National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun, China.
German Cancer Research Center (DKFZ), Heidelberg University, Heidelberg, Germany.
Front Immunol. 2021 Jul 21;12:690112. doi: 10.3389/fimmu.2021.690112. eCollection 2021.
The immunotherapeutic treatment of various cancers with an increasing number of immune checkpoint inhibitors (ICIs) has profoundly improved the clinical management of advanced diseases. However, just a fraction of patients clinically responds to and benefits from the mentioned therapies; a large proportion of patients do not respond or quickly become resistant, and hyper- and pseudoprogression occur in certain patient populations. Furthermore, no effective predictive factors have been clearly screened or defined. In this review, we discuss factors underlying the elucidation of potential immunotherapeutic resistance mechanisms and the identification of predictive factors for immunotherapeutic responses. Considering the heterogeneity of tumours and the complex immune microenvironment (composition of various immune cell subtypes, disease processes, and lines of treatment), checkpoint expression levels may not be the only factors underlying immunotherapy difficulty and resistance. Researchers should consider the tumour microenvironment (TME) landscape in greater depth from the aspect of not only immune cells but also the tumour histology, molecular subtype, clonal heterogeneity and evolution as well as micro-changes in the fine structural features of the tumour area, such as myeloid cell polarization, fibroblast clusters and tertiary lymphoid structure formation. A comprehensive analysis of the immune and molecular profiles of tumour lesions is needed to determine the potential predictive value of the immune landscape on immunotherapeutic responses, and precision medicine has become more important.
越来越多的免疫检查点抑制剂(ICIs)被用于治疗各种癌症的免疫治疗,这极大地改善了晚期疾病的临床管理。然而,只有一小部分患者对所述治疗有临床反应并从中受益;很大一部分患者没有反应或很快产生耐药性,并且某些患者群体中会出现超进展和假性进展。此外,还没有明确筛选或定义有效的预测因素。在这篇综述中,我们讨论了阐明潜在免疫治疗耐药机制和鉴定免疫治疗反应预测因素的基础因素。考虑到肿瘤的异质性和复杂的免疫微环境(各种免疫细胞亚型、疾病过程和治疗方案的组成),检查点表达水平可能不是免疫治疗困难和耐药的唯一因素。研究人员应该更深入地考虑肿瘤微环境(TME)景观,不仅要考虑免疫细胞,还要考虑肿瘤组织学、分子亚型、克隆异质性和进化以及肿瘤区域精细结构特征的微小变化,如髓样细胞极化、成纤维细胞簇和三级淋巴结构形成。需要对肿瘤病变的免疫和分子特征进行综合分析,以确定免疫景观对免疫治疗反应的潜在预测价值,精准医疗变得更加重要。