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1.  Clustering phenotype populations by genome-wide RNAi and multiparametric imaging 
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 for discovering further functional relationships for a broad spectrum of biological module
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 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.
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.
PMCID: PMC2913390  PMID: 20531400
DNA damage response signalling; massively parallel phenotyping; phenotype networks; RNAi screening
2.  Proteomic snapshot of the EGF-induced ubiquitin network 
In this work, the authors report the first proteome-wide analysis of EGF-regulated ubiquitination, revealing surprisingly pervasive growth factor-induced ubiquitination across a broad range of cellular systems and signaling pathways.
Epidermal growth factor (EGF) triggers a novel ubiquitin (Ub)-based signaling cascade that appears to intersect both housekeeping and regulatory circuitries of cellular physiology.The EGF-regulated Ubiproteome includes scores ubiquitinating and deubiquitinating enzymes, suggesting that the Ub signal might be rapidly transmitted and amplified through the Ub machinery.The EGF-Ubiproteome overlaps significantly with the EGF-phosphotyrosine proteome, pointing to a possible crosstalk between these two signaling mechanisms.The significant number of biological insights uncovered in our study (among which EphA2 as a novel, downstream ubiquitinated target of EGF receptor) illustrates the general relevance of such proteomic screens and calls for further analysis of the dynamics of the Ubiproteome.
Ubiquitination is a process by which one or more ubiquitin (Ub) monomers or chains are covalently attached to target proteins by E3 ligases. Deubiquitinating enzymes (DUBs) revert Ub conjugation, thus ensuring a dynamic equilibrium between pools of ubiquitinated and deubiquitinated proteins (Amerik and Hochstrasser, 2004). Traditionally, ubiquitination has been associated with protein degradation; however, it is now becoming apparent that this post-translation modification is an important signaling mechanism that can modulate the function, localization and protein/protein interaction abilities of targets (Mukhopadhyay and Riezman, 2007; Ravid and Hochstrasser, 2008).
One of the best-characterized signaling pathways involving ubiquitination is the epidermal growth factor (EGF)-induced pathway. Upon EGF stimulation, a variety of proteins are subject to Ub modification. These include the EGF receptor (EGFR), which undergoes both multiple monoubiquitination (Haglund et al, 2003) and K63-linked polyubiquitination (Huang et al, 2006), as well as components of the downstream endocytic machinery, which are modified by monoubiquitination (Polo et al, 2002; Mukhopadhyay and Riezman, 2007). Ubiquitination of the EGFR has been shown to have an impact on receptor internalization, intracellular sorting and metabolic fate (Acconcia et al, 2009). However, little is known about the wider impact of EGF-induced ubiquitination on cellular homeostasis and on the pleiotropic biological functions of the EGFR. In this paper, we attempt to address this issue by characterizing the repertoire of proteins that are ubiquitinated upon EGF stimulation, i.e., the EGF-Ubiproteome.
To achieve this, we employed two different purification procedures (endogenous—based on the purification of proteins modified by endogenous Ub from human cells; tandem affinity purification (TAP)—based on the purification of proteins modified by an ectopically expressed tagged-Ub from mouse cells) with stable isotope labeling with amino acids in cell culture-based MS to obtain both steady-state Ubiproteomes and EGF-induced Ubiproteomes. The steady-state Ubiproteomes consist of 1175 and 582 unambiguously identified proteins for the endogenous and TAP approaches, respectively, which we largely validated. Approximately 15% of the steady-state Ubiproteome was EGF-regulated at 10 min after stimulation; 176 of 1175 in the endogenous approach and 105 of 582 in the TAP approach. Both hyper- and hypoubiquitinated proteins were detected, indicating that EGFR-mediated signaling can modulate the ubiquitin network in both directions. Interestingly, many E2, E3 and DUBs were present in the EGF-Ubiproteome, suggesting that the Ub signal might be rapidly transmitted and amplified through the Ub machinery. Moreover, analysis of Ub-chain topology, performed using mass spectrometry and specific abs, suggested that the K63-linkage was the major Ub-based signal in the EGF-induced pathway.
To obtain a higher-resolution molecular picture of the EGF-regulated Ub network, we performed a network analysis on the non-redundant EGF-Ubiproteome (265 proteins). This analysis revealed that in addition to well-established liaisons with endocytosis-related pathways, the EGF-Ubiproteome intersects many circuitries of intracellular signaling involved in, e.g., DNA damage checkpoint regulation, cell-to-cell adhesion mechanisms and actin remodeling (Figure 5A).
Moreover, the EGF-Ubiproteome was enriched in hubs, proteins that can establish multiple protein/protein interaction and thereby regulate the organization of networks. These results are indicative of a crosstalk between EGFR-activated pathways and other signaling pathways through the Ub-network.
As EGF binding to its receptor also triggers a series of phosphorylation events, we examined whether there was any overlap between our EGF-Ubiproteome and published EGF-induced phosphotyrosine (pY) proteomes (Blagoev et al, 2004; Oyama et al, 2009; Hammond et al, 2010). We observed a significant overlap between ubiquitinated and pY proteins: 23% (61 of 265) of the EGF-Ubiproteome proteins were also tyrosine phosphorylated. Pathway analysis of these 61 Ub/pY-containing proteins revealed a significant enrichment in endocytic and signal-transduction pathways, while ‘hub analysis' revealed that Ub/pY-containing proteins are enriched in highly connected proteins to an even greater extent than Ub-containing proteins alone. These data point to a complex interplay between the Ub and pY networks and suggest that the flow of information from the receptor to downstream signaling molecules is driven by two complementary and interlinked enzymatic cascades: kinases/phosphatases and E3 ligases/DUBs.
Finally, we provided a proof of principle of the biological relevance of our EGF-Ubiproteome. We focused on EphA2, a receptor tyrosine kinase, which is involved in development and is often overexpressed in cancer (Pasquale, 2008). We started from the observation that EphA2 is present in the EGF-Ubiproteome and that proteins of the EGF-Ubiproteome are enriched in the Ephrin receptor signaling pathway(s). We confirmed the MS data by demonstrating that the EphA2 is ubiquitinated upon EGF stimulation. Moreover, EphA2 also undergoes tyrosine phosphorylation, indicating crosstalk between the two receptors. The EGFR kinase domain was essential for these modifications of EphA2, and a partial co-internalization with EGFR upon EGF activation was clearly detectable. Finally, we demonstrated by knockdown of EphA2 in MCF10A cells that this receptor is critically involved in EGFR biological outcomes, such as proliferation and migration (Figure 7).
Overall, our results unveil the complex impact of growth factor signaling on Ub-based intracellular networks to levels that extend well beyond what might have been expected and highlight the ‘resource' feature of our EGF-Ubiproteome.
The activity, localization and fate of many cellular proteins are regulated through ubiquitination, a process whereby one or more ubiquitin (Ub) monomers or chains are covalently attached to target proteins. While Ub-conjugated and Ub-associated proteomes have been described, we lack a high-resolution picture of the dynamics of ubiquitination in response to signaling. In this study, we describe the epidermal growth factor (EGF)-regulated Ubiproteome, as obtained by two complementary purification strategies coupled to quantitative proteomics. Our results unveil the complex impact of growth factor signaling on Ub-based intracellular networks to levels that extend well beyond what might have been expected. In addition to endocytic proteins, the EGF-regulated Ubiproteome includes a large number of signaling proteins, ubiquitinating and deubiquitinating enzymes, transporters and proteins involved in translation and transcription. The Ub-based signaling network appears to intersect both housekeeping and regulatory circuitries of cellular physiology. Finally, as proof of principle of the biological relevance of the EGF-Ubiproteome, we demonstrated that EphA2 is a novel, downstream ubiquitinated target of epidermal growth factor receptor (EGFR), critically involved in EGFR biological responses.
PMCID: PMC3049407  PMID: 21245847
EGF; network; proteomics; signaling; ubiquitin
3.  A Combination of Screening and Computational Approaches for the Identification of Novel Compounds That Decrease Mast Cell Degranulation 
Journal of Biomolecular Screening  2015;20(6):720-728.
High-content screening of compound libraries poses various challenges in the early steps in drug discovery such as gaining insights into the mode of action of the selected compounds. Here, we addressed these challenges by integrating two biological screens through bioinformatics and computational analysis. We screened a small-molecule library enriched in amphiphilic compounds in a degranulation assay in rat basophilic leukemia 2H3 (RBL-2H3) cells. The same library was rescreened in a high-content image-based endocytosis assay in HeLa cells. This assay was previously applied to a genome-wide RNAi screen that produced quantitative multiparametric phenotypic profiles for genes that directly or indirectly affect endocytosis. By correlating the endocytic profiles of the compounds with the genome-wide siRNA profiles, we identified candidate pathways that may be inhibited by the compounds. Among these, we focused on the Akt pathway and validated its inhibition in HeLa and RBL-2H3 cells. We further showed that the compounds inhibited the translocation of the Akt-PH domain to the plasma membrane. The approach performed here can be used to integrate chemical and functional genomics screens for investigating the mechanism of action of compounds.
PMCID: PMC4512528  PMID: 25838434
mast cell; phosphorylation; Akt; screening
4.  A parallel genome-wide RNAi screening strategy to identify host proteins important for entry of Marburg virus and H5N1 influenza virus 
Virology Journal  2015;12:194.
Genome-wide RNAi screening has been widely used to identify host proteins involved in replication and infection of different viruses, and numerous host factors are implicated in the replication cycles of these viruses, demonstrating the power of this approach. However, discrepancies on target identification of the same viruses by different groups suggest that high throughput RNAi screening strategies need to be carefully designed, developed and optimized prior to the large scale screening.
Two genome-wide RNAi screens were performed in parallel against the entry of pseudotyped Marburg viruses and avian influenza virus H5N1 utilizing an HIV-1 based surrogate system, to identify host factors which are important for virus entry. A comparative analysis approach was employed in data analysis, which alleviated systematic positional effects and reduced the false positive number of virus-specific hits.
The parallel nature of the strategy allows us to easily identify the host factors for a specific virus with a greatly reduced number of false positives in the initial screen, which is one of the major problems with high throughput screening. The power of this strategy is illustrated by a genome-wide RNAi screen for identifying the host factors important for Marburg virus and/or avian influenza virus H5N1 as described in this study.
This strategy is particularly useful for highly pathogenic viruses since pseudotyping allows us to perform high throughput screens in the biosafety level 2 (BSL-2) containment instead of the BSL-3 or BSL-4 for the infectious viruses, with alleviated safety concerns. The screening strategy together with the unique comparative analysis approach makes the data more suitable for hit selection and enables us to identify virus-specific hits with a much lower false positive rate.
PMCID: PMC4657351  PMID: 26596270
5.  Comparative Genomics Reveals Two Novel RNAi Factors in Trypanosoma brucei and Provides Insight into the Core Machinery 
PLoS Pathogens  2012;8(5):e1002678.
The introduction ten years ago of RNA interference (RNAi) as a tool for molecular exploration in Trypanosoma brucei has led to a surge in our understanding of the pathogenesis and biology of this human parasite. In particular, a genome-wide RNAi screen has recently been combined with next-generation Illumina sequencing to expose catalogues of genes associated with loss of fitness in distinct developmental stages. At present, this technology is restricted to RNAi-positive protozoan parasites, which excludes T. cruzi, Leishmania major, and Plasmodium falciparum. Therefore, elucidating the mechanism of RNAi and identifying the essential components of the pathway is fundamental for improving RNAi efficiency in T. brucei and for transferring the RNAi tool to RNAi-deficient pathogens. Here we used comparative genomics of RNAi-positive and -negative trypanosomatid protozoans to identify the repertoire of factors in T. brucei. In addition to the previously characterized Argonaute 1 (AGO1) protein and the cytoplasmic and nuclear Dicers, TbDCL1 and TbDCL2, respectively, we identified the RNA Interference Factors 4 and 5 (TbRIF4 and TbRIF5). TbRIF4 is a 3′-5′ exonuclease of the DnaQ superfamily and plays a critical role in the conversion of duplex siRNAs to the single-stranded form, thus generating a TbAGO1-siRNA complex required for target-specific cleavage. TbRIF5 is essential for cytoplasmic RNAi and appears to act as a TbDCL1 cofactor. The availability of the core RNAi machinery in T. brucei provides a platform to gain mechanistic insights in this ancient eukaryote and to identify the minimal set of components required to reconstitute RNAi in RNAi-deficient parasites.
Author Summary
RNA interference (RNAi), a naturally-occurring pathway whereby the presence of double-stranded RNA in a cell triggers the degradation of homologous mRNA, has been harnessed in many organisms as an invaluable molecular biology tool to interrogate gene function. Although this technology is widely used in the protozoan parasite Trypanosoma brucei, other parasites of considerable public health significance, such as Trypanosoma cruzi, Leishmania major, and Plasmodium falciparum do not perform RNAi. Since RNAi has recently been introduced into budding yeast, this opens up the possibility that RNAi can be reconstituted in these pathogens. The key to this is getting a handle on the essential RNAi factors in T. brucei. By applying comparative genomics we identified five genes that are present in the RNAi-proficient species, but not in RNAi-deficient species: three previously identified RNAi factors, and two novel ones, which are described here. This insight into the core T. brucei RNAi machinery represents a major step towards transferring this pathway to RNAi-deficient parasites.
PMCID: PMC3359990  PMID: 22654659
6.  A novel computational model of the circadian clock in Arabidopsis that incorporates PRR7 and PRR9 
We developed a mathematical model of the Arabidopsis circadian clock, including PRR7 and PRR9, which is able to predict several single, double and triple mutant phenotypes.Sensitivity Analysis was used to identify the properties and time sensing mechanisms of model structures.PRR7 and CCA1/LHY were identified as weak points of the mathematical model indicating where more experimental data is needed for further model development.Detailed dynamical studies showed that the timing of an evening light sensing element is essential for day length responsiveness
In recent years, molecular genetic techniques have revealed a complex network of components in the Arabidopsis circadian clock. Mathematical models allow for a detailed study of the dynamics and architecture of such complex gene networks leading to a better understanding of the genetic interactions. It is important to maintain a constant iteration with experimentation, to include novel components as they are discovered and use the updated model to design new experiments. This study develops a framework to introduce new components into the mathematical model of the Arabidopsis circadian clock accelerating the iterative model development process and gaining insight into the system's properties.
We used the interlocked feedback loop model published in Locke et al (2005) as the base model. In Arabidopsis, the first suggested regulatory loop involves the morning expressed transcription factors CIRCADIAN CLOCK-ASSOCIATED 1 (CCA1) and LATE ELONGATED HYPOCOTYL (LHY), and the evening expressed pseudo-response regulator TIMING OF CAB EXPRESSION (TOC1). The hypothetical component X had been introduced to realize a longer delay between gene expression of CCA1/LHY and TOC1. The introduction of Y was motivated by the need for a mechanism to reproduce the dampening short period rhythms of the cca1/lhy double mutant and to include an additional light input at the end of the day.
In this study, the new components pseudo-response regulators PRR7 and PRR9 were added in negative feedback loops based on the biological hypothesis that they are activated by LHY and in turn repress LHY transcription (Farré et al, 2005; Figure 1). We present three iterations steps of model development (Figure 1A–C).
A wide range of tools was used to establish and analyze new model structures. One of the challenges facing mathematical modeling of biological processes is parameter identification; they are notoriously difficult to determine experimentally. We established an optimization procedure based on an evolutionary strategy with a cost function mainly derived from wild-type characteristics. This ensured that the model was not restricted by a specific set of parameters and enabled us to use a large set of biological mutant information to assess the predictive capability of the model structure. Models were evaluated by means of an extended phenotype catalogue, allowing for an easy and fair comparison of the structures. We also carried out detailed simulation analysis of component interactions to identify weak points in the structure and suggest further modifications. Finally, we applied sensitivity analysis in a novel manner, using it to direct the model development. Sensitivity analysis provides quantitative measures of robustness; the two measures in this study were the traces of component concentrations over time (classical state sensitivities) and phase behavior (measured by the phase response curve). Three major results emerged from the model development process.
First, the iteration process helped us to learn about general characteristics of the system. We observed that the timing of Y expression is critical for evening light entrainment, which enables the system to respond to changes in day length. This is important for our understanding of the mechanism of light input to the clock and will add in the identification of biological candidates for this function. In addition, our results suggest that a detailed description of the mechanisms of genetic interactions is important for the systems behavior. We observed that the introduction of an experimentally based precise light regulation mechanism on PRR9 expression had a significant effect on the systems behavior.
Second, the final model structure (Figure 1C) was capable of predicting a wide range of mutant phenotypes, such as a reduction of TOC1 expression by RNAi (toc1RNAi), mutations in PRR7 and PRR9 and the novel mutant combinations prr9toc1RNAi and prr7prr9toc1RNAi. However, it was unable to predict the mutations in CCA1 and LHY.
Finally, sensitivity analysis identified the weak points of the system. The developed model structure was heavily based on the TOC1/Y feedback loop. This could explain the model's failure to predict the cca1lhy double mutant phenotype. More detailed information on the regulation of CCA1 and LHY expression will be important to achieve the right balance between the different regulatory loops in the mathematical model. This is in accordance with genetic studies that have identified several genes involved in the regulation of LHY and CCA1 expression. The identification of their mechanism of action will be necessary for the next model development.
In plants, as in animals, the core mechanism to retain rhythmic gene expression relies on the interaction of multiple feedback loops. In recent years, molecular genetic techniques have revealed a complex network of clock components in Arabidopsis. To gain insight into the dynamics of these interactions, new components need to be integrated into the mathematical model of the plant clock. Our approach accelerates the iterative process of model identification, to incorporate new components, and to systematically test different proposed structural hypotheses. Recent studies indicate that the pseudo-response regulators PRR7 and PRR9 play a key role in the core clock of Arabidopsis. We incorporate PRR7 and PRR9 into an existing model involving the transcription factors TIMING OF CAB (TOC1), LATE ELONGATED HYPOCOTYL (LHY) and CIRCADIAN CLOCK ASSOCIATED (CCA1). We propose candidate models based on experimental hypotheses and identify the computational models with the application of an optimization routine. Validation is accomplished through systematic analysis of various mutant phenotypes. We introduce and apply sensitivity analysis as a novel tool for analyzing and distinguishing the characteristics of proposed architectures, which also allows for further validation of the hypothesized structures.
PMCID: PMC1682023  PMID: 17102803
Arabidopsis; circadian rhythms; mathematical modeling; parameter optimization; sensitivity analysis
7.  Endocytic Crosstalk: Cavins, Caveolins, and Caveolae Regulate Clathrin-Independent Endocytosis 
PLoS Biology  2014;12(4):e1001832.
Caveolar proteins and caveolae negatively regulate a second clathrin-independent endocytic CLIC/GEEC pathway; caveolin-1 affects membrane diffusion properties of raft-associated CLIC cargo, and the scaffolding domain of caveolin-1 is required and sufficient for endocytic inhibition.
Several studies have suggested crosstalk between different clathrin-independent endocytic pathways. However, the molecular mechanisms and functional relevance of these interactions are unclear. Caveolins and cavins are crucial components of caveolae, specialized microdomains that also constitute an endocytic route. Here we show that specific caveolar proteins are independently acting negative regulators of clathrin-independent endocytosis. Cavin-1 and Cavin-3, but not Cavin-2 or Cavin-4, are potent inhibitors of the clathrin-independent carriers/GPI-AP enriched early endosomal compartment (CLIC/GEEC) endocytic pathway, in a process independent of caveola formation. Caveolin-1 (CAV1) and CAV3 also inhibit the CLIC/GEEC pathway upon over-expression. Expression of caveolar protein leads to reduction in formation of early CLIC/GEEC carriers, as detected by quantitative electron microscopy analysis. Furthermore, the CLIC/GEEC pathway is upregulated in cells lacking CAV1/Cavin-1 or with reduced expression of Cavin-1 and Cavin-3. Inhibition by caveolins can be mimicked by the isolated caveolin scaffolding domain and is associated with perturbed diffusion of lipid microdomain components, as revealed by fluorescence recovery after photobleaching (FRAP) studies. In the absence of cavins (and caveolae) CAV1 is itself endocytosed preferentially through the CLIC/GEEC pathway, but the pathway loses polarization and sorting attributes with consequences for membrane dynamics and endocytic polarization in migrating cells and adult muscle tissue. We also found that noncaveolar Cavin-1 can act as a modulator for the activity of the key regulator of the CLIC/GEEC pathway, Cdc42. This work provides new insights into the regulation of noncaveolar clathrin-independent endocytosis by specific caveolar proteins, illustrating multiple levels of crosstalk between these pathways. We show for the first time a role for specific cavins in regulating the CLIC/GEEC pathway, provide a new tool to study this pathway, identify caveola-independent functions of the cavins and propose a novel mechanism for inhibition of the CLIC/GEEC pathway by caveolin.
Author Summary
Endocytosis is the process that allows cells to take up molecules from the environment. Several endocytic pathways exist in mammalian cells. While the best understood endocytic pathway uses clathrin, recent years have seen a great increase in our understanding of clathrin-independent endocytic pathways. Here we characterize the crosstalk between caveolae, flask-shaped specialized microdomains present at the plasma membrane, and a second clathrin-independent pathway, the CLIC/GEEC Cdc42-regulated endocytic pathway. These pathways are segregated in migrating cells with caveolae at the rear and CLIC/GEEC endocytosis at the leading edge. Here we find that specific caveolar proteins, caveolins and cavins, can also negatively regulate the CLIC/GEEC pathway. With the help of several techniques, including quantitative electron microscopy analysis and real-time live-cell imaging, we demonstrate that expression of caveolar proteins affects early carrier formation, causes cellular lipid changes, and changes the activity of the key regulator of the CLIC/GEEC pathway, Cdc42. The functional consequences of loss of caveolar proteins on the CLIC/GEEC pathway included inhibition of polarized cell migration and increased endocytosis in tissue explants.
PMCID: PMC3979662  PMID: 24714042
8.  Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens 
BMC Bioinformatics  2008;9:264.
The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens.
Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms.
We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens.
PMCID: PMC2443381  PMID: 18534020
9.  Modularity and hormone sensitivity of the Drosophila melanogaster insulin receptor/target of rapamycin interaction proteome 
First systematic analysis of the evolutionary conserved InR/TOR pathway interaction proteome in Drosophila.Quantitative mass spectrometry revealed that 22% of identified protein interactions are regulated by the growth hormone insulin affecting membrane proximal as well as intracellular signaling complexes.Systematic RNA interference linked a significant fraction of network components to the control of dTOR kinase activity.Combined biochemical and genetic data suggest dTTT, a dTOR-containing complex required for cell growth control by dTORC1 and dTORC2 in vivo.
Cellular growth is a fundamental process that requires constant adaptations to changing environmental conditions, like growth factor and nutrient availability, energy levels and more. Over the years, the insulin receptor/target of rapamycin pathway (InR/TOR) emerged as a key signaling system for the control of metazoan cell growth. Genetic screens carried out in the fruit fly Drosophila melanogaster identified key InR/TOR pathway components and their relationships. Phenotypes such as altered cell growth are likely to emerge from perturbed dynamic networks containing InR/TOR pathway components, which stably or transiently interact with other cellular proteins to form complexes and networks thereof. Systematic studies on the topology and dynamics of protein interaction networks become therefore highly relevant to gain systems level understanding of deregulated cell growth. Despite much progress in genetic analysis only few systematic protein interaction studies have been reported for Drosophila, which in most cases lack quantitative information representing the dynamic nature of such networks. Here, we present the first quantitative affinity purification mass spectrometry (AP–MS/MS) analysis on the evolutionary conserved InR/TOR signaling network in Drosophila. Systematic RNAi-based functional analysis of identified network components revealed key components linked to the regulation of the central effector kinase dTOR. This includes also dTTT, a novel dTOR-containing complex required for the control of dTORC1 and dTORC2 in vivo.
For systematic AP–MS analysis, we generated Drosophila Kc167 cell lines inducibly expressing affinity-tagged bait proteins previously linked to InR/TOR signaling. Bait expressing Kc167 cell lines were harvested before and after insulin stimulation for subsequent affinity purification. Following LC–MS/MS analysis and probabilistic data filtering using SAINT (Choi et al, 2010), we generated a quantitative network model from 97 high confidence protein–protein interactions and 58 network components (Figure 2). The presented network displayed a high degree of orthologous interactions conserved also in human cells and identified a number of novel molecular interactions with InR/TOR signaling components for future hypothesis driven analysis.
To measure insulin-induced changes within the InR/TOR interaction proteome, we applied a recently introduced label-free quantitative MS approach (Rinner et al, 2007). The obtained quantitative data suggest that 22% of all interactions in the network are regulated by insulin. Major changes could be observed within the membrane proximal InR/chico/PI3K signaling complexes, and also in 14-3-3 protein containing signaling complexes and dTORC1, a complex that contains besides dTOR all major orthologous proteins found also in human mTORC1 including the two dTORC1 substrates d4E-BP (Thor) and S6 Kinase (S6K). Insulin triggered both, dissociation and association of dTORC1 proteins. Among the proteins that showed enhanced binding to dTORC1 upon insulin stimulation we found Unkempt, a RING-finger protein with a proposed role in ubiquitin-mediated protein degradation (Lores et al, 2010). Besides dTORC1 our systematic AP–MS analysis also revealed the presence of dTORC2, the second major TOR complex in Drosophila. dTORC2 contains the Drosophila orthologous of human mTORC2 proteins, but in contrast to dTORC1 was not affected upon insulin stimulation. Interestingly, we also found a specific set of proteins that were not linked to the canonical TOR complexes TORC1 and TORC2 in dTOR purifications. These include LqfR (liquid facets related), Pontin, Reptin, Spaghetti and the gene product of CG16908. We found the same set of proteins when we used CG16908 as a bait, suggesting complex formation among the identified proteins. None of the dTORC1/2 components besides dTOR was identified in CG16908 purifications, indicating that these proteins form dTOR complexes distinct from dTORC1 and dTORC2. Based on known interaction information from other species and data obtained from this study we refer to this complex as dTTT (Drosophila TOR, TELO2, TTI1) (Horejsi et al, 2010; [18]Hurov et al, 2010; [20]Kaizuka et al, 2010). A directed quantitative MS analysis of dTOR complex components suggests that dTORC1 is the most abundant dTOR complex we identified in Kc167 cells.
We next studied the potential roles of the identified network components for controlling the activity of the dInR/TOR pathway using systematic RNAi depletion and quantitative western blotting to measure the changes in abundance of phosphorylated substrates of dTORC1 (Thor/d4E-BP, dS6K) and dTORC2 (dPKB) in RNAi-treated cells (Figure 5). Overall, we could identify 16 proteins (out of 58) whose depletion caused an at least 50% increase or decrease in the levels of phosphorylated d4E-BP, S6K and/or PKB compared with control GFP RNAi. Besides established pathway components, we found several novel regulators within the dInR/TOR interaction network. For example, RNAi against the novel insulin-regulated dTORC1 component Unkempt resulted in enhanced phosphorylation of the dTORC1 substrate d4E-BP, which suggests a negative role for Unkempt on dTORC1 activity. In contrast, depletion of CG16908 and LqfR caused hypo-phosphorylation of all dTOR substrates similar to dTOR itself, suggesting a positive role for the dTTT complex on dTOR activity. Subsequently, we tested whether dTTT components also plays a role in dTOR-mediated cell growth in vivo. Depletion of both dTTT components, CG16908 and LqfR, in the Drosophila eye resulted in a substantial decrease in eye size. Likewise, FLP-FRT-mediated mitotic recombination resulted in CG16908 and LqfR mutant clones with a similar reduced growth phenotype as observed in dTOR mutant clones. Hence, the combined biochemical and genetic analysis revealed dTTT as a dTOR-containing complex required for the activity of both dTORC1 and dTORC2 and thus plays a critical role in controlling cell growth.
Taken together, these results illustrate how a systematic quantitative AP–MS approach when combined with systematic functional analysis in Drosophila can reveal novel insights into the dynamic organization of regulatory networks for cell growth control in metazoans.
Using quantitative mass spectrometry, this study reports how insulin affects the modularity of the interaction proteome of the Drosophila InR/TOR pathway, an evolutionary conserved signaling system for the control of metazoan cell growth. Systematic functional analysis linked a significant number of identified network components to the control of dTOR activity and revealed dTTT, a dTOR complex required for in vivo cell growth control by dTORC1 and dTORC2.
Genetic analysis in Drosophila melanogaster has been widely used to identify a system of genes that control cell growth in response to insulin and nutrients. Many of these genes encode components of the insulin receptor/target of rapamycin (InR/TOR) pathway. However, the biochemical context of this regulatory system is still poorly characterized in Drosophila. Here, we present the first quantitative study that systematically characterizes the modularity and hormone sensitivity of the interaction proteome underlying growth control by the dInR/TOR pathway. Applying quantitative affinity purification and mass spectrometry, we identified 97 high confidence protein interactions among 58 network components. In all, 22% of the detected interactions were regulated by insulin affecting membrane proximal as well as intracellular signaling complexes. Systematic functional analysis linked a subset of network components to the control of dTORC1 and dTORC2 activity. Furthermore, our data suggest the presence of three distinct dTOR kinase complexes, including the evolutionary conserved dTTT complex (Drosophila TOR, TELO2, TTI1). Subsequent genetic studies in flies suggest a role for dTTT in controlling cell growth via a dTORC1- and dTORC2-dependent mechanism.
PMCID: PMC3261712  PMID: 22068330
cell growth; InR/TOR pathway; interaction proteome; quantitative mass spectrometry; signaling
10.  High-Content Analysis of Sequential Events during the Early Phase of Influenza A Virus Infection 
PLoS ONE  2013;8(7):e68450.
Influenza A virus (IAV) represents a worldwide threat to public health by causing severe morbidity and mortality every year. Due to high mutation rate, new strains of IAV emerge frequently. These IAVs are often drug-resistant and require vaccine reformulation. A promising approach to circumvent this problem is to target host cell determinants crucial for IAV infection, but dispensable for the cell. Several RNAi-based screens have identified about one thousand cellular factors that promote IAV infection. However, systematic analyses to determine their specific functions are lacking. To address this issue, we developed quantitative, imaging-based assays to dissect seven consecutive steps in the early phases of IAV infection in tissue culture cells. The entry steps for which we developed the assays were: virus binding to the cell membrane, endocytosis, exposure to low pH in endocytic vacuoles, acid-activated fusion of viral envelope with the vacuolar membrane, nucleocapsid uncoating in the cytosol, nuclear import of viral ribonucleoproteins, and expression of the viral nucleoprotein. We adapted the assays to automated microscopy and optimized them for high-content screening. To quantify the image data, we performed both single and multi-parametric analyses, in combination with machine learning. By time-course experiments, we determined the optimal time points for each assay. Our quality control experiments showed that the assays were sufficiently robust for high-content analysis. The methods we describe in this study provide a powerful high-throughput platform to understand the host cell processes, which can eventually lead to the discovery of novel anti-pathogen strategies.
PMCID: PMC3709902  PMID: 23874633
11.  Genome wide screening of RNAi factors of Sf21 cells reveal several novel pathway associated proteins 
BMC Genomics  2014;15(1):775.
RNA interference (RNAi) leads to sequence specific knock-down of gene expression and has emerged as an important tool to analyse gene functions, pathway analysis and gene therapy. Although RNAi is a conserved cellular process involving common elements and factors, species-specific differences have been observed among different eukaryotes. Identification of components for RNAi pathway is pursued intensively and successful genome-wide screens have been performed for components of RNAi pathways in various organisms. Functional comparative genomics analysis offers evolutionary insight that forms basis of discoveries of novel RNAi-factors within related organisms. Keeping in view the academic and commercial utility of insect derived cell-line from Spodoptera frugiperda, we pursued the identification and functional analysis of components of RNAi-machinery of Sf21 cell-line using genome-wide application.
The genome and transcriptome of Sf21 was assembled and annotated. In silico application of comparative genome analysis among insects allowed us to identify several RNAi factors in Sf21 line. The candidate RNAi factors from assembled genome were validated by knockdown analysis of candidate factors using the siRNA screens on the Sf21-gfp reporter cell-line. Forty two (42) potential factors were identified using the cell based assay. These include core RNAi elements including Dicer-2, Argonaute-1, Drosha, Aubergine and auxiliary modules like chromatin factors, RNA helicases, RNA processing module, signalling allied proteins and others. Phylogenetic analyses and domain architecture revealed that Spodoptera frugiperda homologs retained identity with Lepidoptera (Bombyx mori) or Coleoptera (Tribolium castaneum) sustaining an evolutionary conserved scaffold in post-transcriptional gene silencing paradigm within insects.
The database of RNAi-factors generated by whole genome association survey offers comprehensive outlook about conservation as well as specific differences of the proteins of RNAi machinery. Understanding the interior involved in different phases of gene silencing also offers impending tool for RNAi-based applications.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-775) contains supplementary material, which is available to authorized users.
PMCID: PMC4247154  PMID: 25199785
RNA interference; siRNA screening; Sf21 cells; Genome-wide screening; Insect RNAi; Spodoptera frugiperda
12.  A genetic interaction map of cell cycle regulators 
Molecular Biology of the Cell  2016;27(8):1397-1407.
A combination of genome-scale RNA interference screening and genetic interaction analysis using process-directed phenotypes is used to assign components to specific pathways and complexes for modulators of mitosis and cytokinesis in Drosophila S2 cells.
Cell-based RNA interference (RNAi) is a powerful approach to screen for modulators of many cellular processes. However, resulting candidate gene lists from cell-based assays comprise diverse effectors, both direct and indirect, and further dissecting their functions can be challenging. Here we screened a genome-wide RNAi library for modulators of mitosis and cytokinesis in Drosophila S2 cells. The screen identified many previously known genes as well as modulators that have previously not been connected to cell cycle control. We then characterized ∼300 candidate modifiers further by genetic interaction analysis using double RNAi and a multiparametric, imaging-based assay. We found that analyzing cell cycle–relevant phenotypes increased the sensitivity for associating novel gene function. Genetic interaction maps based on mitotic index and nuclear size grouped candidates into known regulatory complexes of mitosis or cytokinesis, respectively, and predicted previously uncharacterized components of known processes. For example, we confirmed a role for the Drosophila CCR4 mRNA processing complex component l(2)NC136 during the mitotic exit. Our results show that the combination of genome-scale RNAi screening and genetic interaction analysis using process-directed phenotypes provides a powerful two-step approach to assigning components to specific pathways and complexes.
PMCID: PMC4831891  PMID: 26912791
13.  Sortin2 enhances endocytic trafficking towards the vacuole in Saccharomyces cerevisiae 
Biological Research  2015;48(1):39.
A highly regulated trafficking of cargo vesicles in eukaryotes performs protein delivery to a variety of cellular compartments of endomembrane system. The two main routes, the secretory and the endocytic pathways have pivotal functions in uni- and multi-cellular organisms. Protein delivery and targeting includes cargo recognition, vesicle formation and fusion. Developing new tools to modulate protein trafficking allows better understanding the endomembrane system mechanisms and their regulation. The compound Sortin2 has been described as a protein trafficking modulator affecting targeting of the vacuolar protein carboxypeptidase Y (CPY), triggering its secretion in Saccharomyces cerevisiae.
A reverse chemical-genetics approach was used to identify key proteins for Sortin2 bioactivity. A genome-wide Sortin2 resistance screen revealed six yeast deletion mutants that do not secrete CPY when grown at Sortin2 condition where the parental strain does: met18, sla1, clc1, dfg10, dpl1 and yjl175w. Integrating mutant phenotype and gene ontology annotation of the corresponding genes and their interactome pointed towards a high representation of genes involved in the endocytic process. In wild type yeast endocytosis towards the vacuole was faster in presence of Sortin2, which further validates the data of the genome-wide screen. This effect of Sortin2 depends on structural features of the molecule, suggesting compound specificity. Sortin2 did not affect endocytic trafficking in Sortin2-resistant mutants, strongly suggesting that the Sortin2 effects on the secretory and endocytic pathways are linked.
Overall, the results reveal that Sortin2 enhances the endocytic transport pathway in Saccharomyces cerevisiae. This cellular effect is most likely at the level where secretory and endocytic pathways are merged. Them Sortin2 specificity over the endomembrane system places it as a powerful biological modulator for cell biology.
Electronic supplementary material
The online version of this article (doi:10.1186/s40659-015-0032-9) contains supplementary material, which is available to authorized users.
PMCID: PMC4515019  PMID: 26209329
Endocytosis; Sortin2; Trafficking modulator; Saccharomyces cerevisiae
14.  Redefining regulation of DNA methylation by RNA interference 
Genomics  2010;96(4):191-198.
Epigenetic changes refer to heritable changes that may modulate gene expression without affecting DNA sequence. DNA methylation is one such heritable epigenetic change, which is causally associated with the transcription regulation of many genes in the mammalian genome. Altered DNA methylation has been implicated in a wide variety of human diseases including cancer. Understanding the regulation of DNA methylation is likely to improve the ability to diagnose and treat these diseases. With the advent of high-throughput RNA interference (RNAi) screens, answering epigenetic questions on a genomic scale is now possible. Two recent genome-wide RNAi screens have addressed the regulation of DNA methylation in cancer, leading to the identification of the regulators of epigenetic silencing by oncogenic RAS and how epigenetic silencing of the tumor suppressor RASSF1A is maintained. These RNAi screens have much wider applications, since similar screens can now be adapted to identify the mechanism of silencing of any human disease-associated gene that is epigenetically regulated. In this review, we discuss two recent genome-wide RNAi screens for epigenetic regulators and explore potential applications in understanding DNA methylation and gene expression regulation in mammalian cells. We also discuss some of the key unanswered questions in the field of DNA methylation and suggest genome-wide RNAi screens designed to answer them.
PMCID: PMC3726036  PMID: 20620207
DNA methylation; Epigenetics; Transcription; RNA interference; Imprinting
15.  Revealing Molecular Mechanisms by Integrating High-Dimensional Functional Screens with Protein Interaction Data 
PLoS Computational Biology  2014;10(9):e1003801.
Functional genomics screens using multi-parametric assays are powerful approaches for identifying genes involved in particular cellular processes. However, they suffer from problems like noise, and often provide little insight into molecular mechanisms. A bottleneck for addressing these issues is the lack of computational methods for the systematic integration of multi-parametric phenotypic datasets with molecular interactions. Here, we present Integrative Multi Profile Analysis of Cellular Traits (IMPACT). The main goal of IMPACT is to identify the most consistent phenotypic profile among interacting genes. This approach utilizes two types of external information: sets of related genes (IMPACT-sets) and network information (IMPACT-modules). Based on the notion that interacting genes are more likely to be involved in similar functions than non-interacting genes, this data is used as a prior to inform the filtering of phenotypic profiles that are similar among interacting genes. IMPACT-sets selects the most frequent profile among a set of related genes. IMPACT-modules identifies sub-networks containing genes with similar phenotype profiles. The statistical significance of these selections is subsequently quantified via permutations of the data. IMPACT (1) handles multiple profiles per gene, (2) rescues genes with weak phenotypes and (3) accounts for multiple biases e.g. caused by the network topology. Application to a genome-wide RNAi screen on endocytosis showed that IMPACT improved the recovery of known endocytosis-related genes, decreased off-target effects, and detected consistent phenotypes. Those findings were confirmed by rescreening 468 genes. Additionally we validated an unexpected influence of the IGF-receptor on EGF-endocytosis. IMPACT facilitates the selection of high-quality phenotypic profiles using different types of independent information, thereby supporting the molecular interpretation of functional screens.
Author Summary
Genome-scale functional genomics screens are important tools for investigating the function of genes. Technological progress allows for the simultaneous measurement of multiple parameters quantifying the response of cells to gene perturbations such as RNA interference. Such multi-dimensional screens provide rich data, but there is a lack of computational methods for interpreting these complex measurements. We have developed two computational methods that combine the data from multi-dimensional functional genomics screens with protein interaction information. These methods search for phenotype patterns that are consistent among interacting genes. Thereby, we could reduce the noise in the data and facilitate the mechanistic interpretation of the findings. The performance of the methods was demonstrated through application to a genome-wide screen studying endocytosis. Subsequent experimental validation demonstrated the improved detection of phenotypic profiles through the use of protein interaction data. Our analysis revealed unexpected roles of specific network modules and protein complexes with respect to endocytosis. Detailed follow-up experiments investigating the dynamics of endocytosis uncovered crosstalk between the cancer-related EGF and IGF pathways with so far unknown effects on endocytosis and cargo trafficking.
PMCID: PMC4154648  PMID: 25188415
16.  Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) 
Shay, Jerry W. | Homma, Noriko | Zhou, Ruyun | Naseer, Muhammad Imran | Chaudhary, Adeel G. | Al-Qahtani, Mohammed | Hirokawa, Nobutaka | Goudarzi, Maryam | Fornace, Albert J. | Baeesa, Saleh | Hussain, Deema | Bangash, Mohammed | Alghamdi, Fahad | Schulten, Hans-Juergen | Carracedo, Angel | Khan, Ishaq | Qashqari, Hanadi | Madkhali, Nawal | Saka, Mohamad | Saini, Kulvinder S. | Jamal, Awatif | Al-Maghrabi, Jaudah | Abuzenadah, Adel | Chaudhary, Adeel | Al Qahtani, Mohammed | Damanhouri, Ghazi | Alkhatabi, Heba | Goodeve, Anne | Crookes, Laura | Niksic, Nikolas | Beauchamp, Nicholas | Abuzenadah, Adel M. | Vaught, Jim | Budowle, Bruce | Assidi, Mourad | Buhmeida, Abdelbaset | Al-Maghrabi, Jaudah | Buhmeida, Abdelbaset | Assidi, Mourad | Merdad, Leena | Kumar, Sudhir | Miura, Sayaka | Gomez, Karen | Carracedo, Angel | Rasool, Mahmood | Rebai, Ahmed | Karim, Sajjad | Eldin, Hend F. Nour | Abusamra, Heba | Alhathli, Elham M. | Salem, Nada | Al-Qahtani, Mohammed H. | Kumar, Sudhir | Faheem, Hossam | Agarwa, Ashok | Nieschlag, Eberhard | Wistuba, Joachim | Damm, Oliver S. | Beg, Mohd A. | Abdel-Meguid, Taha A. | Mosli, Hisham A. | Bajouh, Osama S. | Abuzenadah, Adel M. | Al-Qahtani, Mohammed H. | Coskun, Serdar | Abu-Elmagd, Muhammad | Buhmeida, Abdelbaset | Dallol, Ashraf | Al-Maghrabi, Jaudah | Hakamy, Sahar | Al-Qahtani, Wejdan | Al-Harbi, Asia | Hussain, Shireen | Assidi, Mourad | Al-Qahtani, Mohammed | Abuzenadah, Adel | Ozkosem, Burak | DuBois, Rick | Messaoudi, Safia S. | Dandana, Maryam T. | Mahjoub, Touhami | Almawi, Wassim Y. | Abdalla, S. | Al-Aama, M. Nabil | Elzawahry, Asmaa | Takahashi, Tsuyoshi | Mimaki, Sachiyo | Furukawa, Eisaku | Nakatsuka, Rie | Kurosaka, Isao | Nishigaki, Takahiko | Nakamura, Hiromi | Serada, Satoshi | Naka, Tetsuji | Hirota, Seiichi | Shibata, Tatsuhiro | Tsuchihara, Katsuya | Nishida, Toshirou | Kato, Mamoru | Mehmood, Sajid | Ashraf, Naeem Mahmood | Asif, Awais | Bilal, Muhammad | Mehmood, Malik Siddique | Hussain, Aadil | Jamal, Qazi Mohammad Sajid | Siddiqui, Mughees Uddin | Alzohairy, Mohammad A. | Al Karaawi, Mohammad A. | Nedjadi, Taoufik | Al-Maghrabi, Jaudah | Assidi, Mourad | Al-Khattabi, Heba | Al-Ammari, Adel | Al-Sayyad, Ahmed | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Zitouni, Hédia | Raguema, Nozha | Ali, Marwa Ben | Malah, Wided | Lfalah, Raja | Almawi, Wassim | Mahjoub, Touhami | Elanbari, Mohammed | Ptitsyn, Andrey | Mahjoub, Sana | El Ghali, Rabeb | Achour, Bechir | Amor, Nidhal Ben | Assidi, Mourad | N’siri, Brahim | Morjani, Hamid | Nedjadi, Taoufik | Al-Ammari, Adel | Al-Sayyad, Ahmed | Salem, Nada | Azhar, Esam | Al-Maghrabi, Jaudah | Chayeb, Vera | Dendena, Maryam | Zitouni, Hedia | Zouari-Limayem, Khedija | Mahjoub, Touhami | Refaat, Bassem | Ashshi, Ahmed M. | Batwa, Sarah A. | Ramadan, Hazem | Awad, Amal | Ateya, Ahmed | El-Shemi, Adel Galal Ahmed | Ashshi, Ahmad | Basalamah, Mohammed | Na, Youjin | Yun, Chae-Ok | El-Shemi, Adel Galal Ahmed | Ashshi, Ahmad | Basalamah, Mohammed | Na, Youjin | Yun, Chae-Ok | El-Shemi, Adel Galal | Refaat, Bassem | Kensara, Osama | Abdelfattah, Amr | Dheeb, Batol Imran | Al-Halbosiy, Mohammed M. F. | Al lihabi, Rghad Kadhim | Khashman, Basim Mohammed | Laiche, Djouhri | Adeel, Chaudhary | Taoufik, Nedjadi | Al-Afghani, Hani | Łastowska, Maria | Al-Balool, Haya H. | Sheth, Harsh | Mercer, Emma | Coxhead, Jonathan M. | Redfern, Chris P. F. | Peters, Heiko | Burt, Alastair D. | Santibanez-Koref, Mauro | Bacon, Chris M. | Chesler, Louis | Rust, Alistair G. | Adams, David J. | Williamson, Daniel | Clifford, Steven C. | Jackson, Michael S. | Singh, Mala | Mansuri, Mohmmad Shoab | Jadeja, Shahnawaz D. | Patel, Hima | Marfatia, Yogesh S. | Begum, Rasheedunnisa | Mohamed, Amal M. | Kamel, Alaa K. | Helmy, Nivin A. | Hammad, Sayda A. | Kayed, Hesham F. | Shehab, Marwa I. | El Gerzawy, Assad | Ead, Maha M. | Ead, Ola M. | Mekkawy, Mona | Mazen, Innas | El-Ruby, Mona | Shahid, S. M. A. | Jamal, Qazi Mohammad Sajid | Arif, J. M. | Lohani, Mohtashim | Imen, Moumni | Leila, Chaouch | Houyem, Ouragini | Kais, Douzi | Fethi, Chaouachi Dorra Mellouli | Mohamed, Bejaoui | Salem, Abbes | Faggad, Areeg | Gebreslasie, Amanuel T. | Zaki, Hani Y. | Abdalla, Badreldin E. | AlShammari, Maha S. | Al-Ali, Rhaya | Al-Balawi, Nader | Al-Enazi, Mansour | Al-Muraikhi, Ali | Busaleh, Fadi | Al-Sahwan, Ali | Borgio, Francis | Sayyed, Abdulazeez | Al-Ali, Amein | Acharya, Sadananda | Zaki, Maha S. | El-Bassyouni, Hala T. | Shehab, Marwa I. | Elshal, Mohammed F. | M., Kaleemuddin | Aldahlawi, Alia M. | Saadah, Omar | McCoy, J. Philip | El-Tarras, Adel E. | Awad, Nabil S. | Alharthi, Abdulla A. | Ibrahim, Mohamed M. M. | Alsehli, Haneen S. | Dallol, Ashraf | Gari, Abdullah M. | Abbas, Mohammed M. | Kadam, Roaa A. | Gari, Mazen M. | Alkaff, Mohmmed H. | Abuzenadah, Adel M. | Gari, Mamdooh A. | Abusamra, Heba | Karim, Sajjad | eldin, Hend F. Nour | Alhathli, Elham M. | Salem, Nada | Kumar, Sudhir | Al-Qahtani, Mohammed H. | Moradi, Fatima A. | Rashidi, Omran M. | Awan, Zuhier A. | Kaya, Ibrahim Hamza | Al-Harazi, Olfat | Colak, Dilek | Alkousi, Nabila A. | Athanasopoulos, Takis | Bahmaid, Afnan O. | Alhwait, Etimad A. | Gari, Mamdooh A. | Alsehli, Haneen S. | Abbas, Mohammed M. | Alkaf, Mohammed H. | Kadam, Roaa | Dallol, Ashraf | Kalamegam, Gauthaman | Eldin, Hend F. Nour | Karim, Sajjad | Abusamra, Heba | Alhathli, Elham | Salem, Nada | Al-Qahtani, Mohammed H. | Kumar, Sudhir | Alsayed, Salma N. | Aljohani, Fawziah H. | Habeeb, Samaher M. | Almashali, Rawan A. | Basit, Sulman | Ahmed, Samia M. | Sharma, Rakesh | Agarwal, Ashok | Durairajanayagam, Damayanthi | Samanta, Luna | Abu-Elmagd, Muhammad | Abuzenadah, Adel M. | Sabanegh, Edmund S. | Assidi, Mourad | Al-Qahtani, Mohammed | Agarwal, Ashok | Sharma, Rakesh | Samanta, Luna | Durairajanayagam, Damayanthi | Assidi, Mourad | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Abuzenadah, Adel M. | Sabanegh, Edmund S. | Samanta, Luna | Agarwal, Ashok | Sharma, Rakesh | Cui, Zhihong | Assidi, Mourad | Abuzenadah, Adel M. | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Alboogmi, Alaa A. | Alansari, Nuha A. | Al-Quaiti, Maha M. | Ashgan, Fai T. | Bandah, Afnan | Jamal, Hasan S. | Rozi, Abdullraheem | Mirza, Zeenat | Abuzenadah, Adel M. | Karim, Sajjad | Al-Qahtani, Mohammed H. | Karim, Sajjad | Schulten, Hans-Juergen | Al Sayyad, Ahmad J. | Farsi, Hasan M. A. | Al-Maghrabi, Jaudah A. | Mirza, Zeenat | Alotibi, Reem | Al-Ahmadi, Alaa | Alansari, Nuha A. | Albogmi, Alaa A. | Al-Quaiti, Maha M. | Ashgan, Fai T. | Bandah, Afnan | Al-Qahtani, Mohammed H. | Ebiya, Rasha A. | Darwish, Samia M. | Montaser, Metwally M. | Abusamra, Heba | Bajic, Vladimir B. | Al-Maghrabi, Jaudah | Gomaa, Wafaey | Hanbazazh, Mehenaz | Al-Ahwal, Mahmoud | Al-Harbi, Asia | Al-Qahtani, Wejdan | Hakamy, Saher | Baba, Ghali | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Al-Maghrabi, Jaudah | Al-Harbi, Abdullah | Al-Ahwal, Mahmoud | Al-Harbi, Asia | Al-Qahtani, Wejdan | Hakamy, Sahar | Baba, Ghalia | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Alhathli, Elham M. | Karim, Sajjad | Salem, Nada | Eldin, Hend Nour | Abusamra, Heba | Kumar, Sudhir | Al-Qahtani, Mohammed H. | Alyamani, Aisha A. | Kalamegam, Gauthaman | Alhwait, Etimad A. | Gari, Mamdooh A. | Abbas, Mohammed M. | Alkaf, Mohammed H. | Alsehli, Haneen S. | Kadam, Roaa A. | Al-Qahtani, Mohammed | Gadi, Rawan | Buhmeida, Abdelbaset | Assidi, Mourad | Chaudhary, Adeel | Merdad, Leena | Alfakeeh, Saadiah M. | Alhwait, Etimad A. | Gari, Mamdooh A. | Abbas, Mohammed M. | Alkaf, Mohammed H. | Alsehli, Haneen S. | Kadam, Roaa | Kalamegam, Gauthaman | Ghazala, Rubi | Mathew, Shilu | Hamed, M. Haroon | Assidi, Mourad | Al-Qahtani, Mohammed | Qadri, Ishtiaq | Mathew, Shilu | Mira, Lobna | Shaabad, Manal | Hussain, Shireen | Assidi, Mourad | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Mathew, Shilu | Shaabad, Manal | Mira, Lobna | Hussain, Shireen | Assidi, Mourad | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Rebai, Ahmed | Assidi, Mourad | Buhmeida, Abdelbaset | Abu-Elmagd, Muhammad | Dallol, Ashraf | Shay, Jerry W. | Almutairi, Mikhlid H. | Ambers, Angie | Churchill, Jennifer | King, Jonathan | Stoljarova, Monika | Gill-King, Harrell | Assidi, Mourad | Abu-Elmagd, Muhammad | Buhmeida, Abdelbaset | Al-Qatani, Muhammad | Budowle, Bruce | Abu-Elmagd, Muhammad | Ahmed, Farid | Dallol, Ashraf | Assidi, Mourad | Almagd, Taha Abo | Hakamy, Sahar | Agarwal, Ashok | Al-Qahtani, Muhammad | Abuzenadah, Adel | Karim, Sajjad | Schulten, Hans-Juergen | Al Sayyad, Ahmad J. | Farsi, Hasan M. A. | Al-Maghrabi, Jaudah A. | Buhmaida, Abdelbaset | Mirza, Zeenat | Alotibi, Reem | Al-Ahmadi, Alaa | Alansari, Nuha A. | Albogmi, Alaa A. | Al-Quaiti, Maha M. | Ashgan, Fai T. | Bandah, Afnan | Al-Qahtani, Mohammed H. | Satar, Rukhsana | Rasool, Mahmood | Ahmad, Waseem | Nazam, Nazia | Lone, Mohamad I. | Naseer, Muhammad I. | Jamal, Mohammad S. | Zaidi, Syed K. | Pushparaj, Peter N. | Jafri, Mohammad A. | Ansari, Shakeel A. | Alqahtani, Mohammed H. | Bashier, Hanan | Al Qahtani, Abrar | Mathew, Shilu | Nour, Amal M. | Alkhatabi, Heba | Zenadah, Adel M. Abu | Buhmeida, Abdelbaset | Assidi, Mourad | Al Qahtani, Muhammed | Faheem, Muhammad | Mathew, Shilu | Mathew, Shiny | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad H. | Alhadrami, Hani A. | Dallol, Ashraf | Abuzenadah, Adel | Hussein, Ibtessam R. | Chaudhary, Adeel G. | Bader, Rima S. | Bassiouni, Randa | Alquaiti, Maha | Ashgan, Fai | Schulten, Hans | Alama, Mohamed Nabil | Al Qahtani, Mohammad H. | Lone, Mohammad I. | Nizam, Nazia | Ahmad, Waseem | Jafri, Mohammad A. | Rasool, Mahmood | Ansari, Shakeel A. | Al-Qahtani, Muhammed H. | Alshihri, Eradah | Abu-Elmagd, Muhammad | Alharbi, Lina | Assidi, Mourad | Al-Qahtani, Mohammed | Mathew, Shilu | Natesan, Peter Pushparaj | Al Qahtani, Muhammed | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Khan, Fazal | Kadam, Roaa | Ahmed, Farid | Assidi, Mourad | Sait, Khalid Hussain Wali | Anfinan, Nisreen | Al Qahtani, Mohammed | Naseer, Muhammad I. | Chaudhary, Adeel G. | Jamal, Mohammad S. | Mathew, Shilu | Mira, Lobna S. | Pushparaj, Peter N. | Ansari, Shakeel A. | Rasool, Mahmood | AlQahtani, Mohammed H. | Naseer, Muhammad I. | Chaudhary, Adeel G. | Mathew, Shilu | Mira, Lobna S. | Jamal, Mohammad S. | Sogaty, Sameera | Bassiouni, Randa I. | Rasool, Mahmood | AlQahtani, Mohammed H. | Rasool, Mahmood | Ansari, Shakeel A. | Jamal, Mohammad S. | Pushparaj, Peter N. | Sibiani, Abdulrahman M. S. | Ahmad, Waseem | Buhmeida, Abdelbaset | Jafri, Mohammad A. | Warsi, Mohiuddin K. | Naseer, Muhammad I. | Al-Qahtani, Mohammed H. | Rubi | Kumar, Kundan | Naqvi, Ahmad A. T. | Ahmad, Faizan | Hassan, Md I. | Jamal, Mohammad S. | Rasool, Mahmood | AlQahtani, Mohammed H. | Ali, Ashraf | Jarullah, Jummanah | Rasool, Mahmood | Buhmeida, Abdelbasit | Khan, Shahida | Abdussami, Ghufrana | Mahfooz, Maryam | Kamal, Mohammad A. | Damanhouri, Ghazi A. | Jamal, Mohammad S. | Jarullah, Bushra | Jarullah, Jummanah | Jarullah, Mohammad S. S. | Ali, Ashraf | Rasool, Mahmood | Jamal, Mohammad S. | Assidi, Mourad | Abu-Elmagd, Muhammad | Bajouh, Osama | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Abuzenadah, Adel | Jamal, Mohammad S. | Jarullah, Jummanah | Mathkoor, Abdulah E. A. | Alsalmi, Hashim M. A. | Oun, Anas M. M. | Damanhauri, Ghazi A. | Rasool, Mahmood | AlQahtani, Mohammed H. | Naseer, Muhammad I. | Rasool, Mahmood | Sogaty, Sameera | Chudhary, Adeel G. | Abutalib, Yousif A. | Merico, Daniele | Walker, Susan | Marshall, Christian R. | Zarrei, Mehdi | Scherer, Stephen W. | Al-Qahtani, Mohammad H. | Naseer, Muhammad I. | Faheem, Muhammad | Chaudhary, Adeel G. | Rasool, Mahmood | Kalamegam, Gauthaman | Ashgan, Fai Talal | Assidi, Mourad | Ahmed, Farid | Zaidi, Syed Kashif | Jan, Mohammed M. | Al-Qahtani, Mohammad H. | Al-Zahrani, Maryam | Lary, Sahira | Hakamy, Sahar | Dallol, Ashraf | Al-Ahwal, Mahmoud | Al-Maghrabi, Jaudah | Dermitzakis, Emmanuel | Abuzenadah, Adel | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Al-refai, Abeer A. | Saleh, Mona | Yassien, Rehab I. | Kamel, Mahmmoud | Habeb, Rabab M. | Filimban, Najlaa | Dallol, Ashraf | Ghannam, Nadia | Al-Qahtani, Mohammed | Abuzenadah, Adel Mohammed | Bibi, Fehmida | Akhtar, Sana | Azhar, Esam I. | Yasir, Muhammad | Nasser, Muhammad I. | Jiman-Fatani, Asif A. | Sawan, Ali | Lahzah, Ruaa A. | Ali, Asho | Hassan, Syed A. | Hasnain, Seyed E. | Tayubi, Iftikhar A. | Abujabal, Hamza A. | Magrabi, Alaa O. | Khan, Fazal | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Abuzenada, Adel | Kumosani, Taha Abduallah | Barbour, Elie | Al-Qahtani, Mohammed | Shabaad, Manal | Mathew, Shilu | Dallol, Ashraf | Merdad, Adnan | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Assidi, Mourad | Abu-Elmagd, Muhammad | Gauthaman, Kalamegam | Gari, Mamdooh | Chaudhary, Adeel | Abuzenadah, Adel | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Hassan, Syed A. | Tayubi, Iftikhar A. | Aljahdali, Hani M. A. | Al Nono, Reham | Gari, Mamdooh | Alsehli, Haneen | Ahmed, Farid | Abbas, Mohammed | Kalamegam, Gauthaman | Al-Qahtani, Mohammed | Mathew, Shilu | Khan, Fazal | Rasool, Mahmood | Jamal, Mohammed Sarwar | Naseer, Muhammad Imran | Mirza, Zeenat | Karim, Sajjad | Ansari, Shakeel | Assidi, Mourad | Kalamegam, Gauthaman | Gari, Mamdooh | Chaudhary, Adeel | Abuzenadah, Adel | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Abu-Elmagd, Muhammad | Kalamegam, Gauthaman | Kadam, Roaa | Alghamdi, Mansour A. | Shamy, Magdy | Costa, Max | Khoder, Mamdouh I. | Assidi, Mourad | Pushparaj, Peter Natesan | Gari, Mamdooh | Al-Qahtani, Mohammed | Kharrat, Najla | Belmabrouk, Sabrine | Abdelhedi, Rania | Benmarzoug, Riadh | Assidi, Mourad | Al Qahtani, Mohammed H. | Rebai, Ahmed | Dhamanhouri, Ghazi | Pushparaj, Peter Natesan | Noorwali, Abdelwahab | Alwasiyah, Mohammad Khalid | Bahamaid, Afnan | Alfakeeh, Saadiah | Alyamani, Aisha | Alsehli, Haneen | Abbas, Mohammed | Gari, Mamdooh | Mobasheri, Ali | Kalamegam, Gauthaman | Al-Qahtani, Mohammed | Faheem, Muhammad | Mathew, Shilu | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad H. | Mathew, Shilu | Faheem, Muhammad | Mathew, Shiny | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad H. | Jamal, Mohammad Sarwar | Zaidi, Syed Kashif | Khan, Raziuddin | Bhatia, Kanchan | Al-Qahtani, Mohammed H. | Ahmad, Saif | AslamTayubi, Iftikhar | Tripathi, Manish | Hassan, Syed Asif | Shrivastava, Rahul | Tayubi, Iftikhar A. | Hassan, Syed | Abujabal, Hamza A. S. | Shah, Ishani | Jarullah, Bushra | Jamal, Mohammad S. | Jarullah, Jummanah | Sheikh, Ishfaq A. | Ahmad, Ejaz | Jamal, Mohammad S. | Rehan, Mohd | Abu-Elmagd, Muhammad | Tayubi, Iftikhar A. | AlBasri, Samera F. | Bajouh, Osama S. | Turki, Rola F. | Abuzenadah, Adel M. | Damanhouri, Ghazi A. | Beg, Mohd A. | Al-Qahtani, Mohammed | Hammoudah, Sahar A. F. | AlHarbi, Khalid M. | El-Attar, Lama M. | Darwish, Ahmed M. Z. | Ibrahim, Sara M. | Dallol, Ashraf | Choudhry, Hani | Abuzenadah, Adel | Awlia, Jalaludden | Chaudhary, Adeel | Ahmed, Farid | Al-Qahtani, Mohammed | Jafri, Mohammad A. | Abu-Elmagd, Muhammad | Assidi, Mourad | Al-Qahtani, Mohammed | khan, Imran | Yasir, Muhammad | Azhar, Esam I. | Al-basri, Sameera | Barbour, Elie | Kumosani, Taha | Khan, Fazal | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Abuzenada, Adel | Kumosani, Taha Abduallah | Barbour, Elie | EL Sayed, Heba M. | Hafez, Eman A. | Schulten, Hans-Juergen | Elaimi, Aisha Hassan | Hussein, Ibtessam R. | Bassiouni, Randa Ibrahim | Alwasiyah, Mohammad Khalid | Wintle, Richard F. | Chaudhary, Adeel | Scherer, Stephen W. | Al-Qahtani, Mohammed | Mirza, Zeenat | Pillai, Vikram Gopalakrishna | Karim, Sajjad | Sharma, Sujata | Kaur, Punit | Srinivasan, Alagiri | Singh, Tej P. | Al-Qahtani, Mohammed | Alotibi, Reem | Al-Ahmadi, Alaa | Al-Adwani, Fatima | Hussein, Deema | Karim, Sajjad | Al-Sharif, Mona | Jamal, Awatif | Al-Ghamdi, Fahad | Al-Maghrabi, Jaudah | Baeesa, Saleh S. | Bangash, Mohammed | Chaudhary, Adeel | Schulten, Hans-Juergen | Al-Qahtani, Mohammed | Faheem, Muhammad | Pushparaj, Peter Natesan | Mathew, Shilu | Kumosani, Taha Abdullah | Kalamegam, Gauthaman | Al-Qahtani, Mohammed | Al-Allaf, Faisal A. | Abduljaleel, Zainularifeen | Alashwal, Abdullah | Taher, Mohiuddin M. | Bouazzaoui, Abdellatif | Abalkhail, Halah | Ba-Hammam, Faisal A. | Athar, Mohammad | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Abu-Elmagd, Muhammad | Ahmed, Farid | Sait, Khalid HussainWali | Anfinan, Nisreen | Gari, Mamdooh | Chaudhary, Adeel | Abuzenadah, Adel | Assidi, Mourad | Al-Qahtani, Mohammed | Mami, Naira Ben | Haffani, Yosr Z. | Medhioub, Mouna | Hamzaoui, Lamine | Cherif, Ameur | Azouz, Msadok | Kalamegam, Gauthaman | Khan, Fazal | Mathew, Shilu | Nasser, Mohammed Imran | Rasool, Mahmood | Ahmed, Farid | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Turkistany, Shereen A. | Al-harbi, Lina M. | Dallol, Ashraf | Sabir, Jamal | Chaudhary, Adeel | Abuzenadah, Adel | Al-Madoudi, Basmah | Al-Aslani, Bayan | Al-Harbi, Khulud | Al-Jahdali, Rwan | Qudaih, Hanadi | Al Hamzy, Emad | Assidi, Mourad | Al Qahtani, Mohammed | Ilyas, Asad M. | Ahmed, Youssri | Gari, Mamdooh | Ahmed, Farid | Alqahtani, Mohammed | Salem, Nada | Karim, Sajjad | Alhathli, Elham M. | Abusamra, Heba | Eldin, Hend F. Nour | Al-Qahtani, Mohammed H. | Kumar, Sudhir | Al-Adwani, Fatima | Hussein, Deema | Al-Sharif, Mona | Jamal, Awatif | Al-Ghamdi, Fahad | Al-Maghrabi, Jaudah | Baeesa, Saleh S. | Bangash, Mohammed | Chaudhary, Adeel | Al-Qahtani, Mohammed | Schulten, Hans-Juergen | Alamandi, Alaa | Alotibi, Reem | Hussein, Deema | Karim, Sajjad | Al-Maghrabi, Jaudah | Al-Ghamdi, Fahad | Jamal, Awatif | Baeesa, Saleh S. | Bangash, Mohammed | Chaudhary, Adeel | Schulten, Hans-Juergen | Al-Qahtani, Mohammed | Subhi, Ohoud | Bagatian, Nadia | Karim, Sajjad | Al-Johari, Adel | Al-Hamour, Osman Abdel | Al-Aradati, Hosam | Al-Mutawa, Abdulmonem | Al-Mashat, Faisal | Al-Maghrabi, Jaudah | Schulten, Hans-Juergen | Al-Qahtani, Mohammad | Bagatian, Nadia | Subhi, Ohoud | Karim, Sajjad | Al-Johari, Adel | Al-Hamour, Osman Abdel | Al-Mutawa, Abdulmonem | Al-Aradati, Hosam | Al-Mashat, Faisal | Al-Qahtani, Mohammad | Schulten, Hans-Juergen | Al-Maghrabi, Jaudah | shah, Muhammad W. | Yasir, Muhammad | Azhar, Esam I | Al-Masoodi, Saad | Haffani, Yosr Z. | Azouz, Msadok | Khamla, Emna | Jlassi, Chaima | Masmoudi, Ahmed S. | Cherif, Ameur | Belbahri, Lassaad | Al-Khayyat, Shadi | Attas, Roba | Abu-Sanad, Atlal | Abuzinadah, Mohammed | Merdad, Adnan | Dallol, Ashraf | Chaudhary, Adeel | Al-Qahtani, Mohammed | Abuzenadah, Adel | Bouazzi, Habib | Trujillo, Carlos | Alwasiyah, Mohammad Khalid | Al-Qahtani, Mohammed | Alotaibi, Maha | Nassir, Rami | Sheikh, Ishfaq A. | Kamal, Mohammad A. | Jiffri, Essam H. | Ashraf, Ghulam M. | Beg, Mohd A. | Aziz, Mohammad A. | Ali, Rizwan | Rasool, Mahmood | Jamal, Mohammad S. | Samman, Nusaibah | Abdussami, Ghufrana | Periyasamy, Sathish | Warsi, Mohiuddin K. | Aldress, Mohammed | Al Otaibi, Majed | Al Yousef, Zeyad | Boudjelal, Mohamed | Buhmeida, Abdelbasit | Al-Qahtani, Mohammed H. | AlAbdulkarim, Ibrahim | Ghazala, Rubi | Mathew, Shilu | Hamed, M. Haroon | Assidi, Mourad | Al-Qahtani, Mohammed | Qadri, Ishtiaq | Sheikh, Ishfaq A. | Abu-Elmagd, Muhammad | Turki, Rola F. | Damanhouri, Ghazi A. | Beg, Mohd A. | Suhail, Mohd | Qureshi, Abid | Jamal, Adil | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad | Qadri, Ishtiaq | El-Readi, Mahmoud Z. | Eid, Safaa Y. | Wink, Michael | Isa, Ahmed M. | Alnuaim, Lulu | Almutawa, Johara | Abu-Rafae, Basim | Alasiri, Saleh | Binsaleh, Saleh | Nazam, Nazia | Lone, Mohamad I. | Ahmad, Waseem | Ansari, Shakeel A. | Alqahtani, Mohamed H.
BMC Genomics  2016;17(Suppl 6):487.
Table of contents
O1 Regulation of genes by telomere length over long distances
Jerry W. Shay
O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy
Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa
O3 Integration of metagenomics and metabolomics in gut microbiome research
Maryam Goudarzi, Albert J. Fornace Jr.
O4 A unique integrated system to discern pathogenesis of central nervous system tumors
Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri
O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis
Heba Alkhatabi
O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service
Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp
O7 Targeted sequencing panels and their utilization in personalized medicine
Adel M. Abuzenadah
O8 International biobanking in the era of precision medicine
Jim Vaught
O9 Biobank and biodata for clinical and forensic applications
Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida
O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors
Jaudah Al-Maghrabi
O11 The CEGMR biobanking unit: achievements, challenges and future plans
Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad
O12 Phylomedicine of tumors
Sudhir Kumar, Sayaka Miura, Karen Gomez
O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment
Angel Carracedo, Mahmood Rasool
O14 From association to causality: translation of GWAS findings for genomic medicine
Ahmed Rebai
O15 E-GRASP: an interactive database and web application for efficient analysis of disease-associated genetic information
Sajjad Karim, Hend F Nour Eldin, Heba Abusamra, Elham M Alhathli, Nada Salem, Mohammed H Al-Qahtani, Sudhir Kumar
O16 The supercomputer facility “AZIZ” at KAU: utility and future prospects
Hossam Faheem
O17 New research into the causes of male infertility
Ashok Agarwa
O18 The Klinefelter syndrome: recent progress in pathophysiology and management
Eberhard Nieschlag, Joachim Wistuba, Oliver S. Damm, Mohd A. Beg, Taha A. Abdel-Meguid, Hisham A. Mosli, Osama S. Bajouh, Adel M. Abuzenadah, Mohammed H. Al-Qahtani
O19 A new look to reproductive medicine in the era of genomics
Serdar Coskun
P1 Wnt signalling receptors expression in Saudi breast cancer patients
Muhammad Abu-Elmagd, Abdelbaset Buhmeida, Ashraf Dallol, Jaudah Al-Maghrabi, Sahar Hakamy, Wejdan Al-Qahtani, Asia Al-Harbi, Shireen Hussain, Mourad Assidi, Mohammed Al-Qahtani, Adel Abuzenadah
P2 Analysis of oxidative stress interactome during spermatogenesis: a systems biology approach to reproduction
Burak Ozkosem, Rick DuBois
P3 Interleukin-18 gene variants are strongly associated with idiopathic recurrent pregnancy loss.
Safia S Messaoudi, Maryam T Dandana, Touhami Mahjoub, Wassim Y Almawi
P4 Effect of environmental factors on gene-gene and gene-environment reactions: model and theoretical study applied to environmental interventions using genotype
S. Abdalla, M. Nabil Al-Aama
P5 Genomics and transcriptomic analysis of imatinib resistance in gastrointestinal stromal tumor
Asmaa Elzawahry, Tsuyoshi Takahashi, Sachiyo Mimaki, Eisaku Furukawa, Rie Nakatsuka, Isao Kurosaka, Takahiko Nishigaki, Hiromi Nakamura, Satoshi Serada, Tetsuji Naka, Seiichi Hirota, Tatsuhiro Shibata, Katsuya Tsuchihara, Toshirou Nishida, Mamoru Kato
P6 In-Silico analysis of putative HCV epitopes against Pakistani human leukocyte antigen background: an approach towards development of future vaccines for Pakistani population
Sajid Mehmood, Naeem Mahmood Ashraf, Awais Asif, Muhammad Bilal, Malik Siddique Mehmood, Aadil Hussain
P7 Inhibition of AChE and BuChE with the natural compounds of Bacopa monerri for the treatment of Alzheimer’s disease: a bioinformatics approach
Qazi Mohammad Sajid Jamal, Mughees Uddin Siddiqui, Mohammad A. Alzohairy, Mohammad A. Al Karaawi
P8 Her2 expression in urothelial cell carcinoma of the bladder in Saudi Arabia
Taoufik Nedjadi, Jaudah Al-Maghrabi, Mourad Assidi, Heba Al-Khattabi, Adel Al-Ammari, Ahmed Al-Sayyad, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P9 Association of angiotensinogen single nucleotide polymorphisms with Preeclampsia in patients from North Africa
Hédia Zitouni, Nozha Raguema, Marwa Ben Ali, Wided Malah, Raja Lfalah, Wassim Almawi, Touhami Mahjoub
P10 Systems biology analysis reveals relations between normal skin, benign nevi and malignant melanoma
Mohammed Elanbari, Andrey Ptitsyn
P11 The apoptotic effect of thymoquinone in Jurkat cells
Sana Mahjoub, Rabeb El Ghali, Bechir Achour, Nidhal Ben Amor, Mourad Assidi, Brahim N'siri, Hamid Morjani
P12 Sonic hedgehog contributes in bladder cancer invasion in Saudi Arabia
Taoufik Nedjadi, Adel Al-Ammari, Ahmed Al-Sayyad, Nada Salem, Esam Azhar, Jaudah Al-Maghrabi
P13 Association of Interleukin 18 gene promoter polymorphisms - 607A/C and -137 G/C with colorectal cancer onset in a sample of Tunisian population
Vera Chayeb, Maryam Dendena, Hedia Zitouni, Khedija Zouari-Limayem, Touhami Mahjoub
P14 Pathological expression of interleukin-6, -11, leukemia inhibitory factor and their receptors in tubal gestation with and without tubal cytomegalovirus infection
Bassem Refaat, Ahmed M Ashshi, Sarah A Batwa
P15 Phenotypic and genetic profiling of avian pathogenic and human diarrhegenic Escherichia coli in Egypt
Hazem Ramadan, Amal Awad, Ahmed Ateya
P16 Cancer-targeting dual gene virotherapy as a promising therapeutic strategy for treatment of hepatocellular carcinoma
Adel Galal Ahmed El-Shemi, Ahmad Ashshi, Mohammed Basalamah, Youjin Na, Chae-Ok YUN
P17 Cancer dual gene therapy with oncolytic adenoviruses expressing TRAIL and IL-12 transgenes markedly eradicated human hepatocellular carcinoma both in vitro and in vivo
Adel Galal Ahmed El-Shemi, Ahmad Ashshi, Mohammed Basalamah, Youjin Na, Chae-Ok Yun
P18 Therapy with paricalcitol attenuates tumor growth and augments tumoricidal and anti-oncogenic effects of 5-fluorouracil on animal model of colon cancer
Adel Galal El-Shemi, Bassem Refaat, Osama Kensara, Amr Abdelfattah
P19 The effects of Rubus idaeus extract on normal human lymphocytes and cancer cell line
Batol Imran Dheeb, Mohammed M. F. Al-Halbosiy, Rghad Kadhim Al lihabi, Basim Mohammed Khashman
P20 Etanercept, a TNF-alpha inhibitor, alleviates mechanical hypersensitivity and spontaneous pain in a rat model of chemotherapy-induced neuropathic pain
Djouhri, Laiche, Chaudhary Adeel, Nedjadi, Taoufik
P21 Sleeping beauty mutagenesis system identified genes and neuronal transcription factor network involved in pediatric solid tumour (medulloblastoma)
Hani Al-Afghani, Maria Łastowska, Haya H Al-Balool, Harsh Sheth, Emma Mercer, Jonathan M Coxhead, Chris PF Redfern, Heiko Peters, Alastair D Burt, Mauro Santibanez-Koref, Chris M Bacon, Louis Chesler, Alistair G Rust, David J Adams, Daniel Williamson, Steven C Clifford, Michael S Jackson
P22 Involvement of interleukin-1 in vitiligo pathogenesis
Mala Singh, Mohmmad Shoab Mansuri, Shahnawaz D. Jadeja, Hima Patel, Yogesh S. Marfatia, Rasheedunnisa Begum
P23 Cytogenetics abnormalities in 12,884 referred population for chromosomal analysis and the role of FISH in refining the diagnosis (cytogenetic experience 2004-2013)
Amal M Mohamed, Alaa K Kamel, Nivin A Helmy, Sayda A Hammad, Hesham F Kayed, Marwa I Shehab, Assad El Gerzawy, Maha M. Ead, Ola M Ead, Mona Mekkawy, Innas Mazen, Mona El-Ruby
P24 Analysis of binding properties of angiotensin-converting enzyme 2 through in silico method
S. M. A. Shahid, Qazi Mohammad Sajid Jamal, J. M. Arif, Mohtashim Lohani
P25 Relationship of genetics markers cis and trans to the β-S globin gene with fetal hemoglobin expression in Tunisian sickle cell patients
Moumni Imen, Chaouch Leila, Ouragini Houyem, Douzi Kais, Chaouachi Dorra Mellouli Fethi, Bejaoui Mohamed, Abbes Salem
P26 Analysis of estrogen receptor alpha gene polymorphisms in breast cancer: link to genetic predisposition in Sudanese women
Areeg Faggad, Amanuel T Gebreslasie, Hani Y Zaki, Badreldin E Abdalla
P27 KCNQI gene polymorphism and its association with CVD and T2DM in the Saudi population
Maha S AlShammari, Rhaya Al-Ali, Nader Al-Balawi , Mansour Al-Enazi, Ali Al-Muraikhi, Fadi Busaleh, Ali Al-Sahwan, Francis Borgio, Abdulazeez Sayyed, Amein Al-Ali, Sadananda Acharya
P28 Clinical, neuroimaging and cytogenetic study of a patient with microcephaly capillary malformation syndrome
Maha S. Zaki, Hala T. El-Bassyouni, Marwa I. Shehab
P29 Altered expression of CD200R1 on dendritic cells of patients with inflammatory bowel diseases: in silico investigations and clinical evaluations
Mohammed F. Elshal, Kaleemuddin M., Alia M. Aldahlawi, Omar Saadah,
J. Philip McCoy
P30 Development of real time PCR diagnostic protocol specific for the Saudi Arabian H1N1 viral strains
Adel E El-Tarras, Nabil S Awad, Abdulla A Alharthi, Mohamed M M Ibrahim
P31 Identification of novel genetic variations affecting Osteoarthritis patients
Haneen S Alsehli, Ashraf Dallol, Abdullah M Gari, Mohammed M Abbas, Roaa A Kadam, Mazen M. Gari, Mohmmed H Alkaff, Adel M Abuzenadah, Mamdooh A Gari
P32 An integrated database of GWAS SNVs and their evolutionary properties
Heba Abusamra, Sajjad Karim, Hend F Nour eldin, Elham M Alhathli, Nada Salem, Sudhir Kumar, Mohammed H Al-Qahtani
P33 Familial hypercholesterolemia in Saudi Arabia: prime time for a national registry and genetic analysis
Fatima A. Moradi, Omran M. Rashidi, Zuhier A. Awan
P34 Comparative genomics and network-based analyses of early hepatocellular carcinoma
Ibrahim Hamza Kaya, Olfat Al-Harazi, Dilek Colak
P35 A TALEN-based oncolytic viral vector approach to knock out ABCB1 gene mediated chemoresistance in cancer stem cells
Nabila A Alkousi, Takis Athanasopoulos
P36 Cartilage differentiation and gene expression of synovial fluid mesenchymal stem cells derived from osteoarthritis patients
Afnan O Bahmaid, Etimad A Alhwait, Mamdooh A Gari, Haneen S Alsehli, Mohammed M Abbas, Mohammed H Alkaf, Roaa Kadam, Ashraf Dallol, Gauthaman Kalamegam
P37 E-GRASP: Adding an evolutionary component to the genome-wide repository of associations (GRASP) resource
Hend F Nour Eldin, Sajjad Karim, Heba Abusamra, Elham Alhathli, Nada Salem, Mohammed H Al-Qahtani, Sudhir Kumar
P38 Screening of AGL gene mutation in Saudi family with glycogen storage disease Type III
Salma N Alsayed, Fawziah H Aljohani, Samaher M Habeeb, Rawan A Almashali, Sulman Basit, Samia M Ahmed
P39 High throughput proteomic data suggest modulation of cAMP dependent protein kinase A and mitochondrial function in infertile patients with varicocele
Rakesh Sharma, Ashok Agarwal, Damayanthi Durairajanayagam, Luna Samanta, Muhammad Abu-Elmagd, Adel M. Abuzenadah, Edmund S. Sabanegh, Mourad Assidi, Mohammed Al-Qahtani
P40 Significant protein profile alterations in men with primary and secondary infertility
Ashok Agarwal, Rakesh Sharma, Luna Samanta, Damayanthi Durairajanayagam, Mourad Assidi, Muhammad Abu-Elmagd, Mohammed Al-Qahtani, Adel M. Abuzenadah, Edmund S. Sabanegh
P41 Spermatozoa maturation in infertile patients involves compromised expression of heat shock proteins
Luna Samanta, Ashok Agarwal, Rakesh Sharma, Zhihong Cui, Mourad Assidi, Adel M. Abuzenadah, Muhammad Abu-Elmagd, Mohammed Al-Qahtani
P42 Array comparative genomic hybridization approach to search genomic answers for spontaneous recurrent abortion in Saudi Arabia
Alaa A Alboogmi, Nuha A Alansari, Maha M Al-Quaiti, Fai T Ashgan, Afnan Bandah, Hasan S Jamal, Abdullraheem Rozi, Zeenat Mirza, Adel M Abuzenadah, Sajjad Karim, Mohammed H Al-Qahtani
P43 Global gene expression profiling of Saudi kidney cancer patients
Sajjad Karim, Hans-Juergen Schulten, Ahmad J Al Sayyad, Hasan MA Farsi, Jaudah A Al-Maghrabi, Zeenat Mirza, Reem Alotibi, Alaa Al-Ahmadi, Nuha A Alansari, Alaa A Albogmi, Maha M Al-Quaiti, Fai T Ashgan, Afnan Bandah, Mohammed H Al-Qahtani
P44 Downregulated StAR gene and male reproductive dysfunction caused by nifedipine and ethosuximide
Rasha A Ebiya, Samia M Darwish, Metwally M. Montaser
P45 Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes
Heba Abusamra, Vladimir B. Bajic
P46 Prognostic significance of Osteopontin expression profile in colorectal carcinoma
Jaudah Al-Maghrabi, Wafaey Gomaa, Mehenaz Hanbazazh, Mahmoud Al-Ahwal, Asia Al-Harbi, Wejdan Al-Qahtani, Saher Hakamy, Ghali Baba, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P47 High Glypican-3 expression pattern predicts longer disease-specific survival in colorectal carcinoma
Jaudah Al-Maghrabi, Abdullah Al-Harbi, Mahmoud Al-Ahwal, Asia Al-Harbi, Wejdan Al-Qahtani, Sahar Hakamy, Ghalia Baba, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P48 An evolutionary re-assessment of GWAS single nucleotide variants implicated in the Cholesterol traits
Elham M Alhathli, Sajjad Karim, Nada Salem, Hend Nour Eldin, Heba Abusamra, Sudhir Kumar, Mohammed H Al-Qahtani
P49 Derivation and characterization of human Wharton’s jelly stem cells (hWJSCs) in vitro for future therapeutic applications
Aisha A Alyamani, Gauthaman Kalamegam, Etimad A Alhwait, Mamdooh A Gari, Mohammed M Abbas, Mohammed H Alkaf, Haneen S Alsehli, Roaa A Kadam, Mohammed Al-Qahtani
P50 Attitudes of healthcare students toward biomedical research in the post-genomic era
Rawan Gadi, Abdelbaset Buhmeida, Mourad Assidi , Adeel Chaudhary, Leena Merdad
P51 Evaluation of the immunomodulatory effects of thymoquinone on human bone marrow mesenchymal stem cells (BM-MSCs) from osteoarthritic patients
Saadiah M Alfakeeh, Etimad A Alhwait, Mamdooh A Gari, Mohammed M Abbas, Mohammed H Alkaf, Haneen S Alsehli, Roaa Kadam, Gauthaman Kalamegam
P52 Implication of IL-10 and IL-28 polymorphism with successful anti-HCV therapy and viral clearance
Rubi Ghazala, Shilu Mathew, M.Haroon Hamed, Mourad Assidi, Mohammed Al-Qahtani, Ishtiaq Qadri
P53 Selection of flavonoids against obesity protein (FTO) using in silico and in vitro approaches
Shilu Mathew, Lobna Mira, Manal Shaabad, Shireen Hussain, Mourad Assidi, Muhammad Abu-Elmagd, Mohammed Al-Qahtani
P54 Computational selection and in vitro validation of flavonoids as new antidepressant agents
Shilu Mathew, Manal Shaabad, Lobna Mira, Shireen Hussain, Mourad Assidi, Muhammad Abu-Elmagd, Mohammed Al-Qahtani
P55 In Silico prediction and prioritization of aging candidate genes associated with
progressive telomere shortening
Ahmed Rebai, Mourad Assidi, Abdelbaset Buhmeida, Muhammad Abu-Elmagd, Ashraf Dallol, Jerry W Shay
P56 Identification of new cancer testis antigen genes in diverse types of malignant human tumour cells
Mikhlid H Almutairi
P57 More comprehensive forensic genetic marker analyses for accurate human remains identification using massively parallel sequencing (MPS)
Angie Ambers, Jennifer Churchill, Jonathan King, Monika Stoljarova, Harrell Gill-King, Mourad Assidi, Muhammad Abu-Elmagd, Abdelbaset Buhmeida, Muhammad Al-Qatani, Bruce Budowle
P58 Flow cytometry approach towards treatment men infertility in Saudi Arabia
Muhammad Abu-Elmagd, Farid Ahmed, Ashraf Dallol, Mourad Assidi, Taha Abo Almagd, Sahar Hakamy, Ashok Agarwal, Muhammad Al-Qahtani, Adel Abuzenadah
P59 Tissue microarray based validation of CyclinD1 expression in renal cell carcinoma of Saudi kidney patients
Sajjad Karim, Hans-Juergen Schulten, Ahmad J Al Sayyad, Hasan MA Farsi, Jaudah A Al-Maghrabi, Abdelbaset Buhmaida, Zeenat Mirza, Reem Alotibi, Alaa Al-Ahmadi, Nuha A Alansari, Alaa A Albogmi, Maha M Al-Quaiti, Fai T Ashgan, Afnan Bandah, Mohammed H Al-Qahtani
P60 Assessment of gold nanoparticles in molecular diagnostics and DNA damage studies
Rukhsana Satar, Mahmood Rasool, Waseem Ahmad, Nazia Nazam, Mohamad I Lone, Muhammad I Naseer, Mohammad S Jamal, Syed K Zaidi, Peter N Pushparaj, Mohammad A Jafri, Shakeel A Ansari, Mohammed H Alqahtani
P61 Surfing the biospecimen management and processing workflow at CEGMR Biobank
Hanan Bashier, Abrar Al Qahtani, Shilu Mathew, Amal M. Nour, Heba Alkhatabi, Adel M. Abu Zenadah, Abdelbaset Buhmeida, Mourad Assidi, Muhammed Al Qahtani
P62 Autism Spectrum Disorder: knowledge, attitude and awareness in Jeddah, Kingdom of Saudi Arabia
Muhammad Faheem, Shilu Mathew, Shiny Mathew, Peter Natesan Pushparaj, Mohammad H. Al-Qahtani
P63 Simultaneous genetic screening of the coagulation pathway genes using the Thromboscan targeted sequencing panel
Hani A. Alhadrami, Ashraf Dallol, Adel Abuzenadah
P64 Genome wide array comparative genomic hybridization analysis in patients with syndromic congenital heart defects
Ibtessam R. Hussein, Adeel G. Chaudhary, Rima S Bader, Randa Bassiouni, Maha Alquaiti, Fai Ashgan, Hans Schulten, Mohamed Nabil Alama, Mohammad H. Al Qahtani
P65 Toxocogenetic evaluation of 1, 2-Dichloroethane in bone marrow, blood and cells of immune system using conventional, molecular and flowcytometric approaches
Mohammad I Lone, Nazia Nizam, Waseem Ahmad, Mohammad A Jafri, Mahmood Rasool, Shakeel A Ansari, Muhammed H Al-Qahtani
P66 Molecular cytogenetic diagnosis of sexual development disorders in newborn: A case of ambiguous genitalia
Eradah Alshihri, Muhammad Abu-Elmagd, Lina Alharbi, Mourad Assidi, Mohammed Al-Qahtani
P67 Identification of disease specific gene expression clusters and pathways in hepatocellular carcinoma using In Silico methodologies
Shilu Mathew, Peter Pushparaj Natesan, Muhammed Al Qahtani
P68 Human Wharton’s Jelly stem cell conditioned medium inhibits primary ovarian cancer cells in vitro: Identification of probable targets and mechanisms using systems biology
Gauthaman Kalamegam, Peter Natesan Pushparaj, Fazal Khan, Roaa Kadam, Farid Ahmed, Mourad Assidi, Khalid Hussain Wali Sait, Nisreen Anfinan, Mohammed Al Qahtani
P69 Mutation spectrum of ASPM (Abnormal Spindle-like, Microcephaly-associated) gene in Saudi Arabian population
Muhammad I Naseer, Adeel G Chaudhary, Mohammad S Jamal, Shilu Mathew, Lobna S Mira, Peter N Pushparaj, Shakeel A Ansari, Mahmood Rasool, Mohammed H AlQahtani
P70 Identification and characterization of novel genes and mutations of primary microcephaly in Saudi Arabian population
Muhammad I Naseer, Adeel G Chaudhary, Shilu Mathew, Lobna S Mira, Mohammad S Jamal, Sameera Sogaty, Randa I Bassiouni, Mahmood Rasool, Mohammed H AlQahtani
P71 Molecular genetic analysis of hereditary nonpolyposis colorectal cancer (Lynch Syndrome) in Saudi Arabian population
Mahmood Rasool, Shakeel A Ansari, Mohammad S Jamal, Peter N Pushparaj, Abdulrahman MS Sibiani, Waseem Ahmad, Abdelbaset Buhmeida, Mohammad A Jafri, Mohiuddin K Warsi, Muhammad I Naseer, Mohammed H Al-Qahtani
P72 Function predication of hypothetical proteins from genome database of chlamydia trachomatis
Rubi, Kundan Kumar, Ahmad AT Naqvi, Faizan Ahmad, Md I Hassan, Mohammad S Jamal, Mahmood Rasool, Mohammed H AlQahtani
P73 Transcription factors as novel molecular targets for skin cancer
Ashraf Ali, Jummanah Jarullah, Mahmood Rasool, Abdelbasit Buhmeida, Shahida Khan, Ghufrana Abdussami, Maryam Mahfooz, Mohammad A Kamal, Ghazi A Damanhouri, Mohammad S Jamal
P74 An In Silico analysis of Plumbagin binding to apoptosis executioner: Caspase-3 and Caspase-7
Bushra Jarullah, Jummanah Jarullah, Mohammad SS Jarullah, Ashraf Ali, Mahmood Rasool, Mohammad S Jamal
P75 Single cell genomics applications for preimplantation genetic screening optimization: Comparative analysis of whole genome amplification technologies
Mourad Assidi, Muhammad Abu-Elmagd, Osama Bajouh, Peter Natesan Pushparaj, Mohammed Al-Qahtani, Adel Abuzenadah
P76 ZFP36 regulates miRs-34a in anti-IgM triggered immature B cells
Mohammad S Jamal, Jummanah Jarullah, Abdulah EA Mathkoor, Hashim MA Alsalmi, Anas MM Oun, Ghazi A Damanhauri, Mahmood Rasool, Mohammed H AlQahtani
P77 Identification of a novel mutation in the STAMBP gene in a family with microcephaly-capillary malformation syndrome
Muhammad I. Naseer, Mahmood Rasool, Sameera Sogaty, Adeel G. Chudhary, Yousif A. Abutalib, Daniele Merico, Susan Walker, Christian R. Marshall, Mehdi Zarrei, Stephen W. Scherer, Mohammad H. Al-Qahtani
P78 Copy number variations in Saudi patients with intellectual disability and epilepsy
Muhammad I. Naseer, Muhammad Faheem, Adeel G. Chaudhary, Mahmood Rasool, Gauthaman Kalamegam, Fai Talal Ashgan, Mourad Assidi, Farid Ahmed, Syed Kashif Zaidi, Mohammed M. Jan, Mohammad H. Al-Qahtani
P79 Prognostic significance of CD44 expression profile in colorectal carcinoma
Maryam Al-Zahrani, Sahira Lary, Sahar Hakamy, Ashraf Dallol, Mahmoud Al-Ahwal, Jaudah Al-Maghrabi, Emmanuel Dermitzakis, Adel Abuzenadah, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P80 Association of the endothelial nitric oxide synthase (eNOS) gene G894T polymorphism with hypertension risk and complications
Abeer A Al-refai, Mona Saleh, Rehab I Yassien, Mahmmoud Kamel, Rabab M Habeb
P81 SNPs array to screen genetic variation among diabetic patients
Najlaa Filimban, Ashraf Dallol, Nadia Ghannam, Mohammed Al-Qahtani, Adel Mohammed Abuzenadah
P82 Detection and genotyping of Helicobacter pylori among gastric cancer patients from Saudi Arabian population
Fehmida Bibi, Sana Akhtar, Esam I. Azhar, Muhammad Yasir, Muhammad I. Nasser, Asif A. Jiman-Fatani, Ali Sawan
P83 Antimicrobial drug resistance and molecular detection of susceptibility to Fluoroquinolones among clinical isolates of Salmonella species from Jeddah-Saudi Arabia
Ruaa A Lahzah, Asho Ali
P84 Identification of the toxic and virulence nature of MAP1138c protein of Mycobacterium avium subsp. paratuberculosis
Syed A Hassan, Seyed E Hasnain, Iftikhar A Tayubi, Hamza A Abujabal, Alaa O Magrabi
P85 In vitro and in silico evaluation of miR137 in human breast cancer
Fazal Khan, Gauthaman Kalamegam, Peter Natesan Pushparaj, Adel Abuzenada, Taha Abduallah Kumosani, Elie Barbour, Mohammed Al-Qahtani
P86 Auruka gene is over-expressed in Saudi breast cancer
Manal Shabaad, Shilu Mathew, Ashraf Dallol, Adnan Merdad, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P87 The potential of immunogenomics in personalized healthcare
Mourad Assidi, Muhammad Abu-Elmagd, Kalamegam Gauthaman, Mamdooh Gari, Adeel Chaudhary, Adel Abuzenadah, Peter Natesan Pushparaj, Mohammed Al-Qahtani
P88 In Silico physiochemical and structural characterization of a putative ORF MAP0591 and its implication in the pathogenesis of Mycobacterium paratuberculosis in ruminants and humans
Syed A Hassan, Iftikhar A Tayubi, Hani MA Aljahdali
P89 Effects of heat shock on human bone marrow mesenchymal stem cells (BM-MSCs): Implications in regenerative medicine
Reham Al Nono, Mamdooh Gari, Haneen Alsehli, Farid Ahmed, Mohammed Abbas, Gauthaman Kalamegam, Mohammed Al-Qahtani
P90 In Silico analyses of the molecular targets of Resveratrol unravels its importance in mast cell mediated allergic responses
Shilu Mathew, Fazal Khan, Mahmood Rasool, Mohammed Sarwar Jamal, Muhammad Imran Naseer, Zeenat Mirza, Sajjad Karim, Shakeel Ansari, Mourad Assidi, Gauthaman Kalamegam, Mamdooh Gari, Adeel Chaudhary, Adel Abuzenadah, Peter Natesan Pushparaj, Mohammed Al-Qahtani
P91 Effects of environmental particulate matter on bone-marrow mesenchymal stem cells
Muhammad Abu-Elmagd, Gauthaman Kalamegam, Roaa Kadam, Mansour A Alghamdi, Magdy Shamy, Max Costa, Mamdouh I Khoder, Mourad Assidi, Peter Natesan Pushparaj, Mamdooh Gari, Mohammed Al-Qahtani
P92 Distinctive charge clusters in human virus proteomes
Najla Kharrat, Sabrine Belmabrouk, Rania Abdelhedi, Riadh Benmarzoug, Mourad Assidi, Mohammed H. Al Qahtani, Ahmed Rebai
P93 In vitro experimental model and approach in identification of new biomarkers of inflammatory forms of arthritis
Ghazi Dhamanhouri, Peter Natesan Pushparaj, Abdelwahab Noorwali, Mohammad Khalid Alwasiyah, Afnan Bahamaid, Saadiah Alfakeeh, Aisha Alyamani, Haneen Alsehli, Mohammed Abbas, Mamdooh Gari, Ali Mobasheri, Gauthaman Kalamegam, Mohammed Al-Qahtani
P94 Molecular docking of GABAA receptor subunit γ-2 with novel anti-epileptic compounds
Muhammad Faheem, Shilu Mathew, Peter Natesan Pushparaj, Mohammad H. Al-Qahtani
P95 Breast cancer knowledge, awareness, and practices among Saudi females residing in Jeddah
Shilu Mathew, Muhammad Faheem, Shiny Mathew, Peter Natesan Pushparaj, Mohammad H. Al-Qahtani
P96 Anti-inflammatory role of Sesamin by Attenuation of Iba1/TNF-α/ICAM-1/iNOS signaling in Diabetic Retinopathy
Mohammad Sarwar Jamal, Syed Kashif Zaidi, Raziuddin Khan, Kanchan Bhatia, Mohammed H. Al-Qahtani, Saif Ahmad
P97 Identification of drug lead molecule against vp35 protein of Ebola virus: An In-Silico approach
Iftikhar AslamTayubi, Manish Tripathi, Syed Asif Hassan, Rahul Shrivastava
P98 An approach to personalized medicine from SNP-calling through disease analysis using whole exome-sequencing of three sub-continental populations
Iftikhar A Tayubi, Syed Hassan, Hamza A.S Abujabal
P99 Low versus high frequency of Glucose –6 – Phosphate Dehydrogenase (G6PD) deficiency in urban against tribal population of Gujarat – A signal to natural selection
Ishani Shah, Bushra Jarullah, Mohammad S Jamal, Jummanah Jarullah
P100 Spontaneous preterm birth and single nucleotide gene polymorphisms: a recent update
Ishfaq A Sheikh, Ejaz Ahmad, Mohammad S Jamal, Mohd Rehan, Muhammad Abu-Elmagd, Iftikhar A Tayubi, Samera F AlBasri, Osama S Bajouh, Rola F Turki, Adel M Abuzenadah, Ghazi A Damanhouri, Mohd A Beg, Mohammed Al-Qahtani
P101 Prevalence of congenital heart diseases among Down syndrome cases in Saudi Arabia: role of molecular genetics in the pathogenesis
Sahar AF Hammoudah, Khalid M AlHarbi, Lama M El-Attar, Ahmed MZ Darwish
P102 Combinatorial efficacy of specific pathway inhibitors in breast cancer cells
Sara M Ibrahim, Ashraf Dallol, Hani Choudhry, Adel Abuzenadah, Jalaludden Awlia, Adeel Chaudhary, Farid Ahmed, Mohammed Al-Qahtani
P103 MiR-143 and miR-145 cluster as potential replacement medicine for the treatment of cancer
Mohammad A Jafri, Muhammad Abu-Elmagd, Mourad Assidi, Mohammed Al-Qahtani
P104 Metagenomic profile of gut microbiota during pregnancy in Saudi population
Imran khan, Muhammad Yasir, Esam I. Azhar, Sameera Al-basri, Elie Barbour, Taha Kumosani
P105 Exploration of anticancer targets of selected metabolites of Phoenix dactylifera L. using systems biological approaches
Fazal Khan, Gauthaman Kalamegam, Peter Natesan Pushparaj, Adel Abuzenada, Taha Abduallah Kumosani, Elie Barbour
P106 CD226 and CD40 gene polymorphism in susceptibility to Juvenile rheumatoid arthritis in Egyptian patients
Heba M. EL Sayed, Eman A. Hafez
P107 Paediatric exome sequencing in autism spectrum disorder ascertained in Saudi families
Hans-Juergen Schulten, Aisha Hassan Elaimi, Ibtessam R Hussein, Randa Ibrahim Bassiouni, Mohammad Khalid Alwasiyah, Richard F Wintle, Adeel Chaudhary, Stephen W Scherer, Mohammed Al-Qahtani
P108 Crystal structure of the complex formed between Phospholipase A2 and the central core hydrophobic fragment of Alzheimer’s β- amyloid peptide: a reductionist approach
Zeenat Mirza, Vikram Gopalakrishna Pillai, Sajjad Karim, Sujata Sharma, Punit Kaur, Alagiri Srinivasan, Tej P Singh, Mohammed Al-Qahtani
P109 Differential expression profiling between meningiomas from female and male patients
Reem Alotibi, Alaa Al-Ahmadi, Fatima Al-Adwani, Deema Hussein, Sajjad Karim, Mona Al-Sharif, Awatif Jamal, Fahad Al-Ghamdi, Jaudah Al-Maghrabi, Saleh S Baeesa, Mohammed Bangash, Adeel Chaudhary, Hans-Juergen Schulten, Mohammed Al-Qahtani
P110 Neurospheres as models of early brain development and therapeutics
Muhammad Faheem, Peter Natesan Pushparaj, Shilu Mathew, Taha Abdullah Kumosani, Gauthaman Kalamegam, Mohammed Al-Qahtani
P111 Identification of a recurrent causative missense mutation p.(W577C) at the LDLR exon 12 in familial hypercholesterolemia affected Saudi families
Faisal A Al-Allaf, Zainularifeen Abduljaleel, Abdullah Alashwal, Mohiuddin M. Taher, Abdellatif Bouazzaoui, Halah Abalkhail, Faisal A. Ba-Hammam, Mohammad Athar
P112 Epithelial ovarian carcinoma (EOC): Systems oncological approach to identify diagnostic, prognostic and therapeutic biomarkers
Gauthaman Kalamegam, Peter Natesan Pushparaj, Muhammad Abu-Elmagd, Farid Ahmed Khalid HussainWali Sait, Nisreen Anfinan, Mamdooh Gari, Adeel Chaudhary, Adel Abuzenadah, Mourad Assidi, Mohammed Al-Qahtani
P113 Crohn’s disease phenotype in northern Tunisian population
Naira Ben Mami, Yosr Z Haffani, Mouna Medhioub, Lamine Hamzaoui, Ameur Cherif, Msadok Azouz
P114 Establishment of In Silico approaches to decipher the potential toxicity and mechanism of action of drug candidates and environmental agents
Gauthaman Kalamegam, Fazal Khan, Shilu Mathew, Mohammed Imran Nasser, Mahmood Rasool, Farid Ahmed, Peter Natesan Pushparaj, Mohammed Al-Qahtani
P115 1q Gain predicts poor prognosis marker for young breast cancer patients
Shereen A Turkistany, Lina M Al-harbi, Ashraf Dallol, Jamal Sabir, Adeel Chaudhary, Adel Abuzenadah
P116 Disorders of sex chromosomes in a diagnostic genomic medicine unit in Saudi Arabia: Prevalence, diagnosis and future guidelines
Basmah Al-Madoudi, Bayan Al-Aslani, Khulud Al-Harbi, Rwan Al-Jahdali, Hanadi Qudaih, Emad Al Hamzy, Mourad Assidi, Mohammed Al Qahtani
P117 Combination of WYE354 and Sunitinib demonstrate synergistic inhibition of acute myeloid leukemia in vitro
Asad M Ilyas, Youssri Ahmed, Mamdooh Gari, Farid Ahmed, Mohammed Alqahtani
P118 Integrated use of evolutionary information in GWAS reveals important SNPs in Asthma
Nada Salem, Sajjad Karim, Elham M Alhathli, Heba Abusamra, Hend F Nour Eldin, Mohammed H Al-Qahtani, Sudhir Kumar
P119 Assessment of BRAF, IDH1, IDH2, and EGFR mutations in a series of primary brain tumors
Fatima Al-Adwani, Deema Hussein, Mona Al-Sharif, Awatif Jamal, Fahad Al-Ghamdi, Jaudah Al-Maghrabi, Saleh S Baeesa, Mohammed Bangash, Adeel Chaudhary, Mohammed Al-Qahtani, Hans-Juergen Schulten
P120 Expression profiles distinguish oligodendrogliomas from glioblastoma multiformes with or without oligodendroglioma component
Alaa Alamandi, Reem Alotibi, Deema Hussein, Sajjad Karim, Jaudah Al-Maghrabi, Fahad Al-Ghamdi, Awatif Jamal, Saleh S Baeesa, Mohammed Bangash, Adeel Chaudhary, Hans-Juergen Schulten, Mohammed Al-Qahtani
P121 Hierarchical clustering in thyroid goiters and hyperplastic lesions
Ohoud Subhi, Nadia Bagatian, Sajjad Karim, Adel Al-Johari, Osman Abdel Al-Hamour, Hosam Al-Aradati, Abdulmonem Al-Mutawa, Faisal Al-Mashat, Jaudah Al-Maghrabi, Hans-Juergen Schulten, Mohammad Al-Qahtani
P122 Differential expression analysis in thyroiditis and papillary thyroid carcinomas with or without coexisting thyroiditis
Nadia Bagatian, Ohoud Subhi, Sajjad Karim, Adel Al-Johari, Osman Abdel Al-Hamour, Abdulmonem Al-Mutawa, Hosam Al-Aradati, Faisal Al-Mashat, Mohammad Al-Qahtani, Hans-Juergen Schulten, Jaudah Al-Maghrabi
P123 Metagenomic analysis of waste water microbiome in Sausdi Arabia
Muhammad W shah, Muhammad Yasir, Esam I Azhar, Saad Al-Masoodi
P124 Molecular characterization of Helicobacter pylori from faecal samples of Tunisian patients with gastric cancer
Yosr Z Haffani, Msadok Azouz, Emna Khamla, Chaima Jlassi, Ahmed S. Masmoudi, Ameur Cherif, Lassaad Belbahri
P125 Diagnostic application of the oncoscan© panel for the identification of hereditary cancer syndrome
Shadi Al-Khayyat, Roba Attas, Atlal Abu-Sanad, Mohammed Abuzinadah, Adnan MerdadAshraf Dallol, Adeel Chaudhary, Mohammed Al-Qahtani, Adel Abuzenadah
P126 Characterization of clinical and neurocognitive features in a family with a novel OGT gene missense mutation c. 1193G > A/ (p. Ala319Thr)
Habib Bouazzi, Carlos Trujillo, Mohammad Khalid Alwasiyah, Mohammed Al-Qahtani
P127 Case report: a rare homozygous deletion mutation of TMEM70 gene associated with 3-Methylglutaconic Aciduria and cataract in a Saudi patient
Maha Alotaibi, Rami Nassir
P128 Isolation and purification of antimicrobial milk proteins
Ishfaq A Sheikh, Mohammad A Kamal, Essam H Jiffri, Ghulam M Ashraf, Mohd A Beg
P129 Integrated analysis reveals association of ATP8B1 gene with colorectal cancer
Mohammad A Aziz, Rizwan Ali, Mahmood Rasool, Mohammad S Jamal, Nusaibah samman, Ghufrana Abdussami, Sathish Periyasamy, Mohiuddin K Warsi, Mohammed Aldress, Majed Al Otaibi, Zeyad Al Yousef, Mohamed Boudjelal, Abdelbasit Buhmeida, Mohammed H Al-Qahtani, Ibrahim AlAbdulkarim
P130 Implication of IL-10 and IL-28 polymorphism with successful anti-HCV therapy and viral clearance
Rubi Ghazala, Shilu Mathew, M. Haroon Hamed, Mourad Assidi, Mohammed Al-Qahtani, Ishtiaq Qadri
P131 Interactions of endocrine disruptor di-(2-ethylhexyl) phthalate (DEHP) and its metabolite mono-2-ethylhexyl phthalate (MEHP) with progesterone receptor
Ishfaq A Sheikh, Muhammad Abu-Elmagd, Rola F Turki, Ghazi A Damanhouri, Mohd A. Beg
P132 Association of HCV nucleotide polymorphism in the development of hepatocellular carcinoma
Mohd Suhail, Abid Qureshi, Adil Jamal, Peter Natesan Pushparaj, Mohammad Al-Qahtani, Ishtiaq Qadri
P133 Gene expression profiling by DNA microarrays in colon cancer treated with chelidonine alkaloid
Mahmoud Z El-Readi, Safaa Y Eid, Michael Wink
P134 Successful in vitro fertilization after eight failed trials
Ahmed M. Isa, Lulu Alnuaim, Johara Almutawa, Basim Abu-Rafae, Saleh Alasiri, Saleh Binsaleh
P135 Genetic sensitivity analysis using SCGE, cell cycle and mitochondrial membrane potential in OPs stressed leukocytes in Rattus norvegicus through flow cytometric input
Nazia Nazam, Mohamad I Lone, Waseem Ahmad, Shakeel A Ansari, Mohamed H Alqahtani
PMCID: PMC4959372  PMID: 27454254
17.  Main Report 
Genetics in Medicine  2006;8(Suppl 1):12S-252S.
States vary widely in their use of newborn screening tests, with some mandating screening for as few as three conditions and others mandating as many as 43 conditions, including varying numbers of the 40+ conditions that can be detected by tandem mass spectrometry (MS/MS). There has been no national guidance on the best candidate conditions for newborn screening since the National Academy of Sciences report of 19751 and the United States Congress Office of Technology Assessment report of 1988,2 despite rapid developments since then in genetics, in screening technologies, and in some treatments.
In 2002, the Maternal and Child Health Bureau (MCHB) of the Health Resources and Services Administration (HRSA) of the United States Department of Health and Human Services (DHHS) commissioned the American College of Medical Genetics (ACMG) to: Conduct an analysis of the scientific literature on the effectiveness of newborn screening.Gather expert opinion to delineate the best evidence for screening for specified conditions and develop recommendations focused on newborn screening, including but not limited to the development of a uniform condition panel.Consider other components of the newborn screening system that are critical to achieving the expected outcomes in those screened.
A group of experts in various areas of subspecialty medicine and primary care, health policy, law, public health, and consumers worked with a steering committee and several expert work groups, using a two-tiered approach to assess and rank conditions. A first step was developing a set of principles to guide the analysis. This was followed by developing criteria by which conditions could be evaluated, and then identifying the conditions to be evaluated. A large and broadly representative group of experts was asked to provide their opinions on the extent to which particular conditions met the selected criteria, relying on supporting evidence and references from the scientific literature. The criteria were distributed among three main categories for each condition: The availability and characteristics of the screening test;The availability and complexity of diagnostic services; andThe availability and efficacy of treatments related to the conditions. A survey process utilizing a data collection instrument was used to gather expert opinion on the conditions in the first tier of the assessment. The data collection format and survey provided the opportunity to quantify expert opinion and to obtain the views of a diverse set of interest groups (necessary due to the subjective nature of some of the criteria). Statistical analysis of data produced a score for each condition, which determined its ranking and initial placement in one of three categories (high scoring, moderately scoring, or low scoring/absence of a newborn screening test). In the second tier of these analyses, the evidence base related to each condition was assessed in depth (e.g., via systematic reviews of reference lists including MedLine, PubMed and others; books; Internet searches; professional guidelines; clinical evidence; and cost/economic evidence and modeling). The fact sheets reflecting these analyses were evaluated by at least two acknowledged experts for each condition. These experts assessed the data and the associated references related to each criterion and provided corrections where appropriate, assigned a value to the level of evidence and the quality of the studies that established the evidence base, and determined whether there were significant variances from the survey data. Survey results were subsequently realigned with the evidence obtained from the scientific literature during the second-tier analysis for all objective criteria, based on input from at least three acknowledged experts in each condition. The information from these two tiers of assessment was then considered with regard to the overriding principles and other technology or condition-specific recommendations. On the basis of this information, conditions were assigned to one of three categories as described above:Core Panel;Secondary Targets (conditions that are part of the differential diagnosis of a core panel condition.); andNot Appropriate for Newborn Screening (either no newborn screening test is available or there is poor performance with regard to multiple other evaluation criteria).
ACMG also considered features of optimal newborn screening programs beyond the tests themselves by assessing the degree to which programs met certain goals (e.g., availability of educational programs, proportions of newborns screened and followed up). Assessments were based on the input of experts serving in various capacities in newborn screening programs and on 2002 data provided by the programs of the National Newborn Screening and Genetics Resource Center (NNSGRC). In addition, a brief cost-effectiveness assessment of newborn screening was conducted.
Uniform panel
A total of 292 individuals determined to be generally representative of the regional distribution of the United States population and of areas of expertise or involvement in newborn screening provided a total of 3,949 evaluations of 84 conditions. For each condition, the responses of at least three experts in that condition were compared with those of all respondents for that condition and found to be consistent. A score of 1,200 on the data collection instrument provided a logical separation point between high scoring conditions (1,200–1,799 of a possible 2,100) and low scoring (<1,000) conditions. A group of conditions with intermediate scores (1,000–1,199) was identified, all of which were part of the differential diagnosis of a high scoring condition or apparent in the result of the multiplex assay. Some are identified by screening laboratories and others by diagnostic laboratories. This group was designated as a “secondary target” category for which the program must report the diagnostic result.
Using the validated evidence base and expert opinion, each condition that had previously been assigned to a category based on scores gathered through the data collection instrument was reconsidered. Again, the factors taken into consideration were: 1) available scientific evidence; 2) availability of a screening test; 3) presence of an efficacious treatment; 4) adequate understanding of the natural history of the condition; and 5) whether the condition was either part of the differential diagnosis of another condition or whether the screening test results related to a clinically significant condition.
The conditions were then assigned to one of three categories as previously described (core panel, secondary targets, or not appropriate for Newborn Screening).
Among the 29 conditions assigned to the core panel are three hemoglobinopathies associated with a Hb/S allele, six amino acidurias, five disorders of fatty oxidation, nine organic acidurias, and six unrelated conditions (congenital hypothyroidism (CH), biotinidase deficiency (BIOT), congenital adrenal hyperplasia (CAH), classical galactosemia (GALT), hearing loss (HEAR) and cystic fibrosis (CF)). Twenty-three of the 29 conditions in the core panel are identified with multiplex technologies such as tandem mass spectrometry (MS/MS) or high pressure liquid chromatography (HPLC). On the basis of the evidence, six of the 35 conditions initially placed in the core panel were moved into the secondary target category, which expanded to 25 conditions. Test results not associated with potential disease in the infant (e.g., carriers) were also placed in the secondary target category. When newborn screening laboratory results definitively establish carrier status, the result should be made available to the health care professional community and families. Twenty-seven conditions were determined to be inappropriate for newborn screening at this time.
Conditions with limited evidence reported in the scientific literature were more difficult to evaluate, quantify and place in one of the three categories. In addition, many conditions were found to occur in multiple forms distinguished by age-of-onset, severity, or other features. Further, unless a condition was already included in newborn screening programs, there was a potential for bias in the information related to some criteria. In such circumstances, the quality of the studies underlying the data such as expert opinion that considered case reports and reasoning from first principles determined the placement of the conditions into particular categories.
Newborn screening program optimization
– Assessment of the activities of newborn screening programs, based on program reports, was done for the six program components: education; screening; follow-up; diagnostic confirmation; management; and program evaluation. Considerable variation was found between programs with regard to whether particular aspects (e.g., prenatal education program availability, tracking of specimen collection and delivery) were included and the degree to which they are provided. Newborn screening program evaluation systems also were assessed in order to determine their adequacy and uniformity with the goal being to improve interprogram evaluation and comparison to ensure that the expected outcomes from having been identified in screening are realized.
The state of the published evidence in the fast-moving worlds of newborn screening and medical genetics has not kept up with the implementation of new technologies, thus requiring the considerable use of expert opinion to develop recommendations about a core panel of conditions for newborn screening. Twenty-nine conditions were identified as primary targets for screening from which all components of the newborn screening system should be maximized. An additional 25 conditions were listed that could be identified in the course of screening for core panel conditions. Programs are obligated to establish a diagnosis and communicate the result to the health care provider and family. It is recognized that screening may not have been maximized for the detection of these secondary conditions but that some proportion of such cases may be found among those screened for core panel conditions. With additional screening, greater training of primary care health care professionals and subspecialists will be needed, as will the development of an infrastructure for appropriate follow-up and management throughout the lives of children who have been identified as having one of these rare conditions. Recommended actions to overcome barriers to an optimal newborn screening system include: The establishment of a national role in the scientific evaluation of conditions and the technologies by which they are screened;Standardization of case definitions and reporting procedures;Enhanced oversight of hospital-based screening activities;Long-term data collection and surveillance; andConsideration of the financial needs of programs to allow them to deliver the appropriate services to the screened population.
PMCID: PMC3109899
18.  Conserved roles for yeast Rho1 and mammalian RhoA GTPases in clathrin-independent endocytosis 
Small GTPases  2012;3(4):229-235.
Eukaryotic cells use numerous endocytic pathways for nutrient uptake, protein turnover and response to the extracellular environment. While clathrin-mediated endocytosis (CME) has been extensively studied in yeast and mammalian cells, recent studies in higher eukaryotes have described multiple clathrin-independent endocytic pathways that depend upon Rho family GTPases and their effector proteins. In contrast, yeast cells have been thought to rely solely on CME. In a recent study, we used CME-defective yeast cells lacking clathrin-binding endocytic adaptor proteins in a genetic screen to identify novel factors involved in endocytosis. This approach revealed the existence of a clathrin-independent endocytic pathway involving the GTPase Rho1, which is the yeast homolog of RhoA. Further characterization of the yeast Rho1-mediated endocytic pathway suggested that the Rho1 pathway requires additional proteins that appear to play conserved roles in RhoA-dependent, clathrin-independent endocytic pathways in mammalian cells. Here, we discuss the parallels between the yeast Rho1-dependent and mammalian RhoA-dependent endocytic pathways, as well as the applications of yeast as a model for studying clathrin-independent endocytosis in higher eukaryotes.
PMCID: PMC3520887  PMID: 23238351
endocytosis; clathrin-independent; yeast; actin; Rho1 GTPase
19.  Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans 
RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. elegans, gene function can be knocked down simply and efficiently by feeding worms with bacteria expressing a dsRNA corresponding to a specific gene 1. While the creation of libraries of RNAi clones covering most of the C. elegans genome 2,3 opened the way for true functional genomic studies (see for example 4-7), most established methods are laborious. Moy and colleagues have developed semi-automated protocols that facilitate genome-wide screens 8. The approach relies on microscopic imaging and image analysis.
Here we describe an alternative protocol for a high-throughput genome-wide screen, based on robotic handling of bacterial RNAi clones, quantitative analysis using the COPAS Biosort (Union Biometrica (UBI)), and an integrated software: the MBioLIMS (Laboratory Information Management System from Modul-Bio) a technology that provides increased throughput for data management and sample tracking. The method allows screens to be conducted on solid medium plates. This is particularly important for some studies, such as those addressing host-pathogen interactions in C. elegans, since certain microbes do not efficiently infect worms in liquid culture.
We show how the method can be used to quantify the importance of genes in anti-fungal innate immunity in C. elegans. In this case, the approach relies on the use of a transgenic strain carrying an epidermal infection-inducible fluorescent reporter gene, with GFP under the control of the promoter of the antimicrobial peptide gene nlp 29 and a red fluorescent reporter that is expressed constitutively in the epidermis. The latter provides an internal control for the functional integrity of the epidermis and nonspecific transgene silencing9. When control worms are infected by the fungus they fluoresce green. Knocking down by RNAi a gene required for nlp 29 expression results in diminished fluorescence after infection. Currently, this protocol allows more than 3,000 RNAi clones to be tested and analyzed per week, opening the possibility of screening the entire genome in less than 2 months.
PMCID: PMC3399495  PMID: 22395785
Molecular Biology;  Issue 60;  C. elegans;  fluorescent reporter;  Biosort;  LIMS;  innate immunity;  Drechmeria coniospora
20.  A novel method for tissue-specific RNAi rescue in Drosophila 
Nucleic Acids Research  2009;37(13):e93.
Targeted gene silencing by RNA interference allows the study of gene function in plants and animals. In cell culture and small animal models, genetic screens can be performed—even tissue-specifically in Drosophila—with genome-wide RNAi libraries. However, a major problem with the use of RNAi approaches is the unavoidable false-positive error caused by off-target effects. Until now, this is minimized by computational RNAi design, comparing RNAi to the mutant phenotype if known, and rescue with a presumed ortholog. The ultimate proof of specificity would be to restore expression of the same gene product in vivo. Here, we present a simple and efficient method to rescue the RNAi-mediated knockdown of two independent genes in Drosophila. By exploiting the degenerate genetic code, we generated Drosophila RNAi Escape Strategy Construct (RESC) rescue proteins containing frequent silent mismatches in the complete RNAi target sequence. RESC products were no longer efficiently silenced by RNAi in cell culture and in vivo. As a proof of principle, we rescue the RNAi-induced loss of function phenotype of the eye color gene white and tracheal defects caused by the knockdown of the heparan sulfate proteoglycan syndecan. Our data suggest that RESC is widely applicable to rescue and validate ubiquitous or tissue-specific RNAi and to perform protein structure–function analysis.
PMCID: PMC2715260  PMID: 19483100
21.  Manipulating and enhancing the RNAi response 
The phenomenon that is known as RNA mediated interference (RNAi) was first observed in the nematode C. elegans. The application of RNAi has now been widely disseminated and the mechanisms underlying the pathway have been uncovered using both genetics and biochemistry. In the worm, it has been demonstrated that RNAi is easily adapted to high throughput analysis and screening protocols. Hence, given the availability of whole genome sequences, RNAi has been used extensively as a tool for annotating gene function. Genetic screens performed with C. elegans have also led to the identification of genes that are essential for RNAi or that modulate the RNAi process. The identification of such genes has made it possible to manipulate and enhance the RNAi response. Moreover, many of the genes identified in C. elegans have been conserved in other organisms. Thus, opportunities are available for researchers to take advantage of the insights gained from the worm and apply them to their own systems in order to improve the efficiency and potency of the RNAi response.
PMCID: PMC2737212  PMID: 19771213
C. elegans; RdRP; RNA interference; siRNA; systemic RNAi
22.  A network-based integrative approach to prioritize reliable hits from multiple genome-wide RNAi screens in Drosophila 
BMC Genomics  2009;10:220.
The recently developed RNA interference (RNAi) technology has created an unprecedented opportunity which allows the function of individual genes in whole organisms or cell lines to be interrogated at genome-wide scale. However, multiple issues, such as off-target effects or low efficacies in knocking down certain genes, have produced RNAi screening results that are often noisy and that potentially yield both high rates of false positives and false negatives. Therefore, integrating RNAi screening results with other information, such as protein-protein interaction (PPI), may help to address these issues.
By analyzing 24 genome-wide RNAi screens interrogating various biological processes in Drosophila, we found that RNAi positive hits were significantly more connected to each other when analyzed within a protein-protein interaction network, as opposed to random cases, for nearly all screens. Based on this finding, we developed a network-based approach to identify false positives (FPs) and false negatives (FNs) in these screening results. This approach relied on a scoring function, which we termed NePhe, to integrate information obtained from both PPI network and RNAi screening results. Using a novel rank-based test, we compared the performance of different NePhe scoring functions and found that diffusion kernel-based methods generally outperformed others, such as direct neighbor-based methods. Using two genome-wide RNAi screens as examples, we validated our approach extensively from multiple aspects. We prioritized hits in the original screens that were more likely to be reproduced by the validation screen and recovered potential FNs whose involvements in the biological process were suggested by previous knowledge and mutant phenotypes. Finally, we demonstrated that the NePhe scoring system helped to biologically interpret RNAi results at the module level.
By comprehensively analyzing multiple genome-wide RNAi screens, we conclude that network information can be effectively integrated with RNAi results to produce suggestive FPs and FNs, and to bring biological insight to the screening results.
PMCID: PMC2697172  PMID: 19435510
23.  RNAi screen of Salmonella invasion shows role of COPI in membrane targeting of cholesterol and Cdc42 
A genome wide RNAi screen identifies 72 host cell genes affecting S. Typhimurium entry, including actin regulators and COPI. This study implicates COPI-dependent cholesterol and sphingolipid localization as a common mechanism of infection by bacterial and viral pathogens.
Genome-scale RNAi screen identifies 72 host genes affecting S. Typhimurium host cell invasion.Step-specific follow-up assays assign the phenotypes to specific steps of the invasion process.COPI effects on host cell binding, ruffling and invasion were traced to a key role of COPI in membrane targeting of cholesterol, sphingolipids, Rac1 and Cdc42.This new role of COPI explains why COPI is required for host cell infection by numerous bacterial and viral pathogens.
Pathogens are not only a menace to public health, but they also provide excellent tools for probing host cell function. Thus, studying infection mechanisms has fueled progress in cell biology (Ridley et al, 1992; Welch et al, 1997). In the presented study, we have performed an RNAi screen to identify host cell genes required for Salmonella host cell invasion. This screen identified proteins known to contribute to Salmonella-induced actin rearrangements (e.g., Cdc42 and the Arp2/3 complex; reviewed in Schlumberger and Hardt, 2006) and vesicular traffic (e.g., Rab7) as well as unexpected hits, such as the COPI complex. COPI is a known organizer of Golgi-to-ER vesicle transport (Bethune et al, 2006; Beck et al, 2009). Here, we show that COPI is also involved in plasma membrane targeting of cholesterol, sphingolipids and the Rho GTPases Cdc42 and Rac1, essential host cell factors required for Salmonella invasion. This explains why COPI depletion inhibits infection by S. Typhimurium and illustrates how combining bacterial pathogenesis and systems approaches can promote cell biology.
Salmonella Typhimurium is a common food-borne pathogen and worldwide a major public health problem causing severe diarrhea. The pathogen uses the host's gut mucosa as a portal of entry and gut tissue invasion is a key event leading to the disease. This explains the intense interest from medicine and basic biology in the mechanism of Salmonella host cell invasion.
Tissue culture infection models have delineated a sequence of events leading host cell invasion (Figure 1; Schlumberger and Hardt, 2006): (i) pathogen binding to the host cell surface; (ii) activation of a syringe-like apparatus (‘Type III secretion system 1', T1) of the bacterium and injection of a bacterial toxin cocktail into the host cell. These toxins include SopE, a key virulence factor triggering invasion (Hardt et al, 1998), which was analyzed in our study; (iii) toxin-triggered membrane ruffling. To a significant extent, this is facilitated by SopE-triggered activation of Cdc42 and Rac1 and subsequent actin polymerization at the site of infection; (iv) engulfment of the pathogen within a vesicular compartment (SCV) and (v) maturation of the SCV, a process driven by a second Type III secretion system (T2), which is expressed by the pathogen upon bacterial entry (Figure 1). This sequence of events mediates Salmonella invasion into the gut epithelium and illustrates that this pathogen can be used for probing mechanisms of host cell actin control, membrane biogenesis, vesicle formation and vesicular trafficking.
SopE is a key virulence factor of invasion and triggers the activation of Cdc42 and Rac1 and subsequent actin polymerization at the site of infection. We have employed a SopE-expressing S. Typhimurium strain and RNAi screening technology to identify host cell factors affecting invasion. First, we developed an automated fluorescence microscopy assay to quantify S. Typhimurium entry in a high-throughput format (Figure 1C). This assay was based on a GFP reporter expressed by the pathogen after invasion and maturation of the SCV. Using this assay, we screened a ‘druggable genome' siRNA library (6978 genes, 3 oligos each, 1 oligo per well) and identified 72 invasion hits. These included established regulators of the actin cytoskeleton (Cdc42, Arp2/3, Nap1; Schlumberger and Hardt, 2006), some of which have not been implicated so far in Salmonella entry (Pfn1, Cap1), as well as proteins not previously thought to influence infection (Atp1a1, Rbx1, COPI complex). Potentially, these hits could affect any step of the invasion process (Figure 1A).
In the second stage of the study, we have assigned each ‘invasion hit' to particular steps of the invasion process. For this purpose, we developed step-specific assays for Salmonella binding, injection, ruffling and membrane engulfment and re-screened the genes found as hits in the first screen (four siRNAs per gene). As expected, a significant number of ‘hits' affected binding to the host cell, others affected binding and ruffling (e.g., Pfn1, Itgβ5, Cap1), a few were specific for the ruffling step (e.g., Cdc42) and some affected SCV maturation, namely Rab7a, the trafficking protein Vps39 and the vacuolar proton pump Atp6ap2. Thus, our experimental strategy allowed mechanistic interpretation and linked novel hits to particular phenotypes, thus providing a basis for further studies (Figure 1).
COPI depletion impaired effector injection and ruffling. This was surprising, as the COPI complex was known to regulate retrogade Golgi-to-ER transport, but was not expected to affect pathogen interactions at the plasma membrane. Therefore, we have investigated the underlying mechanism. We have observed that COPI depletion entailed dramatic changes in the plasma membrane composition (Figure 6). Cholesterol and sphingolipids, which form domains (‘lipid rafts') in the plasma membrane, were depleted from the cell surface and redirected into a large vesicular compartment. The same was true for the Rho GTPases Rac1 and Cdc42. This strong decrease in the amount of cholesterol-enriched microdomains and Rho GTPases in the plasma membrane explained the observed defects in S. Typhimurium host cell invasion and assigned a novel role for COPI in controlling mammalian plasma membrane composition. It should be noted that other viral and bacterial pathogens do show a similar dependency on host cellular COPI and plasma membrane lipids. This includes notorious pathogens such as Staphylococcus aureus (Ramet et al, 2002; Potrich et al, 2009), Listeria monocytogenes (Seveau et al, 2004; Agaisse et al, 2005; Cheng et al, 2005; Gekara et al, 2005), Mycobacterium tuberculosis (Munoz et al, 2009), Chlamydia trachomatis (Elwell et al, 2008), influenza virus (Hao et al, 2008; Konig et al, 2010), hepatitis C virus (Tai et al, 2009; Popescu and Dubuisson, 2010) and the vesicular stomatitis virus (presented study) and suggests that COPI-mediated control of host cell plasma membrane composition might be of broad importance for pathogenesis. Future work will have to address whether this might offer starting points for developing anti-infective therapeutics with a very broad spectrum of activity.
The pathogen Salmonella Typhimurium is a common cause of diarrhea and invades the gut tissue by injecting a cocktail of virulence factors into epithelial cells, triggering actin rearrangements, membrane ruffling and pathogen entry. One of these factors is SopE, a G-nucleotide exchange factor for the host cellular Rho GTPases Rac1 and Cdc42. How SopE mediates cellular invasion is incompletely understood. Using genome-scale RNAi screening we identified 72 known and novel host cell proteins affecting SopE-mediated entry. Follow-up assays assigned these ‘hits' to particular steps of the invasion process; i.e., binding, effector injection, membrane ruffling, membrane closure and maturation of the Salmonella-containing vacuole. Depletion of the COPI complex revealed a unique effect on virulence factor injection and membrane ruffling. Both effects are attributable to mislocalization of cholesterol, sphingolipids, Rac1 and Cdc42 away from the plasma membrane into a large intracellular compartment. Equivalent results were obtained with the vesicular stomatitis virus. Therefore, COPI-facilitated maintenance of lipids may represent a novel, unifying mechanism essential for a wide range of pathogens, offering opportunities for designing new drugs.
PMCID: PMC3094068  PMID: 21407211
coatomer; HeLa; Salmonella; siRNA; systems biology
24.  Functional genomic screening to enhance oncolytic virotherapy 
British Journal of Cancer  2012;108(2):245-249.
Functional genomic screening has emerged as a powerful approach for understanding complex biological phenomena. Of the available tools, genome-wide RNA interference (RNAi) technology is unquestionably the most incisive, as it directly probes gene function. Recent applications of RNAi screening have been impressive. Notable amongst these are its use in elucidated mechanism(s) for signal transduction, various aspects of cell biology, tumourigenesis and metastasis, resistance to cancer therapeutics, and the host's response to a pathogen. Herein we discuss how recent RNAi screening efforts have helped turn our attention to the targetability of non-oncogene support pathways for cancer treatment, with a particular focus on a recent study that identified a non-oncogene addiction to the ER stress response as a synergist target for oncolytic virus therapy (OVT). Moreover, we give our thoughts on the future of RNAi screening as a tool to enhance OVT and describe recent technical improvements that are poised to make genome-scale RNAi experiments more sensitive, less noisy, more applicable in vivo, and more easily validated in clinically relevant animal models.
PMCID: PMC3566825  PMID: 23169279
RNAi; screening; oncolytic; virotherapy; cancer
25.  Signature-Based Small Molecule Screening Identifies Cytosine Arabinoside as an EWS/FLI Modulator in Ewing Sarcoma 
PLoS Medicine  2007;4(4):e122.
The presence of tumor-specific mutations in the cancer genome represents a potential opportunity for pharmacologic intervention to therapeutic benefit. Unfortunately, many classes of oncoproteins (e.g., transcription factors) are not amenable to conventional small-molecule screening. Despite the identification of tumor-specific somatic mutations, most cancer therapy still utilizes nonspecific, cytotoxic drugs. One illustrative example is the treatment of Ewing sarcoma. Although the EWS/FLI oncoprotein, present in the vast majority of Ewing tumors, was characterized over ten years ago, it has never been exploited as a target of therapy. Previously, this target has been intractable to modulation with traditional small-molecule library screening approaches. Here we describe a gene expression–based approach to identify compounds that induce a signature of EWS/FLI attenuation. We hypothesize that screening small-molecule libraries highly enriched for FDA-approved drugs will provide a more rapid path to clinical application.
Methods and Findings
A gene expression signature for the EWS/FLI off state was determined with microarray expression profiling of Ewing sarcoma cell lines with EWS/FLI-directed RNA interference. A small-molecule library enriched for FDA-approved drugs was screened with a high-throughput, ligation-mediated amplification assay with a fluorescent, bead-based detection. Screening identified cytosine arabinoside (ARA-C) as a modulator of EWS/FLI. ARA-C reduced EWS/FLI protein abundance and accordingly diminished cell viability and transformation and abrogated tumor growth in a xenograft model. Given the poor outcomes of many patients with Ewing sarcoma and the well-established ARA-C safety profile, clinical trials testing ARA-C are warranted.
We demonstrate that a gene expression–based approach to small-molecule library screening can identify, for rapid clinical testing, candidate drugs that modulate previously intractable targets. Furthermore, this is a generic approach that can, in principle, be applied to the identification of modulators of any tumor-associated oncoprotein in the rare pediatric malignancies, but also in the more common adult cancers.
Todd Golub and colleagues show that a gene expression-based screen of small-molecule libraries can identify candidate drugs that modulate cancer-associated oncoproteins.
Editors' Summary
Cancer occurs when cells accumulate genetic changes (mutations) that allow them to divide uncontrollably and to travel throughout the body (metastasize). Chemotherapy, a mainstay of cancer treatments, works by killing rapidly dividing cells. Because some normal tissues also contain dividing cells and are therefore sensitive to chemotherapy drugs, it is hard to treat cancer without causing serious side effects. In recent years, however, researchers have identified some of the mutations that drive the growth of cancer cells. This raises the possibility of designing drugs that kill only cancer cells by specifically targeting “oncoproteins” (the abnormal proteins generated by mutations that transform normal cells into cancer cells). Some “targeted” drugs have already reached the clinic, but unfortunately medicinal chemists do not know how to inhibit the function of many classes of oncoproteins with the small organic molecules that make the best medicines. One oncoprotein in this category is EWS/FLI. This contains part of a protein called EWS fused to part of a transcription factor (a protein that controls cell behavior by telling the cell which proteins to make) called FLI. About 80% of patients with Ewing sarcoma (the second commonest childhood cancer of bone and soft tissue) have the mutation responsible for EWS/FLI expression. Localized Ewing sarcoma can be treated with nontargeted chemotherapy (often in combination with surgery and radiotherapy), but treatment for recurrent or metastatic disease remains very poor.
Why Was This Study Done?
Researchers have known for years that EWS/FLI expression drives the development of Ewing sarcoma by activating the expression of target genes needed for tumor formation. However, EWS/FLI has never been exploited as a target for therapy of this cancer—mainly because traditional approaches used to screen libraries of small molecules do not identify compounds that modulate the activity of transcription factors. In this study, the researchers have used a new gene expression–based, high-throughput screening (GE-HTS) approach to identify compounds that modulate the activity of EWS/FLI.
What Did the Researchers Do and Find?
The researchers used a molecular biology technique called microarray expression profiling to define a 14-gene expression signature that differentiates between Ewing sarcoma cells in which the EWS/FLI fusion protein is active and those in which it is inactive. They then used this signature to screen a library of about 1,000 chemicals (many already approved for other clinical uses) in a “ligation-mediated amplification assay.” For this, the researchers grew Ewing sarcoma cells with the test chemicals, extracted RNA from the cells, and generated a DNA copy of the RNA. They then added two short pieces of DNA (probes) specific for each signature gene to the samples. In samples that expressed a given signature gene, both probes bound and were then ligated (joined together) and amplified. Because one of each probe pair also contained a unique “capture sequence,” the signature genes expressed in each sample were finally identified by adding colored fluorescent beads, each linked to DNA complementary to a different capture sequence. The most active modulator of EWS/FLI activity identified by this GE-HTS approach was cytosine arabinoside (ARA-C). At levels achievable in people, this compound reduced the abundance of EWS/FLI protein in and the viability and cancer-like behavior of Ewing sarcoma cells growing in test tubes. ARA-C treatment also slowed the growth of Ewing sarcoma cells transplanted into mice.
What Do These Findings Mean?
These findings identify ARA-C, which is already used to treat children with some forms of leukemia, as a potent modulator of EWS/FLI activity. More laboratory experiments are needed to discover how ARA-C changes the behavior of Ewing sarcoma cells. Nevertheless, given the poor outcomes currently seen in many patients with Ewing sarcoma and the historical reluctance to test new drugs in children, these findings strongly support the initiation of clinical trials of ARA-C in children with Ewing sarcoma. These results also show that the GE-HTS approach is a powerful way to identify candidate drugs able to modulate the activity of some of the oncoproteins (including transcription factors and other previously intractable targets) that drive cancer development.
Additional Information.
Please access these Web sites via the online version of this summary at
Cancerquest from Emory University, provides information on cancer biology (also includes information in Spanish, Chinese and Russian)
The MedlinePlus encyclopedia has pages on Ewing sarcoma
Information for patients and health professionals on Ewing sarcoma is available from the US National Cancer Institute
Cancerbackup offers information for patients and their parents on Ewing sarcoma
Wikipedia has pages on DNA microarrays and expression profiling (note that Wikipedia is a free online encyclopedia that anyone can edit)
PMCID: PMC1851624  PMID: 17425403

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