Ying-Tzu Yen

Combined delivery of salinomycin and docetaxel by dual-targeting gelatinase nanoparticles effectively inhibits cervical cancer cells and cancer stem cells

Intra-tumor heterogeneity is widely accepted as one of the key factors, which hinders cancer patients from achieving full recovery. Especially, cancer stem cells (CSCs) may exhibit self-renewal capacity, which makes it harder for complete elimination of tumor. Therefore, simultaneously inhibiting CSCs and non-CSCs in tumors becomes a promising strategy to obtain sustainable anticancer efficacy. Salinomycin (Sal) was reported to be critical to inhibit CSCs. However, the poor bioavailability and catastrophic side effects brought about limitations to clinical practice. To solve this problem, we previously constructed gelatinase-stimuli nanoparticles composed of nontoxic, biocompatible polyethylene glycol-polycaprolactone (PEG-PCL) copolymer with a gelatinase-cleavable peptide Pro-Val-Gly-Leu-Iso-Gly (PVGLIG) inserted between the two blocks of the copolymer. By applying our "smart" gelatinase-responsive nanoparticles for Sal delivery, we have demonstrated specific accumulation in tumor, anti-CSCs ability and reduced toxicity of Sal-NPs in our previous study. In the present study, we synthesized Sal-Docetaxel-loaded gelatinase-stimuli nanoparticles (Sal-Doc NP) and confirmed single emulsion as the optimal method of producing Sal-Doc NPs (Sal-Doc SE-NP) in comparison with nanoprecipitation. Sal-Doc SE-NPs inhibited both CSCs and non-CSCs in mice transplanted with cervical cancer, and might be associated with enhanced restriction of epithelial-mesenchymal transition (EMT) pathway. Besides, the tumorigenic capacity and growing speed were obviously suppressed in Sal-Doc-SE-NPs-treated group in rechallenge experiment. Our results suggest that Sal-Doc-loaded gelatinase-stimuli nanoparticles could be a promising strategy to enhance antitumor efficacy and reduce side effects by simultaneously suppressing CSCs and non-CSCs.

Tumour extracellular vesicle surface Protein-mRNA integration assay for early detection of epithelial ovarian cancer

Early detection of epithelial ovarian cancer (EOC) is crucial for improving clinical outcomes. However, the sensitivity of primary serological marker cancer antigen 125 (CA125) is suboptimal for detecting early-stage EOC. Tumour-derived extracellular vesicles (EVs) are promising biomarkers for early cancer detection. We developed an EOC EV Surface Protein-mRNA Integration (SPRI) Assay for early detection of EOC. This assay quantifies reference mRNAs within subpopulations of EOC EVs enriched by EV Click Beads targeting three EOC EV surface protein markers. Three EOC EV surface protein markers (i.e., FRα, MSLN, and TROP2) were selected through a bioinformatic framework using multi-omics data and underwent rigorous validation using EOC cell lines and EOC tissue microarrays. We then explored the translational potential of the EOC EV SPRI Assay through a phase II case-control study. The EOC EV SPRI Score was established using a logistic regression model in a training cohort (n = 118) and then validated in an independent validation cohort (n = 118). EOC EV SPRI Score demonstrated superior performance for distinguishing EOC from benign ovarian masses and healthy donors with an area under the receiver operating characteristic (AUROC) of 0.99 (95% CI: 0.97-1.00) in the training cohort and 0.93 (95% CI: 0.88-0.97) in the validation cohort. It outperformed matched serum CA125, and the performance remained excellent in earlier stages of EOC (Stage I/II, AUROC = 0.93, 95% CI: 0.88-0.98) and the subgroup of high-grade serous carcinoma (AUROC = 0.97, 95% CI: 0.87-0.97). The EOC EV SPRI assay demonstrated significant potential for early detection of EOC and improving long-term patient outcomes. This work is supported by National Institutes of Health (R01CA277530, R01CA255727, R01CA253651, R01CA253651-04S1, R21CA280444, R01CA246304, U01EB026421, R44CA288163, U01CA271887, and U01CA230705), DOD (HT9425-23-1-0361) and OCRA (CRDG-2023-3-1000) for the U.S. Additionally, we acknowledge the support of the Science and Technology Foundation of Suzhou (SZS2023006, SSD2023004) and the Youth Innovation Promotion Association CAS (2023335) for the work conducted at SINANO.