Page 43 - 20dynamics of cancer

28 CHAPTER 2

1.0 0.8
Fraction surviving 0.6 0.4

0.2

5 10 15 20
Age in months

Figure 2.7 Age of lymphoma onset in mice with different mismatch repair
genotypes: Mlh3, dashed line; Pms2, dot-dashed line; Mlh1, solid line; and
Mlh3Pms2, dotted line. For each genotype, both alleles at each locus were
knocked out. Data presented as traditional Kaplan-Meier plots, which show
the fraction of mice without tumors at each age. Figure modified from Frank
et al. (2005).

various hypotheses to explain these incidence and acceleration patterns.
The retinoblastoma data have been particularly important in under-
standing how inherited and somatic mutations influence cancer progres-
sion (Knudson 1993).
Many recent laboratory studies compare the age-onset patterns of
cancer between mice with different genotypes. These controlled exper-
iments provide a clearer picture of the role of inherited genetic differ-
ences than do the uncontrolled comparisons between humans with dif-
ferent inherited mutations. However, most of the mouse studies have
small sample sizes, making it difficult to obtain good estimates for age-
onset patterns.
Figure 2.7 compares the age-onset patterns of tumors between mice
with different DNA mismatch repair (MMR) genes knocked out. The fig-
ure presents Kaplan-Meier survival plots, the traditional way in which
such data are reported. These plots show an association between the
increase in mutation rate for defective MMR genes and a shift to earlier
ages of tumor onset, in which the ordering of mutation rate is: Mlh3 <
Pms2 < Mlh1 ≈ Mlh3Pms2 (Frank et al. 2005).
Analyses of laboratory experiments usually do not extract the quan-
titative information about age-specific incidence and acceleration from
survival plots. Thus, such experiments leave unanalyzed much of the