Potential indicators in circulating cell-free DNA for monitoring PARP inhibitor resistance in high-grade serous ovarian cancer.

Abstract

5564 Background: Although the clinical application of PARP inhibitors (PARPis) has brought great survival benefits to patients with high-grade serous ovarian carcinoma (HGSOC), its resistance has gradually become a major challenge for clinicians with the widespread use of PARPis. Unfortunately, there are no effective, non-invasive means for monitoring PARPis resistance in time during maintain therapy. Methods: We collected peripheral blood samples (n = 37) from 37 healthy subjects and a series of longitudinal peripheral blood samples (n = 61) of 25 platinum-sensitive HGSOC patients undergoing Olaparib maintenance therapy. The genome of white blood cell and cfDNA in plasma was extracted for germline and somatic mutation detection by Circular Ligation Amplification and sequencing (CLAmp-seq) based on a targeted 42-gene panel, respectively. Before cfDNA mutation analysis, background noise introduced by random NGS error was removed and clonal hematopoietic mutations were filtered. Variant-supporting reads > 2 and without germline mutations were defined as the criterion for somatic mutations. Progression-free survival (PFS) was collected through regular follow-up. We analyzed the dynamic changes of cfDNA mutation profiles, the correlation between cfDNA mutations and the prognosis of patients, and screened specific mutation sites that closely associated with Olaparib resistance. Results: The elevation of maximum mutant allele frequency (Max MAF) in cfDNA during Olaparib maintenance therapy predicted a poor prognosis of patients ( P = 0.0043). Pathogenic germline mutations in BRCA1/2 or RAD51 were strongly associated with longer PFS ( P = 0.0229) and acquired new MRE11A mutations significantly shortened the PFS in patients ( P = 0.0005). Dynamic fluctuations of somatic mutation sites in CHEK2:p.K373E ( P = 0.0091) and CHEK2:p.R406H ( P = 0.0002) can be used to evaluate the therapeutic efficacy of patients. Remarkably, MRE11A:p.K464R may be a vital driving factor of Olaparib resistance and all patients who acquired new MRE11A:p.K464R in post-treatment cfDNA developed resistance to Olaparib and had significantly shorter PFS than those without it ( P = 0.0005). Besides, the combination of CHEK2:p.R406H and acquired new MRE11A:p.K464R in post-treatment improved the predictive efficiency of patients’ prognosis compared with them alone ( P < 0.0001). Conclusions: Olaparib resistance was robustly associated with the mutation load of tumor cells, and analysis of mutation profiles in cfDNA can be accurately monitor the status of Olaparib resistance in patients with HGSOC. Acquired new MRE11A:p.K464R may be a vital driver of Olaparib resistance and is expected to be a target for anti-tumor drug development.