A common and unstable copy number variant is associated with differences in Glo1 expression and anxiety-like behavior

Glyoxalase 1 (Glo1) has been implicated in anxiety-like behavior in mice and in multiple psychiatric diseases in humans. We used mouse Affymetrix exon arrays to detect copy number variants (CNV) among inbred mouse strains and thereby identified a ∼475 kb tandem duplication on chromosome 17 that includes Glo1 (30,174,390–30,651,226 Mb; mouse genome build 36). We developed a PCR-based strategy and used it to detect this duplication in 23 of 71 inbred strains tested, and in various outbred and wild-caught mice. Presence of the duplication is associated with a cis-acting expression QTL for Glo1 (LOD>30) in BXD recombinant inbred strains. However, evidence for an eQTL for Glo1 was not obtained when we analyzed single SNPs or 3-SNP haplotypes in a panel of 27 inbred strains. We conclude that association analysis in the inbred strain panel failed to detect an eQTL because the duplication was present on multiple highly divergent haplotypes. Furthermore, we suggest that non-allelic homologous recombination has led to multiple reversions to the non-duplicated state among inbred strains. We show associations between multiple duplication-containing haplotypes, Glo1 expression and anxiety-like behavior in both inbred strain panels and outbred CD-1 mice. Our findings provide a molecular basis for differential expression of Glo1 and further implicate Glo1 in anxiety-like behavior. More broadly, these results identify problems with commonly employed tests for association in inbred strains when CNVs are present. Finally, these data provide an example of biologically significant phenotypic variability in model organisms that can be attributed to CNVs.

Transcriptional profiling of the effects of 25-hydroxycholesterol on human hepatocyte metabolism and the antiviral state it conveys against the hepatitis C virus

Background

Hepatitis C virus (HCV) infection is a global health problem. A number of studies have implicated a direct role of cellular lipid metabolism in the HCV life cycle and inhibitors of the mevalonate pathway have been demonstrated to result in an antiviral state within the host cell. Transcriptome profiling was conducted on Huh-7 human hepatoma cells bearing subgenomic HCV replicons with and without treatment with 25-hydroxycholesterol (25-HC), an inhibitor of the mevalonate pathway that alters lipid metabolism, to assess metabolic determinants of pro- and antiviral states within the host cell. These data were compared with gene expression profiles from HCV-infected chimpanzees.

Results

Transcriptome profiling of Huh-7 cells treated with 25-HC gave 47 downregulated genes, 16 of which are clearly related to the mevalonate pathway. Fewer genes were observed to be upregulated (22) in the presence of 25-HC and 5 genes were uniquely upregulated in the HCV replicon bearing cells. Comparison of these gene expression profiles with data collected during the initial rise in viremia in 4 previously characterized HCV-infected chimpanzees yielded 54 overlapping genes, 4 of which showed interesting differential regulation at the mRNA level in both systems. These genes are PROX1, INSIG-1, NK4, and UBD. The expression of these genes was perturbed with siRNAs and with overexpression vectors in HCV replicon cells, and the effect on HCV replication and translation was assessed. Both PROX1 and NK4 regulated HCV replication in conjunction with an antiviral state induced by 25-hydroxycholesterol.

Conclusion

Treatment of Huh-7 cells bearing HCV replicons with 25-HC leads to the downregulation of many key genes involved in the mevalonate pathway leading to an antiviral state within the host cell. Furthermore, dysregulation of a larger subset of genes not directly related to the mevalonate pathway occurs both in 25-HC-treated HCV replicon harbouring cells as well as during the initial rise in viremia in infected chimpanzees. Functional studies of 3 of these genes demonstrates that they do not directly act as antiviral gene products but that they indirectly contribute to the antiviral state in the host cell. These genes may also represent novel biomarkers for HCV infection, since they demonstrate an outcome-specific expression profile.

Expression analysis of G Protein-Coupled Receptors in mouse macrophages

Background

Monocytes and macrophages express an extensive repertoire of G Protein-Coupled Receptors (GPCRs) that regulate inflammation and immunity. In this study we performed a systematic micro-array analysis of GPCR expression in primary mouse macrophages to identify family members that are either enriched in macrophages compared to a panel of other cell types, or are regulated by an inflammatory stimulus, the bacterial product lipopolysaccharide (LPS).

Results

Several members of the P2RY family had striking expression patterns in macrophages; P2ry6 mRNA was essentially expressed in a macrophage-specific fashion, whilst P2ry1 and P2ry5 mRNA levels were strongly down-regulated by LPS. Expression of several other GPCRs was either restricted to macrophages (e.g. Gpr84) or to both macrophages and neural tissues (e.g. P2ry12, Gpr85). The GPCR repertoire expressed by bone marrow-derived macrophages and thioglycollate-elicited peritoneal macrophages had some commonality, but there were also several GPCRs preferentially expressed by either cell population.

Conclusion

The constitutive or regulated expression in macrophages of several GPCRs identified in this study has not previously been described. Future studies on such GPCRs and their agonists are likely to provide important insights into macrophage biology, as well as novel inflammatory pathways that could be future targets for drug discovery.

Power-law-like distributions in biomedical publications and research funding

A search of the literature reveals that researchers study relatively few genes out of the total human genome.

Gene annotation, as measured by links to the biomedical literature and funded grants, is governed by a power law, indicating that researchers favor the extensive study of relatively few genes. This emphasizes the need for data-driven science to accomplish genome-wide gene annotation.

Genomewide association analysis in diverse inbred mice: power and population structure

The discovery of quantitative trait loci (QTL) in model organisms has relied heavily on the ability to perform controlled breeding to generate genotypic and phenotypic diversity. Recently, we and others have demonstrated the use of an existing set of diverse inbred mice (referred to here as the mouse diversity panel, MDP) as a QTL mapping population. The use of the MDP population has many advantages relative to traditional F(2) mapping populations, including increased phenotypic diversity, a higher recombination frequency, and the ability to collect genotype and phenotype data in community databases. However, these methods are complicated by population structure inherent in the MDP and the lack of an analytical framework to assess statistical power. To address these issues, we measured gene expression levels in hypothalamus across the MDP. We then mapped these phenotypes as quantitative traits with our association algorithm, resulting in a large set of expression QTL (eQTL). We utilized these eQTL, and specifically cis-eQTL, to develop a novel nonparametric method for association analysis in structured populations like the MDP. These eQTL data confirmed that the MDP is a suitable mapping population for QTL discovery and that eQTL results can serve as a gold standard for relative measures of statistical power.

Visual Artificial Tongue for Quantitative Metal-Cation Analysis by an Off-the-Shelf Dye Array

A chemical-probe array composed of 47 off-the-shelf dyes was prepared in solution format (New York Tongue 1: NYT-1) and was tested in the identification and quantitation of 47 cation analytes, including 44 metal ions, in addition to H(+), NH(4) (+), and tetrabutylammonium (TBA). The cation solutions were tested in a series of concentrations and the fold-change in effective absorbance was analyzed by principal-component analysis (PCA), hierarchical-cluster analysis (HCA), and nearest-neighbor decision to determine both identity and quantity of the analytes. Apart from alkali-metal ions (Na(+), K(+), Li(+), Cs(+), and Rb(+)), which behave very similarly to each other due mainly to their low response, most of the cations were clearly distinguishable at 10 mM concentration. The practical detection limit of each analyte was also determined by a sequential dilution and the nearest-neighbor decision method. In the finalized working analyte concentration range (approximately 10 mM down to 0.33 microM), by considering alkali metals as one analyte group, most of the analytes were correctly identified (99.4 %). Furthermore, the success rate at which the concentration of each analyte was correctly determined was also high (96.8 %).

The influence of cholesterol and lipid metabolism on host cell structure and hepatitis C virus replication

The hepatitis C virus (HCV) replicates on a membrane protein complex composed of viral proteins, replicating RNA, and altered cellular membranes. Small-molecule inhibitors of cellular lipid-cholesterol metabolism such as 25-hydroxycholesterol, cerulenin, lovastatin, and GGTI-286 all show a negative effect on HCV replication. Perturbation of host cell lipid and cholesterol metabolism can disrupt replication complexes by altering membranous structures where replication occurs. Changes in cholesterol and (or) lipid composition can have a general effect on membrane structure. Alternatively, metabolic changes can exert a more subtle influence over replication complexes by altering localization of host proteins through alterations in lipid anchoring. Here, we use Huh-7 cells harboring subgenomic HCV replicons to demonstrate that 25-hydroxycholesterol, cerulenin, lovastatin, and GGTI-286 do not disrupt the membranous web where replication occurs, whereas cholesterol-depleting agents such as beta-cyclodextrin do. Cellular imaging suggests that the HCV RNA can remain associated with subcellular compartments connected with replication complexes in the presence of metabolic inhibitors. Therefore, at least 2 different molecular mechanisms are possible for the inhibition of HCV replication through the modulation of cellular lipid and cholesterol metabolism.

An efficient rapid system for profiling the cellular activities of molecular libraries

Rapid quantitative methods for characterizing small molecules, peptides, proteins, or RNAs in a broad array of cellular assays would allow one to discover new biological activities associated with these molecules and also provide a more comprehensive profile of drug candidates early in the drug development process. Here we describe a robotic system, termed the automated compound profiler, capable of both propagating a large number of cell lines in parallel and assaying large collections of molecules simultaneously against a matrix of cellular assays in a highly reproducible manner. To illustrate its utility, we have characterized a set of 1,400 kinase inhibitors in a panel of 35 activated tyrosine-kinase-dependent cellular assays in dose-response format in a single experiment. Analysis of the resulting multidimensional dataset revealed subclusters of both inhibitors and kinases with closely correlated activities. The approach also identified activities for the p38 inhibitor BIRB796 and the dual src/abl inhibitor BMS-354825 and exposed the expected side activities for Glivec/STI571, including cellular inhibition of c-kit and platelet-derived growth factor receptor. This methodology provides a powerful tool for unraveling the cellular biology and molecular pharmacology of both naturally occurring and synthetic chemical diversity.

Comparative analysis of haplotype association mapping algorithms

BACKGROUND

Finding the genetic causes of quantitative traits is a complex and difficult task. Classical methods for mapping quantitative trail loci (QTL) in miceuse an F2 cross between two strains with substantially different phenotype and an interval mapping method to compute confidence intervals at each position in the genome. This process requires significant resources for breeding and genotyping, and the data generated are usually only applicable to one phenotype of interest. Recently, we reported the application of a haplotype association mapping method which utilizes dense genotyping data across a diverse panel of inbred mouse strains and a marker association algorithm that is independent of any specific phenotype. As the availability of genotyping data grows in size and density, analysis of these haplotype association mapping methods should be of increasing value to the statistical genetics community.

RESULTS

We describe a detailed comparative analysis of variations on our marker association method. In particular, we describe the use of inferred haplotypes from adjacent SNPs, parametric and nonparametric statistics, and control of multiple testing error. These results show that nonparametric methods are slightly better in the test cases we study, although the choice of test statistic may often be dependent on the specific phenotype and haplotype structure being studied. The use of multi-SNP windows to infer local haplotype structure is critical to the use of a diverse panel of inbred strains for QTL mapping. Finally, because the marginal effect of any single gene in a complex disease is often relatively small, these methods require the use of sensitive methods for controlling family-wise error. We also report our initial application of this method to phenotypes cataloged in the Mouse Phenome Database.

CONCLUSION

The use of inbred strains of mice for QTL mapping has many advantages over traditional methods. However, there are also limitations in comparison to the traditional linkage analysis from F2 and RI lines. Application of these methods requires careful consideration of algorithmic choices based on both theoretical and practical factors. Our findings suggest general guidelines, though a complete evaluation of these methods can only be performed as more genetic data in complex diseases becomes available.

Gene Expression Evolves Faster in Narrowly Than in Broadly Expressed Mammalian Genes

Despite much recent interest, it remains unclear what determines the rate of evolution of gene expression. To study this issue we develop a new measure, called "Expression Conservation Index" (ECI), to quantify the degree of tissue-expression conservation between two homologous genes. Applying this measure to a large set of gene expression data from human and mouse, we show that tissue expression tends to evolve rapidly for genes that are expressed in only a limited number of tissues, whereas tissue expression can be conserved for a long time for genes expressed in a large number of tissues. Therefore, expression breadth is an important determinant for evolutionary conservation of tissue expression. In addition, we find a rapid decrease in ECI with the synonymous divergence between duplicate genes, suggesting fast divergence in tissue expression between duplicate genes.

Large-scale profiling of Rab GTPase trafficking networks: the membrome

Rab GTPases and SNARE fusion proteins direct cargo trafficking through the exocytic and endocytic pathways of eukaryotic cells. We have used steady state mRNA expression profiling and computational hierarchical clustering methods to generate a global overview of the distribution of Rabs, SNAREs, and coat machinery components, as well as their respective adaptors, effectors, and regulators in 79 human and 61 mouse nonredundant tissues. We now show that this systems biology approach can be used to define building blocks for membrane trafficking based on Rab-centric protein activity hubs. These Rab-regulated hubs provide a framework for an integrated coding system, the membrome network, which regulates the dynamics of the specialized membrane architecture of differentiated cells. The distribution of Rab-regulated hubs illustrates a number of facets that guides the overall organization of subcellular compartments of cells and tissues through the activity of dynamic protein interaction networks. An interactive website for exploring datasets comprising components of the Rab-regulated hubs that define the membrome of different cell and organ systems in both human and mouse is available at http://www.membrome.org/.

HierS: hierarchical scaffold clustering using topological chemical graphs

An exhaustive ring-based algorithm, HierS, has been developed in order to provide an intuitive approach to compound clustering for analyzing high-throughput screening results. The recursive algorithm rapidly identifies all possible ring-delimited substructures within a set of compounds. Molecules are grouped by shared ring substructures (scaffolds) so that common scaffolds obtain higher membership. Once all of the scaffolds for a set of compounds are identified, the hierarchical structural relationships between the scaffold structures are established. The complex network of hierarchical relationships is then utilized to navigate compounds in a structurally directed fashion. When the scaffold hierarchy is traversed, over-represented structural features can be rapidly identified so that excess compounds that contain them can be removed without significantly impacting the structural diversity landscape of the compound set. Furthermore, the removed compounds can provide the opportunity to follow-up on active compounds that had previously been discarded because of practical limitations on follow-up capacity. A Web-based interface has been developed that incorporates this algorithm in order to allow for an interactive analysis. In addition, biological data are coupled to scaffolds by the inclusion of activity histograms, which indicate how the compounds in each scaffold class performed in previous high-throughput screening campaigns.

Uncovering regulatory pathways that affect hematopoietic stem cell function using 'genetical genomics'

We combined large-scale mRNA expression analysis and gene mapping to identify genes and loci that control hematopoietic stem cell (HSC) function. We measured mRNA expression levels in purified HSCs isolated from a panel of densely genotyped recombinant inbred mouse strains. We mapped quantitative trait loci (QTLs) associated with variation in expression of thousands of transcripts. By comparing the physical transcript position with the location of the controlling QTL, we identified polymorphic cis-acting stem cell genes. We also identified multiple trans-acting control loci that modify expression of large numbers of genes. These groups of coregulated transcripts identify pathways that specify variation in stem cells. We illustrate this concept with the identification of candidate genes involved with HSC turnover. We compared expression QTLs in HSCs and brain from the same mice and identified both shared and tissue-specific QTLs. Our data are accessible through WebQTL, a web-based interface that allows custom genetic linkage analysis and identification of coregulated transcripts.

Use of a dense single nucleotide polymorphism map for in silico mapping in the mouse

Rapid expansion of available data, both phenotypic and genotypic, for multiple strains of mice has enabled the development of new methods to interrogate the mouse genome for functional genetic perturbations. In silico mapping provides an expedient way to associate the natural diversity of phenotypic traits with ancestrally inherited polymorphisms for the purpose of dissecting genetic traits. In mouse, the current single nucleotide polymorphism (SNP) data have lacked the density across the genome and coverage of enough strains to properly achieve this goal. To remedy this, 470,407 allele calls were produced for 10,990 evenly spaced SNP loci across 48 inbred mouse strains. Use of the SNP set with statistical models that considered unique patterns within blocks of three SNPs as an inferred haplotype could successfully map known single gene traits and a cloned quantitative trait gene. Application of this method to high-density lipoprotein and gallstone phenotypes reproduced previously characterized quantitative trait loci (QTL). The inferred haplotype data also facilitates the refinement of QTL regions such that candidate genes can be more easily identified and characterized as shown for adenylate cyclase 7.

Applications of a rat multiple tissue gene expression data set

With the sequencing and assembly of the rat genome comes the difficult task of assigning functions to genes. Tissue localization of gene expression gives some information about the potential role of a gene in physiology. Various examples of the utility of multiple tissue gene expression data sets are illustrated here. First, we highlight their use in finding genes that might play an important role in a particular tissue on the basis of exclusive expression in that tissue or coexpression with a gene or genes with known function. Second, we show how this data might be used to explain known phenotypic differences between strains. Third, we show how expression patterns of genes in a genomic interval might identify candidate genes in quantitative trait loci (QTL) mapping studies. Lastly, we show how multiple tissue and species data can help researchers prioritize follow up studies to microarray experiments. All of these applications of multiple tissue gene expression data sets will play a role in functionally annotating the rat genome.

A gene atlas of the mouse and human protein-encoding transcriptomes

The tissue-specific pattern of mRNA expression can indicate important clues about gene function. High-density oligonucleotide arrays offer the opportunity to examine patterns of gene expression on a genome scale. Toward this end, we have designed custom arrays that interrogate the expression of the vast majority of protein-encoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues. The resulting data set provides the expression patterns for thousands of predicted genes, as well as known and poorly characterized genes, from mice and humans. We have explored this data set for global trends in gene expression, evaluated commonly used lines of evidence in gene prediction methodologies, and investigated patterns indicative of chromosomal organization of transcription. We describe hundreds of regions of correlated transcription and show that some are subject to both tissue and parental allele-specific expression, suggesting a link between spatial expression and imprinting.

Genome-wide analysis of CREB target genes reveals a core promoter requirement for cAMP responsiveness

We have employed a hidden Markov model (HMM) based on known cAMP responsive elements to search for putative CREB target genes. The best scoring sites were positionally conserved between mouse and human orthologs, suggesting that this parameter can be used to enrich for true CREB targets. Target validation experiments revealed a core promoter requirement for transcriptional induction via CREB; TATA-less promoters were unresponsive to cAMP compared to TATA-containing genes, despite comparable binding of CREB to both sets of genes in vivo. Indeed, insertion of a TATA box motif rescued cAMP responsiveness on a TATA-less promoter. These results illustrate a mechanism by which subsets of target genes for a transcription factor are differentially regulated depending on core promoter configuration.

Genomic analysis of the host response to hepatitis C virus infection

We have examined the progression of hepatitis C virus (HCV) infections by gene expression analysis of liver biopsies in acutely infected chimpanzees that developed persistent infection, transient viral clearance, or sustained clearance. Both common responses and outcome-specific changes in expression were observed. All chimpanzees showed gene expression patterns consistent with an IFN-alpha response that correlated with the magnitude and duration of infection. Transient and sustained viral clearance were uniquely associated with induction of IFN-gamma-induced genes and other genes involved in antigen processing and presentation and the adaptive immune response. During the early stages of infection, host genes involved in lipid metabolism were also differentially regulated. We also show that drugs that affect these biosynthetic pathways can regulate HCV replication in HCV replicon systems. Our results reveal genome-wide transcriptional changes that reflect the establishment, spread, and control of infection, and they reveal potentially unique antiviral programs associated with clearance of HCV infection.

Large scale molecular analysis identifies genes with altered expression in salivary adenoid cystic carcinoma

Salivary gland cancers comprise a heterogeneous group of neoplasms whose biological and clinical characteristics differ considerably from those of mucosal squamous cell carcinomas of the head and neck. One of the most common subtypes, adenoid cystic carcinoma (ACC), is notable for its myoepithelial differentiation, proclivity for hematogenous spread, and slow but progressive clinical course. The molecular alterations that underlie its development and progression are poorly characterized. Here we used oligonucleotide microarray analysis to survey the expression of 8920 different human genes in 15 ACCs, one ACC cell line, and five normal major salivary glands. We observed expression of genes indicative of myoepithelial differentiation, as expected, including those whose protein products are components of basement membranes and extracellular matrix. Other genes that were highly ranked for their expression in ACC were those encoding the transcription factors SOX4 and AP-2 gamma, the latter of which also was overexpressed in ACC relative to 175 other carcinomas from 10 anatomical sites that we had previously profiled. Additional genes, which were highly expressed in ACC compared to the other carcinomas, included casein kinase 1, epsilon and frizzled-7, both members of the Wnt/beta-catenin signaling pathway. Our study documents for the first time the diverse spectrum of genes overexpressed in ACC and highlights gene products and pathways that in the future might be exploited as therapeutic targets for this cancer, which up until now, has shown limited response to chemotherapeutic approaches.

Gene expression during the priming phase of liver regeneration after partial hepatectomy in mice

Understanding the gene-expression patterns during liver regeneration may help to reveal how regenerative processes are initiated and controlled as well as shed new light onto processes that lead to liver disease. Using high-density oligonucleotide arrays, we have examined the gene-expression program in the livers of mice after partial hepatectomy. A time course was constructed for gene expression between 0 and 4 h after partial hepatectomy, corresponding to the priming phase of liver regeneration. The genomic program for liver regeneration involves transcription-factor generation, stress and inflammatory responses, cytoskeletal and extracellular matrix modification, and regulation of cell-cycle entry. The genome-wide changes that are observed provide a detailed and comprehensive map of the initial priming stage of liver regeneration.

Genomic effects of polyamide/DNA interactions on mRNA expression

Here we characterize the biological activity of a hairpin polyamide 1 that inhibits binding of the minor-groove transcription factor LEF-1, constitutively expressed in colon cancers. Genome-wide analysis of mRNA expression in DLD1 colon cancer cells treated with 1 reveals that a limited number of genes are affected; the most significant changes correspond to genes related to cell cycle, signaling, and proteolysis rather than the anticipated WNT signaling pathway. Treated cells display increased doubling time and hypersensitivity to DNA damage that most likely results from downregulation of DNA-damage checkpoint genes, including YWAE (14-3-3epsilon protein) and DDIT3. Promoter analyses on a genomic level revealed numerous potential polyamide binding sites and multiple possible mechanisms for transcriptional antagonism, underscoring the utility of gene expression profiling in understanding the effects of polyamides on transcription at the cellular level.

Coordinated transcription of key pathways in the mouse by the circadian clock

In mammals, circadian control of physiology and behavior is driven by a master pacemaker located in the suprachiasmatic nuclei (SCN) of the hypothalamus. We have used gene expression profiling to identify cycling transcripts in the SCN and in the liver. Our analysis revealed approximately 650 cycling transcripts and showed that the majority of these were specific to either the SCN or the liver. Genetic and genomic analysis suggests that a relatively small number of output genes are directly regulated by core oscillator components. Major processes regulated by the SCN and liver were found to be under circadian regulation. Importantly, rate-limiting steps in these various pathways were key sites of circadian control, highlighting the fundamental role that circadian clocks play in cellular and organismal physiology.

Large-scale analysis of the human and mouse transcriptomes

High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations.

Synthesis and biological evaluation of myoseverin derivatives: microtubule assembly inhibitors

Myoseverin, a trisubstituted purine, inhibits microtubule assembly in vitro, interferes with normal mitotic spindle assembly, and arrests the cell cycle in mitosis in U937 cells. We synthesized a variety of myoseverin derivatives and screened them for inhibition of spindle assembly in Xenopus egg extracts and for microtubule disassembly in vitro. Selected compounds were tested against 60 cancer cell lines at the National Cancer Institute as possible anticancer drug candidates.

Molecular classification of human carcinomas by use of gene expression signatures

Classification of human tumors according to their primary anatomical site of origin is fundamental for the optimal treatment of patients with cancer. Here we describe the use of large-scale RNA profiling and supervised machine learning algorithms to construct a first-generation molecular classification scheme for carcinomas of the prostate, breast, lung, ovary, colorectum, kidney, liver, pancreas, bladder/ureter, and gastroesophagus, which collectively account for approximately 70% of all cancer-related deaths in the United States. The classification scheme was based on identifying gene subsets whose expression typifies each cancer class, and we quantified the extent to which these genes are characteristic of a specific tumor type by accurately and confidently predicting the anatomical site of tumor origin for 90% of 175 carcinomas, including 9 of 12 metastatic lesions. The predictor gene subsets include those whose expression is typical of specific types of normal epithelial differentiation, as well as other genes whose expression is elevated in cancer. This study demonstrates the feasibility of predicting the tissue origin of a carcinoma in the context of multiple cancer classes.

Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer

Detection, treatment, and prediction of outcome for men with prostate cancer increasingly depend on a molecular understanding of tumor development and behavior. We characterized primary prostate cancer by monitoring expression levels of more than 8900 genes in normal and malignant tissues. Patterns of gene expression across tissues revealed a precise distinction between normal and tumor samples, and revealed a striking group of about 400 genes that were overexpressed in tumor tissues. We ranked these genes according to their differential expression in normal and cancer tissues by selecting for highly and specifically overexpressed genes in the majority of cancers with correspondingly low or absent expression in normal tissues. Several such genes were identified that act within a variety of biochemical pathways and encode secreted molecules with diagnostic potential, such as the secreted macrophage inhibitory cytokine, MIC-1. Other genes, such as fatty acid synthase, encode enzymes known as drug targets in other contexts, which suggests new therapeutic approaches.

Destabilization of Ca2+-free gelsolin may not be responsible for proteolysis in Familial Amyloidosis of Finnish Type

Mutations at position 187 in secreted gelsolin enable aberrant proteolysis at the 172-173 and 243-244 amide bonds, affording the 71-residue amyloidogenic peptide deposited in Familial Amyloidosis of Finnish Type (FAF). Thermodynamic comparisons of two different domain 2 constructs were carried out to study possible effects of the mutations on proteolytic susceptibility. In the construct we consider to be most representative of domain 2 in the context of the full-length protein (134-266), the D187N FAF variant is slightly destabilized relative to wild type (WT) under the conditions of urea denaturation, but exhibits a T(m) identical to WT. The D187Y variant is less stable to intermediate urea concentrations and exhibits a T(m) that is estimated to be approximately 5 degrees C lower than WT (pH 7.4, Ca(2+)-free). Although the thermodynamic data indicate that the FAF mutations may slightly destabilize domain 2, these changes are probably not sufficient to shift the native to denatured state equilibrium enough to enable the proteolysis leading to FAF. Biophysical data indicate that these two FAF variants may have different native state structures and possibly different pathways of amyloidosis.

Docking molecules by families to increase the diversity of hits in database screens: computational strategy and experimental evaluation

Molecular docking programs screen chemical databases for novel ligands that fit protein binding sites. When one compound fits the site well, close analogs typically do the same. Therefore, many of the compounds that are found in such screens resemble one another. This reduces the variety and novelty of the compounds suggested. In an attempt to increase the diversity of docking hit lists, the Available Chemicals Directory was grouped into families of related structures. All members of every family were docked and scored, but only the best scoring molecule of a high-ranking family was allowed in the hit list. The identity and scores of the other members of these families were recorded as annotations to the best family member, but they were not independently ranked. This family-based docking method was compared with molecule-by-molecule docking in screens against the structures of thymidylate synthase, dihydrofolate reductase (DHFR), and the cavity site of the mutant T4 lysozyme Leu99 --> Ala (L99A). In each case, the diversity of the hit list increased, and more families of known ligands were found. To investigate whether the newly identified hits were sensible, we tested representative examples experimentally for binding to L99A and DHFR. Of the six compounds tested against L99A, five bound to the internal cavity. Of the seven compounds tested against DHFR, six inhibited the enzyme with apparent K(i) values between 0.26 and 100 microM. The segregation of potential ligands into families of related molecules is a simple technique to increase the diversity of candidates suggested by database screens. The general approach should be applicable to most docking methods. Proteins 2001;42:279-293.