Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Department of Gynecology, Shiga General Hospital, 5-4-30, Moriyama, Moriyama-city, Shiga, 524-8524, Japan.
Sci Rep. 2021 Jun 1;11(1):11427. doi: 10.1038/s41598-021-91012-w.
Based on our previous phase II clinical trial of anti-programmed death-1 (PD-1) antibody nivolumab for platinum-resistant ovarian cancer (n = 19, UMIN000005714), we aimed to identify the biomarkers predictive of response. Tumor gene expression was evaluated by proliferative, mesenchymal, differentiated, and immunoreactive gene signatures derived from high-grade serous carcinomas and a signature established prior for ovarian clear cell carcinoma. Resulting signature scores were statistically assessed with both univariate and multivariate approaches for correlation to clinical response. Analyses were performed to identify pathways differentially expressed by either the complete response (CR) or progressive disease (PD) patient groups. The clear cell gene signature was scored significantly higher in the CR group, and the proliferative gene signature had significantly higher scores in the PD group where nivolumab was not effective (respective p values 0.005 and 0.026). Combinations of gene signatures improved correlation with response, where a visual projection of immunoreactive, proliferative, and clear cell signatures differentiated clinical response. An applicable clinical response prediction formula was derived. Ovarian cancer-specific gene signatures and related pathway scores provide a robust preliminary indicator for ovarian cancer patients prior to anti-PD-1 therapy decisions.
基于我们之前进行的抗程序性死亡受体-1(PD-1)抗体纳武利尤单抗治疗铂耐药卵巢癌的 II 期临床试验(n=19,UMIN000005714),我们旨在确定预测反应的生物标志物。通过源自高级别浆液性癌的增殖、间充质、分化和免疫反应基因特征以及先前为卵巢透明细胞癌建立的特征来评估肿瘤基因表达。通过单变量和多变量方法对生成的特征评分进行统计学评估,以与临床反应相关联。进行了分析以确定由完全缓解(CR)或疾病进展(PD)患者组表达差异的途径。CR 组的透明细胞基因特征评分显著更高,而 PD 组的增殖基因特征评分在纳武利尤单抗无效的情况下显著更高(各自的 p 值分别为 0.005 和 0.026)。基因特征的组合改善了与反应的相关性,其中免疫反应性、增殖性和透明细胞特征的可视化投影可区分临床反应。得出了一个可行的临床反应预测公式。卵巢癌特异性基因特征和相关途径评分在接受抗 PD-1 治疗之前为卵巢癌患者提供了一个强大的初步指标。