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在三阴性乳腺癌异种移植模型中,对苯乙烯马来酸包裹的RL71的作用进行多变量统计分析。

A multivariate statistical analysis of the effects of styrene maleic acid encapsulated RL71 in a xenograft model of triple negative breast cancer.

作者信息

Martey Orleans N K, Greish Khaled, Smith Paul F, Rosengren Rhonda J

机构信息

Department of Pharmacology and Toxicology, School of Biomedical Sciences, University of Otago, Dunedin 9045, New Zealand.

Department of Molecular Medicine, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Kingdom of Bahrain.

出版信息

J Biol Methods. 2019 Dec 16;6(4):e121. doi: 10.14440/jbm.2019.306. eCollection 2019.

Abstract

We have previously shown that the curcumin derivative 3,5-bis(3,4,5-trimethoxybenzylidene)-1-methylpiperidine-4-one (RL71), when encapsulated in styrene maleic acid micelles (SMA-RL71), significantly suppressed the growth of MDA-MB-231 xenografts by 67%. Univariate statistical analysis showed that pEGFR/EGFR, pAkt/Akt, pmTOR/mTOR and p4EBP1/4EPBP1 were all significantly decreased in tumors from treated mice compared to SMA controls. In this study, multivariate statistical analyses (MVAs) were performed to identify the molecular networks that worked together to drive tumor suppression, with the aim to determine if this analysis could also be used to predict treatment outcome. Linear discriminant analysis correctly predicted, to 100% certainty, mice that received SMA-RL71 treatment. Additionally, results from multiple linear regression showed that the expression of Ki67, PKC-α, PP2AA-α, PP2AA-β and CaD1 networked together to drive tumor growth suppression. Overall, the MVAs provided evidence for a molecular network of signaling proteins that drives tumor suppression in response to SMA-RL71 treatment, which should be explored further in animal studies of cancer.

摘要

我们之前已经表明,姜黄素衍生物3,5-双(3,4,5-三甲氧基亚苄基)-1-甲基哌啶-4-酮(RL7)包裹于苯乙烯马来酸共聚物胶束(SMA-RL7)中时,能显著抑制MDA-MB-231异种移植瘤的生长,抑制率达67%。单因素统计分析表明,与SMA对照组相比,接受治疗小鼠肿瘤中的pEGFR/EGFR、pAkt/Akt、pmTOR/mTOR和p4EBP1/4EBP1均显著降低。在本研究中,进行了多因素统计分析(MVA)以识别共同作用驱动肿瘤抑制的分子网络,目的是确定该分析是否也可用于预测治疗结果。线性判别分析能100%准确预测接受SMA-RL7治疗的小鼠。此外,多元线性回归结果表明,Ki67、PKC-α、PP2AA-α、PP2AA-β和CaD1的表达共同作用驱动肿瘤生长抑制。总体而言,多因素统计分析为响应SMA-RL7治疗驱动肿瘤抑制的信号蛋白分子网络提供了证据,这应在癌症动物研究中进一步探索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac0a/6974696/d4daebdb883f/jbm-6-4-e121-g001.jpg

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