An International Database and Integrated Analysis Tools for the Study of Cancer Gene Expression

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An International Database and Integrated Analysis Tools for the Study of Cancer Gene Expression The Pharmacogenomics Journal (2002) 2, 156–164 2002 Nature Publishing Group All rights reserved 1470-269X/02 $25.00 www.nature.com/tpj REVIEW An international database and integrated analysis tools for the study of cancer gene expression RL Strausberg1 ABSTRACT AA Camargo2 Researchers working collaboratively in Brazil and the United States have 3 assembled an International Database of Cancer Gene Expression. Several stra- GJ Riggins tegies have been employed to generate gene expression data including CF Schaefer1 expressed sequence tags (ESTs), serial analysis of gene expression (SAGE), SJ de Souza2 and open reading-frame expressed sequence tags (ORESTES). The database LH Grouse1 contains six million gene tags that reflect the gene expression profiles in a 3 wide variety of cancerous tissues and their normal counterparts. All A Lal sequences are deposited in the public databases, GenBank and SAGEmap. A 1 KH Buetow suite of informatics tools was designed to facilitate in silico analysis of the K Boon3 gene expression datasets and are available through the NCI Cancer Genome SF Greenhut1 Anatomy Project web site (http://cgap.nci.nih.gov). 2 The Pharmacogenomics Journal (2002) 2, 156–164. doi: 10.1038/ AJG Simpson sj.tpj.6500103 1National Cancer Institute, Bethesda, MD, USA; 2Ludwig Institute for Cancer Research, Keywords: cancer; genomics; ORESTES; SAGE; CGAP; gene expression Sa˜o Paulo, Brazil; 3Duke University Medical Center, Durham, NC, USA Cancer is fundamentally a disease of the genome. The genomic changes associa- Correspondence: ted with cancer appear in many shapes and forms, from point mutations and RL Strausberg, National Cancer Institute, 31 Center Drive, Room 10A07, MSC 2580, deletions of single nucleotides to the translocation of large chromosomal seg- Bethesda, MD 20892, USA ments. Moreover, alterations within the genome, in concert with changes in the Tel: 301 451–8027 environment, modulate patterns of gene expression, at both the transcript and Fax: 301 480–4368 protein levels. The challenge to cancer research is to relate the variations in gene E-mail: RLSȰnih.gov expression with specific types of cancer. Indeed, over the past few years, impress- ive efforts have been made to read these molecular signatures of cancer, toward the goal of gaining a more comprehensive understanding of the basic mech- anisms of cancers, which will lead to improved detection, diagnosis, inter- vention, and ultimately prevention.1–9 The platform vital to support these studies is a complete catalog of human and mouse genes, with a specific focus on those genes expressed in cancer cells and their normal counterparts. In 1997, the National Cancer Institute initiated the Cancer Genome Anatomy Project (CGAP)10–13 with the aim of facilitating the interface of genomics and cancer research. The first initiative developed within CGAP was the Tumor Gene Index. The Index was focused to develop a catalog of the genes expressed in a variety of normal and cancerous tissues. Subsequently, additional components evolved within CGAP to further annotate these genes, integrate the gene data- base with the human genome sequence, and correlate these genes with chromo- somal aberrations observed in cancers. For example, the Genetic Annotation Initiative (GAI)14–15 has assembled a database of gene-based single nucleotide polymorphisms (SNPs). These SNPs were identified through analysis of the exten- sive CGAP sequence database, which represents cancerous tissues obtained from Received 18 January 2002 many different individuals. The Cancer Chromosomal Aberration Project Revised 21 February 2002 (cCAP),16,17 another CGAP program, has advanced the convergence of the human Accepted 27 February 2002 physical map and DNA sequence with the cytogenetic map through precise International database of cancer gene expression RL Strausberg et al. 157 mapping of bacterial artificial chromosomes (BACs) clones METHODS APPLIED TO CATALOG GENE EXPRESSION along all human chromosomes using fluorescent in situ The CGAP and HGCP programs have both used approaches hybridization (FISH). Many of the BACs used in this initiat- to build gene catalogs based on cDNAs derived from human ive were substrates also utilized by the public Human Gen- and mouse tumors, as well as normal tissues. The CGAP pro- ome Project. The cCAP is a component of the International ject has utilized two gene-tagging strategies to build a gene BAC Mapping Consortium Project.16 CGAP also displays the expression catalog, the expressed sequence tag (EST) wealth of information about chromosome abnormalities approach,22 and serial analysis of gene expression (SAGE).23 that occur in cancers that is cataloged in the Mitelman Data- In the traditional EST approach, clones from cDNA libraries base of Chromosome Aberrations.18 An electronic and freely are subjected to single-pass sequencing from the 5Ј and/or 3Ј accessible version of this database is available for viewing on end of the cDNAs, producing sequences of several hundred the CGAP web site (http://cgap.nci.nih.gov/). nucleotides, such that a unique identifier is assigned to each In 1998 the Ludwig Institute for Cancer Research (LICR) cDNA. The cDNA libraries are constructed using primers for in Sa˜o Paulo, Brazil, sought to catalog gene expression in first-strand synthesis that are anchored at the 3Ј transcript cancer cells through the application of a novel gene tagging end (the poly(A) sequence). The resulting cDNA molecules approach, open reading frame ESTs (ORESTES). This led to may represent the entire transcript, but are more often a partnership between the LICR and the State of Sa˜o Paulo incomplete, either because of mRNA degradation or incom- Research Foundation (FAPESP) to launch the FAPESP/LICR plete enzymatic processivity during conversion of mRNA to Human Cancer Genome Project (HGCP).19–21 cDNA. Thus, for a specific transcript, there may be multiple In 1998, when discussions between the leaders of the forms of cDNA within a library. To facilitate gene cat- CGAP and HGCP projects were initiated, the synergy aloging, CGAP has focused its sequencing effort on the 3Ј between the programs was immediately apparent and an cDNA end, starting from the poly(A) sequence. Using this informal collaboration quickly formed. The notion for the approach, it is more likely that sequences from transcripts collaboration was that the gene tagging technologies being derived from the same gene will be recognized as such employed in both projects were complementary, as were the (although alternative polyadenylation sites add compli- specific types of cancer that were being targeted. All mem- cation to cataloging gene transcripts). bers of each group were committed to contributing the gene The serial analysis of gene expression (SAGE) approach tag data to public databases maintained by the National produces very short sequence tags (usually 10 nucleotides in Center for Biotechnology Information (NCBI). This would length) located adjacent to defined restriction sites near the ensure that the worldwide community of academic and 3Ј end of the cDNA. In this approach, cDNAs are digested industrial researchers would have access to the data for with a frequently cutting restriction enzyme (often NlaIII) application to both basic and applied cancer research. to which adapters are added that encode the sequence of a Recently, a formal relationship between the Brazilian and type IIs restriction enzyme (BsmF1), such that the 10 nucleo- United States scientists resulted in the creation of an inter- tides adjacent to the NlaIII site are isolated. The individual national database of cancer gene expression. In this report, tags are concatenated to form a single DNA molecule, which the content of this cancer gene expression database, as well is then subjected to DNA sequence analysis. The power of as informatics tools for utilizing the database, are described. SAGE is two-fold. First, unlike EST sequences, which can The web sites for each of these projects, as well as the vary in both location within the transcript and sequence informatics tools, are described in Table 1. length, the SAGE tags are precisely anchored at a defined Table 1 The URLs for the CGAP and HGCP projects and descriptions of the analysis tools available on the CGAP web site Name Purpose Web site CGAP Determines the genomic and gene expression profiles of http://cgap.nci.nih.gov/ normal, precancer and cancer cells. FAPESP/LICR HGCP Supports discovery of new human genes and is pursuing http://www.ludwig.org.br/ORESTES completion of all gene coding regions. Library Finder Searches for one or more tissue-specific libraries from the http://cgap.nci.nih.gov/Tissues/LibraryFinder CGAP, MGC, SAGE, or dbEST collections. Gene Library Finds all the genes in a specific cDNA library or group of http://cgap.nci.nih.gov/Tissues/LibrarySummarizer Summarizer (GLS) libraries. cDNA xProfiler Compares gene expression between two pools of libraries. http://cgap.nci.nih.gov/Tissues/xProfiler Differential Gene Distinguishes the statistical differences in gene expression http://cgap.nci.nih.gov/Tissues/GXS Expression Displayer between two pools of libraries. (DGED) Gene Finder Finds one gene or list of genes, based on selected search http://cgap.nci.nih.gov/Genes/GeneFinder criteria. Links to a Gene Info page, including Virtual Northern, and various NCBI and NCI databases are provided. www.nature.com/tpj International database of cancer gene expression RL Strausberg et al. 158 restriction site within the transcript and are the same length. Therefore, in
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