Michail Sideris

High-Grade Serous Ovarian Carcinoma in the Genomics Era: Current Applications, Challenges and Future Directions

High-grade serous ovarian carcinoma (HGSOC) is characterised by profound genomic instability and limited durable responses to standard therapy, leading to poor prognosis. The use of next-generation sequencing technologies has improved understanding of its molecular landscape, revealing consistent Tumour Protein p53 (TP53) mutations, homologous recombination defects, pathway alterations, and epigenetic dysregulation. Such genomic profiling now underpins the classification criteria between the ovarian cancer subtypes described by the Cancer Genome Atlas. Widespread chromosomal instability and pathogenic variants in multiple genes distinguish HGSOC from other subtypes of ovarian cancer and, further, from low-grade serous ovarian cancer. Importantly, the new-found understanding of the genomic landscape of HGSOC guides the use of platinum-based chemotherapies and Poly(ADP-ribose) Polymerase (PARP) inhibitors, with homologous recombination deficiency emerging as a cancer vulnerability that enhances treatment response. A combined multi-omics approach integrates transcriptomics, proteomics, metabolomics, and epigenomics to further the understanding of the characteristics, therapeutic targets and treatment resistance within HGSOC. Despite these advances, major challenges persist, including intratumoural heterogeneity and the poor diversity of genomic datasets. Artificial Intelligence (AI) technology, Clustered regularly interspaced short palindromic repeats (CRISPR)-based gene editing, neoantigen-guided immunotherapy and ovarian cancer vaccination indicate a promising future for genomics-guided interventions and support the integration of genomics within multi-omic approaches to improve HGSOC outcomes.

Molecular Biomarkers in Borderline Ovarian Tumors: Towards Personalized Treatment and Prognostic Assessment

Borderline Ovarian Tumours (BOTs) are a heterogenous group of ovarian neoplasms which have increased mitotic activity but lack stromal invasion. We performed a narrative review of the literature, aiming to identify prognostic molecular biomarkers that can potentially be used for treatment personalisation. We identified and discussed BRAF/KRAS, Cancer Antigen 125 (Ca 125), Calprotectin, p16ink4a, and Microsatellite instability (MSI) as the most studied biomarkers related to BOTs. Overall, BRAF and KRAS mutations are associated with earlier-stage and favourable prognosis; KRASmt may indicate extraovarian disease in serous BOT (sBOT). Ca125, the only currently clinically used biomarker, can be assessed pre-operatively and has an established role in post-operative surveillance, especially when it is raised pre-operatively or a high potential for malignant transformation is suspected post-operatively. p16ink4a expression trends could also indicate the malignant transformation of the tumour. Calprotectin has an inferior specificity to Ca125 and is not yet established as a biomarker, whilst there is very limited evidence available for MSI. As new evidence is coming along with artificial intelligence platforms, these biomarkers can be integrated and used towards the development of a precision model for treatment stratification and counselling in women diagnosed with BOTs.

A systematic review and meta-analysis of the diagnostic effectiveness of human papillomavirus methylation biomarkers for detection of cervical cancer