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

doi:10.1016/j.cell.2011.11.060

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 journal › Article › peer-review

286 Scopus citations

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 language	English (US)
Pages (from-to)	362-375
Number of pages	14
Journal	Cell
Volume	148
Issue number	1-2
DOIs	https://doi.org/10.1016/j.cell.2011.11.060
State	Published - Jan 20 2012
Externally published	Yes

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)

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title = "Computational modeling of pancreatic cancer reveals kinetics of metastasis suggesting optimum treatment strategies",

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.",

author = "Hiroshi Haeno and Mithat Gonen and Davis, {Meghan B.} and Herman, {Joseph M.} and Iacobuzio-Donahue, {Christine A.} and Franziska Michor",

note = "Funding Information: The authors would like to thank the Michor lab and Georg L{\"u}beck for helpful comments. This work was supported by National Institutes of Health grants CA106610 and CA62924 (C.A.I.-D.), Pilot Funding from the Sol Goldman Pancreatic Cancer Research Center, the Michael Rolfe Pancreatic Cancer Foundation, the George Rubis Endowment for Pancreatic Cancer Research, the Joseph C. Monastra Foundation for Pancreatic Cancer Research, and The Alfredo Scatena Memorial Fund. Furthermore, we would like to acknowledge support from the National Cancer Institute's Physical Sciences-Oncology Center, U54CA143798 (H.H., M.G., and F.M.). ",

year = "2012",

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doi = "10.1016/j.cell.2011.11.060",

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T1 - Computational modeling of pancreatic cancer reveals kinetics of metastasis suggesting optimum treatment strategies

AU - Haeno, Hiroshi

AU - Gonen, Mithat

AU - Davis, Meghan B.

AU - Herman, Joseph M.

AU - Iacobuzio-Donahue, Christine A.

AU - Michor, Franziska

N1 - Funding Information: The authors would like to thank the Michor lab and Georg Lübeck for helpful comments. This work was supported by National Institutes of Health grants CA106610 and CA62924 (C.A.I.-D.), Pilot Funding from the Sol Goldman Pancreatic Cancer Research Center, the Michael Rolfe Pancreatic Cancer Foundation, the George Rubis Endowment for Pancreatic Cancer Research, the Joseph C. Monastra Foundation for Pancreatic Cancer Research, and The Alfredo Scatena Memorial Fund. Furthermore, we would like to acknowledge support from the National Cancer Institute's Physical Sciences-Oncology Center, U54CA143798 (H.H., M.G., and F.M.).

PY - 2012/1/20

Y1 - 2012/1/20

N2 - 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.

AB - 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.

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

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