The joint analysis of single-cell transcriptomics, proteomics, lipidomics, metabolomics and spatial metabolomics is continually transforming our understanding of the mechanisms of metabolic reprogramming in tumor cells. Since head and neck tumor is the sixth most common tumor in the world, the study of the metabolic mechanism of its occurrence, development and prognosis is still undeveloped. In the past decade, this field has witnessed tremendous technological revolutions and considerable development that enables major breakthroughs to be made in the study of human tumor metabolism. In this review, a comprehensive comparison of traditional metabolomics and spatial metabolomics has been concluded, and the recent progress and challenges of the application of spatial metabolomics combined multi-omics in the research of metabolic reprogramming in tumors are reviewed. Furthermore, we also highlight the advances of spatial metabolomics in the study of metabolic mechanisms of head and neck tumors, and provide an outlook of its application prospects.
In this study, based on three tumor samples obtained from patients with sporadic vestibular schwannoma, 32,011 cells were obtained by single-cell transcriptome sequencing, and 22,309 high-quality cells were obtained after quality control and double cells removal. Then, 18 cell clusters were obtained after cluster analysis, and each cluster was annotated as six types of cells. Afterward, an in-depth analysis was conducted based on the defined six cell clusters, including characterizing the functional characteristics of each cell subtype, describing the cell development and differentiation pathway, exploring the interaction between cells, and analyzing the transcriptional regulatory network within the clusters. Based on these four dimensions, various types of cells in sporadic vestibular schwannoma tumor tissues were described in detail. For the first time, we expanded on the functional state of cell clusters that have been reported and described Schwann cells in the peripheral nervous system, which have not been reported in previous studies. Combined with the data of sporadic vestibular schwannoma and normal tissues in the gene expression omnibus (GEO) database, the candidate biomarkers of sporadic vestibular schwannoma were explored. Overall, this study described the single-cell map of sporadic vestibular schwannoma for the first time, revealing the functional state and development trajectory of different cell types. Combined with the analysis of data in the GEO database and immunohistochemical verification, it was concluded that HLA-DPB1 and VSIG4 may be candidate biomarkers and potential therapeutic targets for patients with sporadic vestibular schwannoma.
We assessed the association between long-term joint exposure to ambient air pollutants and the risk of laryngeal cancer and whether this risk was modified by genetic susceptibility. We used a multivariable Cox proportional hazards regression model to analyze data from UK Biobank to determine the relationship between long-term exposure to air pollutants–nitric oxide (NO), nitrogen dioxide (NO2), and 2.5-µm and 10-µm particulate matter (PM2.5 and PM10) and the risk of laryngeal cancer. In multivariable-adjusted models, in model 3 and compared with the participants with lower quintile scores for air pollution, the participants with the highest quintile scores for air pollution had a higher laryngeal cancer risk. The observed association was more pronounced among the participants who were female, were smokers, had a systolic blood pressure equal to or greater than 120 mmHg, and had diabetes. Compared with the participants with a low GRS and the lowest quintile score for air pollution exposure, those with an intermediate GRS and the highest quintile score for air pollution exposure had a higher risk of laryngeal cancer. Long-term exposure to NO2, NO, or PM2.5, individually or jointly, was associated with a risk of incident laryngeal cancer, especially in the participants with an intermediate GRS.
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