卵巢癌PARP抑制剂疗效的预测性生物标志物:一项最新的系统综述。

Ying-Wen Wang, Isaac Allen, Gabriel Funingana, Marc Tischkowitz, Yvonne Walburga Joko-Fru
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引用次数: 0

摘要

背景:PARP抑制剂治疗卵巢癌有效,特别是对BRCA1/2致病变异携带者和HRD(同源重组缺陷)患者。对毒性和成本的担忧促使人们寻找可预测的生物标志物。我们提出了一项更新的系统综述,扩展了之前关于PARP抑制剂生物标志物的ESMO综述。方法:根据ESMO 2020年审查方案,我们将检索范围延长至2023年3月31日,包括PubMed和临床试验数据。我们还查阅了综述文章的参考文献列表。我们使用随机效应模型进行了荟萃分析,以评估风险比,并评估生物标志物的预测潜力和PARP抑制剂对生存的有效性。结果:共发现375篇文献,筛选后纳入103篇(62篇初级研究,41篇综述)。HRD仍然是主要的生物标志物(95%),尤其是BRCA1/2变异(77%)。在非hrd类别中,6篇文章(10%)介绍了创新的生物标志物,包括adp -核糖基化,HOXA9启动子甲基化,患者来源的类器官,KELIM和SLFN11。讨论:通过核RAD51水平进行实时同源重组修复的前瞻性评估显示出希望,但需要验证。新兴的生物标志物如adp -核糖基化、HOXA9启动子甲基化、患者来源的类器官、KELIM和SLFN11提供了潜力,但需要大规模验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive biomarkers for the efficacy of PARP inhibitors in ovarian cancer: an updated systematic review.

Background: PARP inhibitors are effective in treating ovarian cancer, especially for BRCA1/2 pathogenic variant carriers and those with HRD (homologous recombination deficiency). Concerns over toxicity and costs have led to the search for predictive biomarkers. We present an updated systematic review, expanding on a previous ESMO review on PARP inhibitor biomarkers.

Methods: Following ESMO's 2020 review protocol, we extended our search to March 31, 2023, including PubMed and clinical trial data. We also reviewed the reference lists of review articles. We conducted a meta-analysis using a random-effects model to evaluate hazard ratios and assess the predictive potential of biomarkers and the effectiveness of PARP inhibitors in survival.

Results: We found 375 articles, 103 of which were included after screening (62 primary research, 41 reviews). HRD remained the primary biomarker (95%), particularly BRCA1/2 variants (77%). In the non-HRD category, six articles (10%) introduced innovative biomarkers, including ADP-ribosylation, HOXA9 promoter methylation, patient-derived organoids, KELIM, and SLFN11.

Discussion: Prospective assessment of real-time homologous recombination repair via nuclear RAD51 levels shows promise but needs validation. Emerging biomarkers like ADP-ribosylation, HOXA9 promoter methylation, patient-derived organoids, KELIM, and SLFN11 offer potential but require large-scale validation.

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