Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.

The influence of agitation sequence and ionic strength on in vitro drug release from hypromellose (E4M and K4M) ER matrices--the use of the USP III apparatus.

Theophylline extended release (ER) matrices containing hypromellose (hydroxypropyl methylcellulose (HPMC) E4M and K4M were evaluated in media with a pH range of 1.2-7.5, using an automated USP type III, Bio-Dis dissolution apparatus. The objectives of this study were to evaluate the effects of systematic agitation, ionic strength and pH on the release of theophylline from the gel forming hydrophilic polymeric matrices with different methoxyl substitution levels. Tribo-electric charging of hypromellose, theophylline and their formulated blends containing E4M and K4M grades has been characterised, along with quantitative observations of flow, compression behaviour and particle morphology. Agitations were studied at 5, 10, 15, 20, 25, 30 dips per minute (dpm) and also in the ascending and descending order in the dissolution vials. The ionic concentration strength of the media was also varied over a range of 0-0.4M to simulate the gastrointestinal fed and fasted states and various physiological pH conditions. To study the effect of ionic strength on the hydrophilic matrices, agitation was set at 20 dpm. The charge results on individual components imply that the positively charged particles have coupled with the negatively charged particles to form a stable ordered mixture which is believed to result in a more homogeneous and stable system. The particle shape analysis showed the HPMC K4M polymer to have a more irregular morphology and a rougher surface texture in comparison to the HPMC E4M polymer, possibly a contributory factor to the gelation process. The results showed gelation occurred quicker for the K4M tablet matrices. Drug release increased with increased agitation. This was more pronounced for the E4M tablet matrices. The ionic strength also had more of an effect on the drug release from the E4M matrices. The experiments highlighted the resilience of the K4M matrices in comparison with the E4M matrices. The results thus show that despite similar viscosities of E4M and K4M, the methoxyl substitution makes a difference to their control of drug release and as such care and consideration should be given to the choice of polymer used for extended release. The use of systematic change of agitation method and ionic strength may indicate potential fed and fasted effects on drug release from hydrophilic matrices.

A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium.

The number and volume of cells in the blood affect a wide range of disorders including cancer and cardiovascular, metabolic, infectious and immune conditions. We consider here the genetic variation in eight clinically relevant hematological parameters, including hemoglobin levels, red and white blood cell counts and platelet counts and volume. We describe common variants within 22 genetic loci reproducibly associated with these hematological parameters in 13,943 samples from six European population-based studies, including 6 associated with red blood cell parameters, 15 associated with platelet parameters and 1 associated with total white blood cell count. We further identified a long-range haplotype at 12q24 associated with coronary artery disease and myocardial infarction in 9,479 cases and 10,527 controls. We show that this haplotype demonstrates extensive disease pleiotropy, as it contains known risk loci for type 1 diabetes, hypertension and celiac disease and has been spread by a selective sweep specific to European and geographically nearby populations.

Meta-analysis of genome-wide scans for human adult stature identifies novel Loci and associations with measures of skeletal frame size.

Recent genome-wide (GW) scans have identified several independent loci affecting human stature, but their contribution through the different skeletal components of height is still poorly understood. We carried out a genome-wide scan in 12,611 participants, followed by replication in an additional 7,187 individuals, and identified 17 genomic regions with GW-significant association with height. Of these, two are entirely novel (rs11809207 in CATSPER4, combined P-value = 6.1x10(-8) and rs910316 in TMED10, P-value = 1.4x10(-7)) and two had previously been described with weak statistical support (rs10472828 in NPR3, P-value = 3x10(-7) and rs849141 in JAZF1, P-value = 3.2x10(-11)). One locus (rs1182188 at GNA12) identifies the first height eQTL. We also assessed the contribution of height loci to the upper- (trunk) and lower-body (hip axis and femur) skeletal components of height. We find evidence for several loci associated with trunk length (including rs6570507 in GPR126, P-value = 4x10(-5) and rs6817306 in LCORL, P-value = 4x10(-4)), hip axis length (including rs6830062 at LCORL, P-value = 4.8x10(-4) and rs4911494 at UQCC, P-value = 1.9x10(-4)), and femur length (including rs710841 at PRKG2, P-value = 2.4x10(-5) and rs10946808 at HIST1H1D, P-value = 6.4x10(-6)). Finally, we used conditional analyses to explore a possible differential contribution of the height loci to these different skeletal size measurements. In addition to validating four novel loci controlling adult stature, our study represents the first effort to assess the contribution of genetic loci to three skeletal components of height. Further statistical tests in larger numbers of individuals will be required to verify if the height loci affect height preferentially through these subcomponents of height.

The largest prospective warfarin-treated cohort supports genetic forecasting.

Genetic variants of cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) are known to influence warfarin dose, but the effect of other genes has not been fully elucidated. We genotyped 183 polymorphisms in 29 candidate genes in 1496 Swedish patients starting warfarin treatment, and tested for association with response. CYP2C9*2 and *3 explained 12% (P = 6.63 x 10(-34)) of the variation in warfarin dose, while a single VKORC1 SNP explained 30% (P = 9.82 x 10(-100)). No SNP outside the CYP2C gene cluster and VKORC1 regions was significantly associated with dose after correction for multiple testing. During initiation of therapy, homozygosity for CYP2C9 and VKORC1 variant alleles increased the risk of over-anticoagulation, hazard ratios 21.84 (95% CI 9.46; 50.42) and 4.56 (95% CI 2.85; 7.30), respectively. One of 8 patients with CYP2C9*3/*3 (12.5%) experienced severe bleeding during the first month compared with 0.27% of other patients (P = .066). A multiple regression model using the predictors CYP2C9, VKORC1, age, sex, and druginteractions explained 59% of the variance in warfarin dose, and 53% in an independent sample of 181 Swedish individuals. In conclusion, CYP2C9 and VKORC1 significantly influenced warfarin dose and predicted individuals predisposed to unstable anticoagulation. Our results strongly support that initiation of warfarin guided by pharmacogenetics would improve clinical outcome.

Repeated replication and a prospective meta-analysis of the association between chromosome 9p21.3 and coronary artery disease.

BACKGROUND: Recently, genome-wide association studies identified variants on chromosome 9p21.3 as affecting the risk of coronary artery disease (CAD). We investigated the association of this locus with CAD in 7 case-control studies and undertook a meta-analysis. METHODS AND RESULTS: A single-nucleotide polymorphism (SNP), rs1333049, representing the 9p21.3 locus, was genotyped in 7 case-control studies involving a total of 4645 patients with myocardial infarction or CAD and 5177 controls. The mode of inheritance was determined. In addition, in 5 of the 7 studies, we genotyped 3 additional SNPs to assess a risk-associated haplotype (ACAC). Finally, a meta-analysis of the present data and previously published samples was conducted. A limited fine mapping of the locus was performed. The risk allele (C) of the lead SNP, rs1333049, was uniformly associated with CAD in each study (P<0.05). In a pooled analysis, the odds ratio per copy of the risk allele was 1.29 (95% confidence interval, 1.22 to 1.37; P=0.0001). Haplotype analysis further suggested that this effect was not homogeneous across the haplotypic background (test for interaction, P=0.0079). An autosomal-additive mode of inheritance best explained the underlying association. The meta-analysis of the rs1333049 SNP in 12,004 cases and 28,949 controls increased the overall level of evidence for association with CAD to P=6.04x10(-10) (odds ratio, 1.24; 95% confidence interval, 1.20 to 1.29). Genotyping of 31 additional SNPs in the region identified several with a highly significant association with CAD, but none had predictive information beyond that of the rs1333049 SNP. CONCLUSIONS: This broad replication provides unprecedented evidence for association between genetic variants at chromosome 9p21.3 and risk of CAD.