Differential response to doxorubicin in breast cancer subtypes simulated by a microfluidic tumor model

Özçelikkale, Altuğ
Noe-Kim, Victoria
Elzey, Bennett D.
Dong, Zizheng
Zhang, Jian-Ting
Kim, Kwangmeyung
Kwon, Ick Chan
Park, Kinam
Han, Bumsoo
Successful drug delivery and overcoming drug resistance are the primary clinical challenges for management and treatment of cancer. The ability to rapidly screen drugs and delivery systems within physiologically relevant environments is critically important; yet is currently limited due to lack of appropriate tumor models. To address this problem, we developed the Tumor-microenvironment-on-chip (T-MOC), a new microfluidic tumor model simulating the interstitial flow, plasma clearance, and transport of the drug within the tumor. We demonstrated T-MOC's capabilities by assessing the delivery and efficacy of doxorubicin in small molecular form versus hyaluronic acid nanoparticle (NP) formulation in MCF-7 and MDA-MB-231, two cell lines representative of different molecular subtypes of breast cancer. Doxorubicin accumulated and penetrated similarly in both cell lines while the NP accumulated more in MDA-MB-231 than MCF-7 potentially due to binding of hyaluronic acid to CD44 expressed by MDA-MB-231. However, the penetration of the NP was less than the molecular drug due to its larger size. In addition, both cell lines cultured on the T-MOC showed increased resistance to the drug compared to 2D culture where MDA-MB-231 attained a drug-resistant tumor-initiating phenotype indicated by increased CD44 expression. When grown in immunocompromised mice, both cell lines exhibited cell-type-dependent resistance and phenotypic changes similar to T-MOC, confirming its predictive ability for in vivo drug response. This initial characterization of T-MOC indicates its transformative potential for in vitro testing of drug efficacy towards prediction of in vivo outcomes and investigation of drug resistance mechanisms for advancement of personalized medicine.


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Citation Formats
A. Özçelikkale et al., “Differential response to doxorubicin in breast cancer subtypes simulated by a microfluidic tumor model,” JOURNAL OF CONTROLLED RELEASE, pp. 129–139, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69547.