Current Advances in Cellular Approaches for Pathophysiology and Treatment of Polycystic Ovary Syndrome

Abstract

Polycystic ovary syndrome (PCOS) is a prevalent gynecological and endocrine disorder that results in irregular menstruation, incomplete follicular development, disrupted ovulation, and reduced fertility rates among affected women of reproductive age. While these symptoms can be managed through appropriate medication and lifestyle interventions, both etiology and treatment options remain limited. Here we provide a comprehensive overview of the latest advancements in cellular approaches utilized for investigating the pathophysiology of PCOS through in vitro cell models, to avoid the confounding systemic effects such as in vitro fertilization (IVF) therapy. The primary objective is to enhance the understanding of abnormalities in PCOS-associated folliculogenesis, particularly focusing on the aberrant roles of granulosa cells and other relevant cell types. Furthermore, this article encompasses analyses of the mechanisms and signaling pathways, microRNA expression and target genes altered in PCOS, and explores the pharmacological approaches considered as potential treatments. By summarizing the aforementioned key findings, this article not only allows us to appreciate the value of using in vitro cell models, but also provides guidance for selecting suitable research models to facilitate the identification of potential treatments and understand the pathophysiology of PCOS at the cellular level.

Keywords: androgen receptor; folliculogenesis; granulosa cells; hyperandrogenism; polycystic ovary syndrome.

Figure 1

The common in-vitro models used in PCOS studies are outlined. The primary GCs from humans and rodents, cell lines, and others related to the reproductive system or endocrine system are utilized in PCOS research.

Figure 2

PCOS is a disorder characterized by polycystic ovaries, hyperandrogenism, and ovulatory dysfunction. The common concepts pertaining to PCOS in in-vitro studies are shown. In-vitro models can be used to study signal transduction, microRNA regulation, and subsequent biological processes.