Inherited genetic variant predisposes to aggressive but not indolent prostate cancer.

Autopsy studies suggest that most aging men will develop lesions that, if detected clinically, would be diagnosed as prostate cancer (PCa). Most of these cancers are indolent and remain localized; however, a subset of PCa is aggressive and accounts for more than 27,000 deaths in the United States annually. Identification of factors specifically associated with risk for more aggressive PCa is urgently needed to reduce overdiagnosis and overtreatment of this common disease. To search for such factors, we compared the frequencies of SNPs among PCa patients who were defined as having either more aggressive or less aggressive disease in four populations examined in the Genetic Markers of Susceptibility (CGEMS) study performed by the National Cancer Institute. SNPs showing possible associations with disease severity were further evaluated in an additional three independent study populations from the United States and Sweden. In total, we studied 4,829 and 12,205 patients with more and less aggressive disease, respectively. We found that the frequency of the TT genotype of SNP rs4054823 at 17p12 was consistently higher among patients with more aggressive compared with less aggressive disease in each of the seven populations studied, with an overall P value of 2.1 x 10(-8) under a recessive model, exceeding the conservative genome-wide significance level. The difference in frequency was largest between patients with high-grade, non-organ-confined disease compared with those with low-grade, organ-confined disease. This study demonstrates that inherited variants predisposing to aggressive but not indolent PCa exist in the genome, and suggests that the clinical potential of such variants as potential early markers for risk of aggressive PCa should be evaluated.

A metabolomic endotype of bioenergetic dysfunction predicts mortality in critically ill patients with acute respiratory failure.

Acute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectrum quantitative and semiquantitative metabolomic analyses of serum from ARF patients to detect bioenergetic dysfunction and determine its association with survival. Plasma samples from surviving and non-surviving patients (N = 15/group) were taken at day 1 and day 3 after admission to the medical intensive care unit and, in survivors, at hospital discharge. Significant differences between survivors and non-survivors (ANOVA, 5% FDR) include bioenergetically relevant intermediates of redox cofactors nicotinamide adenine dinucleotide (NAD) and NAD phosphate (NADP), increased acyl-carnitines, bile acids, and decreased acyl-glycerophosphocholines. Many metabolites associated with poor outcomes are substrates of NAD(P)-dependent enzymatic processes, while alterations in NAD cofactors rely on bioavailability of dietary B-vitamins thiamine, riboflavin and pyridoxine. Changes in the efficiency of the nicotinamide-derived cofactors' biosynthetic pathways also associate with alterations in glutathione-dependent drug metabolism characterized by substantial differences observed in the acetaminophen metabolome. Based on these findings, a four-feature model developed with semi-quantitative and quantitative metabolomic results predicted patient outcomes with high accuracy (AUROC = 0.91). Collectively, this metabolomic endotype points to a close association between mitochondrial and bioenergetic dysfunction and mortality in human ARF, thus pointing to new pharmacologic targets to reduce mortality in this condition.

Genetic variants and family history predict prostate cancer similar to prostate-specific antigen.

PURPOSE: Although prostate-specific antigen (PSA) is the best biomarker for predicting prostate cancer, its predictive performance needs to be improved. Results from the Prostate Cancer Prevention Trial revealed the overall performance measured by the areas under curve of the receiver operating characteristic at 0.68. The goal of the present study is to assess the ability of genetic variants as a PSA-independent method to predict prostate cancer risk. EXPERIMENTAL DESIGN: We systematically evaluated all prostate cancer risk variants that were identified from genome-wide association studies during the past year in a large population-based prostate cancer case-control study population in Sweden, including 2,893 prostate cancer patients and 1,781 men without prostate cancer. RESULTS: Twelve single nucleotide polymorphisms were independently associated with prostate cancer risk in this Swedish study population. Using a cutoff of any 11 risk alleles or family history, the sensitivity and specificity for predicting prostate cancer were 0.25 and 0.86, respectively. The overall predictive performance of prostate cancer using genetic variants, family history, and age, measured by areas under curve was 0.65 (95% confidence interval, 0.63-0.66), significantly improved over that of family history and age (0.61%; 95% confidence interval, 0.59-0.62; P = 2.3 x 10(-10)). CONCLUSION: The predictive performance for prostate cancer using genetic variants and family history is similar to that of PSA. The utility of genetic testing, alone and in combination with PSA levels, should be evaluated in large studies such as the European Randomized Study for Prostate Cancer trial and Prostate Cancer Prevention Trial.

A novel prostate cancer susceptibility locus at 19q13.

A two-stage genome-wide association study (GWAS) of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative identified single nucleotide polymorphisms (SNP) in 150 regions across the genome that may be associated with prostate cancer (PCa) risk. We filtered these results to identify 43 independent SNPs where the frequency of the risk allele was consistently higher in cases than in controls in each of the five CGEMS study populations. Genotype information for 22 of these 43 SNPs was obtained either directly by genotyping or indirectly by imputation in our PCa GWAS of 500 cases and 500 controls selected from a population-based case-control study in Sweden [Cancer of the Prostate in Sweden (CAPS)]. Two of these 22 SNPs were significantly associated with PCa risk (P<0.05). We then genotyped these two SNPs in the remaining cases (n=2,393) and controls (n=1,222) from CAPS and found that rs887391 at 19q13 was highly associated with PCa risk (P=9.4 x 10(-4)). A similar trend of association was found for this SNP in a case-control study from Johns Hopkins Hospital (JHH), albeit the result was not statistically significant. Altogether, the frequency of the risk allele of rs887391 was consistently higher in cases than controls among each of seven study populations examined, with an overall P=3.2 x 10(-7) from a combined allelic test. A fine-mapping study in a 110-kb region at 19q13 among CAPS and JHH study populations revealed that rs887391 was the most strongly associated SNP in the region. Additional confirmation studies of this region are warranted.

Evidence for two independent prostate cancer risk-associated loci in the HNF1B gene at 17q12.

We carried out a fine-mapping study in the HNF1B gene at 17q12 in two study populations and identified a second locus associated with prostate cancer risk, approximately 26 kb centromeric to the first known locus (rs4430796); these loci are separated by a recombination hot spot. We confirmed the association with a SNP in the second locus (rs11649743) in five additional populations, with P = 1.7 x 10(-9) for an allelic test of the seven studies combined. The association at each SNP remained significant after adjustment for the other SNP.