Low-dose anti-inflammatory combinatorial therapy reduced cancer stem cell formation in patient-derived preclinical models for tumour relapse prevention
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s41416-018-0301-9.pdf
Description
Published version
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4.54 MB
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Checksum (MD5)
66b70f7625a8f1309831d18978816025
Author(s)
Khoo, Bee Luan
Grenci, Gianluca
Lim, Joey Sze Yun
Lim, Yan Ping
Fong, July
Yeap, Wei Hseun
Lim, Su Bin
Chua, Song Lin
Wong, Siew Cheng
Yap, Yoon-Sim
Date Issued
February 2019
Journal
British Journal of Cancer
Citation
Khoo, Bee Luan, Gianluca Grenci, Joey Sze Yun Lim et al. "Low-dose anti-inflammatory combinatorial therapy reduced cancer stem cell formation in patient-derived preclinical models for tumour relapse prevention." British Journal of Cancer (February 2019) 120:407-423 © 2019, The Author(s).
Version
Final published version
Abstract
Background: Emergence of drug-resistant cancer phenotypes is a challenge for anti-cancer therapy. Cancer stem cells are identified as one of the ways by which chemoresistance develops. Method: We investigated the anti-inflammatory combinatorial treatment (DA) of doxorubicin and aspirin using a preclinical microfluidic model on cancer cell lines and patient-derived circulating tumour cell clusters. The model had been previously demonstrated to predict patient overall prognosis. Results: We demonstrated that low-dose aspirin with a sub-optimal dose of doxorubicin for 72 h could generate higher killing efficacy and enhanced apoptosis. Seven days of DA treatment significantly reduced the proportion of cancer stem cells and colony-forming ability. DA treatment delayed the inhibition of interleukin-6 secretion, which is mediated by both COX-dependent and independent pathways. The response of patients varied due to clinical heterogeneity, with 62.5% and 64.7% of samples demonstrating higher killing efficacy or reduction in cancer stem cell (CSC) proportions after DA treatment, respectively. These results highlight the importance of using patient-derived models for drug discovery. Conclusions: This preclinical proof of concept seeks to reduce the onset of CSCs generated post treatment by stressful stimuli. Our study will promote a better understanding of anti-inflammatory treatments for cancer and reduce the risk of relapse in patients.
MIT Department
Singapore-MIT Alliance in Research and Technology (SMART)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Biological Engineering
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Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/s41416-018-0301-9
