Department of Chemistry and CICECO - Aveiro Institute of Materials (CICECO/UA), University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
iBIMED - Institute of Biomedicine, Department of Medical Sciences, Universidade de Aveiro, Agra do Crasto, 3810-193 Aveiro, Portugal.
Biochim Biophys Acta Mol Basis Dis. 2020 May 1;1866(5):165713. doi: 10.1016/j.bbadis.2020.165713. Epub 2020 Jan 31.
Metabolomic strategies have been extensively used to search for biomarkers of disease, including cancer, in biological complex mixtures such as cells, tissues and biofluids. In breast cancer research, murine models are of great value and metabolomics has been increasingly applied to characterize tumor or organ tissues, or biofluids, for instance to follow-up metabolism during cancer progression or response to specific therapies.
This review briefly introduces the different murine models used in breast cancer research and proceeds to present the metabolomic studies reported so far to describe the deviant metabolic behavior associated to breast cancer, in each type of model: xenografts (cell- or patient-derived), spontaneous (naturally-occurring or genetically engineered) and carcinogen-induced. The type of sample and strategies followed are identified, as well as the main findings from of study.
Metabolomics has gradually become relevant in characterizing murine models of breast cancer, using either Nuclear Magnetic Resonance (NMR) or Mass Spectromety (MS). Both tissue and biofluids are matrixes of interest in this context, although in some type of models, reports have focused primarily on the former. The aims of tissue studies have comprised the search for mechanistic knowledge of carcinogenesis, metastasis development and response/resistance to therapies. Biofluid metabolomics has mainly aimed at finding non-invasive biomarkers for early breast cancer detection or prognosis determination.
Metabolomics provides exquisite detail on murine tumor and systemic metabolism of breast cancer. This knowledge paves the way for the discovery of new biomarkers, potentially translatable to in vivo non-invasive patient follow-up.
代谢组学策略已被广泛用于在细胞、组织和生物体液等生物复杂混合物中寻找疾病标志物，包括癌症。在乳腺癌研究中，鼠模型具有重要价值，代谢组学已越来越多地应用于描述肿瘤或器官组织或生物体液，例如，在癌症进展或对特定治疗的反应过程中，跟踪代谢变化。
本文简要介绍了用于乳腺癌研究的不同鼠模型，然后介绍了迄今为止报道的代谢组学研究，以描述与乳腺癌相关的代谢异常行为，包括异种移植（细胞或患者来源）、自发（自然发生或基因工程）和致癌物诱导的模型。确定了所使用的样本类型和策略，以及研究的主要发现。
代谢组学已逐渐成为描述乳腺癌鼠模型的重要手段，既可以使用核磁共振（NMR）也可以使用质谱（MS）。在这种情况下，组织和生物体液都是感兴趣的基质，但在某些类型的模型中，报告主要集中在前者上。组织研究的目的包括寻找致癌发生、转移发展和对治疗的反应/耐药的机制知识。生物体液代谢组学主要旨在寻找用于早期乳腺癌检测或预后判断的非侵入性生物标志物。
代谢组学为乳腺癌鼠肿瘤和全身代谢提供了详细的信息。这些知识为发现新的生物标志物铺平了道路，这些标志物可能具有转化为体内非侵入性患者随访的潜力。
