Thiol-ene enabled detection of thiophosphorylated kinase substrates

Protein phosphorylation is a ubiquitous posttranslational modification that regulates cell signaling in both prokaryotes and eukaryotes. Although the study of phosphorylation has made great progress, several major hurdles remain, including the difficulty of the assignment of endogenous substrates to a discrete kinase and of global phosphoproteomics investigations. We have developed a novel chemical strategy for detecting phosphorylated proteins. This method utilizes adenosine 5'-O-(3-thiotriphosphate) (ATPγS), which results in the transfer of a thiophosphate moiety by a kinase to its substrate(s). This group can subsequently be employed as a nucleophilic handle to promote protein detection. To selectively label thiophosphorylated proteins, cellular thiols (e.g., cysteine-containing proteins) must first be blocked. Most common cysteine-capping strategies rely upon the nucleophilicity of the sulfur group and would therefore also modify the thiophosphate moiety. We hypothesized that the radical-mediated thiol-ene reaction, however, would be selective for cysteine over thiophosphorylated amino acids due to the differences in the electronics and pKa values between these groups. Here, we report rapid and specific tagging of thiophosphorylated proteins in vitro following chemoselective thiol capping using the thiol-ene reaction.

Taming of a superbase for selective phenol desilylation and natural product isolation

Hydroxyl moieties are highly prevalent in natural products. We previously reported a chemoselective strategy for enrichment of hydroxyl-functionalized molecules by formation of a silyl ether bond to a resin. To generate smaller pools of molecules for analysis, we developed cleavage conditions to promote stepwise release of phenolic silyl ethers followed by aliphatic silyl ethers with a "tamed" version of the superbase 1,1,3,3-tetramethylguanadine. We demonstrate this as a general strategy for selective deprotection of phenolic silyl ethers under neutral conditions at room temperature.

Selective estrogen receptor modulators and pharmacogenomic variation in ZNF423 regulation of BRCA1 expression: individualized breast cancer prevention

The selective estrogen receptor modulators (SERM) tamoxifen and raloxifene can reduce the occurrence of breast cancer in high-risk women by 50%, but this U.S. Food and Drug Administration-approved prevention therapy is not often used. We attempted to identify genetic factors that contribute to variation in SERM breast cancer prevention, using DNA from the NSABP P-1 and P-2 breast cancer prevention trials. An initial discovery genome-wide association study identified common single-nucleotide polymorphisms (SNP) in or near the ZNF423 and CTSO genes that were associated with breast cancer risk during SERM therapy. We then showed that both ZNF423 and CTSO participated in the estrogen-dependent induction of BRCA1 expression, in both cases with SNP-dependent variation in induction. ZNF423 appeared to be an estrogen-inducible BRCA1 transcription factor. The OR for differences in breast cancer risk during SERM therapy for subjects homozygous for both protective or both risk alleles for ZNF423 and CTSO was 5.71.

Abstract 2271: Metformin pharmacogenomics: A genome-wide associate study to identify genetic and epigenetic biomarkers involved in metformin response

BACKGROUND Metformin, a widely used anti-diabetic drug, is being considered as a highly promising agent for treatment and prevention of many types of cancer, including breast cancer. Although the exact mechanism of action of metformin is unknown, it is thought that metformin is an AMPK activator. To better individualize metformin therapy and explore additional underlying molecular mechanism associated with metformin action, we conducted a metformin pharmacogenomic study using 266 genomic data-enriched lymphoblastoid cell lines (LCLs).

METHODS Genome-wide microarray data were generated for all LCLs, including 1.3 million SNPs, 485K DNA methylation probes and 54K mRNA expression probe sets. Metformin cytotoxicity assay was performed using MTS assay. Genome-wide association (GWA) analyses and integrated analyses using all the genomic data and metformin cytotoxicity (IC50 value) were performed to identify top candidate genes for functional validation in breast cancer cell lines, MDA-MB 231 and Hs578T, using siRNA screening approach. Further mechanistic study was performed to investigate the role of candidates in regulation of AMPK activity.

RESULTS GWA analyses in LCLs identified 198 mRNA expression probe sets and 210 DNA methylation probes associated with metformin IC50 with p-value <10-4, respectively. Analysis of 1.3 million SNPs found 12 loci (a region containing at least 1 SNP of p-value <10-5 and 1 SNP of p-value <10-3 within 50kb) that were associated with metformin IC50. Integrated SNP loci-mRNA expression-IC50 analysis indicated that the SNP loci on chromosome 16 was associated with metformin IC50 through a trans-regulation of expression of 7 genes with p-value <10-4. Integrated methylation-mRNA expression-IC50 analysis showed that 15 DNA methylation probes in 6 genes were associated with metformin IC50 through both cis- and trans-regulation of expression of 48 genes with p-value <10-4, including 4 methylation probes in 3 of those 6 genes that were cis-correlated with its own gene expression. Ingenuity pathway analysis of top 62 candidate genes identified four major pathways and 55 genes within those pathways were selected for functional validation in breast cancer cell lines. The knockdown experiment showed that down regulation of 25 genes significantly altered metformin sensitivity in MDA-MB231, and 14 of them also showed the same effect in Hs578T. Preliminary mechanistic experiment indicated that knockdown of 7 genes significantly reduced AMPK activity in MDA-MB231 and 3 of them had same effect in Hs578T.

CONCLUSIONS GWAS using a genomic data-enriched LCL model system, together with functional validation in breast cancer cell lines, could help us to identify novel genetic and epigenetic biomarkers involved in metformin response and help us to better understand the mechanisms of metformin in cancer treatment.

Citation Format: Nifang Niu, Xianglin Tan, Brooke L. Fridley, Daniel J. Schaid, Ryan P. Abo, Anthony Batzler, Erin E. Carlson, Gregory Jenkins, Sebastian Moran, Holger Andrea Heyn, Manel Esteller Badosa, Liewei Wang. Metformin pharmacogenomics: A genome-wide associate study to identify genetic and epigenetic biomarkers involved in metformin response. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2271. doi:10.1158/1538-7445.AM2013-2271

TSPYL5 SNPs: association with plasma estradiol concentrations and aromatase expression

We performed a discovery genome-wide association study to identify genetic factors associated with variation in plasma estradiol (E2) concentrations using DNA from 772 postmenopausal women with estrogen receptor (ER)-positive breast cancer prior to the initiation of aromatase inhibitor therapy. Association analyses showed that the single nucleotide polymorphisms (SNP) (rs1864729) with the lowest P value (P = 3.49E-08), mapped to chromosome 8 near TSPYL5. We also identified 17 imputed SNPs in or near TSPYL5 with P values < 5E-08, one of which, rs2583506, created a functional estrogen response element. We then used a panel of lymphoblastoid cell lines (LCLs) stably transfected with ERα with known genome-wide SNP genotypes to demonstrate that TSPYL5 expression increased after E2 exposure of cells heterozygous for variant TSPYL5 SNP genotypes, but not in those homozygous for wild-type alleles. TSPYL5 knockdown decreased, and overexpression increased aromatase (CYP19A1) expression in MCF-7 cells, LCLs, and adipocytes through the skin/adipose (I.4) promoter. Chromatin immunoprecipitation assay showed that TSPYL5 bound to the CYP19A1 I.4 promoter. A putative TSPYL5 binding motif was identified in 43 genes, and TSPYL5 appeared to function as a transcription factor for most of those genes. In summary, genome-wide significant SNPs in TSPYL5 were associated with elevated plasma E2 in postmenopausal breast cancer patients. SNP rs2583506 created a functional estrogen response element, and LCLs with variant SNP genotypes displayed increased E2-dependent TSPYL5 expression. TSPYL5 induced CYP19A1 expression and that of many other genes. These studies have revealed a novel mechanism for regulating aromatase expression and plasma E2 concentrations in postmenopausal women with ER(+) breast cancer.

Mechanistic insight into inhibition of two-component system signaling

Two-component signal transduction systems (TCSs) are commonly used by bacteria to couple environmental stimuli to adaptive responses. Targeting the highly conserved kinase domain in these systems represents a promising strategy for the design of a broad-spectrum antibiotic; however, development of such compounds has been marred by an incomplete understanding of the conserved binding features within the active site that could be exploited in molecule design. Consequently, a large percentage of the available TCS inhibitors demonstrate poor target specificity and act via multiple mechanisms, with aggregation of the kinase being the most notable. In order to elucidate the mode of action of some of these compounds, molecular modeling was employed to dock a suite of molecules into the ATP-binding domain of several histidine kinases. This effort revealed a key structural feature of the domain that is likely interacting with several known inhibitors and is also highly conserved. Furthermore, generation of several simplified scaffolds derived from a reported inhibitor and characterization of these compounds using activity assays, protein aggregation studies and saturation transfer differential (STD) NMR suggests that targeting of this protein feature may provide a basis for the design of ATP-competitive compounds.

Selective penicillin-binding protein imaging probes reveal substructure in bacterial cell division

The peptidoglycan cell wall is a common target for antibiotic therapy, but its structure and assembly are only partially understood. Peptidoglycan synthesis requires a suite of penicillin-binding proteins (PBPs), the individual roles of which are difficult to determine because each enzyme is often dispensable for growth perhaps due to functional redundancy. To address this challenge, we sought to generate tools that would enable selective examination of a subset of PBPs. We designed and synthesized fluorescent and biotin derivatives of the β-lactam-containing antibiotic cephalosporin C. These probes facilitated specific in vivo labeling of active PBPs in both Bacillus subtilis PY79 and an unencapsulated derivative of D39 Streptococcus pneumoniae. Microscopy and gel-based analysis indicated that the cephalosporin C-based probes are more selective than BOCILLIN-FL, a commercially available penicillin V analogue, which labels all PBPs. Dual labeling of live cells performed by saturation of cephalosporin C-susceptible PBPs followed by tagging of the remaining PBP population with BOCILLIN-FL demonstrated that the two sets of PBPs are not co-localized. This suggests that even PBPs that are located at a particular site (e.g., septum) are not all intermixed, but rather that PBP subpopulations are discretely localized. Accordingly, the Ceph C probes represent new tools to explore a subset of PBPs and have the potential to facilitate a deeper understand of the roles of this critical class of proteins.

Chemoselective hydroxyl group transformation: an elusive target

The selective reaction of one functional group in the presence of others is not a trivial task. A noteworthy amount of research has been dedicated to the chemoselective reaction of the hydroxyl moiety. This group is prevalent in many biologically important molecules including natural products and proteins. However, targeting the hydroxyl group is difficult for many reasons including its relatively low nucleophilicity in comparison to other ubiquitous functional groups such as amines and thiols. Additionally, many of the developed chemoselective reactions cannot be used in the presence of water. Despite these complications, chemoselective transformation of the hydroxyl moiety has been utilized in the synthesis of complex natural product derivatives, the reaction of tyrosine residues in proteins, the isolation of natural products and is the mechanism of action of myriad drugs. Here, methods for selective targeting of this group, as well as applications of several devised methods, are described.

Activity-based probe for histidine kinase signaling

Bacterial two-component systems (TCSs) are signaling pathways composed of two proteins: a histidine kinase (HK) and a response regulator (RR). Upon stimulation, the HK autophosphorylates at a conserved histidine. The phosphoryl group is subsequently transferred to an aspartate on an RR, eliciting an adaptive response, often up- or downregulation of gene expression. TCS signaling controls many functions in bacteria, including development, virulence, and antibiotic resistance, making the proteins involved in these systems potential therapeutic targets. Efficient methods for the profiling of HKs are currently lacking. For direct readout of HK activity, we sought to design a probe that enables detection of the phosphotransfer event; however, analysis of the phosphohistidine species is made difficult by the instability of the P-N bond. We anticipated that use of a γ-thiophosphorylated ATP analogue, which would yield a thiophosphorylated histidine intermediate, could overcome this challenge. We determined that the fluorophore-conjugated probe, BODIPY-FL-ATPγS, labels active HK proteins and is competitive for the ATP binding site. This activity-based probe provides a new strategy for analysis of TCSs and other HK-mediated processes and will facilitate both functional studies and inhibitor identification.

Siloxyl ether functionalized resins for chemoselective enrichment of carboxylic acids

Although the carboxylic acid moiety is prevalent in many biologically produced molecules, including natural products and proteins, methods to chemoselectively target this functional group have remained elusive. Generally, strategies that utilize carboxylate nucleophilicity also promote reactions with other nucleophiles such as amines and hydroxyls. A reagent was sought to facilitate the selective isolation of carboxylic acid containing compounds from complex mixtures. Here, the development of siloxyl ether functionalized solid supports is described.

Evaluation of CYP2D6 and efficacy of tamoxifen and raloxifene in women treated for breast cancer chemoprevention: results from the NSABP P1 and P2 clinical trials

BACKGROUND

Controversy exists regarding the association between CYP2D6 enzyme activity and tamoxifen effectiveness in the adjuvant treatment of invasive breast cancer; however, this association in the primary prevention of breast cancer is unknown.

METHODS

We conducted a nested case-control study in the context of the NSABP P1 and P2 prevention trials to determine the impact of CYP2D6 genotype, CYP2D6 inhibitor use, and metabolizer status (CYP2D6 genotype combined with CYP2D6 inhibitor use), on breast cancer events. Women who developed breast cancer (both noninvasive and invasive) while on 5 years of selective estrogen receptor modulators therapy (cases) were matched to controls free of breast cancer. Comprehensive CYP2D6 genotyping was conducted for alleles associated with absent (*3, *4, *5, and *6), reduced (*10, *17, and *41), and increased (*1XN and *2XN) enzyme activity. Information regarding the use of CYP2D6 inhibitors was recorded.

RESULTS

A total of 591 cases were matched to 1,126 controls and DNA was genotyped in more than 97%. In patients treated with tamoxifen, there was no association of CYP2D6 genotype [OR (extensive/poor metabolizer): 0.90; 95% CI: 0.46-1.74, P = 0.74), use of a potent CYP2D6 inhibitor (OR 0.92; 95% CI: 0.575-1.486), or CYP2D6 metabolizer status (OR 1.03; 95% CI: 0.669-1.607) with breast cancer occurrence. Likewise, there was no association between any CYP2D6 metabolism parameter with breast cancer events in raloxifene-treated patients.

CONCLUSION

In the NSABP P1 and P2 clinical trials, alterations in CYP2D6 metabolism are not associated with either tamoxifen or raloxifene efficacy.

Chemoselective enrichment for natural products discovery

Natural products account for a significant proportion of modern day therapeutic agents. However, the discovery of novel compounds is hindered by the isolation process, which often relies upon extraction and chromatographic separation techniques. These methods, which are dependent upon the physicochemical properties of the compounds, have a limited ability to both purify and concentrate the minor components of a biological extract. We have devised an isolation strategy based upon an orthogonal chemical feature, namely, functional group composition. Development of a functional group-targeted method is expected to achieve exceptional resolution given the large number of distinct moieties present in natural product extracts. Here, we describe the generation of controllably reversible covalent enrichment tags for the chemoselective isolation of alcohol-containing natural products from complex mixtures.

A general glycomimetic strategy yields non-carbohydrate inhibitors of DC-SIGN

Shikimic acid can be transformed into monovalent and multivalent glycomimetics that target different members of the C-type lectin class, including DC-SIGN, a dendritic cell lectin that facilitates HIV transmission.

Natural products as chemical probes

Natural products have evolved to encompass a broad spectrum of chemical and functional diversity. It is this diversity, along with their structural complexity, that enables nature's small molecules to target a nearly limitless number of biological macromolecules and to often do so in a highly selective fashion. Because of these characteristics, natural products have seen great success as therapeutic agents. However, this vast pool of compounds holds much promise beyond the development of future drugs. These features also make them ideal tools for the study of biological systems. Recent examples of the use of natural products and their derivatives as chemical probes to explore biological phenomena and assemble biochemical pathways are presented here.

Estimation of genotype relative risks from pedigree data by retrospective likelihoods

Pedigrees collected for linkage studies are a valuable resource that could be used to estimate genetic relative risks (RRs) for genetic variants recently discovered in case-control genome wide association studies. To estimate RRs from highly ascertained pedigrees, a pedigree "retrospective likelihood" can be used, which adjusts for ascertainment by conditioning on the phenotypes of pedigree members. We explore a variety of approaches to compute the retrospective likelihood, and illustrate a Newton-Raphson method that is computationally efficient particularly for single nucleotide polymorphisms (SNPs) modeled as log-additive effect of alleles on the RR. We also illustrate, by simulations, that a naïve "composite likelihood" method that can lead to biased RR estimates, mainly by not conditioning on the ascertainment process-or as we propose-the disease status of all pedigree members. Applications of the retrospective likelihood to pedigrees collected for a prostate cancer linkage study and recently reported risk-SNPs illustrate the utility of our methods, with results showing that the RRs estimated from the highly ascertained pedigrees are consistent with odds ratios estimated in case-control studies. We also evaluate the potential impact of residual correlations of disease risk among family members due to shared unmeasured risk factors (genetic or environmental) by allowing for a random baseline risk parameter. When modeling only the affected family members in our data, there was little evidence for heterogeneity in baseline risks across families.

Genome-wide linkage analyses of hereditary prostate cancer families with colon cancer provide further evidence for a susceptibility locus on 15q11-q14

The search for susceptibility loci in hereditary prostate cancer (HPC) is challenging because of locus and disease heterogeneity. One approach to reduce disease heterogeneity is to stratify families on the basis of the occurrence of multiple cancer types. This method may increase the power for detecting susceptibility loci, including those with pleiotropic effects. We have completed a genome-wide SNP linkage analysis of 96 HPC families, each of which has one or more first-degree relatives with colon cancer (CCa), and further analyzed the subset of families with two or more CCa cases (n = 27). When only a prostate cancer (PCa) phenotype was considered to be affected, we observed suggestive evidence for linkage (LOD ≥1.86) at 15q14, 18q21 and 19q13 in all families, and at 1p32 and 15q11-q14 in families with two or more CCa cases. When both the PCa and CCa phenotypes were considered affected, suggestive evidence for linkage was observed at 11q25, 15q14 and 18q21 in all families, and at 1q31, 11q14 and 15q11-14 in families with two or more CCa cases. The strongest linkage signal was identified at 15q14 when both PCa and CCa phenotypes were considered to be affected in families with two or more CCa cases (recessive HLOD = 3.88). These results provide further support for the presence of HPC susceptibility loci on chromosomes 11q14, 15q11-q14 and 19q13 and highlight loci at 1q31, 11q, 15q11-14 and 18q21 as having possible pleiotropic effects. This study shows the benefit of using a comprehensive family cancer history to create more genetically homogenous subsets of HPC families for linkage analyses.

Dense genome-wide SNP linkage scan in 301 hereditary prostate cancer families identifies multiple regions with suggestive evidence for linkage

The search for susceptibility loci in hereditary prostate cancer (HPC) has proven challenging due to genetic and disease heterogeneity. Multiple risk loci have been identified to date, however few loci have been replicated across independent linkage studies. In addition, most previous analyses have been hampered by the relatively poor information content provided by microsatellite scans. To overcome these issues, we have performed linkage analyses on members of 301 HPC families genotyped using the Illumina SNP linkage panel IVb. The information content for this panel, averaged over all pedigrees and all chromosomes, was 86% (range 83-87% over chromosomes). Analyses were also stratified on families according to disease aggressiveness, age at diagnosis and number of affected individuals to achieve more genetically homogeneous subsets. Suggestive evidence for linkage was identified at 7q21 (HLOD = 1.87), 8q22 (KCLOD = 1.88) and 15q13-q14 (HLOD = 1.99) in 289 Caucasian families, and nominal evidence for linkage was identified at 2q24 (LOD = 1.73) in 12 African American families. Analysis of more aggressive prostate cancer phenotypes provided evidence for linkage to 11q25 (KCLOD = 2.02), 15q26 (HLOD = 1.99) and 17p12 (HLOD = 2.13). Subset analyses according to age at diagnosis and number of affected individuals also identified several regions with suggestive evidence for linkage, including a KCLOD of 2.82 at 15q13-q14 in 128 Caucasian families with younger ages at diagnosis. The results presented here provide further evidence for a prostate cancer susceptibility locus on chromosome 15q and demonstrate the power of utilizing high information content SNP scans in combination with homogenous collections of large prostate cancer pedigrees.

Searching for epistasis and linkage heterogeneity by correlations of pedigree-specific linkage scores

Recognizing that multiple genes are likely responsible for common complex traits, statistical methods are needed to rapidly screen for either interacting genes or locus heterogeneity in genetic linkage data. To achieve this, some investigators have proposed examining the correlation of pedigree linkage scores between pairs of chromosomal regions, because large positive correlations suggest interacting loci and large negative correlations suggest locus heterogeneity (Cox et al. [1999]; Maclean et al. [1993]). However, the statistical significance of these extreme correlations has been difficult to determine due to the autocorrelation of linkage scores along chromosomes. In this study, we provide novel solutions to this problem by using results from random field theory, combined with simulations to determine the null correlation for syntenic loci. Simulations illustrate that our new methods control the Type-I error rates, so that one can avoid the extremely conservative Bonferroni correction, as well as the extremely time-consuming permutational method to compute P-values for non-syntenic loci. Application of these methods to prostate cancer linkage studies illustrates interpretation of results and provides insights into the impact of marker information content on the resulting statistical correlations, and ultimately the asymptotic P-values.

Enrichment tags for enhanced-resolution profiling of the polar metabolome

The field of metabolomics aims to develop and apply methods to study the full complement of endogenous small molecules in biological systems. One of the major challenges in metabolomics is obtaining adequate resolution of compounds with similar physicochemical properties. The resolution of polar metabolites can be exceptionally problematic as these compounds are often poorly retained with reverse phase matrices. Here, we describe an advanced chemoselective tagging strategy to enrich and profile highly polar metabolites. Metabolite-reactive tags were appended with a hydrophobic p-Cl-phenylalanine residue, which conferred enhanced retention and resolution upon labeled small-molecules. Notably, the increased resolution afforded by hydrophobic tags minimized overlap in tandem mass spectrometry profiles for polar metabolites, thereby facilitating their structure determination in complex biological samples. Additionally, the chlorine atom of the tag permitted the discrimination of tagged metabolites from background peaks (i.e., false positives) and the discovery of metabolites that possess multiple copies of the same functional group. These studies designate chemoselective small-molecule tags as versatile tools for enriching and profiling challenging fractions of the metabolome.

Strong Evidence of a Genetic Determinant for Mammographic Density, a Major Risk Factor for Breast Cancer

Increased mammographic density (MD), the proportion of dense tissue visible on a mammogram, is a strong risk factor for breast cancer, common in the population and clusters in families. We conducted the first genome-wide linkage scan to identify genes influencing MD. DNA was obtained from 889 relatives (756 women, 133 men) from 89 families. Percent MD was estimated on 618 (82%) female family members using a validated computer-assisted thresholding method. The genome-wide scan included 403 microsatellite DNA markers with an average spacing of 9 cM. Fine mapping of a region of chromosome 5p (5p13.1-5p15.1) was done using 21 additional closely spaced DNA markers. Linkage analyses were conducted to quantify the evidence for a gene responsible for MD across the genome. The maximum log odds for linkage (LOD) score from the genome-wide scan was on chromosome 5p (LOD = 2.9, supporting linkage by a factor of 10(2.9) or 794 to 1) with a 1-LOD interval spanning 28.6 cM. Two suggestive regions for linkage were also identified on chromosome 12 (LOD = 2.6, 1-LOD interval of 14.8 cM; and LOD = 2.5, 1-LOD interval of 17.2 cM). Finer mapping of the region surrounding the maximum LOD on chromosome 5p resulted in stronger and statistically significant evidence for linkage (LOD = 4.2) and a narrowed 1-LOD interval (13.4 cM). The putative locus on chromosome 5p is likely to account for up to 22% of variation in MD. Hence, 1 or more of the 45 candidate genes in this region could explain a large proportion of MD and, potentially, breast cancer.

Genome-wide linkage scan of prostate cancer Gleason score and confirmation of chromosome 19q

Despite evidence that prostate cancer has a genetic etiology, it has been extremely difficult to confirm genetic linkage results across studies, emphasizing the large extent of genetic heterogeneity associated with this disease. Because prostate cancer is common--approximately one in six men will be diagnosed with prostate cancer in their life--genetic linkage studies are likely plagued by phenocopies (i.e., men with prostate cancer due to environmental or lifestyle factors), weakly penetrant alleles, or a combination of both, making it difficult to replicate linkage findings. One way to account for heterogeneous causes is to use clinical information that is related to the aggressiveness of disease as an endpoint for linkage analyses. Gleason grade is a measure of prostate tumor differentiation, with higher grades associated with more aggressive disease. This semi-quantitative score has been used as a quantitative trait for linkage analysis in several prior studies. Our aim was to determine if prior linkage reports of Gleason grade to specific loci could be replicated, and to ascertain if new regions of linkage could be found. Gleason scores were available for 391 affected sib pairs from 183 hereditary prostate cancer pedigrees as part of the PROGRESS study. Analyzing Gleason score as a quantitative trait, and using microsatellite markers, suggestive evidence for linkage (P-value <or= 0.001) was found on chromosomes 19q and 5q, with P-values <or= 0.01 observed on chromosomes 3q, 7q, and 16q. Our results confirm reports of Gleason score linkage to chromosome 19q and suggest new loci for further investigation.

Chemoselective probes for metabolite enrichment and profiling

Chemical probes that target classes of proteins based on shared functional properties have emerged as powerful tools for proteomics. The metabolome rivals, if not surpasses, the proteome in terms of size and complexity, suggesting that efforts to profile metabolites would also benefit from targeted technologies. Here we apply the principle of chemoselective probes to the metabolome, creating a general strategy to tag, enrich and profile large classes of small molecules from biological systems. Key to success was incorporation of a protease-cleavage step to release captured metabolites in a format compatible with liquid chromatography-mass spectrometry (LC-MS) analysis. This technology, termed metabolite enrichment by tagging and proteolytic release (METPR), is applicable to small molecules of any physicochemical class, including polar, labile and low-mass (<100 Da) compounds. We applied METPR to profile changes in the thiol metabolome of human cancer cells treated with the antioxidant N-acetyl-L-cysteine.

Affected relative pairs and simultaneous search for two-locus linkage in the presence of epistasis

It is commonly believed that multiple interacting genes increase the susceptibility of genetically complex diseases, yet few linkage analyses of human diseases scan for more than one locus at a time. To overcome some of the statistical and computational limitations of a simultaneous search for two disease susceptibility loci in the presence of epistasis, we developed new score statistics to simultaneously scan for two disease susceptibility loci in pedigree data. These model-free score statistics are based on developments for model-free maximum lod scores, which in turn are based on variance components for indicators of disease status. To overcome reduced power caused by many parameters in the general two-locus model, we impose constraints on ratios of variance components, much like those used for robust single-locus linkage statistics (e.g., minimax constraints). The resulting three-degree of freedom score statistic, constrained as a one-sided multivariate test, can be computed rapidly, making simultaneous search feasible for human genetic linkage studies. Furthermore, using recent developments to rapidly compute simulation P-values for score statistics, it is feasible to empirically evaluate the statistical significance of the proposed score statistics. Application of these methods to two large studies of the genetic linkage of prostate cancer illuminates their strengths and limitations. The results provide weak suggestions for linkage of several pairs of chromosomal regions (chromosome pairs 1-21, 3-13, 5-9, and 14-19), all of which showed stronger linkage signals when the score statistics accounted for epistasis. These novel score statistics should prove useful for linkage studies of other complex human diseases.