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GSE73219
Homo sapiens
12 Downloadable Samples
Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
Global transcriptomic alterations of both coding and non-coding RNA species are a ubiquitous feature associated with human cancers including hepatocellular carcinoma (HCC). Dysregulation of RNA-binding proteins (RBPs), the key regulators of RNA processing, is one mechanism in which cancer cells select to promote tumorigenesis. We analyzed genomic alterations amongst a family of more than 800 mRNA RBPs (mRBPs) in 1,225 clinical specimens from HCC patients and found that RBPs are significantly activated through gene amplification in a subset of tumors with poor prognosis, suggesting their potential oncogenic roles in HCC progression. Amongst the top candidates, RD binding protein (RDBP) was further characterized for its oncogenic role and effects on the HCC transcriptome. While the activation of RDBP induced an oncogenic phenotype, the abrogation of RDBP in HCC cells significantly decreased cancer associated phenotypes such as cell proliferation, migration/invasion and tumorigenicity in vivo. Further microarray analyses revealed that RDBP-dependent genes were tumor-related with a significant enrichment for c-Myc targets, suggesting interplay between RDBP and c-Myc signaling. Similar data were also found in HCC clinical specimens where c-Myc amplification was uncommon. Consistently, the RDBP-dependent c-Myc target gene signature was able to predict HCC patient survival in two independent cohorts of more than 400 patients. Taken together, our results suggest that oncogenic activation of RDBP is a novel mechanism that contributes to global transcriptome imbalance that is selective for the activation of c-Myc oncogenic signaling in HCC.
Publication Title
Oncogenic Activation of the RNA Binding Protein NELFE and MYC Signaling in Hepatocellular Carcinoma.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 9 Downloadable Samples
Illumina HiSeq 2500
Description
Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns
Publication Title
Multilayered Control of Alternative Splicing Regulatory Networks by Transcription Factors.
Sample Metadata Fields
Cell line, Subject
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