Clinical implications of tumor-based next-generation sequencing in ovarian cancer.

Abstract

5545 Background: Epithelial ovarian cancer is genetically heterogeneous, both among and within histologic subtypes. Advances in next-generation sequencing have made it feasible to ascertain the somatic genetic signature of each patient, however, critical analysis of population-level sequencing results is required to maximize the potential of this technology. Here, we aimed to assess the clinical relevance of tumor-based next-generation sequencing (tbNGS) in a large cohort of patients with high-grade epithelial ovarian cancer. Methods: Our study population comprised patients with high-grade serous (n = 972), clear cell (n = 33), endometrioid (n = 28), mucinous (n = 4), and mixed (n = 34) or unspecified (n = 21) epithelial ovarian carcinoma diagnosed between April 2013 and September 2021. tbNGS results were identified within the electronic medical record using optical character recognition and natural language processing. Genetic, clinical, and demographic information was collected for patients who had undergone tbNGS. Progression-free survival (PFS) and overall survival (OS) were calculated from date of first treatment to date of first recurrence and date of death, respectively. Data were analyzed using descriptive statistics, univariate and multivariate Cox regression models, and clustering analyses. Results: Of 1092 patients in the described population, 409 (37.5%) had tbNGS results identified. Nearly all (96.1%) revealed one or more genetic aberrations. Most patients (74.6%) had an actionable mutation, defined as relaying eligibility for a targeted treatment or clinical trial. The most frequent alterations were TP53, PIK3CA, and NF1 mutations; and CCNE1 amplification. Ten different targeted institutional and commercial panels were employed, covering a range of 35 to 600+ gene loci. The median time from diagnosis to testing was 14.5 months, likely corresponding to time of recurrence. Though no standalone alterations were significantly related to survival, multivariate and clustering analyses identified several genetic patterns which corresponded to patient outcomes. Mutation of BRAF, PIK3R1, NOTCH3, MET, and/or ATR was correlated with shorter PFS (HR 1.84, p = 0.001); mutation of ATM, RB1, CDKN2A, FGFR1, and/or FGFR2 was associated with improved PFS (HR 0.64, p = 0.04), as was mutation of NBN and/or ATRX (HR 0.54, p < 0.05). MYC, NOTCH3, and/or CREBBP mutations were significantly correlated with worse OS (HR 1.95, p = 0.02). In our population, 40 patients (9.78%) were enrolled in genotypically-relevant clinical trials. Conclusions: tbNGS is prevalent at our institution, and often yields actionable information. We identified several mutational patterns that correlate to patient survival. Detailed analysis of population-level tumor genomics may help to identify therapeutic targets and guide development of clinical decision support tools.