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.

头颈癌是第六大常见恶性肿瘤，占所有癌症病例的 5%。它的起病不明显，通常会导致晚期诊断，提示需要早期检测以改善患者预后。目前，早期诊断标志物的研究主要依赖于基因组学、蛋白质组学、转录组学等方法，不幸的是，这些方法需要肿瘤组织均质化，导致时间和空间信息的丢失。空间代谢组学作为组学工具包的最新成员而脱颖而出。该方法对新鲜组织标本进行原位质谱分析，同时有效保留其时空信息。空间代谢组学在生命科学研究中的应用具有明显的优势。本文全面回顾了空间代谢组学在头颈癌研究中的进展，包括对癌细胞代谢重编程的见解。各种质谱成像技术，例如二次离子质谱、基质辅助激光解吸/电离和解吸电喷雾电离，可以对头颈癌进行原位代谢物分析。最后，重点强调当前可用技术在头颈癌早期诊断、切缘评估和预后中的应用。