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411
The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration.
- Nat Biotechnol,
, 2007
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Predicting the functional impact of protein mutations: application to cancer genomics
- Nucleic Acids Res. 39, e118. ACS Chemical Biology Letters dx.doi.org/10.1021/cb500347p | ACS Chem. Biol
, 2011
"... As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conserva ..."
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Cited by 102 (3 self)
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As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (19200), assumed to be strongly functional, from common polymorphisms (35600), assumed to be weakly functional (area under the receiver operating characteristic curve of 0.86). In cancer, using recurrence, multiplicity and annotation for 10000 mutations in the COSMIC database, the method does well in assign-ing higher scores to more likely functional mutations (‘drivers’). To guide experimental prioritization, we report a list of about 1000 top human cancer genes frequently mutated in one or more cancer types ranked by likely functional impact; and, an additional 1000 candidate cancer genes with rare but likely functional mutations. In addition, we estimate that at least 5 % of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function.
Small molecule-mediated disruption of Wnt-dependent signaling in tissue regeneration and cancer. Nat Chem Biol. 2009; 5(2):100–107. [PubMed: 19125156
"... tissue regeneration and cancer ..."
The genomic complexity of primary human prostate cancer.
- Nature
, 2011
"... Prostate cancer is the second most common cause of male cancer deaths in the United States. However, the full range of prostate cancer genomic alterations is incompletely characterized. Here we present the complete sequence of seven primary human prostate cancers and their paired normal counterpart ..."
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Cited by 30 (0 self)
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Prostate cancer is the second most common cause of male cancer deaths in the United States. However, the full range of prostate cancer genomic alterations is incompletely characterized. Here we present the complete sequence of seven primary human prostate cancers and their paired normal counterparts. Several tumours contained complex chains of balanced (that is, 'copy-neutral') rearrangements that occurred within or adjacent to known cancer genes. Rearrangement breakpoints were enriched near open chromatin, androgen receptor and ERG DNA binding sites in the setting of the ETS gene fusion TMPRSS2-ERG, but inversely correlated with these regions in tumours lacking ETS fusions. This observation suggests a link between chromatin or transcriptional regulation and the genesis of genomic aberrations. Three tumours contained rearrangements that disrupted CADM2, and four harboured events disrupting either PTEN (unbalanced events), a prostate tumour suppressor, or MAGI2 (balanced events), a PTEN interacting protein not previously implicated in prostate tumorigenesis. Thus, genomic rearrangements may arise from transcriptional or chromatin aberrancies and engage prostate tumorigenic mechanisms. Among men in the United States, prostate cancer accounts for more than 200,000 new cancer cases and 32,000 deaths annually 1 . Although androgen deprivation therapy yields transient efficacy, most patients with metastatic prostate cancer eventually die of their disease. These aspects underscore the critical need to articulate both genetic underpinnings and novel therapeutic targets in prostate cancer. Recent years have heralded a marked expansion in our understanding of the somatic genetic basis of prostate cancer. Of considerable importance has been the discovery of recurrent gene fusions that render ETS transcription factors under the control of androgenresponsive or other promoters 2-5 . These findings suggest that genomic rearrangements may comprise a major mechanism driving prostate carcinogenesis. Other types of somatic alterations also engage important mechanisms
Genetic progression and the waiting time to cancer
- PLoS Comput. Biol
, 2007
"... Cancer results from genetic alterations that disturb the normal cooperative behavior of cells. Recent high-throughput genomic studies of cancer cells have shown that the mutational landscape of cancer is complex and that individual cancers may evolve through mutations in as many as 20 different canc ..."
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Cited by 27 (1 self)
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Cancer results from genetic alterations that disturb the normal cooperative behavior of cells. Recent high-throughput genomic studies of cancer cells have shown that the mutational landscape of cancer is complex and that individual cancers may evolve through mutations in as many as 20 different cancer-associated genes. We use data published by Sjöblom et al. (2006) to develop a new mathematical model for the somatic evolution of colorectal cancers. We employ the Wright-Fisher process for exploring the basic parameters of this evolutionary process and derive an analytical approximation for the expected waiting time to the cancer phenotype. Our results highlight the relative importance of selection over both the size of the cell population at risk and the mutation rate. The model predicts that the observed genetic diversity of cancer genomes can arise under a normal mutation rate if the average selective advantage per mutation is on the order of 1%. Increased mutation rates due to genetic instability would allow even smaller selective advantages during tumorigenesis. The complexity of cancer progression can be understood as the result of multiple sequential mutations, each of which has a relatively small but positive effect on net cell growth.
CanPredict: a computational tool for predicting cancer-associated missense
, 2007
"... mutations ..."
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M: Modeling cancer progression via pathway dependencies
- PLoS Comput Biol
"... Cancer is a heterogeneous disease often requiring a complexity of alterations to drive a normal cell to a malignancy and ultimately to a metastatic state. Certain genetic perturbations have been implicated for initiation and progression. However, to a great extent, underlying mechanisms often remain ..."
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Cited by 16 (3 self)
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Cancer is a heterogeneous disease often requiring a complexity of alterations to drive a normal cell to a malignancy and ultimately to a metastatic state. Certain genetic perturbations have been implicated for initiation and progression. However, to a great extent, underlying mechanisms often remain elusive. These genetic perturbations are most likely reflected by the altered expression of sets of genes or pathways, rather than individual genes, thus creating a need for models of deregulation of pathways to help provide an understanding of the mechanisms of tumorigenesis. We introduce an integrative hierarchical analysis of tumor progression that discovers which a priori defined pathways are relevant either throughout or in particular steps of progression. Pathway interaction networks are inferred for these relevant pathways over the steps in progression. This is followed by the refinement of the relevant pathways to those genes most differentially expressed in particular disease stages. The final analysis infers a gene interaction network for these refined pathways. We apply this approach to model progression in prostate cancer and melanoma, resulting in a deeper understanding of the mechanisms of tumorigenesis. Our analysis supports previous findings for the deregulation of several pathways involved in cell cycle control and proliferation in both cancer types. A novel finding
Proteomics analysis of conditioned media from three breast cancer cell lines: a mine for biomarkers and therapeutic targets
- Mol. Cell. Proteomics
, 2007
"... A “bottom-up ” proteomics approach and a two-dimen-sional (strong cation exchange followed by reversed-phase) LC-MS/MS strategy on a linear ion trap (LTQ) were utilized to identify and compare expressions of extracel-lular and membrane-bound proteins in the conditioned media of three breast cell lin ..."
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Cited by 16 (0 self)
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A “bottom-up ” proteomics approach and a two-dimen-sional (strong cation exchange followed by reversed-phase) LC-MS/MS strategy on a linear ion trap (LTQ) were utilized to identify and compare expressions of extracel-lular and membrane-bound proteins in the conditioned media of three breast cell lines (MCF-10A, BT474, and MDA-MB-468). Proteomics analysis of the media identi-fied in excess of 600, 500, and 700 proteins in MCF-10A, BT474, and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6, and 10 (ranging in concentration from 2 to 50 g/liter) in MDA-MB-468 conditioned medium as validated by ELISA and confidently identified Her-2/neu in BT474 cells. Subcellu-lar localization was determined based on Genome Ontol-ogy terms for all the 1,139 proteins of which 34 % were
The waiting time for m mutations
- Electron. J. Probab
, 2008
"... b a b i l i t y ..."
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