PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (78)
 

Clipboard (0)
None

Select a Filter Below

Year of Publication
more »
1.  TDP-1, the Caenorhabditis elegans ortholog of TDP-43, limits the accumulation of double-stranded RNA 
The EMBO Journal  2014;33(24):2947-2966.
Caenorhabditis elegans mutants deleted for TDP-1, an ortholog of the neurodegeneration-associated RNA-binding protein TDP-43, display only mild phenotypes. Nevertheless, transcriptome sequencing revealed that many RNAs were altered in accumulation and/or processing in the mutant. Analysis of these transcriptional abnormalities demonstrates that a primary function of TDP-1 is to limit formation or stability of double-stranded RNA. Specifically, we found that deletion of tdp-1: (1) preferentially alters the accumulation of RNAs with inherent double-stranded structure (dsRNA); (2) increases the accumulation of nuclear dsRNA foci; (3) enhances the frequency of adenosine-to-inosine RNA editing; and (4) dramatically increases the amount of transcripts immunoprecipitable with a dsRNA-specific antibody, including intronic sequences, RNAs with antisense overlap to another transcript, and transposons. We also show that TDP-43 knockdown in human cells results in accumulation of dsRNA, indicating that suppression of dsRNA is a conserved function of TDP-43 in mammals. Altered accumulation of structured RNA may account for some of the previously described molecular phenotypes (e.g., altered splicing) resulting from reduction of TDP-43 function.
doi:10.15252/embj.201488740
PMCID: PMC4282642  PMID: 25391662
neurodegeneration; RNA editing; RNA structure; splicing
2.  TDP-1, the Caenorhabditis elegans ortholog of TDP-43, limits the accumulation of double-stranded RNA 
The EMBO Journal  2014;33(24):2947-2966.
Caenorhabditis elegans mutants deleted for TDP-1, an ortholog of the neurodegeneration-associated RNA-binding protein TDP-43, display only mild phenotypes. Nevertheless, transcriptome sequencing revealed that many RNAs were altered in accumulation and/or processing in the mutant. Analysis of these transcriptional abnormalities demonstrates that a primary function of TDP-1 is to limit formation or stability of double-stranded RNA. Specifically, we found that deletion of tdp-1: (1) preferentially alters the accumulation of RNAs with inherent double-stranded structure (dsRNA); (2) increases the accumulation of nuclear dsRNA foci; (3) enhances the frequency of adenosine-to-inosine RNA editing; and (4) dramatically increases the amount of transcripts immunoprecipitable with a dsRNA-specific antibody, including intronic sequences, RNAs with antisense overlap to another transcript, and transposons. We also show that TDP-43 knockdown in human cells results in accumulation of dsRNA, indicating that suppression of dsRNA is a conserved function of TDP-43 in mammals. Altered accumulation of structured RNA may account for some of the previously described molecular phenotypes (e.g., altered splicing) resulting from reduction of TDP-43 function.
doi:10.15252/embj.201488740
PMCID: PMC4282642  PMID: 25391662
neurodegeneration; RNA editing; RNA structure; splicing
3.  Identification of genes expressed by immune cells of the colon that are regulated by colorectal cancer-associated variants 
A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case–control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10–5). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways.
doi:10.1002/ijc.28557
PMCID: PMC3949167  PMID: 24154973
genome-wide association study; genetic risk factors; colon cancer; tumor microenvironment
4.  Redefining Genomic Privacy: Trust and Empowerment 
PLoS Biology  2014;12(11):e1001983.
Current models of protecting human subjects create a zero-sum game of privacy versus data utility. We propose shifting the paradigm to techniques that facilitate trust between researchers and participants.
Fulfilling the promise of the genetic revolution requires the analysis of large datasets containing information from thousands to millions of participants. However, sharing human genomic data requires protecting subjects from potential harm. Current models rely on de-identification techniques in which privacy versus data utility becomes a zero-sum game. Instead, we propose the use of trust-enabling techniques to create a solution in which researchers and participants both win. To do so we introduce three principles that facilitate trust in genetic research and outline one possible framework built upon those principles. Our hope is that such trust-centric frameworks provide a sustainable solution that reconciles genetic privacy with data sharing and facilitates genetic research.
doi:10.1371/journal.pbio.1001983
PMCID: PMC4219652  PMID: 25369215
5.  ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis 
F1000Research  2014;3:146.
High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network combined with human curated pathways derived from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.
doi:10.12688/f1000research.4431.2
PMCID: PMC4184317  PMID: 25309732
6.  Computational approaches to identify functional genetic variants in cancer genomes 
Nature methods  2013;10(8):723-729.
The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor, but only a minority drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype.
doi:10.1038/nmeth.2562
PMCID: PMC3919555  PMID: 23900255
7.  ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis 
F1000Research  2014;3:146.
High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network and human curated pathways from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.
doi:10.12688/f1000research.4431.1
PMCID: PMC4184317  PMID: 25309732
9.  Glucocorticoid-Induced Reversal of Interleukin-1β-Stimulated Inflammatory Gene Expression in Human Oviductal Cells 
PLoS ONE  2014;9(5):e97997.
Studies indicate that high-grade serous ovarian carcinoma (HGSOC), the most common epithelial ovarian carcinoma histotype, originates from the fallopian tube epithelium (FTE). Risk factors for this cancer include reproductive parameters associated with lifetime ovulatory events. Ovulation is an acute inflammatory process during which the FTE is exposed to follicular fluid containing both pro- and anti-inflammatory molecules, such as interleukin-1 (IL1), tumor necrosis factor (TNF), and cortisol. Repeated exposure to inflammatory cytokines may contribute to transforming events in the FTE, with glucocorticoids exerting a protective effect. The global response of FTE cells to inflammatory cytokines or glucocorticoids has not been investigated. To examine the response of FTE cells and the ability of glucocorticoids to oppose this response, an immortalized human FTE cell line, OE-E6/E7, was treated with IL1β, dexamethasone (DEX), IL1β and DEX, or vehicle and genome-wide gene expression profiling was performed. IL1β altered the expression of 47 genes of which 17 were reversed by DEX. DEX treatment alone altered the expression of 590 genes, whereas combined DEX and IL1β treatment altered the expression of 784 genes. Network and pathway enrichment analysis indicated that many genes altered by DEX are involved in cytokine, chemokine, and cell cycle signaling, including NFκΒ target genes and interacting proteins. Quantitative real time RT-PCR studies validated the gene array data for IL8, IL23A, PI3 and TACC2 in OE-E6/E7 cells. Consistent with the array data, Western blot analysis showed increased levels of PTGS2 protein induced by IL1β that was blocked by DEX. A parallel experiment using primary cultured human FTE cells indicated similar effects on PTGS2, IL8, IL23A, PI3 and TACC2 transcripts. These findings support the hypothesis that pro-inflammatory signaling is induced in FTE cells by inflammatory mediators and raises the possibility that dysregulation of glucocorticoid signaling could contribute to increased risk for HGSOC.
doi:10.1371/journal.pone.0097997
PMCID: PMC4029821  PMID: 24848801
10.  Inferring clonal evolution of tumors from single nucleotide somatic mutations 
BMC Bioinformatics  2014;15:35.
Background
High-throughput sequencing allows the detection and quantification of frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor cell populations. In some cases, the evolutionary history and population frequency of the subclonal lineages of tumor cells present in the sample can be reconstructed from these SNV frequency measurements. But automated methods to do this reconstruction are not available and the conditions under which reconstruction is possible have not been described.
Results
We describe the conditions under which the evolutionary history can be uniquely reconstructed from SNV frequencies from single or multiple samples from the tumor population and we introduce a new statistical model, PhyloSub, that infers the phylogeny and genotype of the major subclonal lineages represented in the population of cancer cells. It uses a Bayesian nonparametric prior over trees that groups SNVs into major subclonal lineages and automatically estimates the number of lineages and their ancestry. We sample from the joint posterior distribution over trees to identify evolutionary histories and cell population frequencies that have the highest probability of generating the observed SNV frequency data. When multiple phylogenies are consistent with a given set of SNV frequencies, PhyloSub represents the uncertainty in the tumor phylogeny using a “partial order plot”. Experiments on a simulated dataset and two real datasets comprising tumor samples from acute myeloid leukemia and chronic lymphocytic leukemia patients demonstrate that PhyloSub can infer both linear (or chain) and branching lineages and its inferences are in good agreement with ground truth, where it is available.
Conclusions
PhyloSub can be applied to frequencies of any “binary” somatic mutation, including SNVs as well as small insertions and deletions. The PhyloSub and partial order plot software is available from https://github.com/morrislab/phylosub/.
doi:10.1186/1471-2105-15-35
PMCID: PMC3922638  PMID: 24484323
12.  The Reactome pathway knowledgebase 
Nucleic Acids Research  2013;42(Database issue):D472-D477.
Reactome (http://www.reactome.org) is a manually curated open-source open-data resource of human pathways and reactions. The current version 46 describes 7088 human proteins (34% of the predicted human proteome), participating in 6744 reactions based on data extracted from 15 107 research publications with PubMed links. The Reactome Web site and analysis tool set have been completely redesigned to increase speed, flexibility and user friendliness. The data model has been extended to support annotation of disease processes due to infectious agents and to mutation.
doi:10.1093/nar/gkt1102
PMCID: PMC3965010  PMID: 24243840
13.  Gramene 2013: comparative plant genomics resources 
Nucleic Acids Research  2013;42(Database issue):D1193-D1199.
Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology.
doi:10.1093/nar/gkt1110
PMCID: PMC3964986  PMID: 24217918
14.  WormBase 2014: new views of curated biology 
Nucleic Acids Research  2013;42(Database issue):D789-D793.
WormBase (http://www.wormbase.org/) is a highly curated resource dedicated to supporting research using the model organism Caenorhabditis elegans. With an electronic history predating the World Wide Web, WormBase contains information ranging from the sequence and phenotype of individual alleles to genome-wide studies generated using next-generation sequencing technologies. In recent years, we have expanded the contents to include data on additional nematodes of agricultural and medical significance, bringing the knowledge of C. elegans to bear on these systems and providing support for underserved research communities. Manual curation of the primary literature remains a central focus of the WormBase project, providing users with reliable, up-to-date and highly cross-linked information. In this update, we describe efforts to organize the original atomized and highly contextualized curated data into integrated syntheses of discrete biological topics. Next, we discuss our experiences coping with the vast increase in available genome sequences made possible through next-generation sequencing platforms. Finally, we describe some of the features and tools of the new WormBase Web site that help users better find and explore data of interest.
doi:10.1093/nar/gkt1063
PMCID: PMC3965043  PMID: 24194605
15.  Web Apollo: a web-based genomic annotation editing platform 
Genome Biology  2013;14(8):R93.
Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world.
doi:10.1186/gb-2013-14-8-r93
PMCID: PMC4053811  PMID: 24000942
GENOME; COLLABORATIVE; EDITOR
16.  Pathprinting: An integrative approach to understand the functional basis of disease 
Genome Medicine  2013;5(7):68.
New strategies to combat complex human disease require systems approaches to biology that integrate experiments from cell lines, primary tissues and model organisms. We have developed Pathprint, a functional approach that compares gene expression profiles in a set of pathways, networks and transcriptionally regulated targets. It can be applied universally to gene expression profiles across species. Integration of large-scale profiling methods and curation of the public repository overcomes platform, species and batch effects to yield a standard measure of functional distance between experiments. We show that pathprints combine mouse and human blood developmental lineage, and can be used to identify new prognostic indicators in acute myeloid leukemia. The code and resources are available at http://compbio.sph.harvard.edu/hidelab/pathprint
doi:10.1186/gm472
PMCID: PMC3971351  PMID: 23890051
17.  Cloud-based uniform ChIP-Seq processing tools for modENCODE and ENCODE 
BMC Genomics  2013;14:494.
Background
Funded by the National Institutes of Health (NIH), the aim of the Model Organism ENCyclopedia of DNA Elements (modENCODE) project is to provide the biological research community with a comprehensive encyclopedia of functional genomic elements for both model organisms C. elegans (worm) and D. melanogaster (fly). With a total size of just under 10 terabytes of data collected and released to the public, one of the challenges faced by researchers is to extract biologically meaningful knowledge from this large data set. While the basic quality control, pre-processing, and analysis of the data has already been performed by members of the modENCODE consortium, many researchers will wish to reinterpret the data set using modifications and enhancements of the original protocols, or combine modENCODE data with other data sets. Unfortunately this can be a time consuming and logistically challenging proposition.
Results
In recognition of this challenge, the modENCODE DCC has released uniform computing resources for analyzing modENCODE data on Galaxy (https://github.com/modENCODE-DCC/Galaxy), on the public Amazon Cloud (http://aws.amazon.com), and on the private Bionimbus Cloud for genomic research (http://www.bionimbus.org). In particular, we have released Galaxy workflows for interpreting ChIP-seq data which use the same quality control (QC) and peak calling standards adopted by the modENCODE and ENCODE communities. For convenience of use, we have created Amazon and Bionimbus Cloud machine images containing Galaxy along with all the modENCODE data, software and other dependencies.
Conclusions
Using these resources provides a framework for running consistent and reproducible analyses on modENCODE data, ultimately allowing researchers to use more of their time using modENCODE data, and less time moving it around.
doi:10.1186/1471-2164-14-494
PMCID: PMC3734164  PMID: 23875683
18.  InterMOD: integrated data and tools for the unification of model organism research 
Scientific Reports  2013;3:1802.
Model organisms are widely used for understanding basic biology, and have significantly contributed to the study of human disease. In recent years, genomic analysis has provided extensive evidence of widespread conservation of gene sequence and function amongst eukaryotes, allowing insights from model organisms to help decipher gene function in a wider range of species. The InterMOD consortium is developing an infrastructure based around the InterMine data warehouse system to integrate genomic and functional data from a number of key model organisms, leading the way to improved cross-species research. So far including budding yeast, nematode worm, fruit fly, zebrafish, rat and mouse, the project has set up data warehouses, synchronized data models, and created analysis tools and links between data from different species. The project unites a number of major model organism databases, improving both the consistency and accessibility of comparative research, to the benefit of the wider scientific community.
doi:10.1038/srep01802
PMCID: PMC3647165  PMID: 23652793
19.  Exome sequencing identifies nonsegregating nonsense ATM and PALB2 variants in familial pancreatic cancer 
Human Genomics  2013;7(1):11.
We sequenced 11 germline exomes from five families with familial pancreatic cancer (FPC). One proband had a germline nonsense variant in ATM with somatic loss of the variant allele. Another proband had a nonsense variant in PALB2 with somatic loss of the variant allele. Both variants were absent in a relative with FPC. These findings question the causal mechanisms of ATM and PALB2 in these families and highlight challenges in identifying the causes of familial cancer syndromes using exome sequencing.
doi:10.1186/1479-7364-7-11
PMCID: PMC3639869  PMID: 23561644
Hereditary cancer; Pancreas cancer; Germline variants; Genetic counseling; Carcinogenesis
20.  Modeling the evolution dynamics of exon-intron structure with a general random fragmentation process 
Background
Most eukaryotic genes are interrupted by spliceosomal introns. The evolution of exon-intron structure remains mysterious despite rapid advance in genome sequencing technique. In this work, a novel approach is taken based on the assumptions that the evolution of exon-intron structure is a stochastic process, and that the characteristics of this process can be understood by examining its historical outcome, the present-day size distribution of internal translated exons (exon). Through the combination of simulation and modeling the size distribution of exons in different species, we propose a general random fragmentation process (GRFP) to characterize the evolution dynamics of exon-intron structure. This model accurately predicts the probability that an exon will be split by a new intron and the distribution of novel insertions along the length of the exon.
Results
As the first observation from this model, we show that the chance for an exon to obtain an intron is proportional to its size to the 3rd power. We also show that such size dependence is nearly constant across gene, with the exception of the exons adjacent to the 5′ UTR. As the second conclusion from the model, we show that intron insertion loci follow a normal distribution with a mean of 0.5 (center of the exon) and a standard deviation of 0.11. Finally, we show that intron insertions within a gene are independent of each other for vertebrates, but are more negatively correlated for non-vertebrate. We use simulation to demonstrate that the negative correlation might result from significant intron loss during evolution, which could be explained by selection against multi-intron genes in these organisms.
Conclusions
The GRFP model suggests that intron gain is dynamic with a higher chance for longer exons; introns are inserted into exons randomly with the highest probability at the center of the exon. GRFP estimates that there are 78 introns in every 10 kb coding sequences for vertebrate genomes, agreeing with empirical observations. GRFP also estimates that there are significant intron losses in the evolution of non-vertebrate genomes, with extreme cases of around 57% intron loss in Drosophila melanogaster, 28% in Caenorhabditis elegans, and 24% in Oryza sativa.
doi:10.1186/1471-2148-13-57
PMCID: PMC3732091  PMID: 23448166
Evolution of exon-intron structure; General random fragmentation process; Simulation
21.  Using GBrowse 2.0 to visualize and share next-generation sequence data 
Briefings in Bioinformatics  2013;14(2):162-171.
GBrowse is a mature web-based genome browser that is suitable for deployment on both public and private web sites. It supports most of genome browser features, including qualitative and quantitative (wiggle) tracks, track uploading, track sharing, interactive track configuration, semantic zooming and limited smooth track panning. As of version 2.0, GBrowse supports next-generation sequencing (NGS) data by providing for the direct display of SAM and BAM sequence alignment files. SAM/BAM tracks provide semantic zooming and support both local and remote data sources. This article provides step-by-step instructions for configuring GBrowse to display NGS data.
doi:10.1093/bib/bbt001
PMCID: PMC3603216  PMID: 23376193
bioinformatics; genomics; DNA sequencing; genome browser; data visualization; data sharing
22.  Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes 
Biankin, Andrew V. | Waddell, Nicola | Kassahn, Karin S. | Gingras, Marie-Claude | Muthuswamy, Lakshmi B. | Johns, Amber L. | Miller, David K. | Wilson, Peter J. | Patch, Ann-Marie | Wu, Jianmin | Chang, David K. | Cowley, Mark J. | Gardiner, Brooke B. | Song, Sarah | Harliwong, Ivon | Idrisoglu, Senel | Nourse, Craig | Nourbakhsh, Ehsan | Manning, Suzanne | Wani, Shivangi | Gongora, Milena | Pajic, Marina | Scarlett, Christopher J. | Gill, Anthony J. | Pinho, Andreia V. | Rooman, Ilse | Anderson, Matthew | Holmes, Oliver | Leonard, Conrad | Taylor, Darrin | Wood, Scott | Xu, Qinying | Nones, Katia | Fink, J. Lynn | Christ, Angelika | Bruxner, Tim | Cloonan, Nicole | Kolle, Gabriel | Newell, Felicity | Pinese, Mark | Mead, R. Scott | Humphris, Jeremy L. | Kaplan, Warren | Jones, Marc D. | Colvin, Emily K. | Nagrial, Adnan M. | Humphrey, Emily S. | Chou, Angela | Chin, Venessa T. | Chantrill, Lorraine A. | Mawson, Amanda | Samra, Jaswinder S. | Kench, James G. | Lovell, Jessica A. | Daly, Roger J. | Merrett, Neil D. | Toon, Christopher | Epari, Krishna | Nguyen, Nam Q. | Barbour, Andrew | Zeps, Nikolajs | Kakkar, Nipun | Zhao, Fengmei | Wu, Yuan Qing | Wang, Min | Muzny, Donna M. | Fisher, William E. | Brunicardi, F. Charles | Hodges, Sally E. | Reid, Jeffrey G. | Drummond, Jennifer | Chang, Kyle | Han, Yi | Lewis, Lora R. | Dinh, Huyen | Buhay, Christian J. | Beck, Timothy | Timms, Lee | Sam, Michelle | Begley, Kimberly | Brown, Andrew | Pai, Deepa | Panchal, Ami | Buchner, Nicholas | De Borja, Richard | Denroche, Robert E. | Yung, Christina K. | Serra, Stefano | Onetto, Nicole | Mukhopadhyay, Debabrata | Tsao, Ming-Sound | Shaw, Patricia A. | Petersen, Gloria M. | Gallinger, Steven | Hruban, Ralph H. | Maitra, Anirban | Iacobuzio-Donahue, Christine A. | Schulick, Richard D. | Wolfgang, Christopher L. | Morgan, Richard A. | Lawlor, Rita T. | Capelli, Paola | Corbo, Vincenzo | Scardoni, Maria | Tortora, Giampaolo | Tempero, Margaret A. | Mann, Karen M. | Jenkins, Nancy A. | Perez-Mancera, Pedro A. | Adams, David J. | Largaespada, David A. | Wessels, Lodewyk F. A. | Rust, Alistair G. | Stein, Lincoln D. | Tuveson, David A. | Copeland, Neal G. | Musgrove, Elizabeth A. | Scarpa, Aldo | Eshleman, James R. | Hudson, Thomas J. | Sutherland, Robert L. | Wheeler, David A. | Pearson, John V. | McPherson, John D. | Gibbs, Richard A. | Grimmond, Sean M.
Nature  2012;491(7424):399-405.
Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.
doi:10.1038/nature11547
PMCID: PMC3530898  PMID: 23103869
23.  A network module-based method for identifying cancer prognostic signatures 
Genome Biology  2012;13(12):R112.
Discovering robust prognostic gene signatures as biomarkers using genomics data can be challenging. We have developed a simple but efficient method for discovering prognostic biomarkers in cancer gene expression data sets using modules derived from a highly reliable gene functional interaction network. When applied to breast cancer, we discover a novel 31-gene signature associated with patient survival. The signature replicates across 5 independent gene expression studies, and outperforms 48 published gene signatures. When applied to ovarian cancer, the algorithm identifies a 75-gene signature associated with patient survival. A Cytoscape plugin implementation of the signature discovery method is available at http://wiki.reactome.org/index.php/Reactome_FI_Cytoscape_Plugin
doi:10.1186/gb-2012-13-12-r112
PMCID: PMC3580410  PMID: 23228031
24.  Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome 
Cancers  2012;4(4):1180-1211.
Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of “cancer” pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics.
doi:10.3390/cancers4041180
PMCID: PMC3712731  PMID: 24213504
pathway database; pathway visualization; network visualization; cancer annotation; EGFR signaling
25.  Early G1 cyclin-dependent kinases as prognostic markers and potential therapeutic targets in esophageal adenocarcinoma 
Clinical Cancer Research  2011;17(13):4513-4522.
Purpose
Chromosomal gain at 7q21 is a frequent event in esophageal adenocarcinoma (EAC). However, this event has not been mapped with fine resolution in a large EAC cohort and its association with clinical endpoints and functional relevance are unclear.
Experimental design
We used a cohort of 116 patients to fine map the 7q21 amplification using SNP microarrays. Prognostic significance and functional role of 7q21 amplification and its gene expression were explored.
Results
Amplification of the 7q21 region was observed in 35% of tumors with a focal, minimal amplicon containing 6 genes. 7q21 amplification was associated with poor survival and analysis of gene expression identified CDK6 as the only gene in the minimal amplicon whose expression was also associated with poor survival. A low level amplification (10%) was observed at the 12q13 region containing the CDK6 homolog, CDK4. Both amplification and expression of CDK4 correlated with poor survival. A combined model of both CDK6 and CDK4 expression is a superior predictor of survival than either alone. Specific knockdown of CDK4 and/or CDK6 by siRNAs shows that they are required for proliferation of EAC cells and that their function is additive. PD-0332991 targets the kinase activity of both molecules and suppresses proliferation and anchorage-independence of EAC cells through activation of the pRB pathway.
Conclusions
We suggest that CDK6 is the driver of 7q21 amplification and that both CDK4 and CDK6 are prognostic markers and bona fide oncogenes in EAC. Targeting these molecules may constitute a viable new therapy for this disease.
doi:10.1158/1078-0432.CCR-11-0244
PMCID: PMC3390776  PMID: 21593195
Esophageal adenocarcinoma; CDK6; CDK4; PD-0332991

Results 1-25 (78)