Ovarian cancer remains the most lethal gynaecological malignancy worldwide, with ~1,800 new cases diagnosed annually in Australia and nearly 250,000 cases globally. Despite three decades of research, treatment paradigms have changed little, and therapy resistance is increasingly common. Because early-stage disease is largely asymptomatic and no validated early detection biomarker exists, most patients present with advanced disease, where survival rates are poor. There is an urgent need for accurate early detection strategies and novel therapeutics targeting chemoresistant disease.
Epigenetic regulation plays a key role in ovarian cancer development and progression. Circular RNAs (circRNAs), a recently recognised class of non-coding RNAs, have emerged as stable, tissue-specific epigenetic regulators with strong biomarker potential. Using long-read sequencing, we identified circRNAs dysregulated in ovarian cancer and developed a highly sensitive digital PCR assay capable of detecting these targets in minute quantities of patient plasma. In parallel, we have functionally characterised these dysregulated circRNAs through overexpression and knockdown models to elucidate their roles in therapy resistance, oncogenesis, and metastasis. This study establishes the feasibility of plasma-based circRNA detection for early diagnosis and provides mechanistic insights that could enable the development of both accurate early detection biomarkers and novel circRNA-targeted therapies for chemoresistant ovarian cancer.