24 Correlation of clinical outcomes and poly ADP ribose polymerase activity in high grade serous ovarian cancer

Abstract

Objectives: PARP proteins are regulators of DNA damage repair in the cell. PARP inhibitors (PARPi) are a class of drugs used to treat ovarian cancer especially in patients with BRCA 1/2 gene mutations and homologous recombination deficiencies. These have previously been used as biomarkers to predict response to PARPi. Preclinical studies suggest that the levels of PARP-1, DDX21, and poly ADP ribosylation (PAR) are indicators of PARP activity. ADP ribosylation (PAR/ MAR) have been suggested as biomarkers to predict PARPi sensitivity. We sought to evaluate the correlation between PARP-1, DDX21, and mono-ADP ribosylation (MAR) expression with response to treatment with PARPi and survival outcomes. Methods: Tissue samples were collected from primary or metastatic sites of 49 patients with high grade serous ovarian cancer who had been prescribed a PARPi. A tumor microarray was made and immunohistochemistry (IHC) for MAR, PARP-1, and DDX21 was performed. IHC staining was graded on a 3-point scale. Clinical data collected included demographics, stage, presence of BRCA mutation, cytore-ductive status, time on PARPi, other adjuvant and salvage treatments, and survival outcomes. Kaplan-Meier analysis and Cox regression analysis were used to determine the effect of the biomarkers on survival outcomes and time on PARPi. Results: We found longer treatment with PARPi was associated with improved overall survival (p<0.01). PARP-1 expression directly correlated with DDX21 expression but it did not reach statistical significance (p=0.062). On Cox regression analysis cytoplasmic MAR approached significance (p=0.055) in predicting progression free survival (PFS) after frontline treatment. Conclusions: In our patient cohort, we saw a direct correlation between PARP-1 and DDX21 and an inverse correlation between MAR and PARP-1. Mono ADP ribosylation may predict PFS after frontline treatment. Pre-treatment biopsies and poly ADP ribosylation should be studied to further explore these biomarkers in predicting PARPi response.