Recent advances in PLGA polymer nanocarriers for ovarian cancer therapy.

Abstract

Ovarian cancer (OC) is the most lethal gynecologic malignancy worldwide, and early diagnosis and effective treatment have been the focus of research in this field. It is because of its late diagnosis, acquired resistance mechanisms, and systemic toxicity of chemotherapeutic agents that the treatment of ovarian cancer is challenging. Combination chemotherapy can potentially improve therapeutic efficacy by activating multiple downstream pathways to overcome resistance and reduce the required dose. In recent years, PLGA-lipid hybrid nanoparticles have demonstrated their potential as an emerging drug delivery system for treating ovarian cancer. PLGA (poly (lactic-co-glycolic acid) has become a highly sought-after biomaterial for the clinical translation of adjustable drug delivery regimens due to its biodegradability, biocompatibility, and multifunctionality, coupled with controlled drug release, which can effectively overcome multidrug resistance and improve the efficiency of chemotherapy. Combination therapies are gradually becoming an ideal alternative to traditional drug formulations. The application of nanoparticles not only improves the therapeutic effect but also reduces the side effects, which provides strong support for personalized precision medicine. We review polymeric nanoparticle carriers for drug combinations used in the treatment of ovarian cancer, particularly the combination of paclitaxel analogs (commonly used first-line therapy for ovarian cancer) with other small molecule therapeutic agents and cavitation combination therapy under ultrasound targeting (Figure 1). The elucidation of these issues will provide a theoretical basis for future exploration of novel NNDDS targeting GRPR for anti-OC therapy. This review presents research on recent advances in PLGA polymer nanoparticles in ovarian cancer, focusing on the use of PLGA degradable microspheres for loading chemotherapeutic agents and ultrasound combination therapy.