A new approach for estimating the progression of pancreatic cancer

Abstract

Cancer of the pancreas is a highly lethal disease and has an extremely poor prognosis. It is the fourth leading cause of death from cancer in the US and the twelfth worldwide. There are currently only few therapeutic options for patients with pancreatic cancer. Hence new insights into the pathogenesis of this lethal disease are urgently needed. In recent years, extensive biological research has been conducted to study the mechanisms that control the initiation and progression of pancreas cancer. Mathematical models have also been used to present quantitative analysis and predict reasonable time schemes for the progression of pancreatic cancer. However, in those published articles, it was assumed that the mutation rate was constant, which is not realistic. In this work, we present a new approach using non-constant mutation rate and hence reveal several important biological parameters of cancer progression, such as initial mutation rate as well as doubling time (or selective advantage coefficients) in different stages, and eventually present a better time scheme. Under more realistic assumptions regarding gene mutation and a more reasonable mutation rate, the averaged values of doubling time and selective advantage coefficient generated by our model are consistent with the predictions made by the published models.