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Find video protocols related to scientific articles indexed in Pubmed.
Differential effects of targeting Notch receptors in a mouse model of liver cancer.
Hepatology
PUBLISHED: 09-26-2014
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Primary liver cancer encompasses both hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC). The Notch signaling pathway, known to be important for the proper development of liver architecture, is also a potential driver of primary liver cancer. However, with four known Notch receptors and several Notch ligands, it is not clear which Notch pathway members play the predominant role in liver cancer. To address this question we utilized antibodies to specifically target Notch1, Notch2, Notch3 or Jag1 in a mouse model of primary liver cancer driven by AKT and NRas. We show that inhibition of Notch2 reduces tumor burden by eliminating highly malignant hepatocellular carcinoma- and cholangiocarcinoma-like tumors. Inhibition of the Notch ligand Jag 1 had a similar effect, consistent with Jag1 acting in cooperation with Notch2. This effect was specific to Notch2, as Notch3 inhibition did not decrease tumor burden. Unexpectedly, Notch1 inhibition altered the relative proportion of tumor types, reducing HCC-like tumors but dramatically increasing CC-like tumors. Finally, we show that Notch2 and Jag1 are expressed in, and Notch2 signaling is activated in, a subset of human HCC samples. Conclusions: These findings underscore the distinct roles of different Notch receptors in the liver and suggest that inhibition of Notch2 signaling represents a novel therapeutic option in the treatment of liver cancer. (Hepatology 2014;).
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Spectrum of diverse genomic alterations define non-clear cell renal carcinoma subtypes.
Nat. Genet.
PUBLISHED: 06-10-2014
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To further understand the molecular distinctions between kidney cancer subtypes, we analyzed exome, transcriptome and copy number alteration data from 167 primary human tumors that included renal oncocytomas and non-clear cell renal cell carcinomas (nccRCCs), consisting of papillary (pRCC), chromophobe (chRCC) and translocation (tRCC) subtypes. We identified ten significantly mutated genes in pRCC, including MET, NF2, SLC5A3, PNKD and CPQ. MET mutations occurred in 15% (10/65) of pRCC samples and included previously unreported recurrent activating mutations. In chRCC, we found TP53, PTEN, FAAH2, PDHB, PDXDC1 and ZNF765 to be significantly mutated. Gene expression analysis identified a five-gene set that enabled the molecular classification of chRCC, renal oncocytoma and pRCC. Using RNA sequencing, we identified previously unreported gene fusions, including ACTG1-MITF fusion. Ectopic expression of the ACTG1-MITF fusion led to cellular transformation and induced the expression of downstream target genes. Finally, we observed upregulation of the anti-apoptotic factor BIRC7 in MiTF-high RCC tumors, suggesting a potential therapeutic role for BIRC7 inhibitors.
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An integrative analysis of colon cancer identifies an essential function for PRPF6 in tumor growth.
Genes Dev.
PUBLISHED: 05-01-2014
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The spliceosome machinery is composed of multimeric protein complexes that generate a diverse repertoire of mRNA through coordinated splicing of heteronuclear RNAs. While somatic mutations in spliceosome components have been discovered in several cancer types, the molecular bases and consequences of spliceosome aberrations in cancer are poorly understood. Here we report for the first time that PRPF6, a member of the tri-snRNP (small ribonucleoprotein) spliceosome complex, drives cancer proliferation by preferential splicing of genes associated with growth regulation. Inhibition of PRPF6 and other tri-snRNP complex proteins, but not other snRNP spliceosome complexes, selectively abrogated growth in cancer cells with high tri-snRNP levels. High-resolution transcriptome analyses revealed that reduced PRPF6 alters the constitutive and alternative splicing of a discrete number of genes, including an oncogenic isoform of the ZAK kinase. These findings implicate an essential role for PRPF6 in cancer via splicing of distinct growth-related gene products.
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Integrated exome and transcriptome sequencing reveals ZAK isoform usage in gastric cancer.
Nat Commun
PUBLISHED: 04-07-2014
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Gastric cancer is the second leading cause of worldwide cancer mortality, yet the underlying genomic alterations remain poorly understood. Here we perform exome and transcriptome sequencing and SNP array assays to characterize 51 primary gastric tumours and 32 cell lines. Meta-analysis of exome data and previously published data sets reveals 24 significantly mutated genes in microsatellite stable (MSS) tumours and 16 in microsatellite instable (MSI) tumours. Over half the patients in our collection could potentially benefit from targeted therapies. We identify 55 splice site mutations accompanied by aberrant splicing products, in addition to mutation-independent differential isoform usage in tumours. ZAK kinase isoform TV1 is preferentially upregulated in gastric tumours and cell lines relative to normal samples. This pattern is also observed in colorectal, bladder and breast cancers. Overexpression of this particular isoform activates multiple cancer-related transcription factor reporters, while depletion of ZAK in gastric cell lines inhibits proliferation. These results reveal the spectrum of genomic and transcriptomic alterations in gastric cancer, and identify isoform-specific oncogenic properties of ZAK.
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Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay.
BMC Bioinformatics
PUBLISHED: 06-24-2013
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The combination of time-lapse imaging of live cells with high-throughput perturbation assays is a powerful tool for genetics and cell biology. The Mitocheck project employed this technique to associate thousands of genes with transient biological phenotypes in cell division, cell death and migration. The original analysis of these data proceeded by assigning nuclear morphologies to cells at each time-point using automated image classification, followed by description of population frequencies and temporal distribution of cellular states through event-order maps. One of the choices made by that analysis was not to rely on temporal tracking of the individual cells, due to the relatively low image sampling frequency, and to focus on effects that could be discerned from population-levelbehaviour.
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The genomic and transcriptomic landscape of a HeLa cell line.
G3 (Bethesda)
PUBLISHED: 04-04-2013
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HeLa is the most widely used model cell line for studying human cellular and molecular biology. To date, no genomic reference for this cell line has been released, and experiments have relied on the human reference genome. Effective design and interpretation of molecular genetic studies performed using HeLa cells require accurate genomic information. Here we present a detailed genomic and transcriptomic characterization of a HeLa cell line. We performed DNA and RNA sequencing of a HeLa Kyoto cell line and analyzed its mutational portfolio and gene expression profile. Segmentation of the genome according to copy number revealed a remarkably high level of aneuploidy and numerous large structural variants at unprecedented resolution. Some of the extensive genomic rearrangements are indicative of catastrophic chromosome shattering, known as chromothripsis. Our analysis of the HeLa gene expression profile revealed that several pathways, including cell cycle and DNA repair, exhibit significantly different expression patterns from those in normal human tissues. Our results provide the first detailed account of genomic variants in the HeLa genome, yielding insight into their impact on gene expression and cellular function as well as their origins. This study underscores the importance of accounting for the strikingly aberrant characteristics of HeLa cells when designing and interpreting experiments, and has implications for the use of HeLa as a model of human biology.
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Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.
Mol. Syst. Biol.
PUBLISHED: 04-12-2010
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Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.
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EBImage--an R package for image processing with applications to cellular phenotypes.
Bioinformatics
PUBLISHED: 03-27-2010
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EBImage provides general purpose functionality for reading, writing, processing and analysis of images. Furthermore, in the context of microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and use of existing tools in the R environment for signal processing, statistical modeling, machine learning and data visualization.
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Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.
Nature
PUBLISHED: 01-22-2010
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Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.