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. Availability: EBImage is free and open source, released under the LGPL license and available from the Bioconductor project (http://www.bioconductor.org/packages/release/bioc/html/EBImage.html). Contact: gregoire.pau@ebi.ac.uk
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.
Smoothened (SMO) inhibitors are under clinical investigation for the treatment of several cancers. Vismodegib is approved for the treatment of locally advanced and metastatic basal cell carcinoma ...(BCC). Most BCC patients experience significant clinical benefit on vismodegib, but some develop resistance. Genomic analysis of tumor biopsies revealed that vismodegib resistance is associated with Hedgehog (Hh) pathway reactivation, predominantly through mutation of the drug target SMO and to a lesser extent through concurrent copy number changes in SUFU and GLI2. SMO mutations either directly impaired drug binding or activated SMO to varying levels. Furthermore, we found evidence for intra-tumor heterogeneity, suggesting that a combination of therapies targeting components at multiple levels of the Hh pathway is required to overcome resistance.
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•Recurrent mechanisms reactivate the Hh pathway in SMO inhibitor-resistant BCC•Drug-binding pocket and activating SMO mutations reduce sensitivity to vismodegib•Downstream SUFU variants co-occur with alterations predicted to increase GLI2 levels•A relapsed tumor can harbor multiple resistance mechanisms
Sharpe et al. identify SMO mutations in the binding pocket for SMO inhibitors or that constitutively activate SMO in vismodegib-resistant basal cell carcinoma. They demonstrate that a single relapsed tumor can harbor clones with different resistance mutations.
Analysis of splice variants from short read RNA-seq data remains a challenging problem. Here we present a novel method for the genome-guided prediction and quantification of splice events from ...RNA-seq data, which enables the analysis of unannotated and complex splice events. Splice junctions and exons are predicted from reads mapped to a reference genome and are assembled into a genome-wide splice graph. Splice events are identified recursively from the graph and are quantified locally based on reads extending across the start or end of each splice variant. We assess prediction accuracy based on simulated and real RNA-seq data, and illustrate how different read aligners (GSNAP, HISAT2, STAR, TopHat2) affect prediction results. We validate our approach for quantification based on simulated data, and compare local estimates of relative splice variant usage with those from other methods (MISO, Cufflinks) based on simulated and real RNA-seq data. In a proof-of-concept study of splice variants in 16 normal human tissues (Illumina Body Map 2.0) we identify 249 internal exons that belong to known genes but are not related to annotated exons. Using independent RNA samples from 14 matched normal human tissues, we validate 9/9 of these exons by RT-PCR and 216/249 by paired-end RNA-seq (2 x 250 bp). These results indicate that de novo prediction of splice variants remains beneficial even in well-studied systems. An implementation of our method is freely available as an R/Bioconductor package Formula: see text.
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.
Primary liver cancer encompasses both hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA). 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 jagged1 (Jag1) in a mouse model of primary liver cancer driven by v‐akt murine thymoma viral oncogene homolog and neuroblastoma RAS viral oncogene homolog (NRas). We show that inhibition of Notch2 reduces tumor burden by eliminating highly malignant HCC‐ and CCA‐like tumors. Inhibition of the Notch ligand, Jag1, had a similar effect, consistent with Jag1 acting in cooperation with Notch2. This effect was specific to Notch2, because 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 2015;61:942–952)
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.
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.
Synopsis
Genetic screens for phenotypic similarity have made key contributions for associating genes with biological processes. Aggregating genes by similarity of their loss‐of‐function phenotype has provided insights into signalling pathways that have a conserved function from Drosophila to human (Nusslein‐Volhard and Wieschaus, 1980; Bier, 2005). Complex visual phenotypes, such as defects in pattern formation during development, greatly facilitated the classification of genes into pathways, and phenotypic similarities in many cases predicted molecular relationships. With RNA interference (RNAi), highly parallel phenotyping of loss‐of‐function effects in cultured cells has become feasible in many organisms whose genome have been sequenced (Boutros and Ahringer, 2008). One of the current challenges is the computational categorization of visual phenotypes and the prediction of gene function and associated biological processes. With large parts of the genome still being in unchartered territory, deriving functional information from large‐scale phenotype analysis promises to uncover novel gene–gene relationships and to generate functional maps to explore cellular processes.
In this study, we developed an automated approach using RNAi‐mediated cell phenotypes, multiparametric imaging and computational modelling to obtain functional information on previously uncharacterized genes. To generate broad, computer‐readable phenotypic signatures, we measured the effect of RNAi‐mediated knockdowns on changes of cell morphology in human cells on a genome‐wide scale. First, the several million cells were stained for nuclear and cytoskeletal markers and then imaged using automated microscopy. On the basis of fluorescent markers, we established an automated image analysis to classify individual cells (Figure 1A). After cell segmentation for determining nuclei and cell boundaries (Figure 1C), we computed 51 cell descriptors that quantified intensities, shape characteristics and texture (Figure 1F). Individual cells were categorized into 1 of 10 classes, which included cells showing protrusion/elongation, cells in metaphase, large cells, condensed cells, cells with lamellipodia and cellular debris (Figure 1D and E). Each siRNA knockdown was summarized by a phenotypic profile and differences between RNAi knockdowns were quantified by the similarity between phenotypic profiles. We termed the vector of scores a phenoprint (Figure 3C) and defined the phenotypic distance between a pair of perturbations as the distance between their corresponding phenoprints.
To visualize the distribution of all phenoprints, we plotted them in a genome‐wide map as a two‐dimensional representation of the phenotypic similarity relationships (Figure 3A). The complete data set and an interactive version of the phenotypic map are available at http://www.cellmorph.org. The map identified phenotypic ‘neighbourhoods’, which are characterized by cells with lamellipodia (WNK3, ANXA4), cells with prominent actin fibres (ODF2, SOD3), abundance of large cells (CA14), many elongated cells (SH2B2, ELMO2), decrease in cell number (TPX2, COPB1, COPA), increase in number of cells in metaphase (BLR1, CIB2) and combinations of phenotypes such as presence of large cells with protrusions and bright nuclei (PTPRZ1, RRM1; Figure 3B).
To test whether phenotypic similarity might serve as a predictor of gene function, we focused our further analysis on two clusters that contained genes associated with the DNA damage response (DDR) and genomic integrity (Figure 3A and C). The first phenotypic cluster included proteins with kinetochore‐associated functions such as NUF2 (Figure 3B) and SGOL1. It also contained the centrosomal protein CEP164 that has been described as an important mediator of the DNA damage‐activated signalling cascade (Sivasubramaniam et al, 2008) and the largely uncharacterized genes DONSON and SON. A second phenotypically distinct cluster included previously described components of the DDR pathway such as RRM1 (Figure 3A–C), CLSPN, PRIM2 and SETD8. Furthermore, this cluster contained the poorly characterized genes CADM1 and CD3EAP.
Cells activate a signalling cascade in response to DNA damage induced by exogenous and endogenous factors. Central are the kinases ATM and ATR as they serve as sensors of DNA damage and activators of further downstream kinases (Harper and Elledge, 2007; Cimprich and Cortez, 2008). To investigate whether DONSON, SON, CADM1 and CD3EAP, which were found in phenotypic ‘neighbourhoods’ to known DDR components, have a role in the DNA damage signalling pathway, we tested the effect of their depletion on the DDR on γ irradiation. As indicated by reduced CHEK1 phosphorylation, siRNA knock down of DONSON, SON, CD3EAP or CADM1 resulted in impaired DDR signalling on γ irradiation. Furthermore, knock down of DONSON or SON reduced phosphorylation of downstream effectors such as NBS1, CHEK1 and the histone variant H2AX on UVC irradiation. DONSON depletion also impaired recruitment of RPA2 onto chromatin and SON knockdown reduced RPA2 phosphorylation indicating that DONSON and SON presumably act downstream of the activation of ATM. In agreement to their phenotypic profile, these results suggest that DONSON, SON, CADM1 and CD3EAP are important mediators of the DDR. Further experiments demonstrated that they are also required for the maintenance of genomic integrity.
In summary, we show that genes with similar phenotypic profiles tend to share similar functions. The power of our computational and experimental approach is demonstrated by the identification of novel signalling regulators whose phenotypic profiles were found in proximity to known biological modules. Therefore, we believe that such phenotypic maps can serve as a resource for functional discovery and characterization of unknown genes. Furthermore, such approaches are also applicable for other perturbation reagents, such as small molecules in drug discovery and development. One could also envision combined maps that contain both siRNAs and small molecules to predict target–small molecule relationships and potential side effects.
How to predict gene function from phenotypic cues is a longstanding question in biology.
Using quantitative multiparametric imaging, RNAi‐mediated cell phenotypes were measured on a genome‐wide scale.
On the basis of phenotypic ‘neighbourhoods’, we identified previously uncharacterized human genes as mediators of the DNA damage response pathway and the maintenance of genomic integrity.
The phenotypic map is provided as an online resource at http://www.cellmorph.org for discovering further functional relationships for a broad spectrum of biological module
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.
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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