代谢组学
计算生物学
蛋白质组学
头颈部癌
癌症
组学
生物
计算机科学
生物信息学
医学
内科学
遗传学
基因
作者
Huiting Zhao,Chaowen Shi,Wei Han,G. Luo,Yumeng Huang,Yujuan Fu,Wen Lu,Qingang Hu,Z. J. Shang,Xihu Yang
出处
期刊:Neoplasia
[Elsevier BV]
日期:2023-12-23
卷期号:47: 100958-100958
被引量:6
标识
DOI:10.1016/j.neo.2023.100958
摘要
Head and neck cancer ranks as the sixth most prevalent malignancy, constituting 5 % of all cancer cases. Its inconspicuous onset often leads to advanced stage diagnoses, prompting the need for early detection to enhance patient prognosis. Currently, research into early diagnostic markers relies predominantly on genomics, proteomics, transcriptomics, and other methods, which, unfortunately, necessitate tumor tissue homogenization, resulting in the loss of temporal and spatial information. Emerging as a recent addition to the omics toolkit, spatial metabolomics stands out. This method conducts in situ mass spectrometry analyses on fresh tissue specimens while effectively preserving their spatiotemporal information. The utilization of spatial metabolomics in life science research offers distinct advantages. This article comprehensively reviews the progress of spatial metabolomics in head and neck cancer research, encompassing insights into cancer cell metabolic reprogramming. Various mass spectrometry imaging techniques, such as secondary ion mass spectrometry, stroma-assisted laser desorption/ionization, and desorption electrospray ionization, enable in situ metabolite analysis for head and neck cancer. Finally, significant emphasis is placed on the application of presently available techniques for early diagnosis, margin assessment, and prognosis of head and neck cancer.
科研通智能强力驱动
Strongly Powered by AbleSci AI