Instantaneous mutation rate in cancer initiation and progression

Shuhao Sun, Fima C Klebaner, Xinan Zhang, Tianhai Tian

Research output: Contribution to journalArticleResearchpeer-review


BACKGROUND: Cancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes. RESULTS: To accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time. CONCLUSIONS: The proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.

Original languageEnglish
Pages (from-to)91-98
Number of pages8
JournalBMC Systems Biology
Issue numberSuppl 6
Publication statusPublished - 22 Nov 2018


  • Cancer
  • Mathematical model
  • Initial mutation rate
  • Cancer cell doubling time

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