Showing papers by "Chris Sander published in 2010"

International network of cancer genome projects

Abstract: The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

Abstract: mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.

The BioPAX community standard for pathway data sharing

Abstract: Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy.

Abstract: Soft-tissue sarcomas, which result in approximately 10,700 diagnoses and 3,800 deaths per year in the United States, show remarkable histologic diversity, with more than 50 recognized subtypes. However, knowledge of their genomic alterations is limited. We describe an integrative analysis of DNA sequence, copy number and mRNA expression in 207 samples encompassing seven major subtypes. Frequently mutated genes included TP53 (17% of pleomorphic liposarcomas), NF1 (10.5% of myxofibrosarcomas and 8% of pleomorphic liposarcomas) and PIK3CA (18% of myxoid/round-cell liposarcomas, or MRCs). PIK3CA mutations in MRCs were associated with Akt activation and poor clinical outcomes. In myxofibrosarcomas and pleomorphic liposarcomas, we found both point mutations and genomic deletions affecting the tumor suppressor NF1. Finally, we found that short hairpin RNA (shRNA)-based knockdown of several genes amplified in dedifferentiated liposarcoma, including CDK4 and YEATS4, decreased cell proliferation. Our study yields a detailed map of molecular alterations across diverse sarcoma subtypes and suggests potential subtype-specific targets for therapy.

NetPath: a public resource of curated signal transduction pathways

Abstract: We have developed NetPath as a resource of curated human signaling pathways. As an initial step, NetPath provides detailed maps of a number of immune signaling pathways, which include approximately 1,600 reactions annotated from the literature and more than 2,800 instances of transcriptionally regulated genes - all linked to over 5,500 published articles. We anticipate NetPath to become a consolidated resource for human signaling pathways that should enable systems biology approaches.

Automated network analysis identifies core pathways in glioblastoma.

Abstract: Background Glioblastoma multiforme (GBM) is the most common and aggressive type of brain tumor in humans and the first cancer with comprehensive genomic profiles mapped by The Cancer Genome Atlas (TCGA) project A central challenge in large-scale genome projects, such as the TCGA GBM project, is the ability to distinguish cancer-causing “driver” mutations from passively selected “passenger” mutations Principal Findings In contrast to a purely frequency based approach to identifying driver mutations in cancer, we propose an automated network-based approach for identifying candidate oncogenic processes and driver genes The approach is based on the hypothesis that cellular networks contain functional modules, and that tumors target specific modules critical to their growth Key elements in the approach include combined analysis of sequence mutations and DNA copy number alterations; use of a unified molecular interaction network consisting of both protein-protein interactions and signaling pathways; and identification and statistical assessment of network modules, ie cohesive groups of genes of interest with a higher density of interactions within groups than between groups Conclusions We confirm and extend the observation that GBM alterations tend to occur within specific functional modules, in spite of considerable patient-to-patient variation, and that two of the largest modules involve signaling via p53, Rb, PI3K and receptor protein kinases We also identify new candidate drivers in GBM, including AGAP2/CENTG1, a putative oncogene and an activator of the PI3K pathway; and, three additional significantly altered modules, including one involved in microtubule organization To facilitate the application of our network-based approach to additional cancer types, we make the method freely available as part of a software tool called NetBox

Somatic mutations of the Parkinson's disease–associated gene PARK2 in glioblastoma and other human malignancies

Abstract: Mutation of the gene PARK2, which encodes an E3 ubiquitin ligase, is the most common cause of early-onset Parkinson's disease. In a search for multisite tumor suppressors, we identified PARK2 as a frequently targeted gene on chromosome 6q25.2-q27 in cancer. Here we describe inactivating somatic mutations and frequent intragenic deletions of PARK2 in human malignancies. The PARK2 mutations in cancer occur in the same domains, and sometimes at the same residues, as the germline mutations causing familial Parkinson's disease. Cancer-specific mutations abrogate the growth-suppressive effects of the PARK2 protein. PARK2 mutations in cancer decrease PARK2's E3 ligase activity, compromising its ability to ubiquitinate cyclin E and resulting in mitotic instability. These data strongly point to PARK2 as a tumor suppressor on 6q25.2-q27. Thus, PARK2, a gene that causes neuronal dysfunction when mutated in the germline, may instead contribute to oncogenesis when altered in non-neuronal somatic cells.

Target mRNA abundance dilutes microRNA and siRNA activity

Abstract: Post-transcriptional regulation by microRNAs and siRNAs depends not only on characteristics of individual binding sites in target mRNA molecules, but also on system-level properties such as overall molecular concentrations. We hypothesize that an intracellular pool of microRNAs/siRNAs faced with a larger number of available predicted target transcripts will downregulate each individual target gene to a lesser extent. To test this hypothesis, we analyzed mRNA expression change from 178 microRNA and siRNA transfection experiments in two cell lines. Wefind that downregulation of particular genes mediated by microRNAs and siRNAs indeed varies with the total concentration of available target transcripts. We conclude that to interpret and design experiments involving gene regulation bysmall RNAs,global properties,such as target mRNA abundance,need to be considered in addition to local determinants. We propose that analysis of microRNA/siRNA targeting would benefit from a more quantitative definition, rather than simple categorization of genes as ‘target’ or ‘not a target.’ Our results are important for understanding microRNA regulation and may also have implications for siRNA design and small RNA therapeutics. Molecular Systems Biology 6: 363; published online 20 April 2010; doi:10.1038/msb.2010.24 Subject Categories: functional genomics; RNA

mRNA turnover rate limits siRNA and microRNA efficacy.

Abstract: The microRNA pathway participates in basic cellular processes and its discovery has enabled the development of si/shRNAs as powerful investigational tools and potential therapeutics. Based on a simple kinetic model of the mRNA life cycle, we hypothesized that mRNAs with high turnover rates may be more resistant to RNAi-mediated silencing. The results of a simple reporter experiment strongly supported this hypothesis. We followed this with a genome-wide scale analysis of a rich corpus of experiments, including RT–qPCR validation data for thousands of siRNAs, siRNA/microRNA overexpression data and mRNA stability data. We find that short-lived transcripts are less affected by microRNA overexpression, suggesting that microRNA target prediction would be improved if mRNA turnover rates were considered. Similarly, short-lived transcripts are more difficult to silence using siRNAs, and our results may explain why certain transcripts are inherently recalcitrant to perturbation by small RNAs.

ChiBE: interactive visualization and manipulation of BioPAX pathway models

Abstract: Summary: Representing models of cellular processes or pathways in a graphically rich form facilitates interpretation of biological observations and generation of new hypotheses. Solving biological problems using large pathway datasets requires software that can combine data mapping, querying and visualization as well as providing access to diverse data resources on the Internet. ChiBE is an open source software application that features user-friendly multi-view display, navigation and manipulation of pathway models in BioPAX format. Pathway views are rendered in a feature-rich format, and may be laid out and edited with state-of-the-art visualization methods, including compound or nested structures for visualizing cellular compartments and molecular complexes. Users can easily query and visualize pathways through an integrated Pathway Commons query tool and analyze molecular profiles in pathway context. Availability: http://www.bilkent.edu.tr/%7Ebcbi/chibe.html Contact: rt.ude.tneklib.sc@rugu Supplementary information: Supplementary data are available at Bioinformatics online.

ZIC1 Overexpression Is Oncogenic in Liposarcoma

Abstract: Liposarcomas are aggressive mesenchymal cancers with poor outcomes that exhibit remarkable histologic diversity (there are five recognized subtypes). Currently, the mainstay of therapy for liposarcoma is surgical excision because liposarcomas are often resistant to traditional chemotherapy. In light of the high mortality associated with liposarcoma and the lack of effective systemic therapy, we sought novel genomic alterations driving liposarcomagenesis that might serve as therapeutic targets. ZIC1, a critical transcription factor for neuronal development, is overexpressed in all five subtypes of liposarcoma compared with normal fat, and in liposarcoma cell lines compared with adipose-derived stem cells. Here, we show that ZIC1 contributes to the pathogenesis of liposarcoma. ZIC1 knockdown inhibits proliferation, reduces invasion, and induces apoptosis in dedifferentiated and myxoid/round cell liposarcoma cell lines, but not in either adipose-derived stem cells or in a lung cancer cell line with low ZIC1 expression. ZIC1 knockdown is associated with increased nuclear expression of p27 proteins and the downregulation of prosurvival target genes BCL2L13, JunD, Fam57A, and EIF3M. Our results show that ZIC1 expression is essential for liposarcomagenesis and that targeting ZIC1 or its downstream targets might lead to novel therapy for liposarcoma.

Discovering modulators of gene expression

Abstract: Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein-protein interactions and transcription factor-target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes.

Erratum: The BioPAX community standard for pathway data sharing (Nat. Biotechnol. (2010) 28 (935-942)

Abstract: Nat. Biotechnol. 28, 935–942 (2010); published online 09 September 2010; corrected after print 7 December 2010 In the version of this article initially published, the affiliation for Ken Fukuda was incorrect. The correct affiliation is Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.

Principle of System Balance for Drug Interactions

Abstract: Drug interactions may be explained by the extent to which a combination of drugs balances or offsets the balance of the metabolism of different cellular components.

Erratum: mRNA Turnover Rate Limits siRNA and microRNA Efficacy

Abstract: Erik Larsson*, Chris Sander and Debora Marks* 1 Computational Biology Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA and 2 Department of Systems Biology, Harvard Medical School, Boston, MA, USA * Corresponding authors. D Marks, Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Alpert 536, Boston, MA 02115, USA. Tel.: þ 1 617 953 4107; Fax: þ 1 646 422 0717; E-mail: deboramarks@gmail.com or E Larsson, Computational Biology Center, Memorial Sloan–Kettering Cancer Center, New York, NY 10065, USA. Tel.: þ 1 646 888 2610; Fax: þ 1 212 422 0717; E-mail: larsson@cbio.mskcc.org

The Role of MicroRNAs in Human Prostate Cancer

Abstract: : We have made significant progress in our analysis of genomic alterations, including those of microRNAs, in prostate cancer over the last two years. We have completed the genomic characterization of almost 250 primary and metastatic prostate cancer samples, which, in addition to microRNA expression profiles, included DNA copynumber profiling, mRNA expression, and exon-sequencing of selected genes. Using these data, we have identified microRNAs that are regulated by copy-number changes and have identified biological processes that appear to be regulated by changes in microRNA expression.

A gene expression signature associated with sensitivity to the multikinase inhibitor dasatinib: Implications for development of a noninvasive biomarker for personalized therapy based on circulating tumor cell analysis.

Abstract: 4544 Background: Src and other Src-family kinases (SFKs) promote prostate cancer (PC) cell growth, survival, invasion, migration and the transition from castration-sensitive to castration-resistant...