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鉴定癌细胞系中对遗传毒性药物的药效生物标志物和共同分子反应机制。

Identification of pharmacodynamic biomarkers and common molecular mechanisms of response to genotoxic agents in cancer cell lines.

机构信息

Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr., Rockville, MD, 20850, USA.

Molecular Pharmacology Group, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.

出版信息

Cancer Chemother Pharmacol. 2019 Oct;84(4):771-780. doi: 10.1007/s00280-019-03898-z. Epub 2019 Jul 31.

Abstract

PURPOSE

Genotoxic agents (GAs) including cisplatin, doxorubicin, gemcitabine, and topotecan are often used in cancer treatment. However, the response to GAs is variable among patients and predictive biomarkers are inadequate to select patients for treatment. Accurate and rapid pharmacodynamics measures of response can, thus, be useful for monitoring therapy and improve clinical outcomes.

METHODS

This study focuses on integrating a database of genome-wide response to treatment (The NCI Transcriptional Pharmacodynamics Workbench) with a database of baseline gene expression (GSE32474) for the NCI-60 cell lines to identify mechanisms of response and pharmacodynamic (PD) biomarkers.

RESULTS AND CONCLUSIONS

Our analysis suggests that GA-induced endoplasmic reticulum (ER) stress may signal for GA-induced cell death. Reducing the uptake of GA, activating DNA repair, and blocking ER-stress induction cooperate to prevent GA-induced cell death in the GA-resistant cells. ATF3, DDIT3, CARS, and PPP1R15A appear as possible candidate PD biomarkers for monitoring the progress of GA treatment. Further validation studies on the proposed intrinsic drug-resistant mechanism and candidate genes are needed using in vivo data from either patient-derived xenograft models or clinical chemotherapy trials.

摘要

目的

包括顺铂、多柔比星、吉西他滨和拓扑替康在内的遗传毒性药物(GA)常用于癌症治疗。然而,患者对 GA 的反应存在差异,且预测生物标志物不足以选择接受治疗的患者。因此,准确快速的反应药效学测量可用于监测治疗并改善临床结局。

方法

本研究专注于整合基因组范围的治疗反应数据库(NCI 转录药效动力学工作台)与 NCI-60 细胞系的基线基因表达数据库(GSE32474),以识别反应机制和药效学(PD)生物标志物。

结果与结论

我们的分析表明,GA 诱导的内质网(ER)应激可能会发出 GA 诱导细胞死亡的信号。在 GA 耐药细胞中,减少 GA 的摄取、激活 DNA 修复以及阻断 ER 应激诱导,共同作用以防止 GA 诱导的细胞死亡。ATF3、DDIT3、CARS 和 PPP1R15A 似乎是监测 GA 治疗进展的潜在 PD 候选生物标志物。需要使用来自患者来源的异种移植模型或临床化疗试验的体内数据,对所提出的内在耐药机制和候选基因进行进一步的验证研究。

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Clinically Relevant Concentrations of Anticancer Drugs: A Guide for Nonclinical Studies.临床相关浓度的抗癌药物:非临床研究指南。
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