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黑色素瘤荷瘤 Libechov 迷你猪模型中黑色素瘤进展和自发消退的代谢组学特征。

Metabolomic characterisation of progression and spontaneous regression of melanoma in the melanoma-bearing Libechov minipig model.

机构信息

Department of Pharmacology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava.

Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovak Republic.

出版信息

Melanoma Res. 2021 Apr 1;31(2):140-151. doi: 10.1097/CMR.0000000000000722.

DOI:10.1097/CMR.0000000000000722
PMID:33625100
Abstract

Melanoma-bearing Libechov minipig (MeLiM) represents a large animal model for melanoma research. This model shows a high incidence of complete spontaneous regression of melanoma - a phenomenon uncommon in humans. Here, we present the first metabolomic characterisation of the MeLiM model comparing animals with progressing and spontaneously regressing melanomas. Plasma samples of 19 minipigs with progression and 27 minipigs with evidence of regression were analysed by a targeted metabolomic assay based on mass spectrometry detection. Differences in plasma metabolomics patterns were investigated by univariate and multivariate statistical analyses. Overall, 185 metabolites were quantified in each plasma sample. Significantly altered metabolomic profile was found, and 42 features were differentially regulated in plasma. Besides, the machine learning approach was used to create a predictive model utilising Arg/Orn and Arg/ADMA ratios to discriminate minipigs with progressive disease development from minipigs with regression evidence. Our results suggest that progression of melanoma in the MeLiM model is associated with alteration of arginine, glycerophospholipid and acylcarnitines metabolism. Moreover, this study provides targeted metabolomics characterisation of an animal model of melanoma with progression and spontaneous regression of tumours.

摘要

携带黑色素瘤的利比希微型猪(MeLiM)是一种用于黑色素瘤研究的大型动物模型。该模型显示出黑色素瘤完全自发消退的高发生率 - 这种现象在人类中很少见。在这里,我们首次对 MeLiM 模型进行了代谢组学特征描述,比较了进展型和自发性消退型黑色素瘤的动物模型。通过基于质谱检测的靶向代谢组学分析,对 19 头进展型和 27 头有证据表明消退的微型猪的血浆样本进行了分析。通过单变量和多变量统计分析研究了血浆代谢组学模式的差异。总体而言,每个血浆样本中定量了 185 种代谢物。发现了明显改变的代谢组学特征,并且在血浆中调节了 42 个特征。此外,还使用机器学习方法创建了一个利用 Arg/Orn 和 Arg/ADMA 比率来区分进展型疾病发展的微型猪和有消退证据的微型猪的预测模型。我们的研究结果表明,MeLiM 模型中黑色素瘤的进展与精氨酸、甘油磷脂和酰基肉碱代谢的改变有关。此外,本研究提供了进展型和自发性肿瘤消退的黑色素瘤动物模型的靶向代谢组学特征描述。

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