表观遗传学
癌症免疫疗法
组学
仿形(计算机编程)
计算生物学
利用
免疫疗法
计算机科学
基因组学
空间分析
癌症
数据科学
生物
生物信息学
地理
基因组
遥感
DNA甲基化
遗传学
基因
基因表达
计算机安全
操作系统
作者
Yanlong Zhang,Joe Yeong,Chin Wee Tan,Xue Guo,Willa Wen‐You Yim,Jeffrey Lim,Felicia Wee,Yaming Wu,Malvika Kharbanda,Jia-Ying Joey Lee,Nye Thane Ngo,Wei Qiang Leow,Lit‐Hsin Loo,Tony KH Lim,Radoslaw M. Sobota,Mai Chan Lau,Melissa J. Davis,Joe Yeong
标识
DOI:10.1016/j.copbio.2024.103111
摘要
In-depth profiling of cancer cells/tissues is expanding our understanding of the genomic, epigenomic, transcriptomic, and proteomic landscape of cancer. However, the complexity of the cancer microenvironment, particularly its immune regulation, has made it difficult to exploit the potential of cancer immunotherapy. High-throughput spatial omics technologies and analysis pipelines have emerged as powerful tools for tackling this challenge. As a result, a potential revolution in cancer diagnosis, prognosis, and treatment is on the horizon. In this review, we discuss the technological advances in spatial profiling of cancer around and beyond the central dogma to harness the full benefits of immunotherapy. We also discuss the promise and challenges of spatial data analysis and interpretation and provide an outlook for the future.
科研通智能强力驱动
Strongly Powered by AbleSci AI