Low-dose anti-inflammatory combinatorial therapy reduced cancer stem cell formation in patient-derived preclinical models for tumour relapse prevention

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. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Singapore-MIT Alliance for Research and Technology (SMART) Published version We are grateful to the personnel who have provided technical support and facility usage located at the Singapore–MIT Alliance for Research and Technology (SMART)—BioSystems and Micromechanics (BioSyM) Laboratory, MBI and SIgN at A*STAR (Agency for Science Technology and Research). We thank Diego Pitta de Araujo of the MBI Science Communications Unit for the help in drawing 3D models of the device. We also appreciate the analysis and facility usage at the Department of Chemistry, NUS, for the elemental analysis. One or more authors have a pending patent related to this work. The experimental work and data collection were supported by the Singapore National Medical Research Council grant NMRC. This work was also supported by the Mechanobiology Institute and the Singapore-MIT Alliance for Research and Technology (SMART) BioSystems and Micromechanics (BioSyM) IRG, which are funded by the National Research Foundation, Prime Minister’s Office, Singapore and by SIgN, which is funded by the Biomedical Research Council, A*STAR.