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在3D培养平台上进行的药物疗效测试可为卵巢癌患者确定有效的药物。

The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients.

作者信息

Åkerlund Emma, Gudoityte Greta, Moussaud-Lamodière Elisabeth, Lind Olina, Bwanika Henri Colyn, Lehti Kaisa, Salehi Sahar, Carlson Joseph, Wallin Emelie, Fernebro Josefin, Östling Päivi, Kallioniemi Olli, Joneborg Ulrika, Seashore-Ludlow Brinton

机构信息

Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institute, Stockholm, Sweden.

Department of Oncology-Pathology, Karolinska Institute, Stockholm, Sweden.

出版信息

NPJ Precis Oncol. 2023 Oct 31;7(1):111. doi: 10.1038/s41698-023-00463-z.

Abstract

Most patients with advanced ovarian cancer (OC) relapse and progress despite systemic therapy, pointing to the need for improved and tailored therapy options. Functional precision medicine can help to identify effective therapies for individual patients in a clinically relevant timeframe. Here, we present a scalable functional precision medicine platform: DET3Ct (Drug Efficacy Testing in 3D Cultures), where the response of patient cells to drugs and drug combinations are quantified with live-cell imaging. We demonstrate the delivery of individual drug sensitivity profiles in 20 samples from 16 patients with ovarian cancer in both 2D and 3D culture formats, achieving over 90% success rate in providing results six days after operation. In this cohort all patients received carboplatin. The carboplatin sensitivity scores were significantly different for patients with a progression free interval (PFI) less than or equal to 12 months and those with more than 12 months (p < 0.05). We find that the 3D culture format better retains proliferation and characteristics of the in vivo setting. Using the DET3Ct platform we evaluate 27 tailored combinations with results available 10 days after operation. Notably, carboplatin and A-1331852 (Bcl-xL inhibitor) showed an additive effect in four of eight OC samples tested, while afatinib and A-1331852 led to synergy in five of seven OC models. In conclusion, our 3D DET3Ct platform can rapidly define potential, clinically relevant data on efficacy of existing drugs in OC for precision medicine purposes, as well as provide insights on emerging drugs and drug combinations that warrant testing in clinical trials.

摘要

大多数晚期卵巢癌(OC)患者尽管接受了全身治疗,但仍会复发和进展,这表明需要改进和定制治疗方案。功能精准医学有助于在临床相关时间范围内为个体患者确定有效的治疗方法。在此,我们展示了一个可扩展的功能精准医学平台:DET3Ct(三维培养中的药物疗效测试),通过活细胞成像对患者细胞对药物及药物组合的反应进行量化。我们展示了以二维和三维培养形式为16例卵巢癌患者的20个样本提供个体药物敏感性概况,术后六天提供结果的成功率超过90%。在这个队列中,所有患者均接受了卡铂治疗。无进展生存期(PFI)小于或等于12个月的患者与超过12个月的患者的卡铂敏感性评分有显著差异(p<0.05)。我们发现三维培养形式能更好地保留体内环境中的增殖和特征。使用DET3Ct平台,我们评估了27种定制组合,术后10天可获得结果。值得注意的是,在测试的八个OC样本中的四个中,卡铂和A-1331852(Bcl-xL抑制剂)显示出相加作用,而在七个OC模型中的五个中,阿法替尼和A-1331852产生了协同作用。总之,我们的三维DET3Ct平台可以快速定义现有药物在OC中疗效的潜在临床相关数据,用于精准医学目的,还能为新兴药物和药物组合提供见解,这些药物和组合值得在临床试验中进行测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50ca/10618545/3bd7b22d60cc/41698_2023_463_Fig1_HTML.jpg

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