Modelling circulating tumour cells for personalised survival prediction in metastatic breast cancer.
PLoS Comput Biol
Public Library of Science (PLoS)
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Ascolani, G., Occhipinti, A., & Lio, P. (2015). Modelling circulating tumour cells for personalised survival prediction in metastatic breast cancer.. PLoS Comput Biol, 11 (5), e1004199. https://doi.org/10.1371/journal.pcbi.1004199
Ductal carcinoma is one of the most common cancers among women, and the main cause of death is the formation of metastases. The development of metastases is caused by cancer cells that migrate from the primary tumour site (the mammary duct) through the blood vessels and extravasating they initiate metastasis. Here, we propose a multi-compartment model which mimics the dynamics of tumoural cells in the mammary duct, in the circulatory system and in the bone. Through a branching process model, we describe the relation between the survival times and the four markers mainly involved in metastatic breast cancer (EPCAM, CD47, CD44 and MET). In particular, the model takes into account the gene expression profile of circulating tumour cells to predict personalised survival probability. We also include the administration of drugs as bisphosphonates, which reduce the formation of circulating tumour cells and their survival in the blood vessels, in order to analyse the dynamic changes induced by the therapy. We analyse the effects of circulating tumour cells on the progression of the disease providing a quantitative measure of the cell driver mutations needed for invading the bone tissue. Our model allows to design intervention scenarios that alter the patient-specific survival probability by modifying the populations of circulating tumour cells and it could be extended to other cancer metastasis dynamics.
Humans, Carcinoma, Ductal, Breast, Breast Neoplasms, Disease Progression, Transforming Growth Factor beta, Survival Rate, Gene Expression Profiling, Models, Biological, Computer Simulation, Female, Neoplastic Cells, Circulating, Kaplan-Meier Estimate, Biomarkers, Tumor
External DOI: https://doi.org/10.1371/journal.pcbi.1004199
This record's URL: https://www.repository.cam.ac.uk/handle/1810/284994
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/