Department of Biomedical Engineering, Pennsylvania State University, State College PA, USA.
Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Soft Matter. 2022 May 11;18(18):3465-3472. doi: 10.1039/d2sm00071g.
Metastatic cancer has a poor prognosis, because it is broadly disseminated and associated with both intrinsic and acquired drug resistance. Critical unmet needs in effectively killing drug resistant cancer cells include overcoming the drug desensitization characteristics of some metastatic cancers/lesions, and tailoring therapeutic regimens to both the tumor microenvironment and the genetic profiles of the resident cancer cells. Bioengineers and materials scientists are developing technologies to determine how metastatic sites exclude therapies, and how extracellular factors (including cells, proteins, metabolites, extracellular matrix, and abiotic factors) at metastatic sites significantly affect drug pharmacodynamics. Two looming challenges are determining which feature, or combination of features, from the tumor microenvironment drive drug resistance, and what the relative impact is of extracellular signals intrinsic cell genetics in determining drug response. Sophisticated systems biology tools that can de-convolve a crowded network of signals and responses, as well as controllable microenvironments capable of providing discrete and tunable extracellular cues can help us begin to interrogate the high dimensional interactions governing drug resistance in patients.
转移性癌症预后不良,因为它广泛传播,并与内在和获得性药物耐药性有关。有效杀死耐药癌细胞的关键未满足需求包括克服一些转移性癌症/病变的药物脱敏特征,以及根据肿瘤微环境和驻留癌细胞的遗传特征定制治疗方案。生物工程师和材料科学家正在开发技术来确定转移性部位如何排除治疗方法,以及转移性部位的细胞外因素(包括细胞、蛋白质、代谢物、细胞外基质和非生物因素)如何显著影响药物药效动力学。两个迫在眉睫的挑战是确定肿瘤微环境中的哪些特征或特征组合驱动药物耐药性,以及细胞外信号对药物反应的相对影响 内在细胞遗传学在决定药物反应中的作用。能够解卷积信号和反应拥挤网络的复杂系统生物学工具,以及能够提供离散和可调细胞外线索的可控微环境,可以帮助我们开始研究控制患者耐药性的高维相互作用。