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 journalArticle

Abstract

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 (US)
Pages (from-to)362-375
Number of pages14
JournalCell
Volume148
Issue number1-2
DOIs
StatePublished - Jan 20 2012

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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    Haeno, H., Gonen, M., Davis, M. B., Herman, J. M., Iacobuzio-Donahue, C. A., & Michor, F. (2012). Computational modeling of pancreatic cancer reveals kinetics of metastasis suggesting optimum treatment strategies. Cell, 148(1-2), 362-375. https://doi.org/10.1016/j.cell.2011.11.060