High-grade serous ovarian cancer (HGSOC) remains a difficult-to-treat and lethal disease, mainly due to the lack of strategies for preventing tumor relapse. PARP inhibitors (PARPi) dramatically increase the progression-free survival in HGSOC patients with mutations in BRCA1/2 or in other homologous DNA recombination-related genes. However, new predictive tools are urgently needed to improve the identification of patients who are likely to benefit from PARPi and, hence, to personalise the treatment. We aim to identify specific biomarkers inferred from two complementary platforms of patientderived models. The consortium includes groups with high expertise in organotypic 3D cultures (which recapitulate the microenvironment of HGSOC peritoneal lesions) and in organoids (which retain the heterogeneity and differentiation potential of cancer cells). The in vitro response to PARPi will be analysed at the transcriptomic and phosphoproteomic levels through the cuttingedge technologies applied by consortium partners. Novel integrative approaches for multi-omics data analysis will be applied to delineate molecular pathways that can discriminate between responders and nonresponders. Candidate biomarkers will be validated in fully annotated retrospective cohorts of HGSOC patients provided by a network of top-level clinical centers with broad expertise in gynaecological oncology. Given that the response to PARPi has also been observed in a fraction of BRCA-wt/HRD-negative patients, new molecular markers could significantly increase the number of patients who can benefit from the treatment. In collaboration with patient organisations, we will also set up new protocols for patient-tailored communication that matches individual psychological profiles, thus improving patient’s wellbeing. By integrating interdisciplinary and novel experimental approaches, this project will advance personalisation strategies for the use of PARPi in HGSOC, thus helping to prevent its recurrence.

PARP inhibitors
predictive biomarkers
organotypic models
organoids
transcriptomics
phosphoproteomics

Acción Estratégica en Salud (AES)