Copy number alterations in stage I epithelial ovarian cancer highlight three genomic patterns associated with prognosis

• DOI: 10.1016/j.ejca.2022.05.005
• Publication Date: 2022-06-14T21:49:17Z
• Authors: Chiara Pesenti; Luca Beltrame; Angelo Velle; Robert Fruscio; Marta Jaconi; Fulvio Borella; Fulvia Milena Cribiù; Enrica Calura; Lara Veronica Ven...; Deborah Lenoci; Federico Agostinis; Dionyssios Katsaros; Nicolò Panini; Tommaso Bianchi; Fabio Landoni; Monica Miozzo; Maurizio D'Incalci; James D. Brenton; Chiara Romualdi; Sergio Marchini
• Keywords: Ovarian Neoplasms; 0303 health sciences; DNA Copy Number Variations; Prognosis; Somatic copy number alteration; Stage I EOC;; Genomics; Carcinoma, Ovarian Epithelial; Prognosis; Genomic Instability; 3. Good health; 03 medical and health sciences; Humans; Female; Neoplasm Recurrence, Local

Stage I epithelial ovarian cancer (EOC) encompasses five histologically different subtypes of tumors confined to the ovaries with a generally favorable prognosis. Despite the intrinsic heterogeneity, all stage I EOCs are treated with complete resection and adjuvant therapy in most of the cases. Owing to the lack of robust prognostic markers, this often leads to overtreatment. Therefore, a better molecular characterization of stage I EOCs could improve the assessment of the risk of relapse and the refinement of optimal treatment options.205 stage I EOCs tumor biopsies with a median follow-up of eight years were gathered from two independent Italian tumor tissue collections, and the genome distribution of somatic copy number alterations (SCNAs) was investigated by shallow whole genome sequencing (sWGS) approach.Despite the variability in SCNAs distribution both across and within the histotypes, we were able to define three common genomic instability patterns, namely stable, unstable, and highly unstable. These patterns were based on the percentage of the genome affected by SCNAs and on their length. The genomic instability pattern was strongly predictive of patients' prognosis also with multivariate models including currently used clinico-pathological variables.The results obtained in this study support the idea that novel molecular markers, in this case genomic instability patterns, can anticipate the behavior of stage I EOC regardless of tumor subtype and provide valuable prognostic information. Thus, it might be propitious to extend the study of these genomic instability patterns to improve rational management of this disease.