Study of Drug Resistance in Chemotherapy Induced by Extracellular Vesicles on a Microchip

Drug resistance in chemotherapy has been greatly challenging for cancer treatment. Research has revealed that extracellular vesicles (EVs) secreted by drug-resistant cells could induce chemoresistance in susceptible cells. However, there are few ways to give direct evidence of it. Herein, we have proposed a microchip-based system to study the drug resistance of a wild-type human lung adenocarcinoma cell line (A549/WT) induced by EVs derived from A549/DDP cells that are resistant to cisplatin (DDP) inherently. EVs derived from A549/DDP were proved to be the crucial factor that enhanced the resistance of A549/WT to DDP through live and dead cell staining, cell viability testing, and immunofluorescence of P-glycoprotein in the off-chip assay. Then, it was further validated that drug resistance of A549/WT cells to DDP significantly increased after being cocultured with A549/DDP cells within 96 h in the on-chip assay. These findings proved that the change of A549/WT drug resistance was caused by intercellular interaction, which was mainly mediated by EVs. In addition, we successfully reversed the EV-induced drug resistance of A549/WT cells by combining DDP and metformin, a hypoglycemic drug with low cytotoxicity when used alone. This microchip system provides a novel tool that has great potential for the investigation of cell interaction, drug resistance, and the tumor microenvironment in fundamental and clinical medicine

Assessment of Drug Susceptibility for Patient-Derived Tumor Models through Lactate Biosensing and Machine Learning

A patient-derived tumor model (PDM) is a practical tool to rapidly screen chemotherapeutics for individual patients. The evaluation method of cell viability directly determines the application of PDMs for drug susceptibility testing. As one of the metabolites of “glycosis”, the lactate content was used to evaluate cell viability, but these assays were not specific for tumor cells. Based on the “Warburg effect”, wherein tumor cells preferentially rely on “aerobic glycolysis” to produce lactate instead of pyruvate in “anaerobic glycolysis” of normal cells, we reported a gold lactate sensor (GLS) to estimate the cell viability of PDMs in drug susceptibility testing. It demonstrated high consistency between the GLS and commercial cell viability assay. Unlike either imaging or cell viability assay, the GLS characterizes the cell viability, enables dynamic monitoring, and distinguishes tumor cells from other cells. Moreover, machine learning (ML) was employed to perform a multi-index assessment for drug susceptibility of PDMs, which proved to be accurate and practical for clinical application. Therefore, the GLS provides an ideal drug susceptibility testing tool for individualized medicine