免疫疗法
嵌合抗原受体
肿瘤微环境
免疫系统
癌症免疫疗法
生物
组学
机制(生物学)
T细胞
癌症
计算生物学
癌症研究
免疫学
生物信息学
哲学
遗传学
认识论
作者
Zhaokai Zhou,Jiahui Wang,Jiaojiao Wang,Shuai Yang,Ruizhi Wang,Ge Zhang,Zhengrui Li,Run Shi,Zhan Wang,Qiong Lu
标识
DOI:10.1186/s12943-024-02047-2
摘要
Abstract Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.
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