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预测新鲜肿瘤样本中药物组合化疗疗效的新系统。

New system to predict chemotherapeutic efficacy of drug combinations in fresh tumor samples.

作者信息

Kischkel Frank Christian, Eich Julia, Meyer Carina I, Weidemüller Paula, Krapfl Jens, Yassin-Kelepir Rauaa, Job Laura, Fraefel Marius, Braicu Ioana, Kopp-Schneider Annette, Sehouli Jalid, De Wilde Rudy Leon

机构信息

TherapySelect, Heidelberg, Germany.

Gynecology Department, Charité Berlin, Virchow Campus Berlin, Germany.

出版信息

PeerJ. 2017 Mar 2;5:e3030. doi: 10.7717/peerj.3030. eCollection 2017.

Abstract

BACKGROUND

To find the best individual chemotherapy for cancer patients, the efficacy of different chemotherapeutic drugs can be predicted by pretesting tumor samples via the chemotherapy-resistance (CTR)-Test. Although drug combinations are widely used among cancer therapy, so far only single drugs are tested by this and other tests. However, several first line chemotherapies are combining two or more chemotherapeutics, leading to the necessity of drug combination testing methods.

METHODS

We established a system to measure and predict the efficacy of chemotherapeutic drug combinations with the help of the Loewe additivity concept in combination with the CTR-test. A combination is measured by using half of the monotherapy's concentration of both drugs simultaneously. With this method, the efficacy of a combination can also be calculated based on single drug measurements.

RESULTS

The established system was tested on a data set of ovarian carcinoma samples using the combination carboplatin and paclitaxel and confirmed by using other tumor species and chemotherapeutics. Comparing the measured and the calculated values of the combination testings revealed a high correlation. Additionally, in 70% of the cases the measured and the calculated values lead to the same chemotherapeutic resistance category of the tumor.

CONCLUSION

Our data suggest that the best drug combination consists of the most efficient single drugs and the worst drug combination of the least efficient single drugs. Our results showed that single measurements are sufficient to predict combinations in specific cases but there are exceptions in which it is necessary to measure combinations, which is possible with the presented system.

摘要

背景

为了找到针对癌症患者的最佳个体化化疗方案,可通过化疗耐药性(CTR)检测对肿瘤样本进行预测试,以预测不同化疗药物的疗效。尽管联合用药在癌症治疗中广泛应用,但迄今为止,该检测及其他检测仅针对单一药物进行。然而,几种一线化疗方案采用了两种或更多种化疗药物联合使用,这就产生了对联合用药检测方法的需求。

方法

我们借助洛维相加性概念并结合CTR检测,建立了一种测量和预测化疗药物联合疗效的系统。通过同时使用每种单一疗法药物浓度的一半来测量联合用药情况。利用这种方法,也可基于单一药物的测量结果计算联合用药的疗效。

结果

使用卡铂和紫杉醇联合用药对一组卵巢癌样本数据集对所建立的系统进行了测试,并通过使用其他肿瘤类型和化疗药物进行了验证。比较联合用药检测的测量值和计算值显示出高度相关性。此外,在70%的病例中,测量值和计算值得出的肿瘤化疗耐药类别相同。

结论

我们的数据表明,最佳的联合用药方案由最有效的单一药物组成,而最差的联合用药方案由效率最低的单一药物组成。我们的结果表明,在特定情况下,单一药物测量足以预测联合用药情况,但也存在例外情况,即有必要测量联合用药情况,而本文所介绍的系统能够做到这一点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5805/5337084/c0401eb8e6df/peerj-05-3030-g001.jpg

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