Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Tarif Awad is active.

Publication


Featured researches published by Tarif Awad.


Blood | 2008

CYP4F2 genetic variant alters required warfarin dose.

Michael D. Caldwell; Tarif Awad; Julie A. Johnson; Brian F. Gage; Mat Falkowski; Paul Gardina; Jason Hubbard; Yaron Turpaz; Taimour Y. Langaee; Charles S. Eby; Cristi R. King; Amy M. Brower; John R. Schmelzer; Ingrid Glurich; Humberto Vidaillet; Steven H. Yale; Kai Qi Zhang; Richard L. Berg; James K. Burmester

Warfarin is an effective, commonly prescribed anticoagulant used to treat and prevent thrombotic events. Because of historically high rates of drug-associated adverse events, warfarin remains underprescribed. Further, interindividual variability in therapeutic dose mandates frequent monitoring until target anticoagulation is achieved. Genetic polymorphisms involved in warfarin metabolism and sensitivity have been implicated in variability of dose. Here, we describe a novel variant that influences warfarin requirements. To identify additional genetic variants that contribute to warfarin requirements, screening of DNA variants in additional genes that code for drug-metabolizing enzymes and drug transport proteins was undertaken using the Affymetrix drug-metabolizing enzymes and transporters panel. A DNA variant (rs2108622; V433M) in cytochrome P450 4F2 (CYP4F2) was associated with warfarin dose in 3 independent white cohorts of patients stabilized on warfarin representing diverse geographic regions in the United States and accounted for a difference in warfarin dose of approximately 1 mg/day between CC and TT subjects. Genetic variation of CYP4F2 was associated with a clinically relevant effect on warfarin requirement.


Proceedings of the National Academy of Sciences of the United States of America | 2008

Highly parallel identification of essential genes in cancer cells

Biao Luo; Hiu Wing Cheung; Aravind Subramanian; Tanaz Sharifnia; Michael Okamoto; Xiaoping Yang; Greg Hinkle; Jesse S. Boehm; Rameen Beroukhim; Barbara A. Weir; Craig H. Mermel; David A. Barbie; Tarif Awad; Xiaochuan Zhou; Tuyen Nguyen; Bruno Piqani; Cheng Li; Todd R. Golub; Matthew Meyerson; Nir Hacohen; William C. Hahn; Eric S. Lander; David M. Sabatini; David E. Root

More complete knowledge of the molecular mechanisms underlying cancer will improve prevention, diagnosis and treatment. Efforts such as The Cancer Genome Atlas are systematically characterizing the structural basis of cancer, by identifying the genomic mutations associated with each cancer type. A powerful complementary approach is to systematically characterize the functional basis of cancer, by identifying the genes essential for growth and related phenotypes in different cancer cells. Such information would be particularly valuable for identifying potential drug targets. Here, we report the development of an efficient, robust approach to perform genome-scale pooled shRNA screens for both positive and negative selection and its application to systematically identify cell essential genes in 12 cancer cell lines. By integrating these functional data with comprehensive genetic analyses of primary human tumors, we identified known and putative oncogenes such as EGFR, KRAS, MYC, BCR-ABL, MYB, CRKL, and CDK4 that are essential for cancer cell proliferation and also altered in human cancers. We further used this approach to identify genes involved in the response of cancer cells to tumoricidal agents and found 4 genes required for the response of CML cells to imatinib treatment: PTPN1, NF1, SMARCB1, and SMARCE1, and 5 regulators of the response to FAS activation, FAS, FADD, CASP8, ARID1A and CBX1. Broad application of this highly parallel genetic screening strategy will not only facilitate the rapid identification of genes that drive the malignant state and its response to therapeutics but will also enable the discovery of genes that participate in any biological process.


BMC Genomics | 2006

Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array

Paul Gardina; Tyson A. Clark; Brian Shimada; Michelle K Staples; Qing Yang; James Veitch; Anthony C. Schweitzer; Tarif Awad; Charles W. Sugnet; Suzanne Dee; Christopher J. Davies; Alan Williams; Yaron Turpaz

BackgroundAlternative splicing is a mechanism for increasing protein diversity by excluding or including exons during post-transcriptional processing. Alternatively spliced proteins are particularly relevant in oncology since they may contribute to the etiology of cancer, provide selective drug targets, or serve as a marker set for cancer diagnosis. While conventional identification of splice variants generally targets individual genes, we present here a new exon-centric array (GeneChip Human Exon 1.0 ST) that allows genome-wide identification of differential splice variation, and concurrently provides a flexible and inclusive analysis of gene expression.ResultsWe analyzed 20 paired tumor-normal colon cancer samples using a microarray designed to detect over one million putative exons that can be virtually assembled into potential gene-level transcripts according to various levels of prior supporting evidence. Analysis of high confidence (empirically supported) transcripts identified 160 differentially expressed genes, with 42 genes occupying a network impacting cell proliferation and another twenty nine genes with unknown functions. A more speculative analysis, including transcripts based solely on computational prediction, produced another 160 differentially expressed genes, three-fourths of which have no previous annotation. We also present a comparison of gene signal estimations from the Exon 1.0 ST and the U133 Plus 2.0 arrays.Novel splicing events were predicted by experimental algorithms that compare the relative contribution of each exon to the cognate transcript intensity in each tissue. The resulting candidate splice variants were validated with RT-PCR. We found nine genes that were differentially spliced between colon tumors and normal colon tissues, several of which have not been previously implicated in cancer. Top scoring candidates from our analysis were also found to substantially overlap with EST-based bioinformatic predictions of alternative splicing in cancer.ConclusionDifferential expression of high confidence transcripts correlated extremely well with known cancer genes and pathways, suggesting that the more speculative transcripts, largely based solely on computational prediction and mostly with no previous annotation, might be novel targets in colon cancer. Five of the identified splicing events affect mediators of cytoskeletal organization (ACTN1, VCL, CALD1, CTTN, TPM1), two affect extracellular matrix proteins (FN1, COL6A3) and another participates in integrin signaling (SLC3A2). Altogether they form a pattern of colon-cancer specific alterations that may particularly impact cell motility.


Proceedings of the National Academy of Sciences of the United States of America | 2002

Influence of the period-dependent circadian clock on diurnal, circadian, and aperiodic gene expression in Drosophila melanogaster

Yiing Lin; Mei Han; Brian Shimada; Lin Wang; Therese M. Gibler; Aloka Amarakone; Tarif Awad; Gary D. Stormo; Russell N. Van Gelder; Paul H. Taghert

We measured daily gene expression in heads of control and period mutant Drosophila by using oligonucleotide microarrays. In control flies, 72 genes showed diurnal rhythms in light-dark cycles; 22 of these also oscillated in free-running conditions. The period gene significantly influenced the expression levels of over 600 nonoscillating transcripts. Expression levels of several hundred genes also differed significantly between control flies kept in light-dark versus constant darkness but differed minimally between per01 flies kept in the same two conditions. Thus, the period-dependent circadian clock regulates only a limited set of rhythmically expressed transcripts. Unexpectedly, period regulates basal and light-regulated gene expression to a very broad extent.


Journal of Biopharmaceutical Statistics | 2004

A Knowledge-Based Clustering Algorithm Driven by Gene Ontology

Jill Cheng; Melissa S. Cline; John Martin; David Finkelstein; Tarif Awad; David Kulp; Michael A. Siani-Rose

Abstract We have developed an algorithm for inferring the degree of similarity between genes by using the graph-based structure of Gene Ontology (GO). We applied this knowledge-based similarity metric to a clique-finding algorithm for detecting sets of related genes with biological classifications. We also combined it with an expression-based distance metric to produce a co-cluster analysis, which accentuates genes with both similar expression profiles and similar biological characteristics and identifies gene clusters that are more stable and biologically meaningful. These algorithms are demonstrated in the analysis of MPRO cell differentiation time series experiments.


Circulation | 2001

Effects of Early Angiotensin-Converting Enzyme Inhibition on Cardiac Gene Expression After Acute Myocardial Infarction

Hongkui Jin; Renhui Yang; Tarif Awad; Fay Wang; Wei Li; Simon-Peter Williams; Annie Ogasawara; Brian Shimada; P. Mickey Williams; Gianfranco de Feo; Nicholas F. Paoni

Background —ACE inhibition after myocardial infarction (MI) has been shown to have beneficial effects on cardiac anatomy and function. The purpose of this study was to examine the effects of ACE inhibition on cardiac gene expression after MI. Methods and Results —Rats were randomized to receive captopril or no treatment 1 day after MI. Eight weeks later, cardiac function and hemodynamics were measured by use of indwelling catheters and perivascular flow probes. Myocardial gene expression was assessed with DNA microarrays and real-time reverse transcription–polymerase chain reaction. The ratios of heart and left ventricular weights to body weight were significantly increased by MI and normalized by captopril. Cardiac index and stroke volume index were lower in the untreated MI group than in sham controls but were normal in the MI+captopril group. Thirty-seven genes were found to be differentially expressed between the untreated MI group and sham controls; 31 were induced and 6 repressed. Captopril partially or completely inhibited changes in 10 of the genes. The 37 genes clustered into 11 functional groups, and 6 had ≥1 genes whose expression was modified by ACE inhibition. Conclusions —ACE inhibition after MI inhibits cardiac hypertrophy, preserves cardiac function, and attenuates changes in myocardial gene expression. Gene expression profiling reveals, however, that some elements of the pathophysiology may be unaffected by the treatment and be targets for new therapies.


Molecular Cancer Therapeutics | 2007

Orphan G protein–coupled receptor GPR56 plays a role in cell transformation and tumorigenesis involving the cell adhesion pathway

Ning Ke; Roshni Sundaram; Guohong Liu; John Chionis; Wufang Fan; Cheryl Rogers; Tarif Awad; Mirta Grifman; Dehua Yu; Flossie Wong-Staal; Qi-Xiang Li

GPR56 is an orphan G protein–coupled receptor, mutations of which have recently been associated with bilateral frontoparietal polymicrogyria, a rare neurologic disease that has implications in brain development. However, no phenotype beyond central nervous system has yet been described for the GPR56-null mutations despite abundant GPR56 expression in many non–central nervous system adult tissues. In the present study, we show that higher GPR56 expression is correlated with the cellular transformation phenotypes of several cancer tissues compared with their normal counterparts, implying a potential oncogenic function. RNA interference–mediated GPR56 silencing results in apoptosis induction and reduced anchorage-independent growth of cancer cells via increased anoikis, whereas cDNA overexpression resulted in increased foci formation in mouse fibroblast NIH3T3 cell line. When GPR56 silencing was induced in vivo in several xenograft tumor models, significant tumor responses (including regression) were observed, suggesting the potential of targeting GPR56 in the development of tumor therapies. The expression profiling of GPR56-silenced A2058 melanoma cell line revealed several genes whose expression was affected by GPR56 silencing, particularly those in the integrin-mediated signaling and cell adhesion pathways. The potential role of GPR56 in cancer cell adhesion was further confirmed by the observation that GPR56 silencing also reduced cell adhesion to the extracellular matrix, which is consistent with the observed increase in anoikis and reduction in anchorage-independent growth phenotypes. The oncogenic potential and apparent absence of physiologic defects in adult human tissues lacking GPR56, as well as the targetable nature of G protein–coupled receptor by small molecule or antibody, make GPR56 an attractive drug target for the development of cancer therapies. [Mol Cancer Ther 2007;6(6):1840–50]


Genes, Brain and Behavior | 2007

Altered gene expression in mice selected for high maternal aggression.

Stephen C. Gammie; Anthony P. Auger; Heather M. Jessen; Rena J. Vanzo; Tarif Awad; Sharon A. Stevenson

We previously applied selective breeding on outbred mice to increase maternal aggression (maternal defense). In this study, we compared gene expression within a continuous region of the central nervous system (CNS) involved in maternal aggression (hypothalamus and preoptic regions) between lactating selected (S) and nonselected control (C) mice (n= 6 per group). Using microarrays representing over 40 000 genes or expressed sequence tags, two statistical algorithms were used to identify significant differences in gene expression: robust multiarray and the probe logarithmic intensity error method. Approximately 200 genes were identified as significant using an intersection from both techniques. A subset of genes was examined for confirmation by real‐time polymerase chain reaction (PCR). Significant decreases were found in S mice for neurotensin and neuropeptide Y receptor Y2 (both confirmed by PCR). Significant increases were found in S mice for neuronal nitric oxide synthase (confirmed by PCR), the K+ channel subunit, Kcna1 (confirmed by PCR), corticotrophin releasing factor binding protein (just above significance using PCR; P= 0.051) and GABA A receptor subunit 1A (not confirmed by PCR, but similar direction). S mice also exhibited significantly higher levels of the neurotransmitter receptor, adenosine A1 receptor and the transcription factors, c‐Fos, and Egr‐1. Interestingly, for 24 genes related to metabolism, all were significantly elevated in S mice, suggesting altered metabolism in these mice. Together, this study provides a list of candidate genes (some previously implicated in maternal aggression and some novel) that may play an important role in the production of this behavior.


BMC Genomics | 2009

Combined genome-wide expression profiling and targeted RNA interference in primary mouse macrophages reveals perturbation of transcriptional networks associated with interferon signalling

Paul Lacaze; Sobia Raza; Garwin Sing; David C. Page; Thorsten Forster; Petter Storm; Marie Craigon; Tarif Awad; Peter Ghazal; Tom C. Freeman

BackgroundInterferons (IFNs) are potent antiviral cytokines capable of reprogramming the macrophage phenotype through the induction of interferon-stimulated genes (ISGs). Here we have used targeted RNA interference to suppress the expression of a number of key genes associated with IFN signalling in murine macrophages prior to stimulation with interferon-gamma. Genome-wide changes in transcript abundance caused by siRNA activity were measured using exon-level microarrays in the presence or absence of IFNγ.ResultsTransfection of murine bone-marrow derived macrophages (BMDMs) with a non-targeting (control) siRNA and 11 sequence-specific siRNAs was performed using a cationic lipid transfection reagent (Lipofectamine2000) prior to stimulation with IFNγ. Total RNA was harvested from cells and gene expression measured on Affymetrix GeneChip Mouse Exon 1.0 ST Arrays. Network-based analysis of these data revealed six siRNAs to cause a marked shift in the macrophage transcriptome in the presence or absence IFNγ. These six siRNAs targeted the Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2 transcripts. The perturbation of the transcriptome by the six siRNAs was highly similar in each case and affected the expression of over 600 downstream transcripts. Regulated transcripts were clustered based on co-expression into five major groups corresponding to transcriptional networks associated with the type I and II IFN response, cell cycle regulation, and NF-KB signalling. In addition we have observed a significant non-specific immune stimulation of cells transfected with siRNA using Lipofectamine2000, suggesting use of this reagent in BMDMs, even at low concentrations, is enough to induce a type I IFN response.ConclusionOur results provide evidence that the type I IFN response in murine BMDMs is dependent on Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2, and that siRNAs targeted to these genes results in perturbation of key transcriptional networks associated with type I and type II IFN signalling and a suppression of macrophage M1 polarization.


Bioinformatics | 2006

A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations

Chun Zhang; Dione K. Bailey; Tarif Awad; Guoying Liu; Guoliang Xing; Manqiu Cao; Venu Valmeekam; Jacques Retief; Hajime Matsuzaki; Margaret Taub; Mark Seielstad; Giulia C. Kennedy

Collaboration


Dive into the Tarif Awad's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Anthony P. Auger

University of Wisconsin-Madison

View shared research outputs
Top Co-Authors

Avatar

Brian F. Gage

University of Washington

View shared research outputs
Top Co-Authors

Avatar

Charles S. Eby

Washington University in St. Louis

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Cristi R. King

Washington University in St. Louis

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge