Performance of the VENTANA FOLR1 Assay for folate receptor alpha: Real-world evidence from 313 Chinese participants

Xiaoyan Chen & Chaofu Wang et al. · 2026-01-06

Folate receptor-α is an ideal precision therapy target of ovarian cancer. The standardization of FRα assay and interpretative criteria is essential for ensuring diagnostic consistency and enhancing clinical efficacy in therapeutic applications. This study aims to analytically verify and evaluate the clinical performance of the VENTANA FOLR1 Assay. This real-world study of Chinese patients analyzed FRα expression using the VENTANA FOLR1 RxDx assay in 313 samples from diverse anatomical sites. Inter- and intra-observer agreement in FRα scoring was evaluated, and correlations between FRα positivity and clinicopathological parameters were examined. Three pathologists demonstrated excellent inter- and intra-observer agreement (> 97 %) in FOLR1 interpretation. 40.9 % of cases showed high FRα expression, with a significantly higher positivity rate in high-grade serous carcinoma among the Chinese cohort. Primary tumors exhibited higher FRα positivity than metastatic lesions (44.2 % vs 32.2 %, p = 0.04). Chemotherapy exposure did not significantly alter FRα positivity across ovarian, fallopian tube, and primary peritoneal cancers, remained comparable to that of the overall cohort (41.2 % vs 40.9 %). Excision/resection samples were identified as optimal for FRα assessment. Our findings demonstrate the high reliability of the VENTANA FOLR1 Assay in Chinese clinical settings. Additionally, we conducted a systematic investigation into the associations between FRα expression and clinicopathological characteristics, highlighting its capacity to reflect FRα heterogeneity, maintain stability in post-chemotherapy FRα expression across various tumor types, and achieve robust performance in excision/resection samples. These findings underscore the value of standardizing FRα testing to improve patient selection for FRα-targeted MIRV therapies in China.
Authors
Xiaoyan Chen, Li Jiang, Liangyan Ruan, Teng Yu, Weiwei Rui, Yue Fan, Huafeng Wang, He Jiang, Chaofu Wang