Identification of potential tumor suppressor genes using the GINI strategy in Mantle Cell Lymphoma cell lines
Inactivation of RB1 in mantle-cell lymphoma detected by nonsense-mediated mRNA decay pathway inhibition and microarray analysis.
No sample metadata fields
View SamplesMCL cell lines were treated with aza and aza in combination with TSA.
Identification of methylated genes associated with aggressive clinicopathological features in mantle cell lymphoma.
Cell line
View SamplesGenome-wide expression analysis of 228 hepatocellular carcinoma and 168 cirrhotic samples as part of a integrated study of gene expression and DNA-methylation de-regulation in patients with hepatocellular carcinoma
DNA methylation-based prognosis and epidrivers in hepatocellular carcinoma.
Sex, Specimen part, Disease, Subject
View SamplesIdentification of druggable targets is a prerequisite for developing targeted therapies against Ewing sarcoma. We report the identification of Protein Kinase C Beta (PRKCB) as a protein specifically and highly expressed in Ewing sarcoma as compared to other pediatric cancers. Its transcriptional activation is directly regulated by the EWSR1-FLI1 oncogene. Getting insights in PRKCB activity we show that, together with PRKCA, it is responsible for the phosphorylation of histone H3T6, allowing global maintenance of H3K4 trimethylation on a variety of gene promoters. In the long term, PRKCB RNA interference induces apoptosis in vitro. More importantly, in xenograft mice models, complete impairment of tumor engraftment and even tumor regression were observed upon PRKCB inhibition, highlighting PRKCB as a most valuable therapeutic target. Deciphering PRKCB roles in Ewing sarcoma using expression profiling, we found a strong overlap with genes modulated by EWSR1-FLI1 and an involvement of RPKCB in regulating crucial signaling pathways. Altogether, we show that PRKCB may have two important independent functions and should be considered as highly valuable for understanding Ewing sarcoma biology and as a promising target for new therapeutic approaches in Ewing sarcoma.
Targeting the EWSR1-FLI1 oncogene-induced protein kinase PKC-β abolishes ewing sarcoma growth.
Cell line
View SamplesHepatocellular carcinoma (HCC) is ranked second in cancer-associated deaths worldwide. Most cases of HCC are secondary to either a viral hepatitis infection (hepatitis B or C) or cirrhosis (alcoholism being the most common cause of hepatic cirrhosis). It is a complex and heterogeneous tumor due to activation of multiple cellular pathways and molecular alterations.
Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets.
Sex, Age, Specimen part, Disease, Disease stage
View SamplesGene expression analysis of different B-cell chronic lymphoproliferative disorders
Improved classification of leukemic B-cell lymphoproliferative disorders using a transcriptional and genetic classifier.
Specimen part
View SamplesGene expression analyis of primary MCL including IGHV mutated and unmutated cases
Molecular subsets of mantle cell lymphoma defined by the IGHV mutational status and SOX11 expression have distinct biologic and clinical features.
Specimen part, Disease, Disease stage
View SamplesMantle cell lymphoma (MCL) is an aggressive B-cell neoplasm displaying heterogeneous outcomes after treatment. In 2003, the Lymphoma/Leukemia Molecular Profiling Project described a powerful biomarker, the "proliferation signature", using gene expression in fresh frozen material. Here we describe the training and validation of a new assay that measures the proliferation signature in RNA derived from routinely available formalin-fixed paraffin-embedded (FFPE) biopsies.
New Molecular Assay for the Proliferation Signature in Mantle Cell Lymphoma Applicable to Formalin-Fixed Paraffin-Embedded Biopsies.
Disease, Disease stage, Subject
View SamplesPurpose: mRNA translation into protein is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs), and genetic variants has yet to be systematically studied. Using high-throughput sequencing (RNA-seq), we have measured cellular levels of mRNAs and ncRNAs, and their isoforms, in lymphoblast cell lines (LCL) and in polysomal fractions, the latter shown to yield strong correlations of mRNAs with expressed protein levels. Analysis of allelic RNA ratios at heterozygous SNPs served to reveal genetic factors in ribosomal loading. Methods: RNA-seq was performed on cytosolic extracts and polysomal fractions (3 ribosomes or more) from three lymphoblastoid cell lines. As each RNA fraction was amplified (NuGen kit), and relative contributions from various RNA classes differed between cytosol and polysomes, the fraction of any given RNA species loaded onto polysomes was difficult to quantitate. Therefore, we focused on relative recovery of the various RNA classes and rank order of single RNAs compared to total RNA. Results: RNA-seq of coding and non-coding RNAs (including microRNAs) in three LCLs revealed significant differences in polysomal loading of individual RNAs and isoforms, and between RNA classes. Moreover, correlated distribution between protein-coding and non-coding RNAs suggests possible interactions between them. Allele-selective RNA recruitment revealed strong genetic influence on polysomal loading for multiple RNAs. Allelic effects can be attributed to generation of different RNA isoforms before polysomal loading or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Several variants and genes identified by this approach are also associated with RNA expression and clinical phenotypes in various databases. Conclusions: These results provide a novel approach using complete transcriptome RNA-seq to study polysomal RNA recruitment and regulatory variants affecting protein translation. Overall design: cells from 3 samples were grown to 5x105 cells/mL density in T75 tissue culture flask and harvested, total RNA and polysome bound RNA was sequenced by Ion Proton
Allele-Selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-Coding and Noncoding RNAs, and RNA Isoforms.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
KAP1 regulates gene networks controlling T-cell development and responsiveness.
Specimen part
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