Dan Liu, Lu Xiao, Yuyuan Wu, Chensirong Yue, Mengmeng Li, Yuanpei Sun, Chaoyong Yang
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引用次数: 0
Abstract
Despite the availability of numerous approved immunotherapies for various cancers, durable progression-free survival remains relatively uncommon among patients with advanced cancer. As research into immunotherapy intensifies, the heterogeneity and complexity of the tumor microenvironment (TME) have emerged as critical determinants of treatment response and a major obstacle to understanding tumor resistance mechanisms. Recent advances in spatially resolved transcriptomics (SRT) enable transcriptome-wide measurement of gene expression while preserving essential spatial information, which supports the characterization of the features of the TME. This review outlines key challenges in cancer immunotherapy and emphasizes the importance of the TME in determining therapeutic efficacy. SRT strategies suitable is systematically introduced for TME profiling, comparing their relative advantages and limitations. Additionally, bioinformatics tools and methods used to reconstruct spatial tissue patterns are discussed from SRT data. Furthermore, how SRT is explored can enhance the understanding of the complexity and heterogeneity of the TME, facilitate the identification of novel therapeutic targets, and advance biomarker discovery to refine personalized treatment strategies for diverse cancer patients. Finally, future perspectives on the application of SRT in cancer immunotherapy and addressing the associated challenges are provided.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.