When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective

被引:8
|
作者
Zhang, Zhiqiang [1 ,2 ]
Bao, Chaohui [1 ]
Jiang, Lu [1 ]
Wang, Shan [1 ]
Wang, Kankan [1 ]
Lu, Chang [3 ]
Fang, Hai [1 ]
机构
[1] Shanghai Jiao Tong Univ, Ruijin Hosp, Shanghai Inst Hematol, Natl Res Ctr Translat Med Shanghai,Sch Med,State K, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Life Sci & Biotechnol, Shanghai, Peoples R China
[3] Imperial Coll London, MRC London Inst Med Sci, London, England
来源
FRONTIERS IN ONCOLOGY | 2023年 / 12卷
基金
中国国家自然科学基金;
关键词
cancer drug resistance; metabolic reprogramming; metabolomics; single-cell metabolomics; spatial metabolomics; IMAGING MASS-SPECTROMETRY; BREAST-CANCER; T-CELLS; CTLA-4; BLOCKADE; IN-VITRO; METABOLISM; ANTIGEN; TARGET; TISSUE; HETEROGENEITY;
D O I
10.3389/fonc.2022.1054233
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Resistance to drug treatment is a critical barrier in cancer therapy. There is an unmet need to explore cancer hallmarks that can be targeted to overcome this resistance for therapeutic gain. Over time, metabolic reprogramming has been recognised as one hallmark that can be used to prevent therapeutic resistance. With the advent of metabolomics, targeting metabolic alterations in cancer cells and host patients represents an emerging therapeutic strategy for overcoming cancer drug resistance. Driven by technological and methodological advances in mass spectrometry imaging, spatial metabolomics involves the profiling of all the metabolites (metabolomics) so that the spatial information is captured bona fide within the sample. Spatial metabolomics offers an opportunity to demonstrate the drug-resistant tumor profile with metabolic heterogeneity, and also poses a data-mining challenge to reveal meaningful insights from high-dimensional spatial information. In this review, we discuss the latest progress, with the focus on currently available bulk, single-cell and spatial metabolomics technologies and their successful applications in pre-clinical and translational studies on cancer drug resistance. We provide a summary of metabolic mechanisms underlying cancer drug resistance from different aspects; these include the Warburg effect, altered amino acid/lipid/drug metabolism, generation of drug-resistant cancer stem cells, and immunosuppressive metabolism. Furthermore, we propose solutions describing how to overcome cancer drug resistance; these include early detection during cancer initiation, monitoring of clinical drug response, novel anticancer drug and target metabolism, immunotherapy, and the emergence of spatial metabolomics. We conclude by describing the perspectives on how spatial omics approaches (integrating spatial metabolomics) could be further developed to improve the management of drug resistance in cancer patients.
引用
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页数:19
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