Modelling circulating tumour cells for personalised survival prediction in metastatic breast cancer

Gianluca Ascolani, Annalisa Occhipinti, Pietro Liò

    Research output: Contribution to journalArticle

    Abstract

    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.
    Original languageEnglish
    Pages (from-to)e1004199
    JournalPLoS Computational Biology
    Volume11
    Issue number5
    DOIs
    Publication statusPublished - 2015

    Fingerprint Dive into the research topics of 'Modelling circulating tumour cells for personalised survival prediction in metastatic breast cancer'. Together they form a unique fingerprint.

  • Profiles

    Cite this