Applicability of drug response metrics for cancer studies using biomaterials

被引:49
作者
Brooks, Elizabeth A. [1 ]
Galarza, Sualyneth [1 ]
Gencoglu, Maria F. [1 ]
Cornelison, R. Chase [2 ]
Munson, Jennifer M. [2 ]
Peyton, Shelly R. [1 ]
机构
[1] Univ Massachusetts, Dept Chem Engn, 240 Thatcher Rd, Amherst, MA 01003 USA
[2] Virginia Tech, Dept Biomed Engn & Mech, 325 Stanger St, Blacksburg, VA 24061 USA
基金
美国国家卫生研究院;
关键词
breast cancer; ovarian cancer; drug resistance; bioengineering; extracellular matrix; tumour microenvironment; SENSITIVITY; PROLIFERATION; RESISTANCE; COCULTURE; CARCINOMA; CULTURE; GROWTH; MODEL; ASSAY;
D O I
10.1098/rstb.2018.0226
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:12
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