Robert M. Stephens

DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists

All tools in the DAVID Bioinformatics Resources aim to provide functional interpretation of large lists of genes derived from genomic studies. The newly updated DAVID Bioinformatics Resources consists of the DAVID Knowledgebase and five integrated, web-based functional annotation tool suites: the DAVID Gene Functional Classification Tool, the DAVID Functional Annotation Tool, the DAVID Gene ID Conversion Tool, the DAVID Gene Name Viewer and the DAVID NIAID Pathogen Genome Browser. The expanded DAVID Knowledgebase now integrates almost all major and well-known public bioinformatics resources centralized by the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of diverse gene/protein identifiers and annotation terms from a variety of public bioinformatics databases. For any uploaded gene list, the DAVID Resources now provides not only the typical gene-term enrichment analysis, but also new tools and functions that allow users to condense large gene lists into gene functional groups, convert between gene/protein identifiers, visualize many-genes-to-many-terms relationships, cluster redundant and heterogeneous terms into groups, search for interesting and related genes or terms, dynamically view genes from their lists on bio-pathways and more. With DAVID (http://david.niaid.nih.gov), investigators gain more power to interpret the biological mechanisms associated with large gene lists.

Genomic Profiling of MicroRNA and Messenger RNA Reveals Deregulated MicroRNA Expression in Prostate Cancer

MicroRNAs are small noncoding RNAs that regulate the expression of protein-coding genes. To evaluate the involvement of microRNAs in prostate cancer, we determined genome-wide expression of microRNAs and mRNAs in 60 primary prostate tumors and 16 nontumor prostate tissues. The mRNA analysis revealed that key components of microRNA processing and several microRNA host genes, e.g., MCM7 and C9orf5, were significantly up-regulated in prostate tumors. Consistent with these findings, tumors expressed the miR-106b-25 cluster, which maps to intron 13 of MCM7, and miR-32, which maps to intron 14 of C9orf5, at significantly higher levels than nontumor prostate. The expression levels of other microRNAs, including a number of miR-106b-25 cluster homologues, were also altered in prostate tumors. Additional differences in microRNA abundance were found between organ-confined tumors and those with extraprostatic disease extension. Lastly, we found evidence that some microRNAs are androgen-regulated and that tumor microRNAs influence transcript abundance of protein-coding target genes in the cancerous prostate. In cell culture, E2F1 and p21/WAF1 were identified as targets of miR-106b, Bim of miR-32, and exportin-6 and protein tyrosine kinase 9 of miR-1. In summary, microRNA expression becomes altered with the development and progression of prostate cancer. Some of these microRNAs regulate the expression of cancer-related genes in prostate cancer cells.

Trk receptors use redundant signal transduction pathways involving SHC and PLC-γ1 to mediate NGF responses

In response to NGF, the Trk receptor tyrosine kinase forms a complex with SHC, a protein that couples receptor tyrosine kinases to p21ras. Complex formation between Trk and SHC, SHC tyrosine phosphorylation, and association of SHC with Grb2 were mediated by autophosphorylation at Y490 in Trk [sequence: see text]. To determine the role of SHC and other Trk substrates in NGF signaling, Trk receptors with mutations in Y490 and Y785 (the PLC-gamma 1 association site) were introduced into PC12nnr5 cells. NGF treatment of PC12nnr5 cells expressing Trk with mutations in either substrate-binding site resulted in normal neurite outgrowth and Erk1 activity and tyrosine phosphorylation. However, PC12nnr5 cells expressing Trk with mutations at both sites failed to stably extend neurites and efficiently induce Erk1 activity and tyrosine phosphorylation in response to NGF. We postulate that Trk receptors can activate Erk1 by either SHC- or PLC-gamma 1-dependent signaling pathways. These results suggest a model whereby Trk receptors utilize at least partially redundant signal transduction pathways to mediate NGF responses.

RTCGD: retroviral tagged cancer gene database

Retroviral insertional mutagenesis in mouse hematopoietic tumors provides a potent cancer gene discovery tool in the post-genome-sequence era. To manage multiple high-throughput insertional mutagenesis screening projects, we developed the Retroviral Tagged Cancer Gene Database (RTCGD; http://RTCGD.ncifcrf.gov). A sequence analysis pipeline determines the genomic position of each retroviral integration site cloned from a mouse tumor, the distance between it and the nearest candidate disease gene(s) and its orientation with respect to the candidate gene(s). The pipeline also identifies genomic regions that are targets of retroviral integration in more than one tumor (common integration sites, CISs) and are thus likely to encode a disease gene. Users can search the database using a specified gene symbol, chromosome number or tumor model to identify both CIS genes and unique viral integration sites or compare the integration sites cloned by different laboratories using different models. As a default setting, users first review the CIS Lists and then Clone Lists. CIS Lists describe CISs and their candidate disease genes along with links to other public databases and clone lists. Clone Lists describe the viral integration site clones along with the tumor model and tumor type from which they were cloned, candidate disease gene(s), genomic position and orientation of the integrated provirus with respect to the candidate gene(s). It also provides a pictorial view of the genomic location of each integration site relative to neighboring genes and markers. Researchers can identify integrations of interest and compare their results with those for multiple tumor models and tumor types using RTCGD.

DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

BackgroundDue to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis.DescriptionThe DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner.ConclusionThe DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://david.abcc.ncifcrf.gov/knowledgebase/.

Tumor Immunobiological Differences in Prostate Cancer between African-American and European-American Men

The incidence and mortality rates of prostate cancer are significantly higher in African-American men when compared with European-American men. We tested the hypothesis that differences in tumor biology contribute to this survival health disparity. Using microarray technology, we obtained gene expression profiles of primary prostate tumors resected from 33 African-American and 36 European-American patients. These tumors were matched on clinical variables. We also evaluated 18 nontumor prostate tissues from seven African-American and 11 European-American patients. The resulting datasets were analyzed for expression differences on the gene and pathway level comparing African-American with European-American patients. Our analysis revealed a significant number of genes, e.g., 162 transcripts at a false-discovery rate of <or=5% to be differently expressed between African-American and European-American patients. Using a disease association analysis, we identified a common relationship of these transcripts with autoimmunity and inflammation. These findings were corroborated on the pathway level with numerous differently expressed genes clustering in immune response, stress response, cytokine signaling, and chemotaxis pathways. Several known metastasis-promoting genes, including autocrine mobility factor receptor, chemokine (C-X-C motif) receptor 4, and matrix metalloproteinase 9, were more highly expressed in tumors from African-Americans than European-Americans. Furthermore, a two-gene tumor signature that accurately differentiated between African-American and European-American patients was identified. This finding was confirmed in a blinded analysis of a second sample set. In conclusion, the gene expression profiles of prostate tumors indicate prominent differences in tumor immunobiology between African-American and European-American men. The profiles portray the existence of a distinct tumor microenvironment in these two patient groups.

DAVID-WS

Summary: The database for annotation, visualization and integrated discovery (DAVID), which can be freely accessed at http://david.abcc.ncifcrf.gov/, is a web-based online bioinformatics resource that aims to provide tools for the functional interpretation of large lists of genes/proteins. It has been used by researchers from more than 5000 institutes worldwide, with a daily submission rate of ∼1200 gene lists from ∼400 unique researchers, and has been cited by more than 6000 scientific publications. However, the current web interface does not support programmatic access to DAVID, and the uniform resource locator (URL)-based application programming interface (API) has a limit on URL size and is stateless in nature as it uses URL request and response messages to communicate with the server, without keeping any state-related details. DAVID-WS (web service) has been developed to automate user tasks by providing stateful web services to access DAVID programmatically without the need for human interactions. Availability: The web service and sample clients (written in Java, Perl, Python and Matlab) are made freely available under the DAVID License at http://david.abcc.ncifcrf.gov/content.jsp?file=WS.html. Contact: xiaoli.jiao@nih.gov; rlempicki@nih.gov

Extracting Biological Meaning from Large Gene Lists with DAVID

High‐throughput genomics screening studies, such as microarray, proteomics, etc., often result in large, “interesting” gene lists, ranging in size from hundreds to thousands of genes. Given the challenges of functionally interpreting such large gene lists, it is necessary to incorporate bioinformatics tools in the analysis. DAVID is a Web‐based application that provides a high‐throughput and integrative gene functional annotation environment to systematically extract biological themes behind large gene lists. High‐throughput gene functional analysis with DAVID will provide important insights that allow investigators to understand the biological themes within their given genomic study. This unit will describe step‐by‐step procedures to use DAVID tools, as well as a brief rationale and key parameters in the DAVID analysis. Curr. Protoc. Bioinform. 27:13.11.1‐13.11.13.

Human Glioma Growth Is Controlled by MicroRNA-10b

MicroRNA (miRNA) expression profiling studies revealed a number of miRNAs dysregulated in the malignant brain tumor glioblastoma. Molecular functions of these miRNAs in gliomagenesis are mainly unknown. We show that inhibition of miR-10b, a miRNA not expressed in human brain and strongly upregulated in both low-grade and high-grade gliomas, reduces glioma cell growth by cell-cycle arrest and apoptosis. These cellular responses are mediated by augmented expression of the direct targets of miR-10b, including BCL2L11/Bim, TFAP2C/AP-2γ, CDKN1A/p21, and CDKN2A/p16, which normally protect cells from uncontrolled growth. Analysis of The Cancer Genome Atlas expression data set reveals a strong positive correlation between numerous genes sustaining cellular growth and miR-10b levels in human glioblastomas, while proapoptotic genes anticorrelate with the expression of miR-10b. Furthermore, survival of glioblastoma patients expressing high levels of miR-10 family members is significantly reduced in comparison to patients with low miR-10 levels, indicating that miR-10 may contribute to glioma growth in vivo. Finally, inhibition of miR-10b in a mouse model of human glioma results in significant reduction of tumor growth. Altogether, our experiments validate an important role of miR-10b in gliomagenesis, reveal a novel mechanism of miR-10b-mediated regulation, and suggest the possibility of its future use as a therapeutic target in gliomas.

Genetic loci associated with delayed clearance of Plasmodium falciparum following artemisinin treatment in Southeast Asia

The recent emergence of artemisinin-resistant Plasmodium falciparum malaria in western Cambodia could threaten prospects for malaria elimination. Identification of the genetic basis of resistance would provide tools for molecular surveillance, aiding efforts to contain resistance. Clinical trials of artesunate efficacy were conducted in Bangladesh, in northwestern Thailand near the Myanmar border, and at two sites in western Cambodia. Parasites collected from trial participants were genotyped at 8,079 single nucleotide polymorphisms (SNPs) using a P. falciparum-specific SNP array. Parasite genotypes were examined for signatures of recent positive selection and association with parasite clearance phenotypes to identify regions of the genome associated with artemisinin resistance. Four SNPs on chromosomes 10 (one), 13 (two), and 14 (one) were significantly associated with delayed parasite clearance. The two SNPs on chromosome 13 are in a region of the genome that appears to be under strong recent positive selection in Cambodia. The SNPs on chromosomes 10 and 13 lie in or near genes involved in postreplication repair, a DNA damage-tolerance pathway. Replication and validation studies are needed to refine the location of loci responsible for artemisinin resistance and to understand the mechanism behind it; however, two SNPs on chromosomes 10 and 13 may be useful markers of delayed parasite clearance in surveillance for artemisinin resistance in Southeast Asia.