Pooled genome linkage scan of aggressive prostate cancer: results from the International Consortium for Prostate Cancer Genetics

While it is widely appreciated that prostate cancers vary substantially in their propensity to progress to a life-threatening stage, the molecular events responsible for this progression have not been identified. Understanding these molecular mechanisms could provide important prognostic information relevant to more effective clinical management of this heterogeneous cancer. Hence, through genetic linkage analyses, we examined the hypothesis that the tendency to develop aggressive prostate cancer may have an important genetic component. Starting with 1,233 familial prostate cancer families with genome scan data available from the International Consortium for Prostate Cancer Genetics, we selected those that had at least three members with the phenotype of clinically aggressive prostate cancer, as defined by either high tumor grade and/or stage, resulting in 166 pedigrees (13%). Genome-wide linkage data were then pooled to perform a combined linkage analysis for these families. Linkage signals reaching a suggestive level of significance were found on chromosomes 6p22.3 (LOD = 3.0), 11q14.1–14.3 (LOD = 2.4), and 20p11.21–q11.21 (LOD = 2.5). For chromosome 11, stronger evidence of linkage (LOD = 3.3) was observed among pedigrees with an average at diagnosis of 65 years or younger. Other chromosomes that showed evidence for heterogeneity in linkage across strata were chromosome 7, with the strongest linkage signal among pedigrees without male-to-male disease transmission (7q21.11, LOD = 4.1), and chromosome 21, with the strongest linkage signal among pedigrees that had African American ancestry (21q22.13–22.3; LOD = 3.2). Our findings suggest several regions that may contain genes which, when mutated, predispose men to develop a more aggressive prostate cancer phenotype. This provides a basis for attempts to identify these genes, with potential clinical utility for men with aggressive prostate cancer and their relatives. The names of all authors and their affiliations are listed in the Acknowledgements. The fact that Dr Schaid’s name is given here for purposes of correspondence should not be taken to imply that he played the sole leading part in writing this article. An erratum to this article can be found at     

Proceedings of the SMBE Tri-National Young Investigators' Workshop 2005. Improved consensus network techniques for genome-scale phylogeny

Although recent studies indicate that estimating phylogenies from alignments of concatenated genes greatly reduces the stochastic error, the potential for systematic error still remains, heightening the need for reliable methods to analyze multigene data sets. Consensus methods provide an alternative, more inclusive, approach for analyzing collections of trees arising from multiple genes. We extend a previously described consensus network method for genome-scale phylogeny (Holland, B. R., K. T. Huber, V. Moulton, and P. J. Lockhart. 2004. Using consensus networks to visualize contradictory evidence for species phylogeny. Mol. Biol. Evol. 21:1459-1461) to incorporate additional information. This additional information could come from bootstrap analysis, Bayesian analysis, or various methods to find confidence sets of trees. The new methods can be extended to include edge weights representing genetic distance. We use three data sets to illustrate the approach: 61 genes from 14 angiosperm taxa and one gymnosperm, 106 genes from eight yeast taxa, and 46 members of a gene family from 15 vertebrate taxa.     

Proceedings of the SMBE Tri-National Young Investigators' Workshop 2005. Control of the false discovery rate applied to the detection of positively selected amino acid sites

In this article, we consider the probabilistic identification of amino acid positions that evolve under positive selection as a multiple hypothesis testing problem. The null hypothesis "H0,s: site s evolves under a negative selection or under a neutral process of evolution" is tested at each codon site of the alignment of homologous coding sequences. Standard hypothesis testing is based on the control of the expected proportion of falsely rejected null hypotheses or type-I error rate. As the number of tests increases, however, the power of an individual test may become unacceptably low. Recent advances in statistics have shown that the false discovery rate--in this case, the expected proportion of sites that do not evolve under positive selection among those that are estimated to evolve under this selection regime--is a quantity that can be controlled. Keeping the proportion of false positives low among the significant results generally leads to an increase in power. In this article, we show that controlling the false detection rate is relevant when searching for positively selected sites. We also compare this new approach to traditional methods using extensive simulations.     

Long-term outcomes of patients receiving drug-eluting stents

Background

We sought to establish the long-term safety of drug-eluting stents compared with bare-metal stents in a usual care setting.

Methods

Using data from a prospective multicentre registry, we compared rates of death and of death or repeat revascularization during 3 years of follow-up of 6440 consecutive patients who underwent angioplasty with either drug-eluting or bare-metal stents between Apr. 1, 2003, and Mar. 31, 2006.

Results

Drug-eluting stents were inserted in 1120 patients and bare-metal stents in 5320. The drug-eluting stents were selected for patients who had a greater burden of comorbid illness, including diabetes mellitus (32.8% v. 20.8% in the bare-metal group, p < 0.001) and renal disease (7.4% v. 5.0%, p = 0.001). At 1-year follow-up, the drug-eluting stents were associated with a mortality of 3.0%, as compared with 3.7% with the bare-metal stents (adjusted odds ratio [OR] 0.62, 95% confidence interval [CI] 0.46–0.83). The rate of the composite outcome of death or repeat revascularization was 12.0% for the drug-eluting stents and 15.8% for the bare-metal stents (adjusted OR 0.40, 95% CI 0.33–0.49). In the subgroup of patients who had acute coronary syndromes, the adjusted OR for this composite outcome was 0.46 (95% CI 0.35–0.61). During the 3 years of observation, the relative risks for death and repeat revascularization varied over time. In year 1, there was an initial period of lower risk in the group with drug-eluting stents than in the group with bare-metal stents; this was followed by a shift toward outcome rates favouring bare-metal stents in years 2 and 3. The adjusted relative risk of the composite outcome of death or repeat revascularization associated with drug-eluting stents relative to bare-metal stents was 0.73 early in the first year of follow-up; it then rose gradually over time, to a peak of 2.24 at 3 years.

Interpretation

Drug-eluting stents are safe and effective in the first year following insertion. Thereafter, the possibility of longer term adverse events cannot be ruled out.Drug-eluting stents now comprise at least 85% of stents used in the United States and up to 40% or more of stents elsewhere. The overwhelming worldwide use of drug-eluting stents has, however, been tempered by the cost differential to bare-metal stents, the lack of data on long-term outcomes in large patient populations and, more recently, emerging concerns about safety because of reports of late thrombosis.^1–8The use of stents has been shown to reduce the rates of repeat revascularization and restenosis after angioplasty compared with angioplasty alone.⁹ Despite this, the long-term efficacy of stent use has been limited by the need for repeat revascularization owing to restenosis.¹⁰ Drug-eluting stents were developed to address this problem. Both clinical trials^11–20 and registry data^21–25 have shown reduced rates of restenosis with drug-eluting stents up to 4 years after implantation. This advantage appears to extend to patients with acute coronary syndromes: a recent 2-year follow-up study involving 7217 patients with acute coronary syndromes suggested that rates of death were lower among patients with drug-eluting stents than among those with bare-metal stents.²⁶The possibility of late thrombosis associated with drug-eluting stents is, however, a concern. Rates of late thrombosis have been reported to be 3.6–5.9 events per 1000 patients receiving drug-eluting stents.²⁷ This adverse event has been the subject of a review by the US Food and Drug Administration and has captured the attention of authoritative bodies around the world.Because of concerns about the long-term safety of drug-eluting stents, we compared the rates of death and of death or repeat revascularization over 3 years among patients who received either bare-metal or drug-eluting stents during angioplasty.     

A Genome-Wide Association Study in Chronic Obstructive Pulmonary Disease (COPD): Identification of Two Major Susceptibility Loci

There is considerable variability in the susceptibility of smokers to develop chronic obstructive pulmonary disease (COPD). The only known genetic risk factor is severe deficiency of α₁-antitrypsin, which is present in 1–2% of individuals with COPD. We conducted a genome-wide association study (GWAS) in a homogenous case-control cohort from Bergen, Norway (823 COPD cases and 810 smoking controls) and evaluated the top 100 single nucleotide polymorphisms (SNPs) in the family-based International COPD Genetics Network (ICGN; 1891 Caucasian individuals from 606 pedigrees) study. The polymorphisms that showed replication were further evaluated in 389 subjects from the US National Emphysema Treatment Trial (NETT) and 472 controls from the Normative Aging Study (NAS) and then in a fourth cohort of 949 individuals from 127 extended pedigrees from the Boston Early-Onset COPD population. Logistic regression models with adjustments of covariates were used to analyze the case-control populations. Family-based association analyses were conducted for a diagnosis of COPD and lung function in the family populations. Two SNPs at the α-nicotinic acetylcholine receptor (CHRNA 3/5) locus were identified in the genome-wide association study. They showed unambiguous replication in the ICGN family-based analysis and in the NETT case-control analysis with combined p-values of 1.48×10⁻¹⁰, (rs8034191) and 5.74×10⁻¹⁰ (rs1051730). Furthermore, these SNPs were significantly associated with lung function in both the ICGN and Boston Early-Onset COPD populations. The C allele of the rs8034191 SNP was estimated to have a population attributable risk for COPD of 12.2%. The association of hedgehog interacting protein (HHIP) locus on chromosome 4 was also consistently replicated, but did not reach genome-wide significance levels. Genome-wide significant association of the HHIP locus with lung function was identified in the Framingham Heart study (Wilk et al., companion article in this issue of PLoS Genetics; doi:10.1371/journal.pgen.1000429). The CHRNA 3/5 and the HHIP loci make a significant contribution to the risk of COPD. CHRNA3/5 is the same locus that has been implicated in the risk of lung cancer.     

A Novel Method to Adjust Efficacy Estimates for Uptake of Other Active Treatments in Long-Term Clinical Trials

Background

When rates of uptake of other drugs differ between treatment arms in long-term trials, the true benefit or harm of the treatment may be underestimated. Methods to allow for such contamination have often been limited by failing to preserve the randomization comparisons. In the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study, patients were randomized to fenofibrate or placebo, but during the trial many started additional drugs, particularly statins, more so in the placebo group. The effects of fenofibrate estimated by intention-to-treat were likely to have been attenuated. We aimed to quantify this effect and to develop a method for use in other long-term trials.

Methodology/Principal Findings

We applied efficacies of statins and other cardiovascular drugs from meta-analyses of randomized trials to adjust the effect of fenofibrate in a penalized Cox model. We assumed that future cardiovascular disease events were reduced by an average of 24% by statins, and 20% by a first other major cardiovascular drug. We applied these estimates to each patient who took these drugs for the period they were on them. We also adjusted the analysis by the rate of discontinuing fenofibrate. Among 4,900 placebo patients, average statin use was 16% over five years. Among 4,895 assigned fenofibrate, statin use was 8% and nonuse of fenofibrate was 10%. In placebo patients, use of cardiovascular drugs was 1% to 3% higher. Before adjustment, fenofibrate was associated with an 11% reduction in coronary events (coronary heart disease death or myocardial infarction) (P = 0.16) and an 11% reduction in cardiovascular disease events (P = 0.04). After adjustment, the effects of fenofibrate on coronary events and cardiovascular disease events were 16% (P = 0.06) and 15% (P = 0.008), respectively.

Conclusions/Significance

This novel application of a penalized Cox model for adjustment of a trial estimate of treatment efficacy incorporates evidence-based estimates for other therapies, preserves comparisons between the randomized groups, and is applicable to other long-term trials. In the FIELD study example, the effects of fenofibrate on the risks of coronary heart disease and cardiovascular disease events were underestimated by up to one-third in the original analysis.

Trial Registration

Controlled-Trials.com ISRCTN64783481     

Genomic aberrations in lung adenocarcinoma in never smokers

Background

Lung cancer in never smokers would rank as the seventh most common cause of cancer death worldwide.

Methods and Findings

We performed high-resolution array comparative genomic hybridization analysis of lung adenocarcinoma in sixty never smokers and identified fourteen new minimal common regions (MCR) of gain or loss, of which five contained a single gene (MOCS2, NSUN3, KHDRBS2, SNTG1 and ST18). One larger MCR of gain contained NSD1. One focal amplification and nine gains contained FUS. NSD1 and FUS are oncogenes hitherto not known to be associated with lung cancer. FISH showed that the amplicon containing FUS was joined to the next telomeric amplicon at 16p11.2. FUS was over-expressed in 10 tumors with gain of 16p11.2 compared to 30 tumors without that gain. Other cancer genes present in aberrations included ARNT, BCL9, CDK4, CDKN2B, EGFR, ERBB2, MDM2, MDM4, MET, MYC and KRAS. Unsupervised hierarchical clustering with adjustment for false-discovery rate revealed clusters differing by the level and pattern of aberrations and displaying particular tumor characteristics. One cluster was strongly associated with gain of MYC. Another cluster was characterized by extensive losses containing tumor suppressor genes of which RB1 and WRN. Tumors in that cluster frequently harbored a central scar-like fibrosis. A third cluster was associated with gains on 7p and 7q, containing ETV1 and BRAF, and displayed the highest rate of EGFR mutations. SNP array analysis validated copy-number aberrations and revealed that RB1 and WRN were altered by recurrent copy-neutral loss of heterozygosity.

Conclusions

The present study has uncovered new aberrations containing cancer genes. The oncogene FUS is a candidate gene in the 16p region that is frequently gained in never smokers. Multiple genetic pathways defined by gains of MYC, deletions of RB1 and WRN or gains on 7p and 7q are involved in lung adenocarcinoma in never smokers.     

Survival analysis of longitudinal microarrays

MOTIVATION: The development of methods for linking gene expressions to various clinical and phenotypic characteristics is an active area of genomic research. Scientists hope that such analysis may, for example, describe relationships between gene function and clinical events such as death or recovery. Methods are available for relating gene expression to measurements that are categorized or continuous, but there is less work in relating expressions to an observed event time such as time to death, response or relapse. When gene expressions are measured over time, there are methods for differentiating temporal patterns. However, methods have not yet been proposed for the survival analysis of longitudinally collected microarrays. RESULTS: We describe an approach for the survival analysis of longitudinal gene expression data. We construct a measure of association between the time to an event and gene expressions collected over time. Statistical significance is addressed using permutations and control of the false discovery rate. Our proposed method is illustrated on a dataset from a multi-center research study of inflammation and response to injury that aims to uncover the biological reasons why patients can have dramatically different outcomes after suffering a traumatic injury (www.gluegrant.org).