The mathematical biology of pancreatic cancer: Models of carcinogenesis and stages

1. The mathematical biology of pancreatic cancer: Models of carcinogenesis and stages G. M. Jacquez

2. Our Dear Friend and ColleagueJawaid Rasul8/2/1953 - 5/22/2011

3. Research stage • In progress • Monograph completed • http://www.biomedware.com/publications/71modelingcarcinogenesisandcancerstagespancreaticcancer.pdf • Not yet peer-reviewed

4. Abstract: Pancreatic cancer has been called the "silent killer" because it is typically diagnosed at advanced stages and because the prognosis is so poor, with a mean survivorship of about one year. The last five years have seen an increased understanding of the genetic basis of pancreatic cancer, and the cascade of mutations and pathways that lead to carcinogenesis are beginning to be elucidated. However, these have yet to be incorporated into models that bridge scales from the cellular to the individual, to the population. We present two compartmental models of pancreatic cancer. The first models pathways and events at the molecular and cellular level that lead to pancreatic cancer, the second deals with cancer stage at diagnosis and may be estimated using cancer registry data. Residence times in these models corresponds to cancer latency, which has implications for cancer surveillance and medical geography.

5. Problem • Approach • Results • Conclusion

6. Problem • Approach • Results • Conclusion

7. Behavsome Genome + Exposome

8. The Challenge • How to integrate burgeoning knowledge of genomics, environment and behaviors to forecast cancer outcomes, and to improve cancer surveillance and control?

9. Solution characteristics • Estimates disease latency • Bridges biological scales • Genetic – molecular – organ – individual – population • Generalizable • Across cancers and populations • Useful • Models can be employed with currently available data based on reasonable assumptions; predict silent cancer burden; conditions for cancer metastasis and remission

10. Problem • Approach • Results • Conclusion

12. Compartmental analysis

13. Residence times in compartmental systems

16. Model coefficients & parameters

19. Linking carcinogenesis and stage

20. Pancreatic cancer in SE MI • 11,068 incident cases 1985-2005, SE Michigan • 8,826 cases with known place of residence and known stage at diagnosis. • Males accounted for 4,202 cases and females 4,424. • 6,356 cases were whites, 2,192 blacks, and the balance American Indian (8 cases), Asian (61) and other or unknown groups (9).

21. Problem • Approach • Results • Conclusion

22. Latency estimates • Closed form solution, disease latency ~Erlang • ~21.2 years initiation to diagnosis

23. Conditions for remission and metastasis

24. Silent cancer burden

25. Problem • Approach • Results • Conclusion

26. Conclusions • Provides estimates of disease latency using the Erlang distribution • Bridges biological scales • Genetic – molecular – organ – individual – population • Appears generalizable • Across cancers and populations • Appears useful • Models can be employed with currently available data based on reasonable assumptions; predicts silent cancer burden; conditions for cancer metastasis and remission

27. Caveats • Not yet peer-reviewed! • Check it out • http://www.biomedware.com/publications/71modelingcarcinogenesisandcancerstagespancreaticcancer.pdf