Mouse models of human cancer web-based resources.

The Mouse Models of Human Cancers Consortium (MMHCC) is a collaborative program designed to derive and characterize mouse models of human malignancies. To enhance information and resource exchange among the MMHCC investigators and other cancer research scientists, the NCI Center for Bioinformatics (NCICB, http://ncicb.nci.nih.gov/) has developed web-based resources that are freely available to the cancer research community. These resources include a website (http://emice.nci.nih.gov) and databases for cancer models (http://cancermodels.nci.nih.gov) and cancer images (http://cancerimages.nci.nih.gov).

An international database and integrated analysis tools for the study of cancer gene expression.

Researchers working collaboratively in Brazil and the United States have assembled an International Database of Cancer Gene Expression. Several strategies have been employed to generate gene expression data including expressed sequence tags (ESTs), serial analysis of gene expression (SAGE), and open reading-frame expressed sequence tags (ORESTES). The database contains six million gene tags that reflect the gene expression profiles in a wide variety of cancerous tissues and their normal counterparts. All sequences are deposited in the public databases, GenBank and SAGEmap. A suite of informatics tools was designed to facilitate in silico analysis of the gene expression datasets and are available through the NCI Cancer Genome Anatomy Project web site (http://cgap.nci.nih.gov).

Molecular characteristics of non-small cell lung cancer.

We used hierarchical clustering to examine gene expression profiles generated by serial analysis of gene expression (SAGE) in a total of nine normal lung epithelial cells and non-small cell lung cancers. Separation of normal and tumor, as well as histopathological subtypes, was evident by using the 3,921 most abundant transcript tags. This distinction remained when only 115 highly differentially expressed tags were used. Furthermore, these 115 transcript tags clustered into groups suggestive of the unique biological and pathological features of the different tissues examined. Adenocarcinomas were characterized by high-level expression of small airway-associated or immunologically related proteins, whereas squamous cell carcinomas overexpressed genes involved in cellular detoxification or antioxidation. The messages of two p53-regulated genes, p21(WAF1/CIP1) and 14-3-3final sigma, were consistently underexpressed in the adenocarcinomas, suggesting that the p53 pathway itself might be compromised in this cancer type. Gene expression patterns observed by SAGE were consistent with results obtained by quantitative real-time PCR or cDNA array analyses by using a total of 43 lung tumor and normal samples. Thus, although derived from only a few tissue libraries, gene expression profiles obtained by using SAGE most likely represent an unbiased yet distinctive molecular signature for the most common forms of human lung cancer.

Glutathione S-transferase genotypes and stomach cancer in a population-based case-control study in Warsaw, Poland.

Glutathione S-transferases are important in the detoxification of a wide range of human carcinogens. Previous studies have shown inconsistent associations between the GSTT1 and GSTM1 null genotypes and stomach cancer risk. We investigated the relationship between these and related genotypes and stomach cancer risk in a population-based case-control study in Warsaw, Poland, where stomach cancer incidence and mortality rates are among the highest in Europe. DNA from blood samples was available for 304 stomach cancer patients and 427 control subjects. We observed a 1.48-fold increased risk for stomach cancer (95% confidence interval 0.97-2.25) in patients with the GSTT1 null genotype but no evidence of increased risk associated with the GSTM1, GSTM3 or GSTP1 genotypes. Furthermore, the stomach cancer risk associated with the GSTT1 null genotype varied by age at diagnosis, with odds ratios of 3.85, 1.91, 1.78 and 0.59 for those diagnosed at ages less than 50, 50-59, 60-69 and 70 years or older, respectively (P trend = 0.01). This was due to a shift in the GSTT1 genotype distribution across age groups among stomach cancer patients only. These results suggest that the GSTT1 null genotype may be associated with increased risk of stomach cancer.

In silico analysis of cancer through the Cancer Genome Anatomy Project.

The Cancer Genome Anatomy Project (CGAP) was designed and implemented to provide public datasets, material resources and informatics tools to serve as a platform to support the elucidation of the molecular signatures of cancer. This overview of CGAP describes the status of this effort to develop resources based on gene expression, polymorphism identification and chromosome aberrations, and we describe a variety of analytical tools designed to facilitate in silico analysis of these datasets.

Collection of genomic DNA from adults in epidemiological studies by buccal cytobrush and mouthwash.

Blood samples are an excellent source of large amounts of genomic DNA. However, alternative sources are often needed in epidemiological studies because of difficulties in obtaining blood samples. This report evaluates the buccal cytobrush and alcohol-containing mouthwash protocols for collecting DNA by mail. Several DNA extraction techniques are also evaluated. The study was conducted in two phases. In phase 1, we compared cytobrush and mouthwash samples collected by mail in two different epidemiological studies: (a) cytobrush samples (n = 120) from a United States case-control study of breast cancer; and (b) mouthwash samples (n = 40) from a prospective cohort of male United States farmers. Findings from phase 1 were confirmed in phase 2, where we randomized cytobrush (n = 28) and mouthwash (n = 25) samples among participants in the breast cancer study to directly compare both collection methods. The median human DNA yield determined by hybridization with a human DNA probe from phenol-chloroform extracts was 1.0 and 1.6 microg/2 brushes for phases 1 and 2, respectively, and 27.5 and 16.6 microg/mouthwash sample for phases 1 and 2, respectively. Most (94-100%) mouthwash extracts contained high molecular weight DNA (>23 kb), in contrast to 55-61% of the brush extracts. PCR success rates for amplification of beta-globin gene fragments (268, 536, and 989 bp) were similar for cytobrush and mouthwash phenol-chloroform extracts (range, 94.4-100%). Also, we obtained high success rates in determining the number of CAG repeats in the androgen receptor gene, characterizing tetranucleotide microsatellites in six gene loci, and screening for mutations in the BRCA1/2 genes in a subset of phenol-chloroform DNA extracts. Relative to DNA extracted by phenol-chloroform from cytobrush samples, DNA extracted by NaOH had lower molecular weight, decreased PCR success rates for most assays performed, and unreliably high spectrophotometer readings for DNA yields. In conclusion, although DNA isolated from either mouthwash or cytobrush samples collected by mail from adults is adequate for a wide range of PCR-based assays, a single mouthwash sample provides substantially larger amounts and higher molecular weight DNA than two cytobrush samples.

The use of common genetic polymorphisms to enhance the epidemiologic study of environmental carcinogens.

Overwhelming evidence indicates that environmental exposures, broadly defined, are responsible for most cancer. There is reason to believe, however, that relatively common polymorphisms in a wide spectrum of genes may modify the effect of these exposures. We discuss the rationale for using common polymorphisms to enhance our understanding of how environmental exposures cause cancer and comment on epidemiologic strategies to assess these effects, including study design, genetic and statistical analysis, and sample size requirements. Special attention is given to sources of potential bias in population studies of gene--environment interactions, including exposure and genotype misclassification and population stratification (i.e., confounding by ethnicity). Nevertheless, by merging epidemiologic and molecular approaches in the twenty-first century, there will be enormous opportunities for unraveling the environmental determinants of cancer. In particular, studies of genetically susceptible subgroups may enable the detection of low levels of risk due to certain common exposures that have eluded traditional epidemiologic methods. Further, by identifying susceptibility genes and their pathways of action, it may be possible to identify previously unsuspected carcinogens. Finally, by gaining a more comprehensive understanding of environmental and genetic risk factors, there should emerge new clinical and public health strategies aimed at preventing and controlling cancer.

A new cancer genome anatomy project web resource for the community.

The National Cancer Institute's Cancer Genome Anatomy Project (CGAP) is developing publicly accessible information, technology, and material resources that provide a platform for the interface of cancer research and genomics. CGAP's efforts have focused toward (1) building and annotating catalogues of genes expressed during cancer development, (2) identifying polymorphisms in those genes, and (3) developing resources for the molecular characterization of cancer-related chromosomal aberrations. To date, CGAP has produced more than 1,000,000 expressed sequence tags, approximately 3,300,000 serial analysis of gene expression tags, and identified more than 10,000 human gene-based single-nucleotide polymorphisms. To enhance access to these datasets by the research community, a new Cancer Genome Project web site (http://cgap.nci.nih.gov/) is being introduced. The web site includes genomic data for humans and mice, including transcript sequence, gene expression patterns, single-nucleotide polymorphisms, clone resources, and cytogenetic information. Descriptions of the methods and reagents used in deriving the CGAP datasets are also provided. An extensive suite of informatics tools facilitates queries and analysis of the CGAP data by the community. One of the newest features of the CGAP web site is an electronic version of the Mitelman Database of Chromosome Aberrations in Cancer.

Human hepatocellular carcinoma is characterized by a highly consistent pattern of genomic imbalances, including frequent loss of 16q23.1-24.1.

Comparative genomic hybridization (CGH) analysis was used to identify chromosomal imbalances in 52 human primary hepatocellular carcinomas (HCCs). The most prominent changes were gains of part or all of chromosome arms 8q (83% of cases) and 1q (73%) and loss of 16q (63%). Other commonly overrepresented sites were 5p, 7q, and Xq. Recurrent sites of DNA sequence amplification included 8q23--24 (five cases) and 11q13--14 (four cases). Other frequently underrepresented sites were 4q, 8p, 16p, and 17p. Taken collectively, these findings and data from other CGH studies of HCCs define a subset of chromosome segments that are consistently over- or underrepresented and highlight sites of putative oncogenes and tumor suppressor genes, respectively, involved in hepatocellular oncogenesis. Loss of heterozygosity analysis with a panel of polymorphic microsatellite markers distributed along 16q defined a minimal region of chromosomal loss at 16q23.1--24.1, suggesting that this region harbors a tumor suppressor gene whose loss/inactivation may contribute to the pathogenesis of many HCCs.

High-throughput development and characterization of a genomewide collection of gene-based single nucleotide polymorphism markers by chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

We describe here a system for the rapid identification, assay development, and characterization of gene-based single nucleotide polymorphisms (SNPs). This system couples informatics tools that mine candidate SNPs from public expressed sequence tag resources and automatically designs assay reagents with detection by a chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry platform. As a proof of concept of this system, a genomewide collection of reagents for 9,115 gene-based SNP genetic markers was rapidly developed and validated. These data provide preliminary insights into patterns of polymorphism in a genomewide collection of gene-based polymorphisms.

Construction of reference genetic maps.

This unit details the specialized resources and procedures used for constructing reference genetic maps. Construction of such maps in humans represents a subset of the linkage analysis problem. Objectives include the addition of a new locus to an established map, development of a detailed map of loci in a localized area, and construction of de novo maps. Conceptually, the procedures for updating a reference map through the addition of a subset of new loci are similar to those used in establishing linkage for a disease locus. However, construction of new maps of multiple loci is most efficiently accomplished using different family resources that permit the use of accumulated typing resources and alternative, highly efficient statistical methods.

Expression-based genetic/physical maps of single-nucleotide polymorphisms identified by the cancer genome anatomy project.

SNPs (Single-Nucleotide Polymorphisms), the most common DNA variant in humans, represent a valuable resource for the genetic analysis of cancer and other illnesses. These markers may be used in a variety of ways to investigate the genetic underpinnings of disease. In gene-based studies, the correlations between allelic variants of genes of interest and particular disease states are assessed. An extensive collection of SNP markers may enable entire molecular pathways regulating cell metabolism, growth, or differentiation to be analyzed by this approach. In addition, high-resolution genetic maps based on SNPs will greatly facilitate linkage analysis and positional cloning. The National Cancer Institute's CGAP-GAI (Cancer Genome Anatomy Project Genetic Annotation Initiative) group has identified 10,243 SNPs by examining publicly available EST (Expressed Sequence Tag) chromatograms. More than 6800 of these polymorphisms have been placed on expression-based integrated genetic/physical maps. In addition to a set of comprehensive SNP maps, we have produced maps containing single nucleotide polymorphisms in genes expressed in breast, colon, kidney, liver, lung, or prostate tissue. The integrated maps, a SNP search engine, and a Java-based tool for viewing candidate SNPs in the context of EST assemblies can be accessed via the CGAP-GAI web site (http://cgap.nci.nih.gov/GAI/). Our SNP detection tools are available to the public for noncommercial use.

Reliable identification of large numbers of candidate SNPs from public EST data.

High-resolution genetic analysis of the human genome promises to provide insight into common disease susceptibility. To perform such analysis will require a collection of high-throughput, high-density analysis reagents. We have developed a polymorphism detection system that uses public-domain sequence data. This detection system is called the single nucleotide polymorphism pipeline (SNPpipeline). The analytic core of the SNPpipeline is composed of three components: PHRED, PHRAP and DEMIGLACE. PHRED and PHRAP are components of a sequence analysis suite developed to perform the semi-automated analysis required for large-scale genomes (provided courtesy of P. Green). Using these informatics tools, which examine redundant raw expressed sequence tag (EST) data, we have identified more than 3,000 candidate single-nucleotide polymorphisms (SNPs). Empiric validation studies of a set of 192 candidates indicate that 82% identify variation in a sample of ten Centre d'Etudes Polymorphism Humain (CEPH) individuals. Our results suggest that existing sequence resources may serve as a valuable source for identifying genetic variation.

Constitutional genetic variation at the human aromatase gene (Cyp19) and breast cancer risk.

The activity of the aromatase enzyme, which converts androgens into oestrogens and has a major role in regulating oestrogen levels in the breast, is thought to be a contributing factor in the development of breast cancer. We undertook this study to assess the role of constitutional genetic variation in the human aromatase gene (Cyp19) in the development of this disease. Our genotyping of 348 cases with breast cancer and 145 controls (all Caucasian women) for a published tetranucleotide repeat polymorphism at intron 4 of the Cyp19 gene revealed the presence of six common and two rare alleles. Contingency table analysis revealed a significant difference in allelic distribution between cases and controls (chi2 5df = 13.52, P = 0.019). The allele measuring 171 bp was over-represented in cases; of 14 individuals homozygous for this allele, 13 were cases. These individuals had a higher incidence of cancer in family members and an earlier age at diagnosis than other cases. In sequencing Cyp19's coding exons and regulatory regions, we discovered a perfect association between a silent polymorphism (G-->A at Val80) and the high-risk genotype. Our conclusion is that constitutional genetic variation at the Cyp19 locus is associated with the risk of developing breast cancer, with the 171-bp allele serving as the high-risk allele.

Discovery of cancer susceptibility genes: study designs, analytic approaches, and trends in technology.

Determining the genetic causes of cancers has immense public health benefits, ranging from prevention to earlier detection and treatment of disease. Although a number of cancer susceptibility genes have been successfully identified, design and analytic issues remain that challenge the current paradigm of gene discovery. Some examples are the definition and measurement of cancer phenotype, the use of intermediate end points, the choice of sample (e.g., affected relative pairs versus large extended pedigrees), the choice of analytic method [e.g., parametric logarithm of the odds (LOD) score method versus model-free methods], and the influence of gene-environment interaction on linkage analysis. Furthermore, association methods, based on either the traditional case-control study design or family-based controls, are popular choices to evaluate candidate genes or screen for linkage disequilibrium. Finally, the study design and analytic methods for gene discovery are determined to some extent by what genomic technology is feasible within the laboratory. Many of the main issues related to gene discovery, as well as trends in genomic technology that will impact on gene discovery, are discussed from the perspective of their strengths and weaknesses, pointing to areas in need of further work.

Asthma and bronchial hyperresponsiveness linked to the XY long arm pseudoautosomal region.

We examined the long arm XY pseudoautosomal region for linkage to asthma, serum IgE, and bronchial hyperresponsiveness. In 57 Caucasian families multipoint nonparametric analyses provide evidence for linkage between DXYS154 and bronchial hyperresponsiveness (P = 0.000057) or asthma (P = 0.00065). This genomic region is approximately 320 kb in size and contains the interleukin-9 receptor gene. These results suggest that a gene controlling asthma and bronchial hyperresponsiveness maybe located in this region and that the interleukin-9 receptor is a potential candidate.