The development of drug resistance in cancer cells is one of the major obstacles to achieving effective chemotherapy. We hypothesized that the combination of a doxorubicin (Dox) prodrug and microRNA (miR)21 inhibitor might show synergistic antitumor effects on drug-resistant breast cancer cells. In this study, we aimed to develop new high-density lipoprotein-mimicking nanoparticles (HMNs) for coencapsulation and codelivery of this potential combination. Dox was coupled with a nuclear localization signal (NLS) peptide to construct a prodrug (NLS-Dox), thereby electrostatically condensing miR21 inhibitor (anti-miR21) to form cationic complexes. The HMNs were formulated by shielding these complexes with anionic lipids and Apo AI proteins. We have characterized that the coloaded HMNs had uniformly dispersed distribution, favorable negatively charged surface, and high coencapsulation efficiency. The HMN formulation effectively codelivered NLS-Dox and anti-miR21 into Dox-resistant breast cancer MCF7/ADR cells and wild-type MCF7 cells via a high-density-lipoprotein receptor-mediated pathway, which facilitated the escape of Pgp drug efflux. The coloaded HMNs consisting of NLS-Dox/anti-miR21 demonstrated greater cytotoxicity with enhanced intracellular accumulation in resistant MCF7/ADR cells compared with free Dox solution. The reversal of drug resistance by coloaded HMNs might be attributed to the suppression of miR21 expression and the related antiapoptosis network. Furthermore, the codelivery of anti-miR21 and NLS-Dox by HMNs showed synergistic antiproliferative effects in MCF7/ADR-bearing nude mice, and was more effective in tumor inhibition than other drug formulations. These data suggested that codelivery of anti-miR21 and chemotherapeutic agents by HMNs might be a promising strategy for antitumor therapy, and could restore the drug sensitivity of cancer cells, alter intracellular drug distribution, and ultimately enhance chemotherapeutic effects.

Neutrophil-derived extracellular vesicles (NEVs) are critically involved in disease progression and are considered potential biomarkers. However, the tedious processes of NEV separation and detection restrain their use. Herein, we presented an integrated microfluidic chip for NEV (IMCN) analysis, which achieved immune-separation of CD66b⁺ NEVs and multiplexed detection of their contained miRNAs (termed NEV signatures) by using 10 μL serum samples. The optimized microchannel and flow rate of the IMCN chip enabled efficient capture of NEVs (>90%). After recognition of the captured NEVs by a specific CD63 aptamer, on-chip rolling circle amplification (RCA) reaction was triggered by the released aptamers and miRNAs from heat-lysed NEVs. Then, the RCA products bound to molecular beacons (MBs), initiating allosteric hairpin structures and amplified "turn on" fluorescence signals (RCA-MB assay). Clinical sample analysis showed that NEV signatures had a high area under curve (AUC) in distinguishing between healthy control (HC) and gastric cancer (GC) (0.891), benign gastric diseases (BGD) and GC (0.857). Notably, the AUC reached 0.912 with a combination of five biomarkers (NEV signatures, CEA, and CA199) to differentiate GC from HC, and the diagnostic accuracy was further increased by using a machine learning (ML)-based ensemble classification system. Therefore, the developed IMCN chip is a valuable platform for NEV analysis and may have potential use in GC diagnosis.