拉曼光谱
代谢组学
重编程
限制
计算生物学
癌症
纳米技术
化学
生物物理学
生物
材料科学
生物信息学
生物化学
细胞
物理
遗传学
光学
机械工程
工程类
作者
Jiabao Xu,Yu Tong,Christos E. Zois,Ji‐Xin Cheng,Yuguo Tang,Adrian L. Harris,Wei E. Huang
出处
期刊:Cancers
[Multidisciplinary Digital Publishing Institute]
日期:2021-04-05
卷期号:13 (7): 1718-1718
被引量:67
标识
DOI:10.3390/cancers13071718
摘要
Metabolic reprogramming is a common hallmark in cancer. The high complexity and heterogeneity in cancer render it challenging for scientists to study cancer metabolism. Despite the recent advances in single-cell metabolomics based on mass spectrometry, the analysis of metabolites is still a destructive process, thus limiting in vivo investigations. Being label-free and nonperturbative, Raman spectroscopy offers intrinsic information for elucidating active biochemical processes at subcellular level. This review summarizes recent applications of Raman-based techniques, including spontaneous Raman spectroscopy and imaging, coherent Raman imaging, and Raman-stable isotope probing, in contribution to the molecular understanding of the complex biological processes in the disease. In addition, this review discusses possible future directions of Raman-based technologies in cancer research.
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