Modeling Spontaneous Metastasis following Surgery: An In Vivo-In Silico Approach.

ABSTRACT: Rapid improvements in the detection and tracking of early-stage tumor progression aim to guide decisions regarding cancer treatments as well as predict metastatic recurrence in patients following surgery. Mathematical models may have the potential to further assist in estimating metastatic risk, particularly when paired with in vivo tumor data that faithfully represent all stages of disease progression. Herein, we describe mathematical analysis that uses data from mouse models of spontaneous metastasis developing after surgical removal of orthotopically implanted primary tumors. Both presurgical (primary tumor) growth and postsurgical (metastatic) growth were quantified using bioluminescence and were then used to generate a mathematical formalism based on general laws of the disease (i.e.,

SUBMITTER: Benzekry S 

PROVIDER: S-EPMC5846333 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature