Computational modeling of pancreatic cancer reveals kinetics of metastasis suggesting optimum treatment strategies

Hiroshi Haeno, Mithat Gonen, Meghan B. Davis, Joseph M. Herman, Christine A. Iacobuzio-Donahue, Franziska Michor

Research output: Contribution to journalArticlepeer-review

335 Citations (Scopus)


Pancreatic cancer is a leading cause of cancer-related death, largely due to metastatic dissemination. We investigated pancreatic cancer progression by utilizing a mathematical framework of metastasis formation together with comprehensive data of 228 patients, 101 of whom had autopsies. We found that pancreatic cancer growth is initially exponential. After estimating the rates of pancreatic cancer growth and dissemination, we determined that patients likely harbor metastases at diagnosis and predicted the number and size distribution of metastases as well as patient survival. These findings were validated in an independent database. Finally, we analyzed the effects of different treatment modalities, finding that therapies that efficiently reduce the growth rate of cells earlier in the course of treatment appear to be superior to upfront tumor resection. These predictions can be validated in the clinic. Our interdisciplinary approach provides insights into the dynamics of pancreatic cancer metastasis and identifies optimum therapeutic interventions.

Original languageEnglish
Pages (from-to)362-375
Number of pages14
Issue number1-2
Publication statusPublished - Jan 20 2012
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Biochemistry,Genetics and Molecular Biology


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