Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies.

Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies.
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DOI:
10.3389/fonc.2022.891018
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发表时间:
2022
影响因子:
4.7
通讯作者:
Dai, Yong
Dai, Yong
中科院分区:
医学3区
文献类型:
--
作者:
He, Michelle Junyi;Pu, Wenjun;Wang, Xi;Zhang, Wei;Tang, Donge;Dai, Yong

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癌症的代谢异质性显著影响其不良的治疗结果和预后。因此,研究继续专注于识别新的生物标志物和代谢脆弱性,这两者都取决于对癌症代谢改变的理解。近几十年来,质谱成像(MSI)的兴起使得能够原位检测组织中大量的小分子。因此,研究人员希望使用MSI介导的空间代谢组学来进一步研究癌症患者中改变的代谢物。在这篇综述中,我们研究了两种最常用的空间代谢组学技术,MALDI-MSI和MALDI-MSI,以及它们在癌症研究中应用的一些最新亮点。我们还描述了AFAFA-MSI作为一个最近的变化从AFA-MSI和比较它与两个主要的技术。具体而言,我们讨论了空间代谢组学结果在四种类型的异质性恶性肿瘤,包括乳腺癌,食管癌,胶质母细胞瘤和肺癌。多项研究已经使用改变的代谢物信息有效地对癌症组织亚型进行了分类。此外,还确定了脂肪酸、高能磷酸盐化合物和抗氧化剂等关键代谢产物的分布趋势。因此,虽然更精细的分布细节的可视化需要进一步改进MSI技术,但过去的研究表明空间代谢组学是研究癌症病理生理复杂性的一个有前途的方向。
Metabolic heterogeneity of cancer contributes significantly to its poor treatment outcomes and prognosis. As a result, studies continue to focus on identifying new biomarkers and metabolic vulnerabilities, both of which depend on the understanding of altered metabolism in cancer. In the recent decades, the rise of mass spectrometry imaging (MSI) enables the in situ detection of large numbers of small molecules in tissues. Therefore, researchers look to using MSI-mediated spatial metabolomics to further study the altered metabolites in cancer patients. In this review, we examined the two most commonly used spatial metabolomics techniques, MALDI-MSI and DESI-MSI, and some recent highlights of their applications in cancer studies. We also described AFADESI-MSI as a recent variation from the DESI-MSI and compare it with the two major techniques. Specifically, we discussed spatial metabolomics results in four types of heterogeneous malignancies, including breast cancer, esophageal cancer, glioblastoma and lung cancer. Multiple studies have effectively classified cancer tissue subtypes using altered metabolites information. In addition, distribution trends of key metabolites such as fatty acids, high-energy phosphate compounds, and antioxidants were identified. Therefore, while the visualization of finer distribution details requires further improvement of MSI techniques, past studies have suggested spatial metabolomics to be a promising direction to study the complexity of cancer pathophysiology.
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