单细胞测序在口腔鳞状细胞癌研究中的价值
The value of single-cell sequencing in oral squamous cell carcinoma research
王小聪 1李明1
作者信息
- 1. 湖南中医药大学口腔医学院,湖南 长沙 410208;长沙市口腔医院特诊中心,湖南 长沙 410004
- 折叠
摘要
单细胞测序(single-cell sequencing,SCS)在口腔鳞状细胞癌(oral squamous cell carcinoma,OSCC)研究中具有巨大潜力.随着SCS技术的发展,其灵敏度和准确度不断提高且成本逐渐降低,SCS将成为肿瘤研究的重要技术工具.SCS技术通过在单个细胞分辨率下识别基因组突变所导致的差异基因表达和表观遗传学信息改变,为发现新的细胞特异性标志物和细胞类型提供巨大帮助.在OSCC研究中,SCS不仅有助于揭示癌细胞的异质性以及更准确地理解肿瘤微环境,也有助于深入探讨恶性细胞、免疫细胞及基质细胞三者间的相互作用,揭示它们在肿瘤发生、发展中的相互影响及作用.利用SCS对肿瘤中的免疫细胞进行分类、理解免疫逃逸机制,将为免疫治疗的有效开展提供关键支持.本综述介绍SCS技术的发展现状,并回顾和讨论该技术在OSCC领域中的最新研究进展和应用前景.
Abstract
Single-cell sequencing(SCS)has great potential in oral squamous cell carcinoma(OSCC)research.With the development of SCS technology,its sensitivity and accuracy are gradually increasing,while its cost is gradually decreasing.SCS is poised to become a crucial technological tool in cancer research.SCS technology provides significant assistance in the discovery of new cell-specific markers and cell types by identifying differential gene expression and epigenetic information alterations caused by genomic mutations at the resolution of a single cell.In OSCC studies,SCS not only helps unveil the heterogeneity of cancer cells and provides more accurate understanding of the tumor microenvironment,but also facilitates a deeper exploration of the interactions between OSCC cells,immune cells and stromal cells.This sheds light on their mutual influences and roles in tumor initiation and progression.Utilizing SCS to classify immune cells in tumors and comprehend immune escape mechanisms is pivotal for the effective development of immunotherapy.This comprehensive review outlined the current status of SCS technology development and discussed its latest research advancements and prospective applications in the field of OSCC.
关键词
口腔鳞状细胞癌/单细胞测序/肿瘤异质性/肿瘤免疫反应/肿瘤微环境Key words
Oral squamous cell carcinoma/Single-cell sequencing/Tumor heterogeneity/Tumor immune response/Tumor microenvironment引用本文复制引用
基金项目
湖南省自然科学基金面上项目(2022JJ30630)
湖南省教育厅科研项目(22A0249)
湖南省卫生健康委科研项目(202108051626)
出版年
2024
国家科技期刊平台
NSTL
万方数据