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Xu J.,University of California at San Francisco | Haigis K.M.,Massachusetts General Hospital | Firestone A.J.,University of California at San Francisco | McNerney M.E.,Institute for Genomics and Systems Biology | And 8 more authors.
Cancer Discovery | Year: 2013

Biochemical properties of Ras oncoproteins and their transforming ability strongly support a dominant mechanism of action in tumorigenesis. However, genetic studies unexpectedly suggested that wild-type (WT) Ras exerts tumor suppressor activity. Expressing oncogenic NrasG12D in the hematopoietic compartment of mice induces an aggressive myeloproliferative neoplasm that is exacerbated in homozygous mutant animals. Here, we show that increased NrasG12D gene dosage, but not inactivation of WT Nras, underlies the aggressive in vivo behavior of NrasG12D/G12D hematopoietic cells. Modulating NrasG12D dosage had discrete effects on myeloid progenitor growth, signal transduction, and sensitivity to MAP-ERK kinase (MEK) inhibition. Furthermore, enforced WT N-Ras expression neither suppressed the growth of Nras -mutant cells nor inhibited myeloid transformation by exogenous NrasG12D. Importantly, NRAS expression increased in human cancer cell lines with NRAS mutations. These data have therapeutic implications and support reconsidering the proposed tumor suppressor activity of WT Ras in other cancers. SIGNIFICANCE: Understanding the mechanisms of Ras -induced transformation and adaptive cellular responses is fundamental. The observation that oncogenic Nras lacks tumor suppressor activity, whereas increased dosage strongly modulates cell growth and alters sensitivity to MEK inhibition, suggests new therapeutic opportunities in cancer. © 2013 American Association for Cancer Research. Source


Rust M.J.,Institute for Genomics and Systems Biology
Cell Systems | Year: 2015

How do rich biological behaviors arise from bi-molecular collisions? © 2015 Elsevier Inc. Source


Barriere A.,Institute for Genomics and Systems Biology | Gordon K.L.,University of Chicago | Ruvinsky I.,Institute for Genomics and Systems Biology | Ruvinsky I.,University of Chicago
PLoS Genetics | Year: 2011

Different functional constraints contribute to different evolutionary rates across genomes. To understand why some sequences evolve faster than others in a single cis-regulatory locus, we investigated function and evolutionary dynamics of the promoter of the Caenorhabditis elegans unc-47 gene. We found that this promoter consists of two distinct domains. The proximal promoter is conserved and is largely sufficient to direct appropriate spatial expression. The distal promoter displays little if any conservation between several closely related nematodes. Despite this divergence, sequences from all species confer robustness of expression, arguing that this function does not require substantial sequence conservation. We showed that even unrelated sequences have the ability to promote robust expression. A prominent feature shared by all of these robustness-promoting sequences is an AT-enriched nucleotide composition consistent with nucleosome depletion. Because general sequence composition can be maintained despite sequence turnover, our results explain how different functional constraints can lead to vastly disparate rates of sequence divergence within a promoter. © 2011 Barrière et al. Source


Khattri A.,University of Chicago | Zuo Z.,University of Chicago | Bragelmann J.,University of Chicago | Bragelmann J.,University of Bonn | And 12 more authors.
Oral Oncology | Year: 2015

Background: The epidermal growth factor receptor (EGFR) is a transmembrane tyrosine kinase receptor and is overexpressed in up to 90% of head and neck squamous cell carcinoma (HNSCC) cases. The EGFR truncation mutation, EGFR variant III (EGFRvIII), harbors an in-frame deletion of exons 2-7 (801 bp) that leads to the constitutive activation of downstream signaling. EGFRvIII has been reported in ∼40% of glioblastomas (GBM), but its presence in HNSCC remains controversial. Methods: EGFRvIII deletion in 638 HNSCC samples was analyzed using: (i) quantitative Real-Time polymerase chain reaction (qRT-PCR) on 108 HNSCC samples with direct detection of the EGFRvIII breakpoint, (ii) RNA-Seq analysis on 7 HNSCC tumor tissues and 425 The Cancer Genome Atlas (TCGA) HNSCC samples, and (iii) immunohistochemistry (IHC) for EGFRvIII using an established antibody (L8A4) on a tissue microarray of 105 HNSCC samples. Results: qRT-PCR did not show the presence of EGFRvIII in any of the samples analyzed. Furthermore, we could not detect any EGFRvIII transcripts in the RNA-Seq data of the seven HNSCC samples. However, 2 samples out of 425 TCGA HNSCC samples had EGFRvIII specific reads. EGFRvIII IHC results were assessed as negative for all samples. Conclusion: Our results firmly establish that EGFRvIII is very rare in HNSCC as only 2 out of 638 (0.31%) samples we analyzed overall, or 2 out of 540 (0.37%) using mRNA based approaches, were positive for EGFRvIII. EGFRvIII is extremely rare in HNSCC and the clinical significance remains unclear. We propose not to include EGFRvIII testing in regular diagnostic tests for HNSCC. © 2014 Elsevier Ltd. All rights reserved. Source


Wilke A.,Argonne National Laboratory | Wilke A.,University of Chicago | Harrison T.,Argonne National Laboratory | Harrison T.,University of Chicago | And 8 more authors.
BMC Bioinformatics | Year: 2012

Background: Computing of sequence similarity results is becoming a limiting factor in metagenome analysis. Sequence similarity search results encoded in an open, exchangeable format have the potential to limit the needs for computational reanalysis of these data sets. A prerequisite for sharing of similarity results is a common reference.Description: We introduce a mechanism for automatically maintaining a comprehensive, non-redundant protein database and for creating a quarterly release of this resource. In addition, we present tools for translating similarity searches into many annotation namespaces, e.g. KEGG or NCBI's GenBank.Conclusions: The data and tools we present allow the creation of multiple result sets using a single computation, permitting computational results to be shared between groups for large sequence data sets. © 2012 Wilke et al.; licensee BioMed Central Ltd. Source

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