Genomic and Epigenomic study of Stage I Epithelial Ovarian Carcinomas to Implement Novel Prognostic Molecular Biomarkers

Pesenti, Chiara (2022). Genomic and Epigenomic study of Stage I Epithelial Ovarian Carcinomas to Implement Novel Prognostic Molecular Biomarkers. PhD thesis The Open University.



Stage I epithelial ovarian carcinomas represent the earliest stage of ovarian carcinoma, when the disease is confined to the ovaries, and is amenable to efficient treatment by cytoreductive surgery followed by adjuvant chemotherapy in cases considered at high- risk of relapse. It is generally characterized by a favourable outcome; with just about 20% of relapse. However, the staging of the tumour is often suboptimal causing on one hand over-treatment of many who receive adjuvant chemotherapy to prevent recurrence, and on the other hand under-treatment of those improperly defined as "low risk", who experience relapses with a much poorer prognosis. The histologically heterogeneity of stage I epithelial ovarian tumours further complicates the development of efficient prognostic markers. Nevertheless, previous results on the transcriptomic signatures of stage I tumours obtained in the hosting Lab, prompted us to extend the current knowledge about the molecular landscape of stage I tumours to potentially identify novel parameters able to stratify patients based on the prognosis.

In my PhD project, I exploited high-throughput Next Generation Sequencing approaches to evaluate the most recurrent Single Nucleotide Variants in a subset of frequently altered genes in ovarian cancer and the Somatic Copy Number Alterations distribution across the genome on a unique cohort of 205 stage I epithelial ovarian cancer patients. These analyses revealed the existence of three different genomic instability patterns namely stable, unstable and highly unstable, based on the on the percentage of genome affected by copy number alterations and their length. These patterns are strictly related to distinct etiopathogenetic processes that drive tumour evolutionary routes. In an effort to define potential mechanisms involved in the generation of genomic instability, five copy number signatures related to different mutational pathways were defined and global DNA methylation was assessed through LINE1 promoter methylation status. The significant association of the genome instability with a reduction in global methylation levels by LINE-1 retrotransposons supports a close relationship between the genomic landscape and tumour epigenetic regulation.

Finally, the three SCNA patterns were correlated to patients’ survival and resulted strongly predictive of patients’ prognosis also in multivariate models with the currently used clinical variables.

These results show that genomic and epigenomic analyses offer novel possibilities to identify markers useful for the management of the disease, offering an improved patient prognosis prediction.

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