Applicability of drug response metrics for cancer studies using biomaterials

Abstract

Bioengineers have built models of the tumour microenvironment (TME) in which to study cell–cell interactions, mechanisms of cancer growth and metastasis, and to test new therapies. These models allow researchers to culture cells in conditions that include features of the in vivo TME implicated in regulating cancer progression, such as extracellular matrix (ECM) stiffness, integrin binding to the ECM, immune and stromal cells, growth factor and cytokine depots, and a three-dimensional geometry more representative of the in vivo TME than tissue culture polystyrene (TCPS). These biomaterials could be particularly useful for drug screening applications to make better predictions of efficacy, offering better translation to preclinical models and clinical trials. However, it can be challenging to compare drug response reports across different biomaterial platforms in the current literature. This is, in part, a result of inconsistent reporting and improper use of drug response metrics, and vast differences in cell growth rates across a large variety of biomaterial designs. This study attempts to clarify the definitions of drug response measurements used in the field, and presents examples in which these measurements can and cannot be applied. We suggest as best practice to measure the growth rate of cells in the absence of drug, and follow our ‘decision tree’ when reporting drug response metrics. This article is part of a discussion meeting issue ‘Forces in cancer: interdisciplinary approaches in tumour mechanobiology’.

Human Plasma-Derived 3D Cultures Model Breast Cancer Treatment Responses and Predict Clinically Effective Drug Treatment Concentrations

“…Drug response metrics based on relative cell count could be influenced by the number of cell divisions or plating density as these metrics do not take into account the initial cell population and the number of cell divisions during the course of the assay [37,39]. GR metrics could be influenced by the potency and efficacy of the drug and resistance profiles of the cell lines [29], as well as by the temporal dependence of drug response [97]. In addition, both types of metrics could be affected by the intra-assay variability due to the fact that the matrix is generated from plasma from non-matching subjects.…”

“…All this evidence suggests that 3D cell culture techniques provide useful advantages for representing in vivo tumor-like environments and modelling drug sensitivity [26][27][28]; however, there are still challenges. Some of the current limitations to these 3D culture models include the incorporation of exogenous ECM materials that might introduce undesired confounding artifacts to the recreation of tumor behaviors, the establishment of differences in cell growth rates in the model, and the varying use of drug metrics across different culture techniques [29]. Protein-based hydrogels, such as fibrin hydrogels, have been used in a wide range of applications including regenerative medicine, drug delivery, and as 3D culture models [30,31].…”

A patient-designed tissue-engineered model of the infiltrative glioblastoma microenvironment

“…Furthermore, IC 50 calculations often did not apply to metrics of invasion, proliferation, and stemness, as these did not consistently decrease toward zero (and sometimes increased) even at high drug concentrations. There are also other metrics – like EC 50 , GI 50 , and GR 50 – which have different calculation requirements and provide different insight ( 36 ), suggesting it is worth exploring the potential of these alternative metrics in future analyses.…”

The forces of cancer

“…hydrogel stiffness). In this issue, Val Weaver and colleagues [9] survey current methods for quantifying ECM and cell mechanics at different scales, with a particular focus on brain and central nervous system tumours [9]. Shelley Peyton and colleagues discuss new metrics for assessing the response of cancer cells in hydrogel and co-culture matrices to small-molecule treatments from an engineering perspective [10].…”