Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab

Abstract

Resistance to targeted cancer therapies such as trastuzumab is a frequent clinical problem not solely because of insufficient expression of HER2 receptor but also because of the overriding activation states of cell signaling pathways. Systems biology approaches lend themselves to rapid in silico testing of factors, which may confer resistance to targeted therapies. In this study, we aimed to develop a new kinetic model that could be interrogated to predict resistance to receptor tyrosine kinase (RTK) inhibitor therapies and directly test predictions in vitro and in clinical samples. The new mathematical model included RTK inhibitor antibody binding, HER2/HER3 dimerization and inhibition, AKT/mitogenactivated protein kinase cross-talk, and the regulatory properties of PTEN. The model was parameterized using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays. Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapy in silico, which was predictive of unseen experiments in vitro using the PTEN inhibitor bp(V). When measured in cancer cell lines, PTEN expression predicts sensitivity to anti-HER2 therapy; furthermore, this quantitative measurement is more predictive of response (relative risk, 3.0; 95% confidence interval, 1.6-5.5; P < 0.0001) than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of 122 breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalized therapy in cancer and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti-HER2 therapies. [Cancer Res 2009;69(16):6713-20]

In-Silico Methodologies for Cancer Multidrug Optimization

“…Based on a mass-action model of heregulin-induced HER2/3 signaling, Faratian et al [110] predicted that PIK3CA inhibition should be combined with RTK inhibitors in tumor cases that have low PTEN.…”

Engineering Simulations for Cancer Systems Biology

“…Constitutive activation and aberrant EGFR signalling has been identified in a wide variety of human cancers and this network is a promising target of anticancer therapy [34]. The key aims of modelling this signalling system are to: describe input-output characteristics of the signalling systems; determine the response of the signalling network to activation by an input signal and its inhibition by drug action; identify the best targets in the signalling network for anticancer therapy; dissect mechanisms of drug resistance; and identify design and selection criteria for an optimal therapeutic strategy [32,33,26].…”

“…drug resistance [11]. The dynamics of these associations are represented by equations describing rates of change of concentrations of species [26]. Such mechanistic representations, while being only simplifications of the real system based on what is known [27], can offer insights into the link between biological mechanisms and signalling responses [28], and so can assist in unravelling the complexities embodied in these signalling networks [21].…”

“…Of particular interest is the use of modelling to assess the impact of drug intervention strategies on signalling network functioning and to understand how therapeutic resistance occurs. Here, for illustration of current practice, we review three systems biology approaches to signalling network modelling with descriptions of large scale models of epidermal growth factor receptor (EGFR) signalling and its application to anticancer therapy [32,33,26].…”

Targeting HER2-Driven Cancers in Non-Breast Cancer Malignancies

“…Furthermore, it would be valuable to identify additional biomarkers alongside HER2 that helps identify the sensitive population who are most likely to benefit. There are already biomarkers downstream of HER2 such as PTEN and SPROUTY [10,11] which can help identify breast cancers that are likely to be more resistant to trastuzumab and these may have value in high HER2 expressing non-breast cancers to help predict sensitivity.…”