bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract IA10: Deciphering the signals from the GWAS hits: From function to epidemiology and back again.
Authors: Gayther Simon A. 
Published: August 2013

Abstract
Genome wide association studies (GWAS) have identified hundreds of single nucleotide polymorphisms (SNPs) that confer susceptibility to a multitude of complex, multifactorial disease traits including cardiovascular disease, diabetes, and several cancers. For the vast majority of identified common genetic variants, the functional rationale underlying disease is largely unknown. The functional effects of common risk associated SNPs are likely to be subtle given that they confer smaller risks (ORs &lt;1.2). More than 90% of confirmed common risk-SNPs lie in non-coding DNA, often several kilobases from the nearest gene suggesting a critical role for non-coding DNA in the functional influence of these SNPs. A significant focus of functional follow-up studies at common susceptibility loci has therefore been to understand the interplay between non-coding DNA elements such as regulators and enhancers, non-coding RNA species such as micro- and long non-coding RNAs, and risk associated germline variants.
GWAS studies have also highlighted regions of the genome that contain plausible cancer susceptibility genes that may be specific to disease etiology (e.g. the FGFR gene in breast cancer), and other genes that may play more general role in cancer (e.g. the TERT gene, multi-cancer risk locus). The current presentation will focus on ovarian cancer. The Ovarian Cancer Association Consortium (OCAC) has identified 11 confirmed susceptibility loci, and suggest multiple candidate genes that have either previously been implicated in ovarian cancer development, or function in pathways such as double strand DNA break and nucleotide excision repair, which suggests they may play a significant role in ovarian cancer risk and/or clinical outcome. Data presented will describe approaches to understanding the functional role of both susceptibility SNPs and candidate genes in the underlying cellular etiology of different subtypes of ovarian cancer, and provide evidence suggesting a role of candidate genes in disease initiation and treatment response. Overall, these studies highlight the challenges we face in the developing field of functional-epidemiology, in particular in understanding common low-penetrance susceptibility loci. However, the emerging data also provide support for the role of GWAS in unearthing critical, previously unknown mechanisms that underlie cancer biology, suggesting these studies may have a substantial clinical impact in the future.
Citation Format: Simon A. Gayther. Deciphering the signals from the GWAS hits: From function to epidemiology and back again. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA10.
Abstract IA13: Chemicals in the environment: BPA and other worries.
Authors: Prins Gail S. 
Published: August 2013

Abstract
While early-life estrogens are thought to play a physiological role in normal prostate gland development and function, inappropriate estrogenic exposures either in timing, dose or type can reprogram the gland and increase susceptibility to abnormal growth with aging including carcinogenesis. Our research using a rat model indicates that estrogen imprinting of the prostate is mediated through structural reorganization of the gland early in life as well as epigenomic reprogramming that together permits life-long memory of the inappropriate developmental exposures. While high-dose estrogen exposures during a critical developmental window (as a model for pharmacologic agents such as DES) lead directly to prostate neoplasia that can progress to carcinoma with aging, early-life exposure to low-dose estradiol or the endocrtine disruptor bisphenol A (BPA) over a range of doses (0.1 to 5,000 ug BPA/kg BW) increases susceptibility of the adult prostate to carcinogenesis driven by elevated estradiol, as occurs in aging males. Data presented will provide a conceptual frame-work for understanding how early life estrogen-exposures via epigenetic reprogramming interact with later-life events through the disruption of pre-set gene expression programs for multiple genes. To assess whether the human prostate may be similarly reprogrammed during early life by hormones and EDCs, we have developed in vitro and in vivo models using normal human prostate stem/progenitor cells. Cultured prostaspheres composed of prostate stem and early-stage progenitor cells express robust levels of ERα, ERβ and GPR30 and exhibit a proliferative response with increased stem cell side populations to low-dose estradiol and BPA. Although AR negative, prostasphere cells express RARs, RXRs and aryl hydrocarbon receptor. While low-dose retinoic acid stimulated prostasphere cell differentiation, arsenic and dioxin perturbed their growth. Together these findings indicate that early stage progenitor and stem cells in the human prostate may be direct targets of EDCs and suggest that humans may be susceptible to prostate disease in a manner similar to the rodent models.
Citation Format: Gail S. Prins. Chemicals in the environment: BPA and other worries. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA13.
Abstract IA16: Susceptibility to neoplasia following HPV infection.
Authors: Schiffman Mark 
Published: August 2013

Abstract
Cervical cancer is caused by persistent infection with one of approximately a dozen carcinogenic human papillomavirus (HPV) infections. HPV16 is the most carcinogenic HPV type, causing one half of cases worldwide.
Cervical cancer arises via three well-defined steps: acute HPV infection; viral persistence linked to development of a high-grade intraepithelial lesion, and invasion. Infections peak in late adolescence and early adulthood, high-grade lesions grow superficially in the years following infection, and invasion of high-grade lesions typically takes decades to occur.
Host susceptibility given exposure to HPV is best considered by stage of the carcinogenic process. Infection is nearly ubiquitous among sexually active women, who appear (at our present state of knowledge) to be universally susceptible if previously unexposed. Common exposure leads to at least partial type-specific immunity as women age. Virtually all infections “clear” within 1-2 years and failure to clear, i.e., persistence, is highly associated with development of a high-grade lesion. Susceptibility to viral persistence is poorly understood, but is apparently the major determinant of carcinogenic risk from infection. If undiagnosed and untreated, high-grade lesions invade in a substantial minority of cases and we have determined no definitively established determinants of susceptibility to invasion.
Accordingly, this talk will focus on what is known about risk factors for HPV persistence/high-grade lesions given HPV infection. The risk factors can be divided conceptually into three groups: 1) viral factors, 2) host behavioral factors, and 3) intrinsic host factors.
Definite viral factors include HPV genetic factors (type and variant lineage) and HPV epigenetic factors (viral methylation). Established host behavioral factors include smoking, long-term oral contraceptive use, and multiparity; the associations are firm but mechanisms are not known. The few known intrinsic host factors include immune status (e.g., HIV immunosuppression), possibly specific HLA associations, and possibly some common genetic variants and methylation patterns. The leading candidates will be mentioned.
Understanding of the viral-host interaction has led to promising biomarkers used to distinguish between acute HPV infection and high-grade lesions, most notably p16 staining, a marker of disruption of the Rb pathway.
Citation Format: Mark Schiffman. Susceptibility to neoplasia following HPV infection. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA16.
Abstract IA18: Large-scale familial whole genome sequencing to evaluate genetic risk.
Authors: Vockley Joseph , Iyer Ramaswamy , Huddleston Kathi , Niederhuber John 
Published: August 2013

Abstract
Whole genome sequencing (WGS) technology and analysis is quickly approaching the stage of development where it can become a medically recognized procedure for prognostics as well as diagnostics. Critical to the development of medical-grade whole genome sequencing is the ability to recognize and minimize technological and biological variation in WGS data. The Inova Translational Medicine Institute (ITMI) has completed a study that generated 1500 whole genome sequences in 15 months and recently launched a study that will generate 20,000 WGS over the next two years. The 1500 sequenced genomes were from individuals from 53 countries, representing four major ancestral groups and many minor sub-groups. ITMI used these data to generate a database of ancestral-specific variants. This database can be used to identify single nucleotide variants in patients with a specific ancestral background as ancestral-specific sequences instead of mutations. This ancestral information was applied to the 487 cancer genes identified in the Wellcome Trust Sanger Institute's Cancer Gene Census, in an attempt to identify germline mutations in these genes, in our cohort of 1500 participants. The result of this analysis identifies the incidence and type of germline mutations in various ethnic groups. The ethical question that remains is what to do with incidental finding of this type as medical whole genome sequencing becomes a common tool in the practice of medicine.
Citation Format: Joseph Vockley, Ramaswamy Iyer, Kathi Huddleston, John Niederhuber. Large-scale familial whole genome sequencing to evaluate genetic risk. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA18.
Abstract IA19: The GAME-ON (Genetic Associations and Mechanisms in Oncology) Consortium: Assessing the functional relevance of genetic variation.
Authors: Monteiro Alvaro N.A. 
Published: August 2013

Abstract
Recently, significant advances in genetics, in particular in genome-wide association studies (GWAS), have uncovered a large number of chromosomal loci associated with cancer risk. Despite these advances the determination of the molecular mechanism behind the detected associations has proven to be a significant challenge. The design of most GWAS genotyping chips take advantage of well characterized tagging single nucleotide polymorphisms (SNPs). These “tags” represent specific proxy markers for a series of other SNPs in high linkage disequilibrium with the tagging SNP in a defined chromosomal region. While the use of tagging SNPs result in reproducible and robust signals during genotyping and minimize the number of SNPs to be tested, the expectation is that they may not necessarily constitute the causal SNP, the nucleotide change that result in a relevant biological activity responsible for cancer predisposition.
Identification of predisposition loci in prostate, ovary, and breast have been accelerated by the COGS (Collaborative Oncologic Gene-Environment Study) project which typed 200,000 SNPs and genotyped an unprecedented number of cancer cases and controls (˜200,000). The GAME-ON (Genetic Associations and Mechanisms in Oncology) consortium has poured over GWAS data for prostate, ovary, breast, lung, and colorectal cancers to develop systematic procedures to dissect functional contribution of SNPs and their target genes. Here I describe our experience in conducting functional analyses for these loci, focusing on ovarian cancer susceptibility loci.
The overall approach can be loosely divided in three stages: in the first we use the most significant SNP found in GWAS analyses or meta-analyses as a starting point to interrogate other candidate functional SNPs in the region. The second stage explores potential target genes in the region. Finally, we focus on tying the candidate functional SNP to the candidate target gene. This final stage may also focus on, depending on the availability of in vivo models, attempts to uncover direct evidence for the participation of the SNP/target gene pairs in the mechanism of oncogenesis. Although in some cases the analytic approaches and tools might be specific to the cancer in question, we feel that the main framework can be utilized for different cancers. Most importantly, perhaps, are the lessons learned during this process as well as identifying the limitations and challenges that lay ahead.
Citation Format: Alvaro N.A. Monteiro. The GAME-ON (Genetic Associations and Mechanisms in Oncology) Consortium: Assessing the functional relevance of genetic variation. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA19.
Abstract IA20: The NCI Cohort Consortium: Increasing power, enhancing collaborations, advancing science.
Authors: Winn Deborah M. 
Published: August 2013

Abstract
The Cohort Consortium is an extramural-intramural partnership formed by the National Cancer Institute (NCI) to foster communication among investigators leading cohort studies of cancer; promote collaborative research projects for topics not easily addressed in a single study; and identify common challenges in cohort research and search for solutions. The Cohort Consortium includes investigators responsible for more than 40 high-quality cancer epidemiology cohorts involving more than 4 million people. The cohorts are international in scope and cover large, rich, and diverse populations. Extensive risk factor data are available on each cohort, and biospecimens, including germline DNA collected at baseline, are available on more than 2 million individuals. Investigators team up to use common protocols and methods, and to conduct coordinated parallel and pooled analyses. Some recent accomplishments include publications of genome-wide association studies of pancreatic cancer and on the effect of high body mass index on mortality after eliminating the influence of tobacco smoking and co-morbidities. The Consortium provides a forum to discuss scientific questions in cancer research that cohort studies can help address such as how metabolomics can best be examined in human population studies and how cohort studies can better address the role of physical and chemical agents on cancer risk. It also can focus attention on new methodologies such as the use of social media and new ways of interacting with cohort study participants that could enhance data collection, data quality, and study participant retention and engagement.
Citation Format: Deborah M. Winn. The NCI Cohort Consortium: Increasing power, enhancing collaborations, advancing science. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA20.
Abstract IA22: From the genome to the metabolome: The promises and limits of metabolomics.
Authors: Daniel Hannelore 
Published: August 2013

Abstract
Metabolomics is the youngest of the profiling techniques employed in the life sciences. It assesses alterations in the pool of metabolites in a biological sample by using nuclear magnetic resonance (NMR) or mass spectrometry techniques (MS) coupled to liquid or gas chromatography. Metabolite profiling is mainly employed to identify exposure markers or disease related biomarkers. The latter currently dominates by profiling of plasma and/or urine samples in large cohort studies associated with disease endpoints. It may also include genotyping with the goal to link changes in the metabolome to single nucleotide polymorphisms or changes in gene/protein expression. By examples from research on type 2 diabetes and partly on cancers a critical assessment of identified “biomarkers” in terms of specificity and sensitivity will be presented. Intrinsic to most cohort studies is that only a few samples (usually collected after overnight fasting) are available for analysis. This neglects the dynamics of changes in the metabolome as a continuum of adaptations to environmental cues. Challenge experiments may allow a more comprehensive metabolic phenotyping of healthy and diseased humans. Moreover, metabolomics needs to move from the descriptive level that just measures concentrations of selected metabolites to new avenues that cover metabolites in entire pathways and by carrying out flux analysis for being explanatory.
Citation Format: Hannelore Daniel. From the genome to the metabolome: The promises and limits of metabolomics. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA22.
Abstract IA23: Using metabolomics in epidemiologic studies: An example for pancreatic cancer.
Authors: Wolpin Brian Matthew 
Published: August 2013

Abstract
Pancreatic cancer is the fourth-leading cause of cancer-related death in the United States. Among individuals who develop pancreatic adenocarcinoma, only 5% will survive 5 years after diagnosis and most patients live for &lt;12 months. Novel strategies for prevention and risk stratification are greatly needed.
Glucose intolerance has emerged as an important predisposing factor for pancreatic adenocarcinoma. Prospective studies have demonstrated an increased risk of pancreatic cancer with increasing body-mass index, a determinant of peripheral insulin resistance and a central risk factor for type II diabetes. Although controversy remains regarding causation versus consequence, diabetes has been associated with pancreatic cancer risk and fasting serum glucose and post-load plasma glucose have been linked with the subsequent risk of pancreatic cancer. Furthermore, studies have linked levels of circulating hormones to pancreatic cancer risk, including insulin, C-peptide and adiponectin. Studies are needed to better understand mechanisms underlying the higher risk of pancreatic cancer among individuals with impaired glucose processing
Metabolism denotes the conversion of food products into energy and the building blocks for cellular functioning. The high-throughput identification and quantification of small molecule metabolites produced by metabolism, including lipids, fatty acids, sugars, nucleotides, and amino acids, has been termed metabolomics. Metabolomics is increasingly being used to evaluate alterations in metabolism and their relationship to human disease. In epidemiologic studies, this technology has particular potential to advance our understanding of disease, as participants have provided information on a variety of exposures and diseases in addition to biologic samples.
Given the strong link between glucose intolerance and pancreatic cancer risk, we pursued a rigorous pilot program of a liquid chromatography/mass spectrometry (LC-MS) metabolomics platform for application to prospectively collected, archived plasma specimens in a nested case-control study of pancreatic adenocarcinoma. This pilot program highlighted important issues relevant to data analysis, including accounting for sample preservative type, sample processing delays, and fasting times. Furthermore, it helped define reproducibility of metabolites using actual archived participant samples. The application of metabolomics to large epidemiologic studies holds promise for defining new biomarkers of disease, including for pancreatic adenocarcinoma.
Citation Format: Brian Matthew Wolpin. Using metabolomics in epidemiologic studies: An example for pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA23.
Abstract PR1: LINE-1 %5-methyl cytosine levels in prediagnostic leukocyte DNA and future bladder cancer risk among PLCO and ATBC cohort subjects.
Authors: Andreotti Gabriella , Karami Sara , Pfeiffer Ruth , Hurwitz Lauren , Liao Linda , Weinstein Stephanie , Albanes Demetrius , Virtamo Jarmo , Silverman Debra , Rothman Nathaniel , Moore Lee 
Published: August 2013

Abstract
Background: Low global methylation levels measured in post-diagnostic case compared to healthy control blood DNA have been associated with elevated bladder cancer risk.
Objective: To examine this association using blood DNA collected prior to bladder cancer diagnosis.
Methods: Cases (n=437) and controls (N=847) were selected from the Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial (PLCO). A replication case-control study was conducted among males from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) cohort (391 cases/778 controls). LINE-1 percent 5-methyl-cytosine (LINE-1 %5-MeC) levels were quantified using bisulfite treated blood DNA and pyrosequencing. Cancer risk was assessed in deciles (D1-D10: 10-100%) and quartiles (Q1-Q4:25-100%) of methylation levels based on controls. Logistic regression was used to evaluate individual and pooled study data.
Findings: In PLCO, significantly lower bladder cancer risk was associated with the lowest LINE-1 %5-MeC decile (D1) compared to D2-D10 subjects adjusted for sex and pack-years of smoking (OR=0.35; 95% CI: 0.18-0.68, p=0.002). Findings were corroborated in the ATBC study, (D1 vs. D2-D10: OR=0.31;95% CI:0.17-0.57, p&lt;0.001) adjusting for pack-years of smoking and intervention assignment. When male data were pooled, a similar association was observed comparing D1 to D2-D10 subjects (OR=0.35;95% CI:0.21-0.57, p&lt;0.001) and by quartiles (OR Q1=0.53;95% CI:0.41-0.70, p&lt;0.001). Smoking status did not modify the associations.
Interpretation: Findings observed in two independent studies using pre-diagnostically collected bladder cancer case/control subject DNA support that higher methylation levels may reflect higher bladder cancer risk prior to diagnosis. Associations using pre-diagnostically collected blood DNA were opposite to those from previous case-control studies using post-diagnostic DNA, suggesting changes in methylation levels associated with the carcinogenic process. Additional prospective studies evaluating LINE1 and gene-specific CpG methylation levels are needed to replicate and extend these findings.
This proffered talk is also presented as Poster 11.
Citation Format: Gabriella Andreotti, Sara Karami, Ruth Pfeiffer, Lauren Hurwitz, Linda Liao, Stephanie Weinstein, Demetrius Albanes, Jarmo Virtamo, Debra Silverman, Nathaniel Rothman, Lee Moore. LINE-1 %5-methyl cytosine levels in prediagnostic leukocyte DNA and future bladder cancer risk among PLCO and ATBC cohort subjects. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr PR1.