Molecular predictors of the outcome of paclitaxel plus carboplatin neoadjuvant therapy in high-grade serous ovarian cancer patients

Anna P. Sokolenko · 2021-06-02

19Citations
Patients with advanced high-grade serous ovarian cancer (HGSOC) are usually treated with paclitaxel and carboplatin; however, predictive markers for this drug combination are unknown. Tumor samples from 71 consecutive HGSOC patients, who received neoadjuvant chemotherapy with paclitaxel and carboplatin, were subjected to molecular analysis. BRCA1/2 germline mutation carriers (n = 22) had longer treatment-free interval (TFI) than non-carriers (n = 49) (9.5 months vs. 3.8 months; P = 0.007). Fifty-one HGSOCs had sufficient quality of tumor DNA for the next-generation sequencing (NGS) analysis by the SeqCap EZ CNV/LOH Backbone Design panel. All 13 tumors obtained from BRCA1/2 germline mutation carriers and 12 sporadic HGSOCs showed a high number of evenly spread chromosomal breaks, which was defined as a BRCAness phenotype; median TFI for this combined group approached 9.5 months. The remaining 26 HGSOCs had similarly high global LOH score (above 20%); however, in contrast to BRCAness tumors, LOH involved large chromosomal segments; these patients had significantly lower TFI (3.7 months; P = 0.006). All patients with CCNE1 amplification (n = 7), TP53 R175H substitution (n = 6), and RB1 mutation (n = 4) had poor response to paclitaxel plus carboplatin. This study describes a cost-efficient method of detecting the BRCAness phenotype, which is compatible with the laboratory-scale NGS equipment. Some molecular predictors allow the identification of potential non-responders to paclitaxel plus carboplatin, who may need to be considered for other treatment options.
TL;DR

A cost-efficient method is described of detecting the BRCAness phenotype, which is compatible with the laboratory-scale NGS equipment, and allows the identification of potential non-responders to paclitaxel plus carboplatin, who may need to be considered for other treatment options.

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Funding

Russian Science Foundation

19-75-10062