We characterize for the first time 64 down-regulated and 22 up-regulated genes in Gleason grade 4/5 cancer, using the gene profile from BPH as control tissue. A number of interesting new genes, previously undescribed in prostate cancer, are presented as possibilities for further study.

Pharmacogenetic approaches can be instrumental for predicting individual differences in response to a therapeutic intervention. Here we used a recently developed murine haplotype-based computational method to identify a genetic factor regulating the metabolism of warfarin, a commonly prescribed anticoagulant with a narrow therapeutic index and a large variation in individual dosing. After quantification of warfarin and nine of its metabolites in plasma from 13 inbred mouse strains, we correlated strain-specific differences in 7-hydroxywarfarin accumulation with genetic variation within a chromosomal region encoding cytochrome P450 2C (Cyp2c) enzymes. This computational prediction was experimentally confirmed by showing that the rate-limiting step in biotransformation of warfarin to its 7-hydroxylated metabolite was inhibited by tolbutamide, a Cyp2c isoform-specific substrate, and that this transformation was mediated by expressed recombinant Cyp2c29. We show that genetic variants responsible for interindividual pharmacokinetic differences in drug metabolism can be identified by computational genetic analysis in mice.

Acetaminophen-induced liver toxicity is the most frequent precipitating cause of acute liver failure and liver transplant, but contemporary medical practice has mainly focused on patient management after a liver injury has been induced. An integrative genetic, transcriptional, and two-dimensional NMR-based metabolomic analysis performed using multiple inbred mouse strains, along with knowledge-based filtering of these data, identified betaine-homocysteine methyltransferase 2 (Bhmt2) as a diet-dependent genetic factor that affected susceptibility to acetaminophen-induced liver toxicity in mice. Through an effect on methionine and glutathione biosynthesis, Bhmt2 could utilize its substrate (S-methylmethionine [SMM]) to confer protection against acetaminophen-induced injury in vivo. Since SMM is only synthesized in plants, Bhmt2 exerts its beneficial effect in a diet-dependent manner. Identification of Bhmt2 and the affected biosynthetic pathway demonstrates how a novel method of integrative genomic analysis in mice can provide a unique and clinically applicable approach to a major public health problem.

We conclude that the increased ratio of hepsin-to-maspin may have an important role in prostate cancer progression and invasion.

Combining the experimental efficiency of a murine hepatic in vitro drug biotransformation system with in silico genetic analysis produces a model system that can rapidly analyze interindividual differences in drug metabolism. This model system was tested by using two clinically important drugs, testosterone and irinotecan, whose metabolism was previously well characterized. The metabolites produced after these drugs were incubated with hepatic in vitro biotransformation systems prepared from the 15 inbred mouse strains were measured. Strain-specific differences in the rate of 16␣-hydroxytestosterone generation and irinotecan glucuronidation correlated with the pattern of genetic variation within Cyp2b9 and Ugt1a loci, respectively. These computational predictions were experimentally confirmed using expressed recombinant enzymes. The genetic changes affecting irinotecan metabolism in mice mirrored those in humans that are known to affect the pharmacokinetics and incidence of adverse responses to this medication.drug metabolism A quantitative simulation demonstrated how utilization of pharmacogenomic information to individualize drug dosage has the potential to significantly improve treatment outcome and reduce the rate of attrition of drugs in clinical development (1). However, we often do not know the genetic factors responsible for interindividual variability in drug response. Typically, drug doses are adjusted empirically based upon therapeutic response or toxic effect, indicating that the initial dose was either subtherapeutic or potentially toxic. Despite its potential, clinical utilization of pharmacogenomic information is limited by our poor understanding of the genetic variables that govern variability in response (1). To enable the routine use of pharmacogenomic testing in clinical practice, efficient strategies for identifying these genetic variables must be developed.Toward this end, we have recently demonstrated that genetic factors affecting the metabolism (2) or the pharmacodynamic response (3, 4) for clinically important drugs can be rapidly identified in mice by computational haplotype-based genetic analysis (5-7). This approach requires administering a test drug to multiple inbred strains and then measuring individual metabolites in plasma at multiple time points after dosing (2). Most drugs are metabolized by multiple pathways, and individual steps in each pathway may be catalyzed by distinct enzymes. Therefore, analysis of the rate of formation of individual metabolites in plasma across multiple inbred murine strains reduced the complexity of this biological process, which enabled the genetic factors that contribute to the overall variability in drug metabolism to be identified (2). Reduction of biological complexity increases the chance of discovering the effect that a genetic difference within a single region has on a measured phenotype (6). This enables the pattern of genetic variation within discrete regions of the mouse genome to be correlated to patterns of phenotypic variation. Thus, ana...

Genes involved in elastin metabolism were differentially expressed in vaginal tissue from women with SUI, suggesting that elastin remodelling may be important in the molecular aetiology of SUI.

We developed a high-throughput method for resequencing for single nucleotide polymorphism (SNP) discovery using high-density microarrays. Over the two-year course of this study a number of improvements in sample preparation methods, hybridization assay, array handling, and analysis method were developed and implemented. DNA from 40 unrelated individuals of three different ethnic origins was amplified, labeled, and hybridized to arrays designed with probes representing genomic, coding, and regulatory regions. Protocol improvements including the use of long PCR and semi-automation reduced labeling and fragmentation costs by 33%. Automation improvements include the development of a scanner autoloader for arrays, a faster array wash station, and a linked laboratory tracking and data management system.

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