Zhiguo Zheng

Characterization of Extrachromosomal Circular DNA in Primary and Cisplatin-Resistant High-Grade Serous Ovarian Cancer

Background: Cisplatin resistance is a major cause of tumor recurrence and mortality in high-grade serous ovarian cancer (HGSOC). Extrachromosomal circular DNA (eccDNA) has emerged as a critical factor in tumor evolution and drug resistance. However, the specific contribution of eccDNA to cisplatin resistance in HGSOC remains unclear. Methods: We performed whole-genome sequencing, Circle-Seq, and RNA-Seq in four pairs of primary and cisplatin-resistant (cisR) HGSOC cell lines to characterize genome-wide eccDNA distribution and features. Functional enrichment analyses were subsequently conducted on differentially expressed eccDNA-related genes. Results: In the SKOV3 cisR cell line, we identified a large extrachromosomal circular DNA (ecDNA) carrying the HIF1A gene, which regulates DNA repair, drug efflux, and epithelial–mesenchymal transition, contributing to cisplatin resistance. Using Circle-Seq, we detected a total of 161,062 eccDNAs, most of which were less than 1000 bp and distributed across all chromosomes. Notably, the number of eccDNAs on chromosome 21 differed significantly between the primary and cisR cell lines. Additionally, eccDNAs were predominantly located in non-coding repetitive elements. Functional analysis of eccDNA-related differentially expressed genes revealed that, compared to primary cell lines, cisR cell lines were associated with mitotic spindle assembly, regulation of vascular permeability, and cell differentiation. eccDNA-related genes involved in these pathways include MISP, WIPF1, RHOD, KRT80, and PLVAP. Conclusions: Our findings suggest that eccDNAs, particularly ecDNA amplifications like HIF1A, contribute significantly to cisplatin resistance mechanisms in HGSOC. These insights highlight eccDNA as a potential target for overcoming therapeutic resistance and improving treatment outcomes in ovarian cancer.

Proteomic landscape of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is a deadly disease with limited diagnostic biomarkers and therapeutic targets. Here we conduct a comprehensive proteomic profiling of ovarian tissue and plasma samples from 813 patients with different histotypes and therapeutic regimens, covering the expression of 10,715 proteins. We identify eight proteins associated with tumor malignancy in the tissue specimens, which are further validated as potential circulating biomarkers in plasma. Targeted proteomics assays are developed for 12 tissue proteins and 7 blood proteins, and machine learning models are constructed to predict one-year recurrence, which are validated in an independent cohort. These findings contribute to the understanding of EOC pathogenesis and provide potential biomarkers for early detection and monitoring of the disease. Additionally, by integrating mutation analysis with proteomic data, we identify multiple proteins related to DNA damage in recurrent resistant tumors, shedding light on the molecular mechanisms underlying treatment resistance. This study provides a multi-histotype proteomic landscape of EOC, advancing our knowledge for improved diagnosis and treatment strategies.