生物
同源重组
DNA修复
突变
抗药性
癌症研究
卵巢癌
基因
癌症
流出
遗传学
肿瘤科
医学
作者
Yoo‐Na Kim,Yeeun Shim,Jieun Seo,Zisun Choi,Yong Jae Lee,Saeam Shin,Sang Wun Kim,Sunghoon Kim,Jong Rak Choi,Jung‐Yun Lee,Seung‐Tae Lee
标识
DOI:10.1158/1078-0432.ccr-22-3715
摘要
Abstract Purpose: Patient-specific molecular alterations leading to PARP inhibitor (PARPi) resistance are relatively unexplored. In this study, we analyzed serially collected circulating tumor DNA (ctDNA) from patients with BRCA1/2 mutations who received PARPis to investigate the resistance mechanisms and their significance in postprogression treatment response and survival. Experimental Design: Patients were prospectively enrolled between January 2018 and December 2021 (NCT05458973). Whole-blood samples were obtained before PARPi administration and serially every 3 months until progression. ctDNA was extracted from the samples and sequenced with a 531-gene panel; gene sets for each resistance mechanism were curated. Results: Fifty-four patients were included in this analysis. Mutation profiles of genes in pre-PARPi samples indicating a high tumor mutational burden and alterations in genes associated with replication fork stabilization and drug efflux were associated with poor progression-free survival on PARPis. BRCA hypomorphism and reversion were found in 1 and 3 patients, respectively. Among 29 patients with matched samples, mutational heterogeneity increased postprogression on PARPis, showing at least one postspecific mutation in 89.7% of the patients. These mutations indicate non-exclusive acquired resistance mechanisms—homologous recombination repair restoration (28%), replication fork stability (34%), upregulated survival pathway (41%), target loss (10%), and drug efflux (3%). We observed poor progression-free survival with subsequent chemotherapy in patients with homologous recombination repair restoration (P = 0.003) and those with the simultaneous involvement of two or more resistance mechanisms (P = 0.040). Conclusions: Analysis of serial ctDNAs highlighted multiple acquired resistance mechanisms, providing valuable insights for improving postprogression treatment and survival.
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