Abstract
This work is devoted to modelling gastrointestinal stromal tumour metastases to the liver, their growth and resistance to therapies. More precisely, resistance to two standard treatments based on tyrosine kinase inhibitors (imatinib and sunitinib) is observed clinically. Using observations from medical images (CT scans), we build a spatial model consisting in a set of non-linear partial differential equations. After calibration of its parameters with clinical data, this model reproduces qualitatively and quantitatively the spatial tumour evolution of one specific patient. Important features of the growth such as the appearance of spatial heterogeneities and the therapeutical failures may be explained by our model. We then investigate numerically the possibility of optimizing the treatment in terms of progression-free survival time and minimum tumour size reachable by varying the dose of the first treatment. We find that according to our model, the progression-free survival time reaches a plateau with respect to this dose. We also demonstrate numerically that the spatial structure of the tumour may provide much more insights on the cancer cell activities than the standard RECIST criteria, which only consists in the measurement of the tumour diameter. Finally, we discuss on the non-predictivity of the model using only CT scans, in the sense that the early behaviour of the lesion is not sufficient to predict the response to the treatment.
Highlights
Gastrointestinal stromal tumours (GIST) are the most common mesenchymal tumours of the gastrointestinal tract, with an incidence of 9–14 cases per million people per year
Since Hounsfield unit makes it possible to quantify the tumour area and to detect its location on CT scans, we introduce a numerical Hounsfield unit, which is a linear combination of the numerical results
We have provided a patient-dependent model, based on PDEs, that describes the global behaviour of GIST metastasis to the liver during the different stages
Summary
Gastrointestinal stromal tumours (GIST) are the most common mesenchymal tumours of the gastrointestinal tract, with an incidence of 9–14 cases per million people per year (see Nilsson et al, 2005). In 25% of cases (see DeMatteo et al, 2000), this type of cancer spreads to the liver. Even though GISTs resist to most of conventional cancer chemotherapies, the discovery of activating mutations of the KIT as well as the role of PDGFR and the new subsequent therapeutic development have revolutionized GISTs treatments. Thanks to the availability of these highly active targeted therapeutic agents, GISTs have become typical models of personalized treatment of cancer (Blay et al, 2012). Several limitations in terms of diagnosis and outcomes still remain
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