Clinical Lipidomics In Understanding Of Lung Cancer: Opportunity And Challenge.
Clinical Lipidomics In Understanding Of Lung Cancer: Opportunity And Challenge.
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DOI：
10.1016/j.canlet.2019.08.014
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发表时间：
2020-02
期刊：
影响因子：
9.7
通讯作者：
Linlin Zhang;Bijun Zhu;Yiming Zeng;Hui Shen;Jiaqiang Zhang;Xiangdong Wang
中科院分区：
文献类型：
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作者：
Linlin Zhang;Bijun Zhu;Yiming Zeng;Hui Shen;Jiaqiang Zhang;Xiangdong Wang
肺癌及其亚型中已证实脂质代谢紊乱。深入挖掘的脂质组学被认为是多组学家族的重要成员和脂质特异性工具，用于了解疾病相关的脂质代谢和脂质种类的疾病特异性功能障碍，发现用于监测治疗策略的生物标志物和靶标，并提供对肺癌脂质分析和病理生理机制的见解。本综述描述了不同肺癌亚型患者的脂质组学特征和模式、综合脂质组学谱在理解肺癌异质性方面的重要价值、标准化方法的迫切需要、脂质相关酶和蛋白质的潜在机制，以及临床表型和脂质组学谱之间整合的重要性。不同肺癌亚型的脂质组学特征在研究设计、对象、方法和分析方面存在极大差异。最近研究的初步数据证明了针对肺癌分期、严重程度、亚型和药物反应的脂质组学特征的特异性。脂质组学和脂质代谢的异质性可能是肺癌系统异质性的一部分，并导致耐药性的发展，尽管需要直接证据来证明肺癌内或肺癌间脂质组学异质性的存在。随着对基因和蛋白质表达谱的了解不断加深，脂质组学谱应与脂质代谢过程中涉及的酶和蛋白质的活性相关联，可以通过基因组学和蛋白质组学进行分析，并为脂质组学谱与基因和蛋白质表达谱的整合提供机会。应强调临床跨组学的概念，将脂质组学数据与临床表型组学整合，以确定疾病特异性和表组特异性生物标志物和靶标，尽管临床表型组学和脂质组学概况之间的整合仍存在大量挑战有待克服。
Disordered lipid metabolisms have been evidenced in lung cancer as well as its subtypes. Lipidomics with in-depth mining is considered as a critical member of the multiple omics family and a lipid-specific tool to understand disease-associated lipid metabolism and disease-specific dysfunctions of lipid species, discover biomarkers and targets for monitoring therapeutic strategies, and provide insights into lipid profiling and pathophysiological mechanisms in lung cancer. The present review describes the characters and patterns of lipidomic profiles in patients with different lung cancer subtypes, important values of comprehensive lipidomic profiles in understanding of lung cancer heterogeneity, urgent needs of standardized methodologies, potential mechanisms by lipid-associated enzymes and proteins, and the importance of integration between clinical phenomes and lipidomic profiles. The characteristics of lipidomic profiles in different lung cancer subtypes are extremely varied among study designs, objects, methods, and analyses. Preliminary data from recent studies demonstrate the specificity of lipidomic profiles specific for lung cancer stage, severity, subtype, and response to drugs. The heterogeneity of lipidomic profiles and lipid metabolism may be part of systems heterogeneity in lung cancer and be responsible for the development of drug resistance, although there are needs for direct evidence to show the existence of intra- or inter-lung cancer heterogeneity of lipidomic profiles. With an increasing understanding of expression profiles of genes and proteins, lipidomic profiles should be associated with activities of enzymes and proteins involved in the processes of lipid metabolism, which can be profiled with genomics and proteomics, and to provide the opportunity for the integration of lipidomic profiles with gene and protein expression profiles. The concept of clinical trans-omics should be emphasized to integrate data of lipidomics with clinical phenomics to identify disease-specific and phenome-specific biomarkers and targets, although there are still a large number of challenges to be overcome in the integration between clinical phenomes and lipidomic profiles.