribute to gliomagenesis, we have conducted a systematic study of RBPs in GBM.By measuring expression levels of 1542 human RBPs in GBM samples and glioma stem cell samples, we identified 58 consistently upregulated RBPs. Survival analysis revealed that increased expression of 21 RBPs was also associated with a poor prognosis. To assess the functional impact of those RBPs, we modulated their expression in GBM cell lines and performed viability, proliferation, and apoptosis assays. Combined results revealed a prominent oncogenic candidate, SNRPB, which encodes core spliceosome machinery components. To reveal the impact of SNRPB on splicing and gene expression, we performed its knockdown in a GBM cell line followed by RNA sequencing. We found that the affected genes were involved in RNA processing, DNA repair, and chromatin remodeling. Additionally, genes and pathways already associated with gliomagenesis, as well as a set of general cancer genes, also presented with splicing and expression alterations.Our study provides new insights into how RBPs, and specifically SNRPB, regulate gene expression and directly impact GBM development.

SUBMITTER: Correa BR

PROVIDER: S-EPMC4901439 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Functional genomics analyses of RNA-binding proteins reveal the splicing regulator SNRPB as an oncogenic candidate in glioblastoma.

Correa Bruna R BR de Araujo Patricia Rosa PR Qiao Mei M Burns Suzanne C SC Chen Chen C Schlegel Richard R Agarwal Seema S Galante Pedro A F PA Penalva Luiz O F LO

Genome biology 20160610 1

<h4>Background</h4>Glioblastoma (GBM) is the most common and aggressive type of brain tumor. Currently, GBM has an extremely poor outcome and there is no effective treatment. In this context, genomic and transcriptomic analyses have become important tools to identify new avenues for therapies. RNA-binding proteins (RBPs) are master regulators of co- and post-transcriptional events; however, their role in GBM remains poorly understood. To further our knowledge of novel regulatory pathways that co ...[more]

PMID: 27287018

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Project description:Glioblastomas remain the deadliest brain tumour, with a dismal ∼12-16-month survival from diagnosis. Therefore, identification of new diagnostic, prognostic and therapeutic tools to tackle glioblastomas is urgently needed. Emerging evidence indicates that the cellular machinery controlling the splicing process (spliceosome) is altered in tumours, leading to oncogenic splicing events associated with tumour progression and aggressiveness. Here, we identify for the first time a profound dysregulation in the expression of relevant spliceosome components and splicing factors (at mRNA and protein levels) in well characterized cohorts of human high-grade astrocytomas, mostly glioblastomas, compared to healthy brain control samples, being SRSF3, RBM22, PTBP1 and RBM3 able to perfectly discriminate between tumours and control samples, and between proneural-like or mesenchymal-like tumours versus control samples from different mouse models with gliomas. Results were confirmed in four additional and independent human cohorts. Silencing of SRSF3, RBM22, PTBP1 and RBM3 decreased aggressiveness parameters in vitro (e.g. proliferation, migration, tumorsphere-formation, etc.) and induced apoptosis, especially SRSF3. Remarkably, SRSF3 was correlated with patient survival and relevant tumour markers, and its silencing in vivo drastically decreased tumour development and progression, likely through a molecular/cellular mechanism involving PDGFRB and associated oncogenic signalling pathways (PI3K-AKT/ERK), which may also involve the distinct alteration of alternative splicing events of specific transcription factors controlling PDGFRB (i.e. TP73). Altogether, our results demonstrate a drastic splicing machinery-associated molecular dysregulation in glioblastomas, which could potentially be considered as a source of novel diagnostic and prognostic biomarkers as well as therapeutic targets for glioblastomas. Remarkably, SRSF3 is directly associated with glioblastoma development, progression, aggressiveness and patient survival and represents a novel potential therapeutic target to tackle this devastating pathology.

Project description:BACKGROUND:Regulation of pre-mRNA splicing diversifies protein products and affects many biological processes. Arabidopsis thaliana Serine/Arginine-rich 45 (SR45), regulates pre-mRNA splicing by interacting with other regulatory proteins and spliceosomal subunits. Although SR45 has orthologs in diverse eukaryotes, including human RNPS1, the sr45-1 null mutant is viable. Narrow flower petals and reduced seed formation suggest that SR45 regulates genes involved in diverse processes, including reproduction. To understand how SR45 is involved in the regulation of reproductive processes, we studied mRNA from the wild-type and sr45-1 inflorescences using RNA-seq, and identified SR45-bound RNAs by immunoprecipitation. RESULTS:Using a variety of bioinformatics tools, we identified a total of 358 SR45 differentially regulated (SDR) genes, 542 SR45-dependent alternative splicing (SAS) events, and 1812 SR45-associated RNAs (SARs). There is little overlap between SDR genes and SAS genes, and neither set of genes is enriched for flower or seed development. However, transcripts from reproductive process genes are significantly overrepresented in SARs. In exploring the fate of SARs, we found that a total of 81 SARs are subject to alternative splicing, while 14 of them are known Nonsense-Mediated Decay (NMD) targets. Motifs related to GGNGG are enriched both in SARs and near different types of SAS events, suggesting that SR45 recognizes this motif directly. Genes involved in plant defense are significantly over-represented among genes whose expression is suppressed by SR45, and sr45-1 plants do indeed show enhanced immunity. CONCLUSION:We find that SR45 is a suppressor of innate immunity. We find that a single motif (GGNGG) is highly enriched in both RNAs bound by SR45 and in sequences near SR45- dependent alternative splicing events in inflorescence tissue. We find that the alternative splicing events regulated by SR45 are enriched for this motif whether the effect of SR45 is activation or repression of the particular event. Thus, our data suggests that SR45 acts to control splice site choice in a way that defies simple categorization as an activator or repressor of splicing.

Project description:Wheat yellow (stripe) rust caused by Puccinia striiformis f. sp. tritici (PST) is one of the most devastating diseases of wheat worldwide. To design effective breeding strategies that maximize the potential for durable disease resistance it is important to understand the molecular basis of PST pathogenicity. In particular, the characterisation of the structure, function and evolutionary dynamics of secreted effector proteins that are detected by host immune receptors can help guide and prioritize breeding efforts. However, to date, our knowledge of the effector repertoire of cereal rust pathogens is limited.We re-sequenced genomes of four PST isolates from the US and UK to identify effector candidates and relate them to their distinct virulence profiles. First, we assessed SNP frequencies between all isolates, with heterokaryotic SNPs being over tenfold more frequent (5.29 ± 2.23 SNPs/kb) than homokaryotic SNPs (0.41 ± 0.28 SNPs/kb). Next, we implemented a bioinformatics pipeline to integrate genomics, transcriptomics, and effector-focused annotations to identify and classify effector candidates in PST. RNAseq analysis highlighted transcripts encoding secreted proteins that were significantly enriched in haustoria compared to infected tissue. The expression of 22 candidate effector genes was characterised using qRT-PCR, revealing distinct temporal expression patterns during infection in wheat. Lastly, we identified proteins that displayed non-synonymous substitutions specifically between the two UK isolates PST-87/7 and PST-08/21, which differ in virulence to two wheat varieties. By focusing on polymorphic variants enriched in haustoria, we identified five polymorphic effector candidates between PST-87/7 and PST-08/21 among 2,999 secreted proteins. These allelic variants are now a priority for functional validation as virulence/avirulence effectors in the corresponding wheat varieties.Integration of genomics, transcriptomics, and effector-directed annotation of PST isolates has enabled us to move beyond the single isolate-directed catalogues of effector proteins and develop a framework for mining effector proteins in closely related isolates and relate these back to their defined virulence profiles. This should ultimately lead to more comprehensive understanding of the PST pathogenesis system, an important first step towards developing more effective surveillance and management strategies for one of the most devastating pathogens of wheat.

Project description:Glioblastoma (GBM) is the most common type of malignant tumor of the central nervous system. The prognosis of patients with GBM is very poor, with a survival time of ~15 months. GBM is highly heterogeneous and highly aggressive. Surgical removal of intracranial tumors does provide a good advantage for patients as there is a high rate of recurrence. The understanding of this type of cancer needs to be strengthened, and the aim of the present study was to identify gene signatures present in GBM and uncover their potential mechanisms. The gene expression profiles of GSE15824 and GSE51062 were downloaded from the Gene Expression Omnibus database. Normalization of the data from primary GBM samples and normal samples in the two databases was conducted using R software. Then, joint analysis of the data was performed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the protein?protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed using Cytoscape software. Identification of prognostic biomarkers was conducted using UALCAN. In total, 9,341 DEGs were identified in the GBM samples, including 9,175 upregulated genes and 166 downregulated genes. The top 1,000 upregulated DEGs and all of the downregulated DEGs were selected for GO, KEGG and prognostic biomarker analyses. The GO results showed that the upregulated DEGs were significantly enriched in biological processes (BP), including immune response, cell division and cell proliferation, and the downregulated DEGs were also significantly enriched in BP, including cell growth, intracellular signal transduction and signal transduction by protein phosphorylation. KEGG pathway analysis showed that the upregulated DEGs were enriched in circadian entrainment, cytokine?cytokine receptor interaction and maturity onset diabetes of the young, while the downregulated DEGs were enriched in the TGF?? signaling pathway, MAPK signaling pathway and pathways in cancer. All of the downregulated genes and the top 1,000 upregulated genes were selected to establish the PPI network, and the sub?networks revealed that these genes were involved in significant pathways, including olfactory transduction, neuroactive ligand?receptor interaction and viral carcinogenesis. In total, seven genes were identified as good prognostic biomarkers. In conclusion, the identified DEGs and hub genes contribute to the understanding of the molecular mechanisms underlying the development of GBM and they may be used as diagnostic and prognostic biomarkers and molecular targets for the treatment of patients with GBM in the future.

Dataset Information

Functional genomics analyses of RNA-binding proteins reveal the splicing regulator SNRPB as an oncogenic candidate in glioblastoma.

Publications

Functional genomics analyses of RNA-binding proteins reveal the splicing regulator SNRPB as an oncogenic candidate in glioblastoma.

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