免疫检查点抑制剂疗效相关预测模型的研究进展

Advances in models predicting efficacy of immune checkpoint inhibitors

免疫检查点抑制剂(immune checkpoint inhibitor,ICI)的应用让肿瘤治疗取得了新突破,但不同患者接受免疫治疗后疗效差异较大,仅部分患者能够从中获益。通过检测一些生物标志物可以预测ICI的疗效,如程序性死亡[蛋白]配体-1(programmed death ligand-1,PD-L1)及肿瘤突变负荷(tumor mutation burden,TMB)等。除此之外,目前已有多项研究基于肿瘤患者的基因组学、转录组学或影像组学等数据,筛选多个生物标志物并建立免疫治疗效果相关预测模型。这类模型具备严谨的建立及验证流程,能够纳入更多肿瘤免疫相关变量,有助于提高对ICI疗效的预测能力。本文就肿瘤免疫治疗效果相关预测模型进行综述,以期为免疫治疗获益人群的筛选提供新思路。

The use of immune checkpoint inhibitor(ICI)has revolutionized the treatment among patients with various types of tumors.However,only some patients can benefit from ICI.The identification of predictive markers of response to treatment in patients is required,such as programmed death ligand-1(PD-L1)and tumor mutation burden(TMB).Besides,there have been numerous studies using sequence and radiomics data based on large populations to explore the factors related to the efficacy,and to establish the prediction model.This kind of model has a rigorous establishment and validation process,can include more tumor immune related variables,and is helpful to improve the prediction ability of the efficacy of ICI.This paper reviewed the establishment of immunotherapy prediction models and provided new thoughts pertaining to screening the potential beneficiaries from immunotherapy.