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Introduction

Introduction Past genetics and epidemiology research has suggested that cancer has a complex etiology, and that both susceptibility genes and environmental risk factors play a defined role in its development. More recently, this dichotomous theory has yielded to complex, interactive models, involving the temporal and metabolic interplay of both sets of causative agents. This novel conceptual framework entails the disciplinary integration necessary for the identification and characterization of cancer susceptibility genes, the definition of their interactions with nongenetic risk factors during the process of cancer development, and the application of this knowledge to the assessment of cancer risk in diverse populations. In addition to the conceptual integration from related but traditionally separated disciplines, studying the genetic and environmental causative interaction that determines cancer susceptibility in individuals, families, and populations involves considerable operational challenges, such as the selection (or de novo development) of study designs appropriate to the question(s) proposed, the integration of complex models into pertinent analytic strategies, and the interdisciplinary synergy to support and conduct such studies in connection with a rapidly evolving methodologic and scientific milieu. For example, genetic studies on cancer susceptibility usually focus on families at extreme high risk who are selected based on “unusual” family history, while epidemiologic studies of candidate genes or of gene-environment interactions mostly adopt population-based, case-control or cohort designs. The multifaceted nature of a relative young discipline, genetic epidemiology, provides the conceptual framework for the integration of these divergent approaches and for the development of innovative study designs and analytic strategies targeted to further our understanding of the complex mechanisms underlying cancer susceptibility. This monograph issue presents the proceedings of the conference: “Innovative Study Designs and Analytic Approaches to the Genetic Epidemiology of Cancer,” held in Seattle, WA, on May 27-29, 1998, and sponsored by the National Cancer Institute (NCI) and the Fred Hutchinson Cancer Research Center, Seattle. A major goal of this conference was to bring together investigators interested in the development of study designs and new analytic methods pertinent to the genetic and epidemiologic study of complex diseases such as cancer within the framework of modern genetic epidemiology. The focus of the papers in this monograph is to discuss the usefulness and practical feasibility, potential advantages, and pitfalls of the most recently developed models for study designs and analytic methods in the genetic epidemiology of cancer and to identify analytical and design issues brought to attention by the recent conceptual and technologic advances in the disciplines merging into genetic epidemiology, as related to their application to the following: 1) the pursuit of new cancer susceptibility genes across the expected spectrum of population distribution and penetrance (Gene Discovery Panel); 2) the ascertainment of the population frequency, the phenotype-genotype correlation, and the modifiers of penetrance, such as other genes or nongenetic risk factors, of each identified cancer susceptibility gene (Gene Characterization Panel); 3) the integration of such methodologies and approaches (Integration Panel); and 4) the evaluation of applications of the discussed approaches in currently ongoing studies (Application Panel). The workshop proceedings encompass the results of the discussion of the four interrelated panels. Although an increasing number of cancer susceptibility genes have been successfully identified during the past few years, design and analytic issues, such as the accurate definition and measurement of cancer phenotype, the use of intermediate end points, the choice of appropriate samples and analytic methods, and the determination of the effect of gene-environment interaction on linkage analysis, still stand in the way of an accelerated rate of discovery. The Gene Discovery Panel, chaired by Dr. Schaid and Dr. Buetow, focuses its discussion on a review of the current designs and analytic challenges in the discovery (mapping) of susceptibility genes for complex diseases such as cancer. The panelists identify the conceptual and methodologic issues representing a barrier to this endeavor; outline a vision for some possible methodologic solutions and for future research in this area; and, finally, examine the conceivable integration of recent and imminent advances in molecular technology into genetic epidemiology studies and its potential for revolutionizing the pace and direction of gene discovery. The collection of manuscripts from the Gene Characterization Panel, led by Dr. Thomas, addresses the methodologic issues pertinent to studies that assess the population characteristics of cloned genes, such as their allele frequencies, penetrance, variation in these parameters across population, and gene-gene and gene-environment interactions. Dr. Thomas provides an overview of the various designs that have been recently proposed and their appropriateness for addressing specific research questions in the area of genetic characterization, and discusses statistical and practical considerations pertinent to the evaluation of cohort and case-control designs using independent and related individuals, optimal multistage sampling, and hybrid designs. The answer to this question clearly depends on such context issues as nature of the outcome variable, the gene frequency and genetic relative risk, and the importance of gene-environment and gene-gene interactions. Dr. Caporaso, Dr. Rothman, and Dr. Wacholder propose an novel approach, based on adjustment for ancestry, attention to study design and appropriate selection of controls, and reduction of the confounding caused by population stratification in the analysis of the associations of genetic polymorphisms to cancer outcome in population studies. Dr. Gauderman, Dr. Witte, and Dr. Thomas review case-control designs for studying gene associations in which relatives of cases are used as controls as an alternative strategy to avoid the problem of population stratification that can lead to false associations with noncausal genes. Various case-relative combinations are discussed in light of their validity to estimate genetic relative risk and their efficiency in respect to the more generally used population-based, case-control design using unrelated controls. During the last few decades, several large cohorts have been established to examine epidemiologic risk factors believed to be associated with cancer. Such cohorts currently include a total of millions of individuals, with extensive baseline and follow-up data, some collection of biologic specimens, and an established infrastructure that could be used to conduct cohort, nested case-control, or case-cohort studies to characterize measured genes in an extremely cost-effective fashion. Dr. Langholz discusses methods of sampling in an efficient manner within these cohorts, the merits of including family members of the original cohort, and the use of molecular markers to control for population stratification. Dr. Siegmund describes the basic statistical theory underlying multistage sampling, a design strategy that can be used to establish family-based disease registries in a cost-effective manner, while retaining the capability of validly addressing a range of scientific questions, from characterizing measured genetic factors and gene-environment interactions to detecting novel susceptibility genes. The application of this theory to a three-stage sampling scheme utilized by the Cooperative Family Registry for epidemiologic studies of colorectal cancer is also described. Advances in molecular genetic techniques and their integration into epidemiologic designs have led to an increased ability to examine gene-environment interactions. Less studied so far, but with increased potential for the future, is interaction between identified genes. Dr. Goldstein and Dr. Andrieu review the known methods to detect gene-environment and gene-gene interactions in view of the available risk estimates, required types of subjects, feasibility of the proposed study design, and efficiency and power considerations. Further investigations are recommended to define the efficiency spectra of each method. Finally, the advantages and disadvantages of the kin-cohort design, recently developed to estimate the penetrance of BRCA1 in a selected population of Ashkenazi Jewish women, are reviewed by Dr. Gail and colleagues. The potential limitations of this design are examined, as well as the considerable advantages. In particular, the effects of violations of assumptions on estimates of penetrance, the selection bias from preferential sampling of probands with heavily affected families, the misclassification of the disease status of relatives, and the possible violation of Hardy-Weinberg equilibrium are discussed. The primary objectives of the Integration Panel are as follows: to address the feasibility of integrating genetic and epidemiologic principles in both gene discovery and gene characterization studies; to evaluate strengths and weaknesses of designs used in gene discovery and characterization from the perspective of such integration; and to evaluate strengths and weaknesses of several proposed study designs for interdisciplinary studies in the genetic epidemiology of cancer. With this goal in mind, Dr. Whittemore and Dr. Nelson review some of the issues that must be considered by genetic epidemiologists when designing a study involving the genetic epidemiology of late-onset chronic diseases such as cancer. The authors discuss how the choice of design is influenced by the study's goals, such as identifying new genes, estimating characteristics of known genes, and learning how to prevent the disease in the genetically susceptible, and propose guidelines for choosing designs that effectively address such goals. Furthermore, the practical constraints in conducting such research are concisely outlined, including problems of potential selection bias, reduced response rates, departures from Hardy-Weinberg frequencies for genotypes, problems particular to family registries, problems particular to the cultures of various ethnic groups, and ethical issues. Last, Dr. Zhao and colleagues expand the challenge to genetic epidemiology methodology by proposing the development of integrated study designs, such as case-family and case-control-family, that would allow for both discovery and characterization of cancer susceptibility genes. Finally, a series of studies illustrating the practical issues encountered in the implementation of the design and methodologic approaches discussed by the previous panels, and their resolution are presented by several investigators involved in gene discovery and characterization projects. One of the strongest risk factors for prostate cancer identified to date is a family history of disease, suggesting that genetic factors play a role in prostate cancer susceptibility and/or etiology. Dr. Jarvik, Dr. Ostrander, and colleagues review the recent findings suggesting there is a prostate cancer susceptibility gene at 1q24-25 and discuss the results of their gene discovery study in high-risk families and the ones from other data sets with regard to observed difficulties in confirming these initial findings of linkage. Dr. Haile and colleagues describe the implementation of a multistage family-based design performed through the University of Southern California Consortium, Los Angeles (USCC), a participating center in the National Cancer Institute's Cooperative Family Registry for Colorectal Cancer Studies. The primary goals of the USCC are to estimate gene frequency and penetrance and to investigate factors that may affect penetrance (gene-gene and gene-environment interactions) for accepted and putative candidate colorectal cancer genes. Within this general framework, the authors address questions related to the proportions of single versus multiple-case families to include in the registry, to the selection of subjects within families on whom to collect risk factor questionnaires, blood samples, and tumor blocks; and the meaningful selection of samples to test for microsatellite instability and from which to establish cell lines. A protocol to tailor decisions about sampling and data collection to the family structure of each family in an attempt to maximize power for planned analyses per unit cost/effort while retaining a valid design is also described. Last, the issue concerning the appropriate use of data derived from high-risk clinics is addressed. Dr. Hopper and colleagues report on a population-based study of breast cancer with a case-control family design in which families are identified either through recently diagnosed cases reported to the Victorian and New South Wales Cancer Registries or through controls selected at random from the Electoral Rolls. This design makes it possible to measure the population burden associated with cancer genes and to study concurrently the roles of both genetic and environmental risk factors on cancer susceptibility. Some of the design issues faced in this study as well as the implications of the population-based finding for genetic testing and public health are discussed. The extension of this model to a collaboration with the NCI-supported Cooperative Family Registry for Breast Cancer Studies, an international infrastructure for studies of the genetic epidemiology of breast cancer, and the practical issues arising out of the first 2 years of experience in establishing and conducting such a novel and innovative project in genetic epidemiology are also reviewed, in view of the benefit of such comprehensive multicenter interdisciplinary infrastructure to research in genetics (with an immediate translation to the population and public health perspective) and genetic epidemiology (allowing for the possible role of genetic factors in explaining the epidemiologic data). Finally, Dr. Le Marchand and colleagues describe recent case-control-family, case-control, and prospective studies of colorectal cancer in Japanese migrants to Hawaii, a population that offered an unique opportunity to identify gene-environment interactions of considerable public health impact, given the common at-risk genotypes and exposures. Understanding the genetic and environmental determinants of cancer and their interplay at the different causative steps of the etiologic process has tremendous public health relevance, since it constitutes the underpinning of targeted preventive measures, early cancer detection, and effective cancer treatment. It is hoped that the contribution of the scientists participating in this workshop and monograph will further the scientific progress toward this goal. The organizers would like to thank the speakers and the panel chairs for their participation in this effort. Their thoughtful outlooks have helped to identify the emerging and, at times, problematic methodologic and design issues in this important area of research, to further a discussion on resolving such issues, and to transmit this knowledge to the scientific community at large. We also thank the reviewers of the published manuscripts for making this monograph possible. Oxford University Press http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JNCI Monographs Oxford University Press

Introduction

JNCI Monographs , Volume 1999 (26) – Dec 1, 1999

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Oxford University Press
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Oxford University Press
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1052-6773
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1745-6614
DOI
10.1093/oxfordjournals.jncimonographs.a024218
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Abstract

Past genetics and epidemiology research has suggested that cancer has a complex etiology, and that both susceptibility genes and environmental risk factors play a defined role in its development. More recently, this dichotomous theory has yielded to complex, interactive models, involving the temporal and metabolic interplay of both sets of causative agents. This novel conceptual framework entails the disciplinary integration necessary for the identification and characterization of cancer susceptibility genes, the definition of their interactions with nongenetic risk factors during the process of cancer development, and the application of this knowledge to the assessment of cancer risk in diverse populations. In addition to the conceptual integration from related but traditionally separated disciplines, studying the genetic and environmental causative interaction that determines cancer susceptibility in individuals, families, and populations involves considerable operational challenges, such as the selection (or de novo development) of study designs appropriate to the question(s) proposed, the integration of complex models into pertinent analytic strategies, and the interdisciplinary synergy to support and conduct such studies in connection with a rapidly evolving methodologic and scientific milieu. For example, genetic studies on cancer susceptibility usually focus on families at extreme high risk who are selected based on “unusual” family history, while epidemiologic studies of candidate genes or of gene-environment interactions mostly adopt population-based, case-control or cohort designs. The multifaceted nature of a relative young discipline, genetic epidemiology, provides the conceptual framework for the integration of these divergent approaches and for the development of innovative study designs and analytic strategies targeted to further our understanding of the complex mechanisms underlying cancer susceptibility. This monograph issue presents the proceedings of the conference: “Innovative Study Designs and Analytic Approaches to the Genetic Epidemiology of Cancer,” held in Seattle, WA, on May 27-29, 1998, and sponsored by the National Cancer Institute (NCI) and the Fred Hutchinson Cancer Research Center, Seattle. A major goal of this conference was to bring together investigators interested in the development of study designs and new analytic methods pertinent to the genetic and epidemiologic study of complex diseases such as cancer within the framework of modern genetic epidemiology. The focus of the papers in this monograph is to discuss the usefulness and practical feasibility, potential advantages, and pitfalls of the most recently developed models for study designs and analytic methods in the genetic epidemiology of cancer and to identify analytical and design issues brought to attention by the recent conceptual and technologic advances in the disciplines merging into genetic epidemiology, as related to their application to the following: 1) the pursuit of new cancer susceptibility genes across the expected spectrum of population distribution and penetrance (Gene Discovery Panel); 2) the ascertainment of the population frequency, the phenotype-genotype correlation, and the modifiers of penetrance, such as other genes or nongenetic risk factors, of each identified cancer susceptibility gene (Gene Characterization Panel); 3) the integration of such methodologies and approaches (Integration Panel); and 4) the evaluation of applications of the discussed approaches in currently ongoing studies (Application Panel). The workshop proceedings encompass the results of the discussion of the four interrelated panels. Although an increasing number of cancer susceptibility genes have been successfully identified during the past few years, design and analytic issues, such as the accurate definition and measurement of cancer phenotype, the use of intermediate end points, the choice of appropriate samples and analytic methods, and the determination of the effect of gene-environment interaction on linkage analysis, still stand in the way of an accelerated rate of discovery. The Gene Discovery Panel, chaired by Dr. Schaid and Dr. Buetow, focuses its discussion on a review of the current designs and analytic challenges in the discovery (mapping) of susceptibility genes for complex diseases such as cancer. The panelists identify the conceptual and methodologic issues representing a barrier to this endeavor; outline a vision for some possible methodologic solutions and for future research in this area; and, finally, examine the conceivable integration of recent and imminent advances in molecular technology into genetic epidemiology studies and its potential for revolutionizing the pace and direction of gene discovery. The collection of manuscripts from the Gene Characterization Panel, led by Dr. Thomas, addresses the methodologic issues pertinent to studies that assess the population characteristics of cloned genes, such as their allele frequencies, penetrance, variation in these parameters across population, and gene-gene and gene-environment interactions. Dr. Thomas provides an overview of the various designs that have been recently proposed and their appropriateness for addressing specific research questions in the area of genetic characterization, and discusses statistical and practical considerations pertinent to the evaluation of cohort and case-control designs using independent and related individuals, optimal multistage sampling, and hybrid designs. The answer to this question clearly depends on such context issues as nature of the outcome variable, the gene frequency and genetic relative risk, and the importance of gene-environment and gene-gene interactions. Dr. Caporaso, Dr. Rothman, and Dr. Wacholder propose an novel approach, based on adjustment for ancestry, attention to study design and appropriate selection of controls, and reduction of the confounding caused by population stratification in the analysis of the associations of genetic polymorphisms to cancer outcome in population studies. Dr. Gauderman, Dr. Witte, and Dr. Thomas review case-control designs for studying gene associations in which relatives of cases are used as controls as an alternative strategy to avoid the problem of population stratification that can lead to false associations with noncausal genes. Various case-relative combinations are discussed in light of their validity to estimate genetic relative risk and their efficiency in respect to the more generally used population-based, case-control design using unrelated controls. During the last few decades, several large cohorts have been established to examine epidemiologic risk factors believed to be associated with cancer. Such cohorts currently include a total of millions of individuals, with extensive baseline and follow-up data, some collection of biologic specimens, and an established infrastructure that could be used to conduct cohort, nested case-control, or case-cohort studies to characterize measured genes in an extremely cost-effective fashion. Dr. Langholz discusses methods of sampling in an efficient manner within these cohorts, the merits of including family members of the original cohort, and the use of molecular markers to control for population stratification. Dr. Siegmund describes the basic statistical theory underlying multistage sampling, a design strategy that can be used to establish family-based disease registries in a cost-effective manner, while retaining the capability of validly addressing a range of scientific questions, from characterizing measured genetic factors and gene-environment interactions to detecting novel susceptibility genes. The application of this theory to a three-stage sampling scheme utilized by the Cooperative Family Registry for epidemiologic studies of colorectal cancer is also described. Advances in molecular genetic techniques and their integration into epidemiologic designs have led to an increased ability to examine gene-environment interactions. Less studied so far, but with increased potential for the future, is interaction between identified genes. Dr. Goldstein and Dr. Andrieu review the known methods to detect gene-environment and gene-gene interactions in view of the available risk estimates, required types of subjects, feasibility of the proposed study design, and efficiency and power considerations. Further investigations are recommended to define the efficiency spectra of each method. Finally, the advantages and disadvantages of the kin-cohort design, recently developed to estimate the penetrance of BRCA1 in a selected population of Ashkenazi Jewish women, are reviewed by Dr. Gail and colleagues. The potential limitations of this design are examined, as well as the considerable advantages. In particular, the effects of violations of assumptions on estimates of penetrance, the selection bias from preferential sampling of probands with heavily affected families, the misclassification of the disease status of relatives, and the possible violation of Hardy-Weinberg equilibrium are discussed. The primary objectives of the Integration Panel are as follows: to address the feasibility of integrating genetic and epidemiologic principles in both gene discovery and gene characterization studies; to evaluate strengths and weaknesses of designs used in gene discovery and characterization from the perspective of such integration; and to evaluate strengths and weaknesses of several proposed study designs for interdisciplinary studies in the genetic epidemiology of cancer. With this goal in mind, Dr. Whittemore and Dr. Nelson review some of the issues that must be considered by genetic epidemiologists when designing a study involving the genetic epidemiology of late-onset chronic diseases such as cancer. The authors discuss how the choice of design is influenced by the study's goals, such as identifying new genes, estimating characteristics of known genes, and learning how to prevent the disease in the genetically susceptible, and propose guidelines for choosing designs that effectively address such goals. Furthermore, the practical constraints in conducting such research are concisely outlined, including problems of potential selection bias, reduced response rates, departures from Hardy-Weinberg frequencies for genotypes, problems particular to family registries, problems particular to the cultures of various ethnic groups, and ethical issues. Last, Dr. Zhao and colleagues expand the challenge to genetic epidemiology methodology by proposing the development of integrated study designs, such as case-family and case-control-family, that would allow for both discovery and characterization of cancer susceptibility genes. Finally, a series of studies illustrating the practical issues encountered in the implementation of the design and methodologic approaches discussed by the previous panels, and their resolution are presented by several investigators involved in gene discovery and characterization projects. One of the strongest risk factors for prostate cancer identified to date is a family history of disease, suggesting that genetic factors play a role in prostate cancer susceptibility and/or etiology. Dr. Jarvik, Dr. Ostrander, and colleagues review the recent findings suggesting there is a prostate cancer susceptibility gene at 1q24-25 and discuss the results of their gene discovery study in high-risk families and the ones from other data sets with regard to observed difficulties in confirming these initial findings of linkage. Dr. Haile and colleagues describe the implementation of a multistage family-based design performed through the University of Southern California Consortium, Los Angeles (USCC), a participating center in the National Cancer Institute's Cooperative Family Registry for Colorectal Cancer Studies. The primary goals of the USCC are to estimate gene frequency and penetrance and to investigate factors that may affect penetrance (gene-gene and gene-environment interactions) for accepted and putative candidate colorectal cancer genes. Within this general framework, the authors address questions related to the proportions of single versus multiple-case families to include in the registry, to the selection of subjects within families on whom to collect risk factor questionnaires, blood samples, and tumor blocks; and the meaningful selection of samples to test for microsatellite instability and from which to establish cell lines. A protocol to tailor decisions about sampling and data collection to the family structure of each family in an attempt to maximize power for planned analyses per unit cost/effort while retaining a valid design is also described. Last, the issue concerning the appropriate use of data derived from high-risk clinics is addressed. Dr. Hopper and colleagues report on a population-based study of breast cancer with a case-control family design in which families are identified either through recently diagnosed cases reported to the Victorian and New South Wales Cancer Registries or through controls selected at random from the Electoral Rolls. This design makes it possible to measure the population burden associated with cancer genes and to study concurrently the roles of both genetic and environmental risk factors on cancer susceptibility. Some of the design issues faced in this study as well as the implications of the population-based finding for genetic testing and public health are discussed. The extension of this model to a collaboration with the NCI-supported Cooperative Family Registry for Breast Cancer Studies, an international infrastructure for studies of the genetic epidemiology of breast cancer, and the practical issues arising out of the first 2 years of experience in establishing and conducting such a novel and innovative project in genetic epidemiology are also reviewed, in view of the benefit of such comprehensive multicenter interdisciplinary infrastructure to research in genetics (with an immediate translation to the population and public health perspective) and genetic epidemiology (allowing for the possible role of genetic factors in explaining the epidemiologic data). Finally, Dr. Le Marchand and colleagues describe recent case-control-family, case-control, and prospective studies of colorectal cancer in Japanese migrants to Hawaii, a population that offered an unique opportunity to identify gene-environment interactions of considerable public health impact, given the common at-risk genotypes and exposures. Understanding the genetic and environmental determinants of cancer and their interplay at the different causative steps of the etiologic process has tremendous public health relevance, since it constitutes the underpinning of targeted preventive measures, early cancer detection, and effective cancer treatment. It is hoped that the contribution of the scientists participating in this workshop and monograph will further the scientific progress toward this goal. The organizers would like to thank the speakers and the panel chairs for their participation in this effort. Their thoughtful outlooks have helped to identify the emerging and, at times, problematic methodologic and design issues in this important area of research, to further a discussion on resolving such issues, and to transmit this knowledge to the scientific community at large. We also thank the reviewers of the published manuscripts for making this monograph possible. Oxford University Press

Journal

JNCI MonographsOxford University Press

Published: Dec 1, 1999

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