Dynamics of Cancer: Incidence, Inheritance, and Evolution

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Overview

The onset of cancer presents one of the most fundamental problems in modern biology. In Dynamics of Cancer, Steven Frank produces the first comprehensive analysis of how particular genetic and environmental causes influence the age of onset.

The book provides a unique conceptual and historical framework for understanding the causes of cancer and other diseases that increase with age. Using a novel quantitative framework of reliability and multistage breakdown, Frank unifies molecular, demographic, and evolutionary levels of analysis. He interprets a wide variety of observations on the age of cancer onset, the genetic and environmental causes of disease, and the organization of tissues with regard to stem cell biology and somatic mutation. Frank uses new quantitative methods to tackle some of the classic problems in cancer biology and aging: how the rate of increase in the incidence of lung cancer declines after individuals quit smoking, the distinction between the dosage of a chemical carcinogen and the time of exposure, and the role of inherited genetic variation in familial patterns of cancer.

This is the only book that presents a full analysis of the age of cancer onset. It is a superb teaching tool and a rich source of ideas for new and experienced researchers. For cancer biologists, population geneticists, evolutionary biologists, and demographers interested in aging, this book provides new insight into disease progression, the inheritance of predisposition to disease, and the evolutionary processes that have shaped organismal design.

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Editorial Reviews

Nature - Robert A. Weinberg
Frank is an evolutionary biologist with a strong mathematics bent. His book grapples with many...issues, offering insights from his mathematical modelling of various steps of tumour progression...One day he may be seen as the pioneer who began the difficult task of building a sturdy foundation for a truly useful mathematical model of cancer development.
Science - David C. Krakauer
Frank's forte in the book is his search for the simplicity that is often masked by the complexities of cancer. With his mathematical models in hand, he turns to the details of cancer genetics, carcinogens, and aging and provides novel integrative insights...Dynamics of Cancer emphasizes both the multiscale dynamics of the disease and an approach that synthesizes empirical knowledge with parsimonious, mathematical theory. Frank moves the field forward, narrowing the gap between a tragic disease of everyday life and the Darwinian world of the genome.
Quarterly Review of Biology - Dominik Wodarz
It will be highly interesting to a wide readership, including students who would like to learn about this subject, theoretical/mathematical biologists, epidemiologists, and molecular/clinical cancer biologists. Although the volume is based on mathematical theory, the excellent writing style ensures that it can be read both by biologists with no background in mathematics, and by theoreticians who would like to learn more about the dynamics that govern cancer initiation and progression.
From the Publisher

"Frank is an evolutionary biologist with a strong mathematics bent. His book grapples with many...issues, offering insights from his mathematical modelling of various steps of tumour progression...One day he may be seen as the pioneer who began the difficult task of building a sturdy foundation for a truly useful mathematical model of cancer development."--Robert A. Weinberg, Nature

"Frank's forte in the book is his search for the simplicity that is often masked by the complexities of cancer. With his mathematical models in hand, he turns to the details of cancer genetics, carcinogens, and aging and provides novel integrative insights...Dynamics of Cancer emphasizes both the multiscale dynamics of the disease and an approach that synthesizes empirical knowledge with parsimonious, mathematical theory. Frank moves the field forward, narrowing the gap between a tragic disease of everyday life and the Darwinian world of the genome."--David C. Krakauer, Science

"This book is a superb teaching tool and a rich source of ideas for new and experienced researchers. For cancer biologists, population geneticists, evolutionary biologists, and demographers interested in aging, this book provides new insight into disease progression and the inheritance of predisposition to disease."--Biology Digest

"It will be highly interesting to a wide readership, including students who would like to learn about this subject, theoretical/mathematical biologists, epidemiologists, and molecular/clinical cancer biologists. Although the volume is based on mathematical theory, the excellent writing style ensures that it can be read both by biologists with no background in mathematics, and by theoreticians who would like to learn more about the dynamics that govern cancer initiation and progression."--Dominik Wodarz, Quarterly Review of Biology

Nature
Frank is an evolutionary biologist with a strong mathematics bent. His book grapples with many...issues, offering insights from his mathematical modelling of various steps of tumour progression...One day he may be seen as the pioneer who began the difficult task of building a sturdy foundation for a truly useful mathematical model of cancer development.
— Robert A. Weinberg
Science
Frank's forte in the book is his search for the simplicity that is often masked by the complexities of cancer. With his mathematical models in hand, he turns to the details of cancer genetics, carcinogens, and aging and provides novel integrative insights...Dynamics of Cancer emphasizes both the multiscale dynamics of the disease and an approach that synthesizes empirical knowledge with parsimonious, mathematical theory. Frank moves the field forward, narrowing the gap between a tragic disease of everyday life and the Darwinian world of the genome.
— David C. Krakauer
Biology Digest
This book is a superb teaching tool and a rich source of ideas for new and experienced researchers. For cancer biologists, population geneticists, evolutionary biologists, and demographers interested in aging, this book provides new insight into disease progression and the inheritance of predisposition to disease.
Quarterly Review of Biology
It will be highly interesting to a wide readership, including students who would like to learn about this subject, theoretical/mathematical biologists, epidemiologists, and molecular/clinical cancer biologists. Although the volume is based on mathematical theory, the excellent writing style ensures that it can be read both by biologists with no background in mathematics, and by theoreticians who would like to learn more about the dynamics that govern cancer initiation and progression.
— Dominik Wodarz
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Product Details

Meet the Author

Steven A. Frank is professor of biology at the University of California, Irvine. He is the author of "Immunology and Evolution of Infectious Disease and Foundations of Social Evolution" (both Princeton).

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Read an Excerpt

Dynamics of Cancer Incidence, Inheritance, and Evolution
By Steven A. Frank Princeton University Press
Copyright © 2007
Princeton University Press
All right reserved.

ISBN: 978-0-691-13366-9


Chapter One Introduction

Through failure we understand biological design. Geneticists discover the role of a gene by studying how a mutation causes a system to fail. Neuroscientists discover mental modules for face recognition or language by observing how particular brain lesions cause cognitive failure.

Cancer is the failure of controls over cellular birth and death. Through cancer, we discover the design of cellular controls that protect against tumors and the architecture of tissue restraints that slow the progress of disease.

Given a particular set of genes and a particular environment, one cannot say that cancer will develop at a certain age. Rather, failure happens at different rates at different ages, according to the age-specific incidence curve that defines failure.

To understand cancer means to understand the genetic and environmental factors that determine the incidence curve. To learn about cancer, we study how genetic and environmental changes shift the incidence curve toward earlier or later ages.

The study of incidence means the study of rates. How does a molecular change alter the rate at which individuals progress to cancer? How does an inherited genetic change alter the rate of progression? How does natural selection shape the design of regulatory processes that governrates of failure?

Over fifty years ago, Armitage and Doll (1954) developed a multistage theory to analyze rates of cancer progression. That abstract theory turned on only one issue: ultimate system failure-cancer-develops through a sequence of component failures. Each component failure, such as loss of control over cellular death or abrogation of a critical DNA repair pathway, moves the system one stage along the progression to disease. Rates of component failure and the number of stages in progression determine the age-specific incidence curve. Mutations that knock out a component or increase the rate of transition between stages shift the incidence curve to earlier ages.

I will review much evidence that supports the multistage theory of cancer progression. Yet that support often remains at a rather vague level: little more than the fact that progression seems to follow through multiple stages. A divide separates multistage theory from the daily work of cancer research.

The distance between theory and ongoing research arose naturally. The theory follows from rates of component failures and age-specific incidence in populations; most cancer research focuses on the mechanistic and biochemical controls of particular components such as the cell cycle, cell death, DNA repair, or nutrient acquisition. It is not easy to tie failure of a particular pathway in cell death to an abstract notion of the rate of component failure and advancement by a stage in cancer progression.

In this book, I work toward connecting the great recent progress in molecular and cellular biology to the bigger problem: how failures in molecular and cellular components determine rates of progression and the age-specific incidence of cancer. I also consider how one can use observed shifts in age-specific incidence to analyze the importance of particular molecular and cellular aberrations. Shifts in incidence curves measure changes in failure rates; changes in failure rates provide a window onto the design of molecular and cellular control systems.

1.1 Aims

The age-specific incidence curve reflects the processes that drive disease progression, the inheritance of predisposing genetic variants, and the consequences of carcinogenic exposures. It is easy to see that these various factors must affect incidence. But it is not so obvious how these factors alter measurable, quantitative properties of age-specific incidence.

My first aim is to explore, in theory, how particular processes cause quantitative shifts in age-specific incidence. That theory provides the tools to develop the second aim: how one can use observed changes in age-specific incidence to reveal the molecular, cellular, inherited, and environmental factors that cause disease. Along the way, I will present a comprehensive summary of observed incidence patterns, and I will synthesize the intellectual history of the subject.

I did not arbitrarily choose to study patterns of age-specific incidence. Rather, as I developed my interests in cancer and other age-related diseases, I came to understand that age-specific incidence forms the nexus through which hidden process flows to observable outcome. In this book, I address the following kinds of questions, which illustrate the link between disease processes and age-related outcomes.

Faulty DNA repair accelerates disease onset-that is easy enough to guess-but does poor repair accelerate disease a little or a lot, early in life or late in life, in some tissues but not in others?

Carcinogenic chemicals shift incidence to earlier ages: one may reasonably measure whether a particular dosage is carcinogenic by whether it causes a shift in age-specific incidence, and measure potency by the degree of shift in the age-incidence curve. Why do some carcinogens cause a greater increase in disease if applied early in life, whereas other carcinogens cause a greater increase if applied late in life? Why do many cancers accelerate rapidly with increasing time of carcinogenic exposure, but accelerate more slowly with increasing dosage of exposure? What processes of disease progression do the chemicals affect, and how do changes in those biochemical aspects of cells and tissues translate into disease progression?

Inherited mutations sometimes abrogate key processes of cell cycle control or DNA repair, leading to a strong predisposition for cancer. Why do such mutations shift incidence to earlier ages, but reduce the rate at which cancer increases (accelerates) with age?

Why do the incidences of most diseases, including cancer, accelerate more slowly later in life? What cellular, physiological, and genetic processes of disease progression inevitably cause the curves of death to flatten in old age?

Inherited mutations shift incidence to earlier ages. How do the particular changes in age-specific incidence caused by a mutation affect the frequency of that mutation in the population?

How do patterns of cell division, tissue organization, and tissue renewal via stem cells affect the accumulation of somatic mutations in cell lineages? How do the rates of cell lineage evolution affect disease progression? How do alternative types of heritable cellular changes, such as DNA methylation and histone modification, affect progression? How can one measure cell lineage evolution within individuals?

I will not answer all of these questions, but I will provide a comprehensive framework within which to study these problems.

Above all, this book is about biological reliability and biological failure. I present a full, largely novel development of reliability theory that accounts for biological properties of variability, inheritance, and multiple pathways of disease. I discuss the consequences of reliability and failure rates for evolutionary aspects of organismal design. Cancer provides an ideal subject for the study of reliability and failure, and through the quantitative study of failure curves, one gains much insight into cancer progression and the ways in which to develop further studies of cancer biology.

1.2 How to Read

Biological analysis coupled with mathematical development can produce great intellectual synergy. But for many readers, the mixed language of a biology-math marriage can seem to be a private dialect understood by only a few intimates.

Perhaps this book would have been an easier read if I had published the quantitative theory separately in journals, and only summarized the main findings here in relation to specific biological problems. But the real advance derives from the interdisciplinary synergism, diluted neither on the biological nor on the mathematical side. If fewer can immediately grasp the whole, more should be attracted to try, and with greater ultimate reward. Progress will ultimately depend on advances in biology, on advances in the conceptual understanding of reliability and failure, and on advances in the quantitative analysis and interpretation of data.

I have designed this book to make the material accessible to readers with different training and different goals. Chapters 2 and 3 provide background on cancer that should be accessible to all readers. Chapter 4 presents a novel historical analysis of the quantitative study of age-specific cancer incidence. Chapter 5 gives a gentle introduction to the quantitative theory, why such theory is needed, and how to use it. That mathematical introduction should be readable by all.

Chapters 6 and 7 develop the mathematical theory, with much original work on the fundamental properties of reliability and failure in biological systems. Each section in those two mathematical chapters includes a nontechnical introduction and conclusion, along with figures that illustrate the main concepts. Those with allergy to mathematics can glance briefly at the section introductions, and then move along quickly before the reaction grows too severe. The rest of the book applies the quantitative concepts of the mathematical chapters, but does so in a way that can be read with nearly full understanding independently of the mathematical details.

Chapters 8, 9, and 10 apply the quantitative theory to observed patterns of age-specific incidence. I first test hypotheses about how inherited, predisposing genotypes shift the age-specific incidence of cancer. I then evaluate alternative explanations for the patterns of age-specific cancer onset in response to chemical carcinogen exposure. Finally, I analyze data on the age-specific incidence of the leading causes of death, such as heart disease, cancer, cerebrovascular disease, and so on.

I then turn to various evolutionary problems. In Chapter 11, I evaluate the population processes by which inherited genetic variants accumulate and affect predisposition to cancer. Chapters 12 and 13 discuss how somatic genetic mutations arise and affect progression to disease. For somatic cell genetics, the renewal of tissues through tissue-specific adult stem cells plays a key role in defining the pattern of cell lineage history and the accumulation of somatic mutations. Chapter 14 finishes by describing empirical methods to study cell lineages and the accumulation of heritable change.

The following section provides an extended summary of each chapter. I give those summaries so that readers with particular interests can locate the appropriate chapters and sections, and quickly see where I present specific analyses and conclusions. The extended summaries also allow one to develop a customized reading strategy in order to focus on a particular set of topics or approaches. Many readers will prefer to skip the summaries for now and move directly to Chapter 2.

1.3 Chapter Summaries

Part I of the book provides background in three chapters: incidence, progression, and conceptual foundations. Each chapter can be read independently as a self-contained synthesis of a major topic.

Chapter 2 describes the age-specific incidence curve. That failure curve defines the outcome of particular genetic, cellular, and environmental processes that lead to cancer. I advocate the acceleration of cancer as the most informative measure of process: acceleration measures how fast the incidence (failure) rate changes with age. I plot the incidence and acceleration curves for 21 common cancers. I include in the Appendix detailed plots comparing incidence between the 1970s and 1990s, and comparing incidence between the USA, Sweden, England, and Japan. I also compare incidence between males and females for the major cancers.

I continue Chapter 2 with summaries of incidence of major childhood cancers and of inherited cancers. I finish with a description of how chemical carcinogens alter age-specific incidence. Taken together, this chapter provides a comprehensive introduction to the observations of cancer incidence, organized in a comparative way that facilitates analysis of the factors that determine incidence.

Chapter 3 introduces cancer progression as a sequence of failures in components that regulate cells and tissues. I review the different ways in which the concept of multistage progression has been used in cancer research. I settle on progression in the general sense of development through multiple stages, with emphasis on how rates of failure for individual stages together determine the observed incidence curve. I then describe multistage progression in colorectal cancer, the clearest example of distinct morphological and genetical stages in tumor development. Interestingly, colorectal cancer appears to have alternative pathways of progression through different morphological and genetic changes; the different pathways are probably governed by different rate processes.

The second part of Chapter 3 focuses on the kinds of physical changes that occur during progression. Such changes include somatic mutation, chromosomal loss and duplication, genomic rearrangements, methylation of DNA, and changes in chromatin structure. Those physical changes alter key processes, resulting, for example, in a reduced tendency for cell suicide (apoptosis), increased somatic mutation and chromosomal instability, abrogation of cell-cycle checkpoints, enhancement of cell-cycle accelerators, acquisition of blood supply into the developing tumor, secretion of proteases to digest barriers against invasion of other tissues, and neglect of normal cellular death signals during migration into a foreign tissue. I finish with a discussion of how changes accumulate over time, with special attention to the role of evolving cell lineages throughout the various stages of tumor development.

Chapter 4 analyzes the history of theories of cancer incidence. I start with the early ideas in the 1920s about multistage progression from chemical carcinogenesis experiments. I follow with the separate line of mathematical multistage theory that developed in the 1950s to explain the patterns of incidence curves. Ashley (1969a) and Knudson (1971) provided the most profound empirical test of multistage progression. They reasoned that if somatic mutation is the normal cause of progression, then individuals who inherit a mutation would have one less step to pass before cancer arises. By the mathematical theory, one less step shifts the incidence curve to earlier ages and reduces the slope (acceleration) of failure. Ashley (1969a) compared incidence in normal individuals and those who inherit a single mutation predisposing to colon cancer: he found the predicted shift in incidence to earlier ages among the predisposed individuals. Knudson (1971) found the same predicted shift between inherited and noninherited cases of retinoblastoma.

I continue Chapter 4 with various developments in the theory of multistage progression. One common argument posits that somatic mutation alone pushes progression too slowly to account for incidence; however, the actual calculations remain ambiguous. Another argument emphasizes the role of clonal expansion, in which a cell at an intermediate stage divides to produce a clonal population that shares the changes suffered by the progenitor cell. The large number of cells in a clonal population raises the target size for the next failure that moves progression to the following stage. I then discuss various consequences of cell lineage history and processes that influence the accumulation of change in lineages. I end by returning to the somatic mutation rate, and how various epigenetic changes such as DNA methylation or histone modification may augment the rate of heritable change in cell lineages.

Part II turns to the dynamics of progression and the causes of the incidence curve. I first present extensive, original developments of multistage theory. I then apply the theory to comparisons between different genotypes that predispose to cancer and to different treatments of chemical carcinogens. I also apply the quantitative theory of age-specific failure to other causes of death besides cancer; the expanded analysis provides a general theory of aging.

(Continues...)



Excerpted from Dynamics of Cancer by Steven A. Frank
Copyright © 2007 by Princeton University Press. Excerpted by permission.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.
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Table of Contents

Chapter 1: Introduction 1
1.1 Aims 2
1.2 How to Read 4
1.3 Chapter Summaries 5

PART I: BACKGROUND

Chapter 2: Age of Cancer Incidence 17
2.1 Incidence and Acceleration 19
2.2 Different Cancers 20
2.3 Childhood Cancers 23
2.4 Inheritance 25
2.5 Carcinogens 29
2.6 Sex Differences 32
2.7 Summary 35

Chapter 3: Multistage Progression 36
3.1 Terminology 37
3.2 What Is Multistage Progression? 38
3.3 Multistage Progression in Colorectal Cancer 39
3.4 Alternative Pathways to Colorectal Cancer 43
3.5 Changes during Progression 49
3.6 What Physical Changes Drive Progression? 50
3.7 What Processes Change during Progression? 51
3.8 How Do Changes Accumulate in Cell Lineages? 55
3.9 Summary 58

Chapter 4: History of Theories 59
4.1 Origins of Multistage Theory 61
4.2 A Way to Test Multistage Models 65
4.3 Cancer Is a Genetic Disease 69
4.4 Can Normal Somatic Mutation Rates Explain Multistage Progression? 71
4.5 Clonal Expansion of
Premalignant Stages 74
4.6 The Geometry of Cell Lineages 76
4.7 Hypermutation, Chromosomal Instability, and Selection 78
4.8 Epigenetics: Methylation and Acetylation 79
4.9 Summary 80

PART II: DYNAMICS

Chapter 5: Progression Dynamics 85
5.1 Background 86
5.2 Observations to Be Explained 89
5.3 Progression Dynamics through Multiple Stages 90
5.4 Why Study Quantitative Theories? 93
5.5 The Basic Model 93
5.6 Technical Definitions of Incidence and Acceleration 94
5.7 Summary 95

Chapter 6: Theory I 96
6.1 Approach 97
6.2 Solution with Equal Transition Rates 97
6.3 Parallel Evolution within Each Individual 100
6.4 Unequal Transition Rates 103
6.5 Time-Varying Transition Rates 109
6.6 Summary 114

Chapter 7: Theory II 115
7.1 Multiple Pathways of Progression 116
7.2 Discrete Genetic Heterogeneity 120
7.3 Continuous Genetic and Environmental Heterogeneity 129
7.4 Weibull and Gompertz Models 136
7.5 Weibull Analysis of Carcinogen Dose-Response Curves 139
7.6 Summary 142

Chapter 8: Genetics of Progression 143
8.1 Comparison between Genotypes in Human Populations 144
8.2 Comparison between Genotypes in Laboratory Populations 154
8.3 Polygenic Heterogeneity 160
8.4 Summary 164

Chapter 9: Carcinogens 165
9.1 Carcinogen Dose-Response 166
9.2 Cessation of Carcinogen Exposure 180
9.3 Mechanistic Hypotheses and Comparative Tests 190
9.4 Summary 201

Chapter 10: Aging 202
10.1 Leading Causes of Death 203
10.2 Multistage Hypotheses 206
10.3 Reliability Models 207
10.4 Conclusions 209
10.5 Summary 209

PART III: EVOLUTION

Chapter 11: Inheritance 213
11.1 Genetic Variants Affect Progression and Incidence 214
11.2 Progression and Incidence Affect Genetic Variation 234
11.3 Few Common or Many Rare Variants? 243
11.4 Summary 250

Chapter 12: Stem Cells: Tissue Renewal 251
12.1 Background 252
12.2 Stem-Transit Program of Renewal 253
12.3 Symmetric versus Asymmetric Stem Cell Divisions 264
12.4 Asymmetric Mitoses and the Stem Line Mutation Rate 265
12.5 Tissue Compartments and Repression of Competition 269
12.6 Summary 270

Chapter 13: Stem Cells: Population Genetics 271
13.1 Mutations during Development 272
13.2 Stem-Transit Design 280
13.3 Symmetric versus Asymmetric Mitoses 283
13.4 Summary 285

Chapter 14: Cell Lineage History 286
14.1 Reconstructing Cellular Phylogeny 287
14.2 Demography of Progression 295
14.3 Somatic Mosaicism 304
14.4 Summary 308

Chapter 15: Conclusions 309

Appendix: Incidence 314
References 335
Author Index 361
Subject Index 373

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