Anti-PD1 and Niraparib (PARPi) combination therapy in gynae carcinosarcoma: Identification of response-predictive biomarkers and resistance mechanisms
Carcinosarcomas (CS) are very rare and aggressive tumors. Gynecologic CS have a 5-year overall survival <10% and most patients relapsed after standard treatments. PARP inhibitor (PARPi) and anti-PD1/L1 independent trials showed some efficacy in relapsed CS. ROCSANbio translational program, merging with a phase III trial evaluating PARPi/anti-PD1 combination in relapsed CS, relies on 3 hypotheses: - CS show high DNA damage response activity, driving PARPi as promising therapy; - The high tumor mutation load observed in CS potentially results in neo-antigens, paving the way for immunotherapies; - Such tumors, with an exhibited cell plasticity, represent a unique model to study its contribution in resistance to treatment. The primary aim will be to define biomarkers within tumors (WP1) and blood (WP2) predicting anti-PD1/PARPi response in CS and to investigate the effect of this new therapeutic strategy on quality of life (QOL) and patient-reported outcome (PRO) in the whole population and by molecular subgroups (WP4). The secondary aim will be to identify resistance mechanisms (WP3). The unique access to materials at diagnosis, inclusion and progression will allow to compare responding and non-responding patients for numerous parameters: For WP1: 1) tumor immune infiltrate and immune checkpoint expression, 2) EMT signature, 3) homologous recombination deficiency signature and mutation burden and 4) tumor neo-epitopes and T cell response. For WP2: circulating 1) tumor DNA and 2) immune cells. For WP3: 1) EMT/tumor cell plasticity, 2) & 3) resistance pathways and 4) mutations in epigenetic modifiers and immune-related genes and their consequences. For WP4: 1) EORTC QOL disease-specific module, 2) Hospital Anxiety and Depression Scale and 3) PRO-CTCAE questionnaire. We expect to identify biomarkers predicting anti-PD1/PARPi response, the impact on QOL and PRO for patients and to discover novel resistance targets representing better candidates for combination therapy.
Funded by the European Union under the Horizon Europe Framework Programme - Grant Agreement Nº: 101095654. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them.