Functional Interrogation of the Impact of ERCC2 Mutations in Bladder Cancer on Cisplatin Sensitivity - Expert Commentary
The investigators assembled a multinational cohort of 2,012 patients with bladder cancer from eight different institutions to profile different ERCC2 mutations. The investigators performed CRISPR to introduce mutations and measure their functional effects through cell survival assays to functionally profile recurrent ERCC2 mutations. They also compared results to the Cagiada computational model, which uses machine learning to predict mutation effects on protein function. From the cohort, 506 ERCC2 mutations were identified in 477 individuals, with 93% being heterozygous missense variants. The mutations were highly enriched (87%) in the conserved helicase domains compared to random distribution (P = 6.12 × 10⁻³⁰). The most frequent variant was the N238S variant, occurring in 14% of ERCC2-mutant cases.
CRISPR-Select analysis revealed that helicase-domain mutations significantly increased cisplatin sensitivity, with mutant cell frequencies decreasing by approximately 80% after cisplatin treatment. Interestingly, single-allele editing confirmed that even heterozygous helicase-domain mutations markedly increased cisplatin sensitivity even in the presence of one wild-type allele. Clinical validation showed that patients with helicase-domain ERCC2 mutations had significantly improved response to platinum-based neoadjuvant chemotherapy. In the neoadjuvant cohort, 72% of patients with helicase-domain mutations responded compared to 56% without mutations (P = 3 × 10⁻⁴). These patients also demonstrated significantly longer overall survival (P = 5 × 10⁻⁴). However, no significant association was observed between ERCC2 mutation status and outcomes in the metastatic cohort (P = 0.35). Computational algorithms showed substantial discrepancies when compared to experimental results, with most tools predicting high pathogenicity rates but failing to capture context-specific cisplatin sensitivity effects. The Cagiada model achieved (83%) accuracy in predicting functional effects, while other computational methods were less reliable.
This important study provides the largest functional characterization of ERCC2 mutations in bladder cancer to date. The findings support the clinical utility of ERCC2 helicase-domain mutations as predictive biomarkers for cisplatin-based neoadjuvant chemotherapy in muscle-invasive bladder cancer.
Written by: Bishoy M. Faltas, MD, Director of Bladder Cancer Research, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York
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