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1 Age Specific Cancer Incidence for Two Major Historical Models, Compared to the Beta Model and SEER Data I(t)=(  t) k-1 (1-  t  I(t)=at k-1 I(t) 

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Presentation on theme: "1 Age Specific Cancer Incidence for Two Major Historical Models, Compared to the Beta Model and SEER Data I(t)=(  t) k-1 (1-  t  I(t)=at k-1 I(t) "— Presentation transcript:

1 1 Age Specific Cancer Incidence for Two Major Historical Models, Compared to the Beta Model and SEER Data I(t)=(  t) k-1 (1-  t  I(t)=at k-1 I(t)   1  2  N(s)exp[(  2 -  2 )(t -s)]ds

2 2 Beta Fit to SEER Data Age-specific incidence per 100,000

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7 7 For the 6 gender-specific sites the fits are performed with t = (age-15)  0, as suggested by Armitage and Doll (1954).

8 8 Beta Fit to SEER Data Age-specific incidence per 100,000 (Ries et al 2000)

9 9 Beta Fit to California Data Age-specific incidence per 100,000 (Saltzstein et al 1998)

10 10 Beta Fit to Dutch Data Age-specific incidence per 100,000 (de Rijke et al 2000), error bars ±2 SEM

11 11 Beta Fit to Dutch Data Age-specific incidence per 100,000 (de Rijke et al 2000), error bars ±2 SEM

12 12 Age-Specific Incidence Normalized to the Peak Value for Each Cancer. All Male Sites Except Childhood Cancers (Hodgkins, Thyroid, Testes).

13 13 Liver Tumor Rates Vs. Age for NTP (TDMS) Mice Controls Removed for Natural Death or Morbidity Error bars = ±1 SEM

14 14 ED01 Control Mice Age-Specific Mortality With Beta Function Fit. Error bars = ±1 SEM

15 15 ED01 Age-specific Mortality for All Neoplasms Causes of Death vs. Dose of 2-AAF, With Beta Function Fit. Error bars = ±1 SEM

16 16 ED01 Age-specific Mortality for All Neoplasms Causes of Death vs. Dose of 2-AAF, With Beta Function Fit. Error bars = ±1 SEM

17 17 ED01 Age-specific Mortality for All Neoplasms Causes of Death vs. Dose of 2-AAF, With Beta Function Fit. Error bars = ±1 SEM

18 18 ED01 Age-specific Mortality for All Neoplasms Causes of Death vs. Dose of 2-AAF, With Beta Function Fit. Error bars = ±1 SEM

19 19 Cell Replicative Senescence As Biological Cause of the Turnover Widely accepted characteristics of replicative senescence: 1.That cellular replicative capacity is limited has been known for 40 years. 2.Has been observed in vitro and in vivo for many cell types, both animal and human. 3.Is closely related to the ageing process. 4.Is a dominant phenotype when fused with immortal tumor-derived cells. 5.Considered to be an important anti-tumor mechanism. 6.Cells senesce by fraction of population, rather than all at the same time. 7.Senescent cells function normally, but are unable to repair or renew themselves.

20 20 Cell Replicative Senescence: Cells Retaining Proliferative Ability Decrease With Number of Cell Divisions.

21 21 Cell Replicative Senescence: Increase in Age Decreases the Number of Cells With Replicative Capacity.

22 22 Cell Replicative Senescence: Beta Model Cells In Vitro Age Non-senescent cells Cells In Vivo Age Remaining pool of cells able to cause cancer Cells in “Cancer Pool” = N o (1-  t)  = (lifespan) -1 I(t) = (  t) k-1 (1-  t)

23 23 Influence of Senescence Rate on Age-Specific Cancer Incidence in Mice.

24 24 Probability of Tumors in p53 Altered Mice Compared to Beta and MVK-s Model Predictions.

25 25 Age-Specific Cancer Mortality for Female CBA Mice Dosed with Melatonin vs. Controls. Data from Anisimov et al 2001.

26 26 Influence of Senescence on Cancer Mortality and Lifetime

27 27 Senescence and Dietary Restriction

28 28 Senescence and Dietary Restriction

29 29 Conclusions 1.Cancer incidence turnover likely caused by cellular senescence 2.Reducing senescence might be an attractive intervention to prolong life, even if cancer is increased. 3.Dietary restriction might be an example of interventions that both reduce senescence and reduce carcinogenesis. There may be others.


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