Prediction of Drug Response in Breast Cancer Using Integrative Experimental/Computational Modeling

Abstract

Nearly 30% of women with early-stage breast cancer develop recurrent disease attributed to resistance to systemic therapy. Prevailing models of chemotherapy failure describe three resistant phenotypes: cells with alterations in transmembrane drug transport, increased detoxification and repair pathways, and alterations leading to failure of apoptosis. Proliferative activity correlates with tumor sensitivity. Cell-cycle status, controlling proliferation, depends on local concentration of oxygen and nutrients. Although physiologic resistance due to diffusion gradients of these substances and drugs is a recognized phenomenon, it has been difficult to quantify its role with any accuracy that can be exploited clinically. We implement a mathematical model of tumor drug response that hypothesizes specific functional relationships linking tumor growth and regression to the underlying phenotype. The model incorporates the effects of local drug, oxygen, and nutrient concentrations within the three-dimensional tumor volume, and includes the experimentally observed resistant phenotypes of individual cells. We conclude that this integrative method, tightly coupling computational modeling with biological data, enhances the value of knowledge gained from current pharmacokinetic measurements, and, further, that such an approach could predict resistance based on specific tumor properties and thus improve treatment outcome. [Cancer Res 2009;69(10):4484-92]

A Novel, Patient-Specific Mathematical Pathology Approach for Assessment of Surgical Volume: Application to Ductal Carcinomain situof The Breast

“…Analysis [1] of the model reveals that the geometric mean of the tumor dimensions (i.e., the cube-root of the surgical volume or, as expressed in our model, the diameter 2R) reaches a (nearly) stationary value, which is set by an overall balance of mass gain from proliferation in well oxygenated areas and mass loss from cell death in hypoxic or nutrient-depleted areas. Our simulations using a range of physiological input values (as described below) show that DCIS tumors reach nearly stationary sizes following a short period of fast growth which may last as little as about two months [31,32]. Given such short growth time compared to yearly screenings by mammogram, we may expect most DCIS tumors to be near their stationary size at the time of diagnosis.…”

Multiscale Cancer Modeling

“…Sinek, Frieboes, Cristini and coworkers developed a cell-scale compartmental model of chemotherapeutic drug (doxorubicin) transport within a cell's cytoplasm and nucleus, which they combined with a mechanistic model of DNA-drug adduct formation, repair, and apoptosis (89)(90)(91). Their model accounted for cell cycling effects by varying the probability of apoptosis with the substrate level via a Hill-type function.…”

Mathematical model of cancer growth controled by metronomic chemotherapies

“…As far as the resistance problem is concerned, let us mention the works of [26,35,36,57]. For instance, Jackson et al [36] developed a PDE model that describes the chemotherapeutic response of a sphericallysymmetric tumor composed of two types of cells differing by their drug sensitivity.…”