Showing papers by "Chris Sander published in 2007"

The microRNA.org resource: targets and expression

Abstract: MicroRNA.org (http://www.microrna.org) is a comprehensive resource of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. Using an improved graphical interface, a user can explore (i) the set of genes that are potentially regulated by a particular microRNA, (ii) the implied cooperativity of multiple microRNAs on a particular mRNA and (iii) microRNA expression profiles in various tissues. To facilitate future updates and development, the microRNA.org database structure and software architecture is flexibly designed to incorporate new expression and target discoveries. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation.

Integration of biological networks and gene expression data using Cytoscape

Abstract: Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.

Cellular cofactors affecting hepatitis C virus infection and replication

Abstract: Recently identified hepatitis C virus (HCV) isolates that are infectious in cell culture provide a genetic system to evaluate the significance of virus-host interactions for HCV replication. We have completed a systematic RNAi screen wherein siRNAs were designed that target 62 host genes encoding proteins that physically interact with HCV RNA or proteins or belong to cellular pathways thought to modulate HCV infection. This includes 10 host proteins that we identify in this study to bind HCV NS5A. siRNAs that target 26 of these host genes alter infectious HCV production >3-fold. Included in this set of 26 were siRNAs that target Dicer, a principal component of the RNAi silencing pathway. Contrary to the hypothesis that RNAi is an antiviral pathway in mammals, as has been reported for subgenomic HCV replicons, siRNAs that target Dicer inhibited HCV replication. Furthermore, siRNAs that target several other components of the RNAi pathway also inhibit HCV replication. MicroRNA profiling of human liver, human hepatoma Huh-7.5 cells, and Huh-7.5 cells that harbor replicating HCV demonstrated that miR-122 is the predominant microRNA in each environment. miR-122 has been previously implicated in positively regulating the replication of HCV genotype 1 replicons. We find that 2'-O-methyl antisense oligonucleotide depletion of miR-122 also inhibits HCV genotype 2a replication and infectious virus production. Our data define 26 host genes that modulate HCV infection and indicate that the requirement for functional RNAi for HCV replication is dominant over any antiviral activity this pathway may exert against HCV.

Determinants of protein function revealed by combinatorial entropy optimization

Abstract: We use a new algorithm (combinatorial entropy optimization [CEO]) to identify specificity residues and functional subfamilies in sets of proteins related by evolution. Specificity residues are conserved within a subfamily but differ between subfamilies, and they typically encode functional diversity. We obtain good agreement between predicted specificity residues and experimentally known functional residues in protein interfaces. Such predicted functional determinants are useful for interpreting the functional consequences of mutations in natural evolution and disease.

Gene expression profiling of liposarcoma identifies distinct biological types/subtypes and potential therapeutic targets in well-differentiated and dedifferentiated liposarcoma.

Abstract: Classification of liposarcoma into three biological types encompassing five subtypes, (a) well-differentiated/dedifferentiated, (b) myxoid/round cell, and (c) pleomorphic, based on morphologic features and cytogenetic aberrations, is widely accepted. However, diagnostic discordance remains even among expert sarcoma pathologists. We sought to develop a more systematic approach to liposarcoma classification based on gene expression analysis and to identify subtype-specific differentially expressed genes that may be involved in liposarcoma genesis/progression and serve as potential therapeutic targets. A classifier based on gene expression profiling was able to distinguish between liposarcoma subtypes, lipoma, and normal fat samples. A 142-gene predictor of tissue class was derived to automatically determine the class of an independent validation set of lipomatous samples and shows the feasibility of liposarcoma classification based entirely on gene expression monitoring. Differentially expressed genes for each liposarcoma subtype compared with normal fat were used to identify histology-specific candidate genes with an in-depth analysis of signaling pathways important to liposarcoma pathogenesis and progression in the well-differentiated/dedifferentiated subset. The activation of cell cycle and checkpoint pathways in well-differentiated/dedifferentiated liposarcoma provides several possible novel therapeutic strategies with MDM2 serving as a particularly promising target. We show that Nutlin-3a, an antagonist of MDM2, preferentially induces apoptosis and growth arrest in dedifferentiated liposarcoma cells compared with normal adipocytes. These results support the development of a clinical trial with MDM2 antagonists for liposarcoma subtypes which overexpress MDM2 and show the promise of using this expression dataset for new drug discovery in liposarcoma.

CancerGenes: a gene selection resource for cancer genome projects

Abstract: The genome sequence framework provided by the human genome project allows us to precisely map human genetic variations in order to study their association with disease and their direct effects on gene function. Since the description of tumor suppressor genes and oncogenes several decades ago, both germ-line variations and somatic mutations have been established to be important in cancer-in terms of risk, oncogenesis, prognosis and response to therapy. The Cancer Genome Atlas initiative proposed by the NIH is poised to elucidate the contribution of somatic mutations to cancer development and progression through the re-sequencing of a substantial fraction of the total collection of human genes-in hundreds of individual tumors and spanning several tumor types. We have developed the CancerGenes resource to simplify the process of gene selection and prioritization in large collaborative projects. CancerGenes combines gene lists annotated by experts with information from key public databases. Each gene is annotated with gene name(s), functional description, organism, chromosome number, location, Entrez Gene ID, GO terms, InterPro descriptions, gene structure, protein length, transcript count, and experimentally determined transcript control regions, as well as links to Entrez Gene, COSMIC, and iHOP gene pages and the UCSC and Ensembl genome browsers. The user-friendly interface provides for searching, sorting and intersection of gene lists. Users may view tabulated results through a web browser or may dynamically download them as a spreadsheet table. CancerGenes is available at http://cbio.mskcc.org/cancergenes.

From bytes to bedside: data integration and computational biology for translational cancer research.

Abstract: Major advances in genome science and molecular technologies provide new opportunities at the interface between basic biological research and medical practice. The unprecedented completeness, accuracy, and volume of genomic and molecular data necessitate a new kind of computational biology for translational research. Key challenges are standardization of data capture and communication, organization of easily accessible repositories, and algorithms for integrated analysis based on heterogeneous sources of information. Also required are new ways of using complementary clinical and biological data, such as computational methods for predicting disease phenotype from molecular and genetic profiling. New combined experimental and computational methods hold the promise of more accurate diagnosis and prognosis as well as more effective prevention and therapy.

Matrix Metalloproteinase-9 (MMP-9) polymorphisms in patients with cutaneous malignant melanoma

Abstract: Cutaneous Malignant Melanoma causes over 75% of skin cancer-related deaths, and it is clear that many factors may contribute to the outcome. Matrix Metalloproteinases (MMPs) play an important role in the degradation and remodeling of the extracellular matrix and basement membrane that, in turn, modulate cell division, migration and angiogenesis. Some polymorphisms are known to influence gene expression, protein activity, stability, and interactions, and they were shown to be associated with certain tumor phenotypes and cancer risk. We tested seven polymorphisms within the MMP-9 gene in 1002 patients with melanoma in order to evaluate germline genetic variants and their association with progression and known risk factors of melanoma. The polymorphisms were selected based on previously published reports and their known or potential functional relevance using in-silico methods. Germline DNA was then genotyped using pyrosequencing, melting temperature profiles, heteroduplex analysis, and fragment size analysis. We found that reference alleles were present in higher frequency in patients who tend to sunburn, have family history of melanoma, higher melanoma stage, intransit metastasis and desmoplastic melanomas among others. However, after adjustment for age, sex, phenotypic index, moles, and freckles only Q279R, P574R and R668Q had significant associations with intransit metastasis, propensity to tan/sunburn and primary melanoma site. This study does not provide strong evidence for further investigation into the role of the MMP-9 SNPs in melanoma progression.