Molecular deconstruction, detection, and computational prediction of microenvironment-modulated cellular responses to cancer therapeutics

被引:9
|
作者
LaBarge, Mark A. [1 ]
Parvin, Bahram [1 ]
Lorens, James B. [2 ,3 ]
机构
[1] Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Div Life Sci, Berkeley, CA 94720 USA
[2] Univ Bergen, Dept Biomed, NO-5020 Bergen, Norway
[3] Univ Bergen, Ctr Canc Biomarkers, NO-5020 Bergen, Norway
基金
美国国家卫生研究院;
关键词
Microenvironment; Cancer; Therapeutic response; Computation; MESENCHYMAL TRANSITION; STEM-CELLS; ADHESION; CULTURE; HETEROGENEITY; ORGANIZATION; MICROARRAY; PLASTICITY; MODELS; GROWTH;
D O I
10.1016/j.addr.2014.02.009
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The field of bioengineering has pioneered the application of new precision fabrication technologies to model the different geometric, physical or molecular components of tissue microenvironments on solid-state substrata. Tissue engineering approaches building on these advances are used to assemble multicellular mimetic-tissues where cells reside within defined spatial contexts. The functional responses of cells in fabricated microenvironments have revealed a rich interplay between the genome and extracellular effectors in determining cellular phenotypes and in a number of cases have revealed the dominance of microenvironment over genotype. Precision bioengineered substrata are limited to a few aspects, whereas cell/tissue-derived microenvironments have many undefined components. Thus, introducing a computational module may serve to integrate these types of platforms to create reasonable models of drug responses in human tissues. This review discusses how combinatorial microenvironment microarrays and other biomimetic microenvironments have revealed emergent properties of cells in particular microenvironmental contexts, the platforms that can measure phenotypic changes within those contexts, and the computational tools that can unify the microenvironment-imposed functional phenotypes with underlying constellations of proteins and genes. Ultimately we propose that a merger of these technologies will enable more accurate pre-clinical drug discovery. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:123 / 131
页数:9
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