Prevalence of predictive biomarkers in a large cohort of molecularly defined adult-type ovarian granulosa cell tumors

Objective. The objective of this study was to determine the prevalence of predictive biomarkers associated with FDA-approved therapies in molecularly defined adult-type ovarian granulosa cell tumors (aGCTs). Methods. We performed a retrospective cross-sectional cohort study of tumor profiles using the inclusion criteria of molecularly defined (FOXL2 c.C402G positive) aGCTs previously sequenced at Foundation Medicine, Inc. The dataset included coding variants for up to 406 genes, microsatellite instability, tumor mutational burden, and genomic loss of heterozygosity (gLOH). PD-L1 expression was determined using the tumor proportion score, as measured using the DAKO 22C3 immunohistochemistry assay. Results. 423 tumor profiles met inclusion criteria. The median age at the time of sample submission was 57 years (interquartile range 48-65). The mean tumor mutational burden was 1.8 mutations per megabase (range 0-8.8). No tumors exhibited microsatellite instability, and none were gLOH-High (>= 16%). Sixty-seven tumors had PD-L1 expression measurement, and 94% were negative. Potentially actionable variants including MTAP deletion (12/173, 5.8%) and activating PIK3CA mutations (23/423, 5.4%) were identified. TP53-mutated aGCT had a higher tumor mutational burden (mean 2.4 mut/Mb, 95% CI 1.7-3.0 mut/Mb vs mean 1.7 mut/Mb, 95% CI 1.5-1.9 mut/Mb; P = .02) and higher gLOH score (mean 4.4%, 95% CI 2.7-6.1% vs mean 1.4%, 95% CI 1.2-1.6%; P = .002) than TP53 non-mutated tumors. Conclusions. No women with molecularly defined aGCT in this large cohort would be eligible for FDA approved pembrolizumab based on either microsatellite instability or high tumor mutational burden. TP53 mutation identified a subset of this tumor type with distinct molecular features. The development of precision treatment options remains a critical unmet need for this rare disease. (c) 2021 Elsevier Inc. All rights reserved.

Automated summary

The study aimed to determine the prevalence of predictive biomarkers associated with FDA-approved therapies in molecularly defined aGCTs. Potentially actionable variants including MTAP deletion and activating PIK3CA mutations were identified in the study's tumor profiles.