Page 112 - 20dynamics of cancer
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THEORY I                                                     97

                              transition may rise when a precancerous cell expands into a large clone,
                              in which a subsequent change to any one of the clonal cells could cause
                              progression to the next stage in carcinogenesis. As the clone grows
                              larger, the target size for a transition increases. Time-varying rates often
                              cause a rise in acceleration to a midlife peak, followed by a late-life
                              decline in acceleration.


                                                      6.1 Approach

                                This chapter and the following one develop the theory of progression
                              dynamics. Most of the sections contain some mathematics. I use the
                              following structure to make the presentation accessible. A section with
                              mathematics begins with a précis that highlights the main results. The
                              mathematical details follow, often with some illustrations to emphasize
                              the key points. The section ends with a brief statement of the conclu-
                              sions.
                                I developed much of the following original theory for this book. Al-
                              though the overall structure and many of the particular results are new,
                              my mathematical work grew from a rich and highly developed field. I
                              gave an overview of the history in Chapter 4. I particularly wish to ac-
                              knowledge the pioneering contributions of Armitage and Doll, Knudson,
                              and Moolgavkar, who have been most influential in my own studies.


                                        6.2 Solution with Equal Transition Rates

                                                          PR ´ ECIS
                                I start with the linear chain of stepwise progression illustrated in Fig-
                              ure 5.2. No type of cancer will always follow the same steps with fixed
                              transition rates between steps. But a thorough understanding of the
                              simplest case puts us in a better position to study more realistic as-
                              sumptions.
                                In this section, I assume that the transitions between steps happen at
                              the same rate, u, and that everyone is born in stage 0. Individuals who
                              progress through the nth stage develop cancer.
                                With these assumptions, the fraction of the population at age t in each
                              precancerous stage is given by the Poisson distribution with a mean of
                              ut. Intuitively, ut would be the average number of transitions passed if
                              there were unlimited stages, because u is the transition rate per stage
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