A compendium of genome-wide associations for cancer: critical synopsis and reappraisal

COMETS Analytics: An Online Tool for Analyzing and Meta-Analyzing Metabolomics Data in Large Research Consortia

Consortium-based research is crucial for producing reliable, high-quality findings, but existing tools for consortium studies have important drawbacks with respect to data protection, ease of deployment, and analytical rigor. To address these concerns, we developed COnsortium of METabolomics Studies (COMETS) Analytics to support and streamline consortium-based analyses of metabolomics and other -omics data. The application requires no specialized expertise and can be run locally to guarantee data protection or through a Web-based server for convenience and speed. Unlike other Web-based tools, COMETS Analytics enables standardized analyses to be run across all cohorts, using an algorithmic, reproducible approach to diagnose, document, and fix model issues. This eliminates the time-consuming and potentially error-prone step of manually customizing models by cohort, helping to accelerate consortium-based projects and enhancing analytical reproducibility. We demonstrated that the application scales well by performing 2 data analyses in 45 cohort studies that together comprised measurements of 4,647 metabolites in up to 134,742 participants. COMETS Analytics performed well in this test, as judged by the minimal errors that analysts had in preparing data inputs and the successful execution of all models attempted. As metabolomics gathers momentum among biomedical and epidemiologic researchers, COMETS Analytics may be a useful tool for facilitating large-scale consortium-based research.

Imaging and quantifying drug delivery in skin - Part 2: Fluorescence andvibrational spectroscopic imaging methods

Understanding the delivery and diffusion of topically-applied drugs on human skin is of paramount importance in both pharmaceutical and cosmetics research. This information is critical in early stages of drug development and allows the identification of the most promising ingredients delivered at optimal concentrations to their target skin compartments. Different skin imaging methods, invasive and non-invasive, are available to characterize and quantify the spatiotemporal distribution of a drug within ex vivo and in vivo human skin. The first part of this review detailed invasive imaging methods (autoradiography, MALDI and SIMS). This second part reviews non-invasive imaging methods that can be applied in vivo: i) fluorescence (conventional, confocal, and multiphoton) and second harmonic generation microscopies and ii) vibrational spectroscopic imaging methods (infrared, confocal Raman, and coherent Raman scattering microscopies). Finally, a flow chart for the selection of imaging methods is presented to guide human skin ex vivo and in vivo drug delivery studies.

Interactions of PVT1 and CASC11 on Prostate Cancer Risk in African Americans

BACKGROUND

African American (AA) men have a higher risk of developing prostate cancer than white men. SNPs are known to play an important role in developing prostate cancer. The impact of PVT1 and its neighborhood genes (CASC11 and MYC) on prostate cancer risk are getting more attention recently. The interactions among these three genes associated with prostate cancer risk are understudied, especially for AA men. The objective of this study is to investigate SNP-SNP interactions in the CASC11-MYC-PVT1 region associated with prostate cancer risk in AA men.

METHODS

We evaluated 205 SNPs using the 2,253 prostate cancer patients and 2,423 controls and applied multiphase (discovery-validation) design. In addition to SNP individual effects, SNP-SNP interactions were evaluated using the SNP Interaction Pattern Identifier, which assesses 45 patterns.

RESULTS

Three SNPs (rs9642880, rs16902359, and rs12680047) and 79 SNP-SNP pairs were significantly associated with prostate cancer risk. These two SNPs (rs16902359 and rs9642880) in CASC11 interacted frequently with other SNPs with 56 and 9 pairs, respectively. We identified the novel interaction of CASC11-PVT1, which is the most common gene interaction (70%) in the top 79 pairs. Several top SNP interactions have a moderate to large effect size (OR, 0.27-0.68) and have a higher prediction power to prostate cancer risk than SNP individual effects.

CONCLUSIONS

Novel SNP-SNP interactions in the CASC11-MYC-PVT1 region have a larger impact than SNP individual effects on prostate cancer risk in AA men.

IMPACT

This gene-gene interaction between CASC11 and PVT1 can provide valuable information to reveal potential biological mechanisms of prostate cancer development.

Systematic Review and Meta-analysis of SNPs from Genome-Wide Association Studies of Head and Neck Cancer

Objective Various genome-wide association studies (GWASs) identified new head and neck cancer (HNC) susceptibility loci, although the evidence has not been systematically summarized. We performed a systematic review and meta-analyses of the GWASs to identify the most commonly reported genetic loci associated with a risk of HNC. Data Sources We searched the PubMed, ISI Web of Science, SCOPUS, and GWAS databases to retrieve eligible studies, in English or Italian, published until June 1, 2017. Review Methods Only GWASs reporting data on the association between single-nucleotide polymorphisms (SNPs) and HNC were included. The quality of included studies was evaluated using the Q-Genie tool. Random-effect meta-analyses were performed considering only SNPs with at least 1 significant result from the included articles, and pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Results Seven studies of case-control design were included in the review. Five studies on nasopharyngeal cancer (NPC) in Chinese, reporting on 27 different SNPs, were included in meta-analyses. Results show that 6 SNPs ( rs2076483, rs2975042, rs9258122, rs29232, and rs9510787) had an increased pooled estimates for A risk alleles (OR [95% CI]: 1.55 [1.36-1.77], 1.90 [1.69-2.14], 1.47 [1.31-1.65], 1.52 [1.32-1.76], and 1.22 [1.13-1.31], respectively) while G risk allele of rs3129055 reported an OR of 1.49 (95% CI, 1.33-1.67). Conclusion Our systematic review identified 5 SNPs located on chromosome 6 ( rs2076483, rs2975042, rs3129055, rs9258122, and rs29232) and 1 ( rs9510787) on chromosome 13 as significantly associated with an increased risk of NPC in Chinese.

GCAT|Genomes for life: a prospective cohort study of the genomes of Catalonia

PURPOSE

The prevalence of chronic non-communicable diseases (NCDs) is increasing worldwide. NCDs are the leading cause of both morbidity and mortality, and it is estimated that by 2030, they will be responsible for 80% of deaths across the world. The Genomes for Life (GCAT) project is a long-term prospective cohort study that was designed to integrate and assess the role of epidemiological, genomic and epigenomic factors in the development of major chronic diseases in Catalonia, a north-east region of Spain.

PARTICIPANTS

At the end of 2017, the GCAT Study will have recruited 20 000 participants aged 40-65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants will be followed biannually at least 20 years after recruitment.

FINDINGS TO DATE

Among all GCAT participants, 59.2% are women and 83.3% of the cohort identified themselves as Caucasian/white. More than half of the participants have higher education levels, 72.2% are current workers and 42.1% are classified as overweight (body mass index ≥25 and <30 kg/m²). We have genotyped 5459 participants, of which 5000 have metabolome data. Further, the whole genome of 808 participants will be sequenced by the end of 2017.

FUTURE PLANS

The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites.

Genomic approaches to accelerate cancer interception

Although major advances have been reported in the last decade in the treatment of late-stage cancer with targeted and immune-based therapies, there is a crucial unmet need to develop new approaches to improve the prevention and early detection of cancer. Advances in genomics and computational biology offer unprecedented opportunities to understand the earliest molecular events associated with carcinogenesis, enabling novel strategies to intercept the development of invasive cancers. This Series paper will highlight emerging big data genomic approaches with the potential to accelerate advances in cancer prevention, screening, and early detection across various tumour types, and the challenges inherent in the development of these tools for clinical use. Through coordinated multicentre consortia, these genomic approaches are likely to transform the landscape of cancer interception in the coming years.

Physical Confirmation and Comparative Genomics of the Rat Mammary carcinoma susceptibility 3 Quantitative Trait Locus

Human breast and rat mammary cancer susceptibility are complex phenotypes where complete sets of risk associated loci remain to be identified for both species. We tested multiple congenic rat strains to physically confirm and positionally map rat Mammary carcinoma susceptibility 3 (Mcs3)-a mammary cancer resistance allele previously predicted at Rattus norvegicus chromosome 1 (RNO1). The mammary cancer susceptible Wistar Furth (WF) strain was the recipient, and the mammary cancer resistant Copenhagen (Cop) strain was the RNO1-segment donor for congenics. Inbred WF females averaged 6.3 carcinogen-induced mammary carcinomas per rat. Two WF.Cop congenic strains averaged 2.8 and 3.4 mammary carcinomas per rat, which confirmed Mcs3 as an independently acting allele. Two other WF.Cop congenic strains averaged 6.6 and 8.1 mammary carcinomas per rat, and, thus, did not contain Mcs3 Rat Mcs3 was delimited to 27.8 Mb of RNO1 from rs8149408 to rs105131702 (RNO1:143700228-171517317 of RGSC 6.0/rn6). Human genetic variants with p values for association to breast cancer risk below 10^-7 had not been reported for Mcs3 orthologous loci; however, human variants located in Mcs3-orthologous regions with potential association to risk (10^-7 < p < 10^-3) were listed in some population-based studies. Further, rat Mcs3 contains sequence orthologous to human 11q13/14-a region frequently amplified in female breast cancer. We conclude that Mcs3 is an independently acting mammary carcinoma resistance allele. Human population-based, genome-targeted association studies interrogating Mcs3 orthologous loci may yield novel breast cancer risk associated variants and genes.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns

Motivation

Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped.

Results

We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns.

Availability and Implementation

The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ .

Contact

hlin1@lsuhsc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Network analysis of genes and their association with diseases

A plethora of network-based approaches within the Systems Biology universe have been applied, to date, to investigate the underlying molecular mechanisms of various human diseases. In the present study, we perform a bipartite, topological and clustering graph analysis in order to gain a better understanding of the relationships between human genetic diseases and the relationships between the genes that are implicated in them. For this purpose, disease-disease and gene-gene networks were constructed from combined gene-disease association networks. The latter, were created by collecting and integrating data from three diverse resources, each one with different content covering from rare monogenic disorders to common complex diseases. This data pluralism enabled us to uncover important associations between diseases with unrelated phenotypic manifestations but with common genetic origin. For our analysis, the topological attributes and the functional implications of the individual networks were taken into account and are shortly discussed. We believe that some observations of this study could advance our understanding regarding the etiology of a disease with distinct pathological manifestations, and simultaneously provide the springboard for the development of preventive and therapeutic strategies and its underlying genetic mechanisms.

A guide on gene prioritization in studies of psychiatric disorders

There has been an increasing interest in the identification of genetic variants causing individual differences in human behavior. Psychiatrists have contributed to the genetics field by defining the most important behavioral characteristics and by studying the association between genetic variants and behavioral differences within phenotypically well-characterized samples in which detailed assessments have been collected (e.g. neuroimaging). These samples are typically limited in size and are therefore not suitable for a genome-wide association analysis. Instead, gene association studies conducted in such samples typically focus on a few genes of interest, allowing smaller sample sizes. However, the selection of high-priority genes is not always straightforward and psychiatrists will usually have a limited background in genetics. We aim to fill this gap by (i) providing a basic introduction to genetics; (ii) showing how the selection of genes of interest can be optimized by the use of two web tools: Polysearch and Gene Prospector; (iii) illustrating how statistical power analyses can be performed and discussing the importance of sufficiently powered studies. This guide can help psychiatrists with limited experience in genetics in designing genetic studies that allow identification of specific behavioral, cognitive, or neural correlates of genetic risk variants, while avoiding common pitfalls. Copyright © 2015 John Wiley & Sons, Ltd.

Genetic Variants in the Insulin-like Growth Factor Pathway and Colorectal Cancer Risk in the Netherlands Cohort Study

Interrelationships between insulin-like growth factors (IGFs), hyperinsulinaemia, diabetes, and colorectal cancer (CRC) indicate involvement of IGFs in colorectal tumorigenesis. We investigated the CRC risk associated with 24 single nucleotide polymorphisms (SNPs) in 9 genes related to the IGF pathway and an IGF1 19-CA repeat polymorphism. Variants were selected from literature and genotyped in toenail DNA from 3,768 subcohort members and 2,580 CRC cases from the Netherlands Cohort Study, which has a case-cohort design (n = 120,852). We used the follow-up period 1986–2002. Eighteen SNPs were unequivocally associated with selected endpoints in the literature and unfavorable alleles were aggregated into a genetic sum score. Cox regression showed that a higher genetic sum score significantly increased CRC risk at all subsites, except the rectum, in men (highest vs. lowest tertile: HR for CRC = 1.36, 95% CI: 1.11, 1.65; P-trend = 0.002). Single SNPs (except the IGF1 SNP rs5742694) were not associated with risk. Models including the total number of IGF1 19-CA repeats showed CRC risk was halved at all subsites in women carrying <38 repeats but not >38 repeats (≤36 versus 38 repeats: HR for CRC = 0.44; 95% CI: 0.33, 0.58; P-trend < 0.001). These findings support a role for variants in IGF-related genes in colorectal tumorigenesis.

Association between Glu504Lys polymorphism of ALDH2 gene and cancer risk: a meta-analysis

Background

The association of the aldehyde dehydrogenases-2 (ALDH2) Glu504Lys polymorphism (also named Glu487Lys, or rs671) and cancers has been investigated. This meta-analysis aims to comprehensively assess the influence of this polymorphism on the overall cancer risk.

Methods

Eligible publications were retrieved according to inclusion/exclusion criteria and the data were analyzed using the Review Manager software (V5.2).

Results

A meta-analysis based on 51 case-control studies consisting of 16774 cases and 32060 controls was performed to evaluate the association between the ALDH2 Glu504Lys polymorphism and cancer risk. The comparison of genotypes Lys+ (Lys/Lys and Lys/Glu) with Glu/Glu yielded a significant 20% increased cancer risk (OR = 1.20, 95%CI: 1.03–1.39, P = 0.02, I² = 92%). Subgroup analysis by cancer type indicated a significantly increased UADT cancer risk (OR = 1.39, 95%CI: 1.11–1.73, P = 0.004, I² = 94%) in individuals with the Lys+ genotypes. Subgroup analysis by country indicated that individuals from Japan with the Lys+ genotypes had a significant 38% increased cancer risk (OR = 1.38, 95%CI: 1.12–1.71, P = 0.003, I² = 93%).

Conclusions

Our results indicated that the ALDH2 Glu504Lys polymorphism is a susceptible loci associated with overall cancers, especially esophageal cancer and among Japanese population.

Logistic Principal Component Analysis for Rare Variants in Gene-Environment Interaction Analysis

The characteristics of low minor allele frequency (MAF) and weak individual effects make genome-wide association studies (GWAS) for rare variant single nucleotide polymorphisms (SNPs) more difficult when using conventional statistical methods. By aggregating the rare variant effects belonging to the same gene, collapsing is the most common way to enhance the detection of rare variant effects for association analyses with a given trait. In this paper, we propose a novel framework of MAF-based logistic principal component analysis (MLPCA) to derive aggregated statistics by explicitly modeling the correlation between rare variant SNP data, which is categorical. The derived aggregated statistics by MLPCA can then be tested as a surrogate variable in regression models to detect the gene-environment interaction from rare variants. In addition, MLPCA searches for the optimal linear combination from the best subset of rare variants according to MAF that has the maximum association with the given trait. We compared the power of our MLPCA-based methods with four existing collapsing methods in gene-environment interaction association analysis using both our simulation data set and Genetic Analysis Workshop 17 (GAW17) data. Our experimental results have demonstrated that MLPCA on two forms of genotype data representations achieves higher statistical power than those existing methods and can be further improved by introducing the appropriate sparsity penalty. The performance improvement by our MLPCA-based methods result from the derived aggregated statistics by explicitly modeling categorical SNP data and searching for the maximum associated subset of SNPs for collapsing, which helps better capture the combined effect from individual rare variants and the interaction with environmental factors.

Perceptions and Attitudes About Genetic Counseling Among Residents of a Midwestern Rural Area

Relatively few investigations of the public's perceptions and attitudes about genetic counseling exist, and most are limited to individuals at-risk for a specific disease. In this study 203 individuals from a Midwest rural area completed an anonymous survey assessing their familiarity with genetic counseling; perceptions of genetic counseling purpose, scope, and practice; attitudes toward genetic counseling/counselors; and willingness to use genetic counseling services. Although very few respondents were familiar with genetic counseling, most reported accurate perceptions and positive attitudes; mean ratings, however, showed less endorsement of trust in information provided by genetic counselors and less agreement that genetic counseling aligns with their values. Logistic regression indicated reported willingness to use genetic counseling services increased if respondents: had completed some college; rated their familiarity with genetic counseling as high; agreed with the statements: genetic counseling may be useful to someone with cancer in their family, genetic counseling is in line with my values, and genetic counselors advise women to get abortions when there is a problem; and disagreed with the statements: genetic counseling is only useful to a small group of people with rare diseases, and genetic counselors must receive a lot of special training. Additional findings, practice implications, and research recommendations are presented.

Quantification of population benefit in evaluation of biomarkers: practical implications for disease detection and prevention

BACKGROUND

With the rapid development of "-omic" technologies, an increasing number of purported biomarkers have been identified for cancer and other diseases. The process of identifying those that are most promising and validating them for use at the population level for prevention and early detection is a critical next step in achieving significant health benefits.

METHODS

In this paper, we propose that in order to effectively translate biomarkers for practical clinical use, it is important to distinguish and quantify the differences between the use of biomarkers and other risk factors to identify preventive interventions versus their use in disease risk prediction and early detection. We developed mathematical models for quantitatively evaluating risk and benefit in use of biomarkers for disease prevention or early detection. Simple numerical examples were used to demonstrate the potential applications of the models for various types of data.

RESULTS

We propose an index which takes into account potential adverse consequences of biomarker-driven interventions - the 'naïve' ratio of population benefit (RPB) - to facilitate evaluating the potential impact of biomarkers on cancer prevention and personalized medicine. The index RPB is developed for both binary and continuous biomarkers/risk factors. Examples with computational analyses are presented in the paper to contrast the differences in using biomarkers/risk factors for prevention and early detection.

CONCLUSIONS

Integrating epidemiologic knowledge into clinical decision making is a key step to translate new biomarkers/risk factors into practical use to achieve health benefits. The RPB proposed in this paper considers the absolute risk of a disease in intervention, and takes into account the risk-benefit effects simultaneously for a marker/exposure at the population level. The RPB illustrates a unique approach to quantitatively assess the risk and potential benefits of using a biomarker/risk factor for intervention in both early detection and prevention.

Supervised categorical principal component analysis for genome-wide association analyses

In order to have a better understanding of unexplained heritability for complex diseases in conventional Genome-Wide Association Studies (GWAS), aggregated association analyses based on predefined functional regions, such as genes and pathways, become popular recently as they enable evaluating joint effect of multiple Single-Nucleotide Polymorphisms (SNPs), which helps increase the detection power, especially when investigating genetic variants with weak individual effects. In this paper, we focus on aggregated analysis methods based on the idea of Principal Component Analysis (PCA). The past approaches using PCA mostly make some inherent genotype data and/or risk effect model assumptions, which may hinder the accurate detection of potential disease SNPs that influence disease phenotypes. In this paper, we derive a general Supervised Categorical Principal Component Analysis (SCPCA), which explicitly models categorical SNP data without imposing any risk effect model assumption. We have evaluated the efficacy of SCPCA with the comparison to a traditional Supervised PCA (SPCA) and a previously developed Supervised Logistic Principal Component Analysis (SLPCA) based on both the simulated genotype data by HAPGEN2 and the genotype data of Crohn's Disease (CD) from Wellcome Trust Case Control Consortium (WTCCC). Our preliminary results have demonstrated the superiority of SCPCA over both SPCA and SLPCA due to its modeling explicitly designed for categorical SNP data as well as its flexibility on the risk effect model assumption.

Significant overlap between human genome-wide association-study nominated breast cancer risk alleles and rat mammary cancer susceptibility loci

Introduction

Human population-based genome-wide association (GWA) studies identify low penetrance breast cancer risk alleles; however, GWA studies alone do not definitively determine causative genes or mechanisms. Stringent genome- wide statistical significance level requirements, set to avoid false-positive associations, yield many false-negative associations. Laboratory rats (Rattus norvegicus) are useful to study many aspects of breast cancer, including genetic susceptibility. Several rat mammary cancer associated loci have been identified using genetic linkage and congenic strain based-approaches. Here, we sought to determine the amount of overlap between GWA study nominated human breast and rat mammary cancer susceptibility loci.

Methods

We queried published GWA studies to identify two groups of SNPs, one that reached genome-wide significance and one comprised of SNPs failing a validation step and not reaching genome- wide significance. Human genome locations of these SNPs were compared to known rat mammary carcinoma susceptibility loci to determine if risk alleles existed in both species. Rat genome regions not known to associate with mammary cancer risk were randomly selected as control regions.

Results

Significantly more human breast cancer risk GWA study nominated SNPs mapped at orthologs of rat mammary cancer loci than to regions not known to contain rat mammary cancer loci. The rat genome was useful to predict associations that had met human genome-wide significance criteria and weaker associations that had not.

Conclusions

Integration of human and rat comparative genomics may be useful to parse out false-negative associations in GWA studies of breast cancer risk.

Pigmentation-related phenotypes and risk of prostate cancer

BACKGROUND

Solar ultraviolet radiation exposure has been inversely related to prostate cancer incidence and mortality, possibly mediated through vitamin D status. Pigmentation-related traits influence endogenous vitamin D synthesis and may alter risk of prostate cancer.

METHODS

We examined prostate cancer in relation to hair and eye colour, and skin phototype in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort. Incident cancer was diagnosed in 1982 out of 20 863 men. Multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated from Cox proportional hazards models.

RESULTS

Prostate cancer risk did not differ by eye colour or skin phototype. Men with naturally red hair were significantly less likely to develop prostate cancer (HR=0.46, 95% CI 0.24-0.89) than men with light brown hair (reference).

CONCLUSION

The red hair phenotype, which results from polymorphisms in the melanocortin-1-receptor (MC1R) gene, is associated with lower risk of prostate cancer. This pigmentation-related trait may influence prostate cancer development either directly, through genetic effects or regulatory mechanisms related to MC1R, another nearby gene, or other pigmentation genes, or indirectly, through associations with other exposures such as sunlight or vitamin D status.

Making sense of OMICS data in population-based environmental health studies

Although experience from the application of OMICS technologies in population-based environmental health studies is still relatively limited, the accumulated evidence shows that it can allow the identification of features (genes, proteins, and metabolites), or sets of such features, which are targeted by particular exposures or correlate with disease risk. Such features or profiles can therefore serve as biomarkers of exposure or disease risk. Blood-based OMIC profiles appear to reflect to some extent events occurring in target tissues and are associated with toxicity or disease and therefore have the potential to facilitate the elucidation of exposure-disease relationships. Further progress in this direction requires better understanding of the significance of exposure-induced network perturbations for disease initiation and progression and the development of a framework that combines agnostic searches with the utilization of prior knowledge, taking account of particular elements which characterize the structure and evolution of complex systems and brings in principles of systems biology.

SNP-SNP interaction network in angiogenesis genes associated with prostate cancer aggressiveness

Angiogenesis has been shown to be associated with prostate cancer development. The majority of prostate cancer studies focused on individual single nucleotide polymorphisms (SNPs) while SNP-SNP interactions are suggested having a great impact on unveiling the underlying mechanism of complex disease. Using 1,151 prostate cancer patients in the Cancer Genetic Markers of Susceptibility (CGEMS) dataset, 2,651 SNPs in the angiogenesis genes associated with prostate cancer aggressiveness were evaluated. SNP-SNP interactions were primarily assessed using the two-stage Random Forests plus Multivariate Adaptive Regression Splines (TRM) approach in the CGEMS group, and were then re-evaluated in the Moffitt group with 1,040 patients. For the identified gene pairs, cross-evaluation was applied to evaluate SNP interactions in both study groups. Five SNP-SNP interactions in three gene pairs (MMP16+ ROBO1, MMP16+ CSF1, and MMP16+ EGFR) were identified to be associated with aggressive prostate cancer in both groups. Three pairs of SNPs (rs1477908+ rs1387665, rs1467251+ rs7625555, and rs1824717+ rs7625555) were in MMP16 and ROBO1, one pair (rs2176771+ rs333970) in MMP16 and CSF1, and one pair (rs1401862+ rs6964705) in MMP16 and EGFR. The results suggest that MMP16 may play an important role in prostate cancer aggressiveness. By integrating our novel findings and available biomedical literature, a hypothetical gene interaction network was proposed. This network demonstrates that our identified SNP-SNP interactions are biologically relevant and shows that EGFR may be the hub for the interactions. The findings provide valuable information to identify genotype combinations at risk of developing aggressive prostate cancer and improve understanding on the genetic etiology of angiogenesis associated with prostate cancer aggressiveness.

Genetic variation in the vitamin d pathway in relation to risk of prostate cancer--results from the breast and prostate cancer cohort consortium

BACKGROUND

Studies suggest that vitamin D status may be associated with prostate cancer risk although the direction and strength of this association differs between experimental and observational studies. Genome-wide association studies have identified genetic variants associated with 25-hydroxyvitamin D [25(OH)D] status. We examined prostate cancer risk in relation to single-nucleotide polymorphisms (SNP) in four genes shown to predict circulating levels of 25(OH)D.

METHODS

SNP markers localized to each of four genes (GC, CYP24A1, CYP2R1, and DHCR7) previously associated with 25(OH)D were genotyped in 10,018 cases and 11,052 controls from the National Cancer Institute (NCI) Breast and Prostate Cancer Cohort Consortium. Logistic regression was used to estimate the individual and cumulative association between genetic variants and risk of overall and aggressive prostate cancer.

RESULTS

We observed a decreased risk of aggressive prostate cancer among men with the allele in rs6013897 near CYP24A1 associated with lower serum 25(OH)D [per A allele, OR, 0.86; 95% confidence interval (CI), 0.80-0.93; Ptrend = 0.0002) but an increased risk for nonaggressive disease (per A allele: OR, 1.10; 95% CI, 1.04-1.17; Ptrend = 0.002). Examination of a polygenic score of the four SNPs revealed statistically significantly lower risk of aggressive prostate cancer among men with a greater number of low vitamin D alleles (OR for 6-8 vs. 0-1 alleles, 0.66; 95% CI, 0.44-0.98; Ptrend = 0.003).

CONCLUSIONS

In this large, pooled analysis, genetic variants related to lower 25(OH)D levels were associated with a decreased risk of aggressive prostate cancer.

IMPACT

Our genetic findings do not support a protective association between loci known to influence vitamin D levels and prostate cancer risk.

Assessment of systematic effects of methodological characteristics on candidate genetic associations

Candidate genetic association studies have been found to have a low replication rate in the past. Here, we aimed to assess whether aspects of reported methodological characteristics in genetic association studies may be related to the magnitude of effects observed. An observational, literature-based investigation of 511 case-control studies of genetic association studies indexed in 2007, was undertaken. Meta-regression analyses were used to assess the relationship between 23 reported methodological characteristics and the magnitude of genetic associations. The 511 studies had been conducted in 52 countries and were published in 220 journals (median impact factor 5.1). The multivariate meta-regression model of methodological characteristics plus disease category accounted for 17.2 % of the between-study variance in the magnitude of the reported genetic associations. Our findings are consistent with the view that better conducted and better reported genetic association research may lead to less inflated results.

Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world

This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations, and expected payoffs. Using substance use and abuse as our driving example, we then turn to the importance of etiological psychological theory in guiding genetic, environmental, and developmental research, as well as the utility of refined phenotypic measures, such as endophenotypes, in the pursuit of etiological understanding and focused tests of genetic and environmental associations. Phenotypic measurement has received considerable attention in the history of psychology and is informed by psychometrics, whereas the environment remains relatively poorly measured and is often confounded with genetic effects (i.e., gene-environment correlation). Genetically informed designs, which are no longer limited to twin and adoption studies thanks to ever-cheaper genotyping, are required to understand environmental influences. Finally, we outline the vast amount of individual difference in structural genomic variation, most of which remains to be leveraged in genetic association tests. Although the genetic data can be massive and burdensome (tens of millions of variants per person), we argue that improved understanding of genomic structure and function will provide investigators with new tools to test specific a priori hypotheses derived from etiological psychological theory, much like current candidate gene research but with less confusion and more payoff than candidate gene research has to date.

Evaluation of excess statistical significance in meta-analyses of 98 biomarker associations with cancer risk

BACKGROUND

Numerous biomarkers have been associated with cancer risk. We assessed whether there is evidence for excess statistical significance in results of cancer biomarker studies, suggesting biases.

METHODS

We systematically searched PubMed for meta-analyses of nongenetic biomarkers and cancer risk. The number of observed studies with statistically significant results was compared with the expected number, based on the statistical power of each study under different assumptions for the plausible effect size. We also evaluated small-study effects using asymmetry tests. All statistical tests were two-sided.

RESULTS

We included 98 meta-analyses with 847 studies. Forty-three meta-analyses (44%) found nominally statistically significant summary effects (random effects). The proportion of meta-analyses with statistically significant effects was highest for infectious agents (86%), inflammatory (67%), and insulin-like growth factor (IGF)/insulin system (52%) biomarkers. Overall, 269 (32%) individual studies observed nominally statistically significant results. A statistically significant excess of the observed over the expected number of studies with statistically significant results was seen in 20 meta-analyses. An excess of observed vs expected was observed in studies of IGF/insulin (P ≤ .04) and inflammation systems (P ≤ .02). Only 12 meta-analyses (12%) had a statistically significant summary effect size, more than 1000 case patients, and no hints of small-study effects or excess statistical significance; only four of them had large effect sizes, three of which pertained to infectious agents (Helicobacter pylori, hepatitis and human papilloma viruses).

CONCLUSIONS

Most well-documented biomarkers of cancer risk without evidence of bias pertain to infectious agents. Conversely, an excess of statistically significant findings was observed in studies of IGF/insulin and inflammation systems, suggesting reporting biases.

Single nucleotide polymorphisms and risk of hepatocellular carcinoma in cirrhosis

Liver carcinogenesis is a complex and multi-factorial process, in which both environmental and genetic features interfere and contribute to malignant transformation. Patients with cirrhosis are particularly exposed and justify periodical screenings in order to detect the early development of hepatocellular carcinoma (HCC). The risk of HCC is, however, not identical from one patient to another. The identification of host factors that may also play an important role in HCC development may improve our understanding of the implications of the various biological pathways involved in liver carcinogenesis; such progress may as well help refine the selection of patients who could benefit from specific preventative measures or could be given adapted screening policies. Numerous candidate-gene studies have reported associations between single nucleotide polymorphisms (SNPs) and the presence of HCC. Some of these publications unfortunately suffer from major methodological drawbacks because of their case-control, retrospective and monocentric aspect. Prospective cohort studies conducted in large homogeneous populations and comprising a sufficient number of events during follow-up may overcome these pitfalls, but require a long time to be conducted and are still scarce. More recently, the first Genome Wide Association studies (GWAs) have enabled the identification of unsuspected loci that may be involved in various steps implicated in liver tumourigenesis. Taken together, these studies highlight variants that modulate oxidative stress, iron metabolism, inflammatory and immune responses, DNA repair mechanisms or systems involved in cell-cycle regulation as genetic traits susceptible to modify the natural history of cirrhotic patients and partly explain the observed differences in the risk of HCC occurrence. However, large genetic epidemiology studies in the field of cancer diseases have suggested the limited ability of polymorphic traits, alone, to refine individual prognosis. The integration of various panels of genes into clinical scores may in the near future define a "genomic risk prediction" specific to liver cancer developed in cirrhotic patients.

Association between benign thyroid and endocrine disorders and subsequent risk of thyroid cancer among 4.5 million U.S. male veterans

CONTEXT

Risk factors for thyroid cancer (TC) in males are poorly understood. OBJECTIVES, SETTING, AND PARTICIPANTS: Our aim was to evaluate the relationship between history of benign thyroid and endocrine disorders and risk of TC among 4.5 million male veterans admitted to U.S. Veterans Affairs hospitals between July 1, 1969, and September 30, 1996.

DESIGN

We conducted a retrospective cohort study based on hospital discharge records with 1053 cases of TC.

MAIN OUTCOME MEASURES

We estimated relative risks (RR) and computed 95% confidence intervals (CI) for TC using time-dependent Poisson regression models. To evaluate potential ascertainment bias and/or delayed diagnosis of TC, we also analyzed RR by time between diagnosis of benign disorder and TC (<5 or ≥ 5 yr).

RESULTS

RR for TC were significantly elevated with many disorders and were often higher less than 5 yr compared with 5 yr or more before TC diagnosis. RR (95% CI) less than 5 yr/at least 5 yr were 67.9 (42.4-108.8)/28.9 (9.2-90.2) for thyroid adenoma, 77.8 (64.5-93.1)/25.9 (17.9-38.0) for nontoxic nodular goiter, 23.9 (13.8-41.3)/12.9 (4.8-34.4) for thyroiditis, 8.8 (6.9-11.3)/6.0 (3.8-9.6) for hypothyroidism, 6.4 (4.4-9.4)/ 2.0 (0.8-4.8) for thyrotoxicosis, and 1.2 (1.0-1.4)/1.1 (0.9-1.5) for diabetes. For some disorders, RR also significantly varied by attained age and race with younger patients and Blacks having higher RR than older patients and Whites.

CONCLUSIONS

We found strong associations for a history of thyroid adenoma, nodular goiter, thyroiditis, or hypothyroidism with TC in males allowing for increased surveillance/delayed diagnosis and evidence that some of these associations are modified by age and race.

Gene discovery in familial cancer syndromes by exome sequencing: prospects for the elucidation of familial colorectal cancer type X

Recent advances in genotyping and sequencing technologies have provided powerful tools with which to explore the genetic basis of both Mendelian (monogenic) and sporadic (polygenic) diseases. Several hundred genome-wide association studies have so far been performed to explore the genetics of various polygenic or complex diseases including those cancers with a genetic predisposition. Exome sequencing has also proven very successful in elucidating the etiology of a range of hitherto poorly understood Mendelian disorders caused by high-penetrance mutations. Despite such progress, the genetic etiology of several familial cancers, such as familial colorectal cancer type X, has remained elusive. Familial colorectal cancer type X and Lynch syndrome are similar in terms of their fulfilling certain clinical criteria, but the former group is not characterized by germline mutations in DNA mismatch-repair genes. On the other hand, the genetics of sporadic colorectal cancer have been investigated by genome-wide association studies, leading to the identification of multiple new susceptibility loci. In addition, there is increasing evidence to suggest that familial and sporadic cancers exhibit similarities in terms of their genetic etiologies. In this review, we have summarized our current knowledge of familial colorectal cancer type X, discussed current approaches to probing its genetic etiology through the application of new sequencing technologies and the recruitment of the results of colorectal cancer genome-wide association studies, and explore the challenges that remain to be overcome given the uncertainty of the current genetic model (ie, monogenic vs polygenic) of familial colorectal cancer type X.

The MTAP-CDKN2A locus confers susceptibility to a naturally occurring canine cancer

BACKGROUND

Advantages offered by canine population substructure, combined with clinical presentations similar to human disorders, makes the dog an attractive system for studies of cancer genetics. Cancers that have been difficult to study in human families or populations are of particular interest. Histiocytic sarcoma is a rare and poorly understood neoplasm in humans that occurs in 15% to 25% of Bernese Mountain Dogs (BMD).

METHODS

Genomic DNA was collected from affected and unaffected BMD in North America and Europe. Both independent and combined genome-wide association studies (GWAS) were used to identify cancer-associated loci. Fine mapping and sequencing narrowed the primary locus to a single gene region.

RESULTS

Both populations shared the same primary locus, which features a single haplotype spanning MTAP and part of CDKN2A and is present in 96% of affected BMD. The haplotype is within the region homologous to human chromosome 9p21, which has been implicated in several types of cancer.

CONCLUSIONS

We present the first GWAS for histiocytic sarcoma in any species. The data identify an associated haplotype in the highly cited tumor suppressor locus near CDKN2A. These data show the power of studying distinctive malignancies in highly predisposed dog breeds.

IMPACT

Here, we establish a naturally occurring model of cancer susceptibility due to CDKN2 dysregulation, thus providing insight about this cancer-associated, complex, and poorly understood genomic region.

Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on chromosome 4--the AdAPT method

Background

Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS.

Methods

We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer.

Results

Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p_trend] = 2.5×10⁻³). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76–0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found.

Conclusion

This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).

Complex-disease networks of trait-associated single-nucleotide polymorphisms (SNPs) unveiled by information theory

Objective

Thousands of complex-disease single-nucleotide polymorphisms (SNPs) have been discovered in genome-wide association studies (GWAS). However, these intragenic SNPs have not been collectively mined to unveil the genetic architecture between complex clinical traits. The authors hypothesize that biological annotations of host genes of trait-associated SNPs may reveal the biomolecular modularity across complex-disease traits and offer insights for drug repositioning.

Methods

Trait-to-polymorphism (SNPs) associations confirmed in GWAS were used. A novel method to quantify trait–trait similarity anchored in Gene Ontology annotations of human proteins and information theory was developed. The results were then validated with the shortest paths of physical protein interactions between biologically similar traits.

Results

A network was constructed consisting of 280 significant intertrait similarities among 177 disease traits, which covered 1438 well-validated disease-associated SNPs. Thirty-nine percent of intertrait connections were confirmed by curators, and the following additional studies demonstrated the validity of a proportion of the remainder. On a phenotypic trait level, higher Gene Ontology similarity between proteins correlated with smaller ‘shortest distance’ in protein interaction networks of complexly inherited diseases (Spearman p<2.2×10⁻¹⁶). Further, ‘cancer traits’ were similar to one another, as were ‘metabolic syndrome traits’ (Fisher's exact test p=0.001 and 3.5×10⁻⁷, respectively).

Conclusion

An imputed disease network by information-anchored functional similarity from GWAS trait-associated SNPs is reported. It is also demonstrated that small shortest paths of protein interactions correlate with complex-disease function. Taken together, these findings provide the framework for investigating drug targets with unbiased functional biomolecular networks rather than worn-out single-gene and subjective canonical pathway approaches.

Infrared spectroscopy and microscopy in cancer research and diagnosis

Since the middle of 20(th) century infrared (IR) spectroscopy coupled to microscopy (IR microspectroscopy) has been recognized as a non destructive, label free, highly sensitive and specific analytical method with many potential useful applications in different fields of biomedical research and in particular cancer research and diagnosis. Although many technological improvements have been made to facilitate biomedical applications of this powerful analytical technique, it has not yet properly come into the scientific background of many potential end users. Therefore, to achieve those fundamental objectives an interdisciplinary approach is needed with basic scientists, spectroscopists, biologists and clinicians who must effectively communicate and understand each other's requirements and challenges. In this review we aim at illustrating some principles of Fourier transform (FT) Infrared (IR) vibrational spectroscopy and microscopy (microFT-IR) as a useful method to interrogate molecules in specimen by mid-IR radiation. Penetrating into basics of molecular vibrations might help us to understand whether, when and how complementary information obtained by microFT-IR could become useful in our research and/or diagnostic activities. MicroFT-IR techniques allowing to acquire information about the molecular composition and structure of a sample within a micrometric scale in a matter of seconds will be illustrated as well as some limitations will be discussed. How biochemical, structural, and dynamical information about the systems can be obtained by bench top microFT-IR instrumentation will be also presented together with some methods to treat and interpret IR spectral data and applicative examples. The mid-IR absorbance spectrum is one of the most information-rich and concise way to represent the whole "… omics" of a cell and, as such, fits all the characteristics for the development of a clinically useful biomarker.

Selenium, selenoproteins and the thyroid gland: interactions in health and disease

The trace element selenium is an essential micronutrient that is required for the biosynthesis of selenocysteine-containing selenoproteins. Most of the known selenoproteins are expressed in the thyroid gland, including some with still unknown functions. Among the well-characterized selenoproteins are the iodothyronine deiodinases, glutathione peroxidases and thioredoxin reductases, enzymes involved in thyroid hormone metabolism, regulation of redox state and protection from oxidative damage. Selenium content in selenium-sensitive tissues such as the liver, kidney or muscle and expression of nonessential selenoproteins, such as the glutathione peroxidases GPx1 and GPx3, is controlled by nutritional supply. The thyroid gland is, however, largely independent from dietary selenium intake and thyroid selenoproteins are preferentially expressed. As a consequence, no explicit effects on thyroid hormone profiles are observed in healthy individuals undergoing selenium supplementation. However, low selenium status correlates with risk of goiter and multiple nodules in European women. Some clinical studies have demonstrated that selenium-deficient patients with autoimmune thyroid disease benefit from selenium supplementation, although the data are conflicting and many parameters must still be defined. The baseline selenium status of an individual could constitute the most important parameter modifying the outcome of selenium supplementation, which might primarily disrupt self-amplifying cycles of the endocrine-immune system interface rectifying the interaction of lymphocytes with thyroid autoantigens. Selenium deficiency is likely to constitute a risk factor for a feedforward derangement of the immune system-thyroid interaction, while selenium supplementation appears to dampen the self-amplifying nature of this derailed interaction.

Comprehensive field synopsis and systematic meta-analyses of genetic association studies in cutaneous melanoma

BACKGROUND

Although genetic studies have reported a number of loci associated with cutaneous melanoma (CM) risk, a comprehensive synopsis of genetic association studies published in the field and systematic meta-analysis for all eligible polymorphisms have not been reported.

METHODS

We systematically annotated data from all genetic association studies published in the CM field (n = 145), including data from genome-wide association studies (GWAS), and performed random-effects meta-analyses across all eligible polymorphisms on the basis of four or more independent case-control datasets in the main analyses. Supplementary analyses of three available datasets derived from GWAS and GWAS-replication studies were also done. Nominally statistically significant associations between polymorphisms and CM were graded for the strength of epidemiological evidence on the basis of the Human Genome Epidemiology Network Venice criteria. All statistical tests were two-sided.

RESULTS

Forty-two polymorphisms across 18 independent loci evaluated in four or more datasets including candidate gene studies and available GWAS data were subjected to meta-analysis. Eight loci were identified in the main meta-analyses as being associated with a risk of CM (P < .05) of which four loci showed a genome-wide statistically significant association (P < 1 × 10(-7)), including 16q24.3 (MC1R), 20q11.22 (MYH7B/PIGU/ASIP), 11q14.3 (TYR), and 5p13.2 (SLC45A2). Grading of the cumulative evidence by the Venice criteria suggested strong epidemiological credibility for all four loci with genome-wide statistical significance and one additional gene at 9p23 (TYRP1). In the supplementary meta-analyses, a locus at 9p21.3 (CDKN2A/MTAP) reached genome-wide statistical significance with CM and had strong epidemiological credibility.

CONCLUSIONS

To the best of our knowledge, this is the first comprehensive field synopsis and systematic meta-analysis to identify genes associated with an increased susceptibility to CM.

Kernel machine SNP-set analysis for censored survival outcomes in genome-wide association studies

In this article, we develop a powerful test for identifying single nucleotide polymorphism (SNP)-sets that are predictive of survival with data from genome-wide association studies. We first group typed SNPs into SNP-sets based on genomic features and then apply a score test to assess the overall effect of each SNP-set on the survival outcome through a kernel machine Cox regression framework. This approach uses genetic information from all SNPs in the SNP-set simultaneously and accounts for linkage disequilibrium (LD), leading to a powerful test with reduced degrees of freedom when the typed SNPs are in LD with each other. This type of test also has the advantage of capturing the potentially nonlinear effects of the SNPs, SNP-SNP interactions (epistasis), and the joint effects of multiple causal variants. By simulating SNP data based on the LD structure of real genes from the HapMap project, we demonstrate that our proposed test is more powerful than the standard single SNP minimum P-value-based test for association studies with censored survival outcomes. We illustrate the proposed test with a real data application.

Evaluation of polygenic risk scores for predicting breast and prostate cancer risk

Recently, polygenic risk scores (PRS) have been shown to be associated with certain complex diseases. The approach has been based on the contribution of counting multiple alleles associated with disease across independent loci, without requiring compelling evidence that every locus had already achieved definitive genome-wide statistical significance. Whether PRS assist in the prediction of risk of common cancers is unknown. We built PRS from lists of genetic markers prioritized by their association with breast cancer (BCa) or prostate cancer (PCa) in a training data set and evaluated whether these scores could improve current genetic prediction of these specific cancers in independent test samples. We used genome-wide association data on 1,145 BCa cases and 1,142 controls from the Nurses' Health Study and 1,164 PCa cases and 1,113 controls from the Prostate Lung Colorectal and Ovarian Cancer Screening Trial. Ten-fold cross validation was used to build and evaluate PRS with 10 to 60,000 independent single nucleotide polymorphisms (SNPs). For both BCa and PCa, the models that included only published risk alleles maximized the cross-validation estimate of the area under the ROC curve (0.53 for breast and 0.57 for prostate). We found no significant evidence that PRS using common variants improved risk prediction for BCa and PCa over replicated SNP scores.

Physical confirmation and mapping of overlapping rat mammary carcinoma susceptibility QTLs, Mcs2 and Mcs6

Only a portion of the estimated heritability of breast cancer susceptibility has been explained by individual loci. Comparative genetic approaches that first use an experimental organism to map susceptibility QTLs are unbiased methods to identify human orthologs to target in human population-based genetic association studies. Here, overlapping rat mammary carcinoma susceptibility (Mcs) predicted QTLs, Mcs6 and Mcs2, were physically confirmed and mapped to identify the human orthologous region. To physically confirm Mcs6 and Mcs2, congenic lines were established using the Wistar-Furth (WF) rat strain, which is susceptible to developing mammary carcinomas, as the recipient (genetic background) and either Wistar-Kyoto (WKy, Mcs6) or Copenhagen (COP, Mcs2), which are resistant, as donor strains. By comparing Mcs phenotypes of WF.WKy congenic lines with distinct segments of WKy chromosome 7 we physically confirmed and mapped Mcs6 to ∼33 Mb between markers D7Rat171 and gUwm64-3. The predicted Mcs2 QTL was also physically confirmed using segments of COP chromosome 7 introgressed into a susceptible WF background. The Mcs6 and Mcs2 overlapping genomic regions contain multiple annotated genes, but none have a clear or well established link to breast cancer susceptibility. Igf1 and Socs2 are two of multiple potential candidate genes in Mcs6. The human genomic region orthologous to rat Mcs6 is on chromosome 12 from base positions 71,270,266 to 105,502,699. This region has not shown a genome-wide significant association to breast cancer risk in pun studies of breast cancer susceptibility.

Therapy-related myeloid neoplasms: pathobiology and clinical characteristics

Therapy-related myeloid neoplasms (t-MNs) are serious long-term consequences of cytotoxic treatments for an antecedent disorder. t-MNs are observed after ionizing radiation as well as conventional chemotherapy including alkylating agents, topoisomerase-II-inhibitors and antimetabolites. In addition, adjuvant use of recombinant human granulocyte-colony stimulating factor may also increase the risk of t-MNs. There is clinical and biological overlap between t-MNs and high-risk de novo myelodysplastic syndromes and acute myeloid leukaemia suggesting similar mechanisms of leukaemogenesis. Human studies and animal models point to a prominent role of genetic susceptibilty in the pathogenesis of t-MNs. Common genetic variants have been identified that modulate t-MN risk, and t-MNs have been observed in some cancer predisposition syndromes. In either case, establishing a leukaemic phenotype requires acquisition of somatic mutations - most likely induced by the cytotoxic treatment. Knowledge of the specific nature of the initiating exposure has allowed the identification of crucial pathogenetic mechanisms and for these to be modelled in vitro and in vivo. Prognosis of patients with t-MNs is dismal and at present, the only curative approach for the majority of these individuals is haematopoietic stem cell transplantation, which is characterized by high transplant-related mortality rates. Novel transplantation strategies using reduced intensity conditioning regimens as well as novel drugs - demethylating agents and targeted therapies - await clinical testing and may improve outcome. Ultimately, individual assessment of genetic risk factors may translate into tailored therapies and establish a strategy for reducing t-MN incidences without jeopardizing therapeutic success rates for the primary disorders.

Colon cancer-related microRNAs: implications for translational research

Colon carcinogenesis is a stepwise progression from polyps to adenocarcinomas and distant metastasis. These pathologic changes are contributed by aberrant activation or inactivation of protein-coding proto-oncogenes and tumor suppressor genes. However, recent discoveries in microRNA research have reshaped our understanding of the role of non-protein-coding genes in carcinogenesis. In this regard, a remarkable number of microRNAs exhibit differential expression in colon cancer tissues. These microRNAs alter cell proliferation, apoptosis and metastasis through their interactions with intracellular signaling networks. From a clinical perspective, polymorphisms within microRNA-binding sites are associated with the risk for colon cancer while microRNAs isolated from feces or blood may serve as biomarkers for early diagnosis. Altered expression of microRNAs or polymorphisms in microRNA-related genes have also been shown to correlate with patient survival or treatment outcome. Further insights into microRNA dysregulation in colon cancer and the advancement of RNA delivery technology will make it very likely to develop novel microRNA-based therapeutics.

Future research perspectives on environment and health: the requirement for a more expansive concept of translational cancer research

The last two decades have seen exciting advances in understanding the human genome, aided by the development of powerful analytical laboratory tools. These advances have enabled genome-wide association studies to link specific genetic variants with an altered risk of cancer. Unfortunately there has not been an analogous refinement of tools on such a comprehensive scale to permit an equally thorough investigation of environmental factors, yet it is known that these play a major role in cancer etiology. This limitation led to the suggested need for an exposome to match the genome. Major advances both in understanding mechanisms of carcinogenesis as well as in the technology to investigate these underlying steps in the disease process offer the potential to redress this imbalance between exposome and genome. This is all the more important in order to fully exploit the large prospective cohort studies with biological specimens now being established to investigate the environmental and genetic basis of common chronic diseases. Currently translational cancer research is understood to equate to a "bench to bedside" process, focused on improved clinical management of cancer. Unfortunately, alone, this is an inadequate response to the growing burden of cancer worldwide. Priority also needs to be placed on understanding the causes of cancer, its prevention and, critically, how to implement promising interventions into health care structures. The need therefore is to translate basic science to the population in parallel to the translation into the clinic. This "two-way" translational cancer research encourages the common soil of basic science to be applied both to the prevention of cancer and to its treatment. In this way the notable advances in relation to carcinogenesis will yield a richer benefit to society through balanced initiatives to understand the causes and prevention of cancer in addition to more effective treatment and care of those people developing the disease.

Most lung and colon cancer susceptibility genes are pair-wise linked in mice, humans and rats

Genetic predisposition controlled by susceptibility quantitative trait loci (QTLs) contributes to a large proportion of common cancers. Studies of genetics of cancer susceptibility, however, did not address systematically the relationship between susceptibility to cancers in different organs. We present five sets of data on genetic architecture of colon and lung cancer susceptibility in mice, humans and rats. They collectively show that the majority of genes for colon and lung cancer susceptibility are linked pair-wise and are likely identical or related. Four CcS/Dem recombinant congenic strains, each differing from strain BALB/cHeA by a different small random subset of ±12.5% of genes received from strain STS/A, suggestively show either extreme susceptibility or extreme resistance for both colon and lung tumors, which is unlikely if the two tumors were controlled by independent susceptibility genes. Indeed, susceptibility to lung cancer (Sluc) loci underlying the extreme susceptibility or resistance of such CcS/Dem strains, mapped in 226 (CcS-10×CcS-19)F2 mice, co-localize with susceptibility to colon cancer (Scc) loci. Analysis of additional Sluc loci that were mapped in OcB/Dem strains and Scc loci in CcS/Dem strains, respectively, shows their widespread pair-wise co-localization (P = 0.0036). Finally, the majority of published human and rat colon cancer susceptibility genes map to chromosomal regions homologous to mouse Sluc loci. 12/12 mouse Scc loci, 9/11 human and 5/7 rat colon cancer susceptibility loci are close to a Sluc locus or its homologous site, forming 21 clusters of lung and colon cancer susceptibility genes from one, two or three species. Our data shows that cancer susceptibility QTLs can have much broader biological effects than presently appreciated. It also demonstrates the power of mouse genetics to predict human susceptibility genes. Comparison of molecular mechanisms of susceptibility genes that are organ-specific and those with trans-organ effects can provide a new dimension in understanding individual cancer susceptibility.

Genetic basis for susceptibility to lung cancer: Recent progress and future directions

Lung cancer is the leading cause of cancer death worldwide, and cigarette smoking is the major environmental factor for its development. To elucidate the genetic differences in the susceptibility to lung cancer among individuals, genetic factors involved in tobacco-induced lung cancers have been extensively investigated and a number of genetic polymorphisms have been identified to date as candidates. Most of the polymorphisms identified are of genes encoding proteins associated with the activity to metabolize tobacco smoke carcinogens and to suppress mutations induced by those carcinogens, and functional significances have been elucidated for some of these polymorphisms. However, the significance of these polymorphisms in the contribution to lung cancer development still remains unclear. Recently, several novel lung cancer susceptibility genes, including those on chromosomes 5p15.33, 6p21, and 15q24-25.1, have been identified by large-scale genome-wide association (GWA) studies. The 15q25 region contains three nicotine acetylcholine receptor subunit genes, and their polymorphisms have been also reported as being associated with nicotine dependence. The 5p15.33 region is associated with risks specifically for lung adenocarcinoma, the commonest histological type and weakly associated with smoking. This locus has been shown to be associated with risks for a wide variety of cancers, including lung adenocarcinoma. Associations of the 6q21 region have not been consistently replicated among studies. The 6q23-25 and 13q31.3 regions were also identified by recent GWA studies as being associated with risk for lung cancer, particularly in never-smokers. However, contributions of genetic differences on these five loci to the susceptibility to overall lung cancer seem to be small. There are several molecular pathways for the development of lung adenocarcinomas, and environmental factors for their development are still unclear, especially those in never-smokers. In addition, geographic differences as well as gender differences in lung cancer risk have been indicated. Furthermore, various genes identified by candidate gene association studies have not been reevaluated for their significance together with genes identified by GWA studies in the same population. Therefore, further studies will be necessary to assess the individual susceptibility to lung cancer based on the combination of polymorphisms in multiple genes, and to establish a novel way of evaluating the individual risk for lung cancer for its prevention.

Genetic variation in the prostate stem cell antigen gene and upper gastrointestinal cancer in white individuals

BACKGROUND & AIMS

An association between gastric cancer and the rs2294008 (C>T) polymorphism in the prostate stem cell antigen (PSCA) gene has been reported for several Asian populations. We set out to determine whether such an association exists in white individuals.

METHODS

We genotyped 166 relatives of gastric cancer patients, including 43 Helicobacter pylori-infected subjects with hypochlorhydria and gastric atrophy, 65 infected subjects without these abnormalities, 58 H pylori-negative relatives, and 100 population controls. Additionally, a population-based study of chronic atrophic gastritis provided 533 cases and 1054 controls. We then genotyped 2 population-based, case-control studies of upper gastrointestinal cancer: the first included 312 gastric cancer cases and 383 controls; the second included 309 gastric cancer cases, 159 esophageal cancer cases, and 211 controls. Odds ratios were computed from logistic models and adjusted for confounding variables.

RESULTS

Carriage of the risk allele (T) of rs2294008 in PSCA was associated with chronic atrophic gastritis (adjusted odds ratio [OR], 1.5; 95% confidence interval [CI]: 1.1-1.9) and noncardia gastric cancer (OR, 1.9; 95% CI: 1.3-2.8). The association was strongest for the diffuse histologic type (OR, 3.2; 95% CI: 1.2-10.7). An inverse association was observed between carriage of the risk allele and gastric cardia cancer (OR, 0.5; 95% CI: 0.3-0.9), esophageal adenocarcinoma (OR, 0.5; 95% CI: 0.3-0.9), and esophageal squamous cell carcinoma (OR, 0.4; 95% CI: 0.2-0.9).

CONCLUSIONS

The rs2294008 polymorphism in PSCA increases the risk of noncardia gastric cancer and its precursors in white individuals but protects against proximal cancers.

Replication of genome-wide discovered breast cancer risk loci in the Cypriot population

Genome-wide association studies (GWAS) have identified associations with robust statistical support for influencing breast cancer susceptibility. Most GWAS and replications have been conducted in Northern European populations and to a lesser extent in Asians, and Ashkenazi Jews. It is important to evaluate whether these variants confer risk across different populations and also to assess the magnitude of risk conferred. The aim of this study was to evaluate previously GWAS-identified breast cancer risk variants in the Cypriot population. Eleven GWAS-discovered single nucleotide polymorphisms (SNPs) were analyzed for association with breast cancer in 1,109 Cypriot female breast cancer patients and 1,177 healthy female controls. Four of the 11 SNPs evaluated were found to be nominally significantly associated (P < 0.05) with breast cancer risk in the Cypriot population. Based on estimated power, five associations would be expected to be nominally significant. The correlation coefficient of effect sizes (per-allele odds ratio) between the Cypriot population and the original GWAS populations where these SNPs had been discovered was 0.58 (P = 0.064), while allele frequencies were very similar (r = 0.88, P < 0.001). Overall, we show modest concordance for breast cancer GWAS-discovered alleles and their effect sizes in the Cypriot population. The effects sizes of GWAS-discovered SNPs need to be verified separately in different populations.