Clinical Research Centre, St. Vincent's University Hospital, Dublin, Ireland;
UCD School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
Clin Chem. 2019 Oct;65(10):1228-1238. doi: 10.1373/clinchem.2019.303644. Epub 2019 Jul 17.
Immunotherapy, especially the use of immune checkpoint inhibitors, has revolutionized the management of several different cancer types in recent years. However, for most types of cancer, only a minority of patients experience a durable response. Furthermore, administration of immunotherapy can result in serious adverse reactions. Thus, for the most efficient and effective use of immunotherapy, accurate predictive biomarkers that have undergone analytical and clinical validation are necessary.
Among the most widely investigated predictive biomarkers for immunotherapy are programmed death-ligand 1 (PD-L1), microsatellite instability/defective mismatch repair (MSI/dMMR), and tumor mutational burden (TMB). MSI/dMMR is approved for clinical use irrespective of the tumor type, whereas PD-L1 is approved only for use in certain cancer types (e.g., for predicting response to first-line pembrolizumab monotherapy in non-small cell lung cancer). Although not yet approved for clinical use, TMB has been shown to predict response to several different forms of immunotherapy and across multiple cancer types. Less widely investigated predictive biomarkers for immunotherapy include tumor-infiltrating CD8 lymphocytes and specific gene signatures. Despite being widely investigated, assays for MSI/dMMR, PD-L1, and TMB lack standardization and are still evolving. An urgent focus of future research should be the optimization and standardization of method for determining these biomarkers.
Biomarkers for predicting response to immunotherapy are paving the way for personalized treatment for patients with diverse cancer types. However, standardization of the available biomarker assays is an urgent requirement.
免疫疗法,特别是免疫检查点抑制剂的使用,近年来彻底改变了多种不同癌症类型的治疗方法。然而,对于大多数类型的癌症,只有少数患者能获得持久的反应。此外,免疫疗法的应用可能会导致严重的不良反应。因此,为了使免疫疗法的使用达到最有效和最有效的效果,需要经过分析和临床验证的准确预测生物标志物。
免疫疗法中研究最广泛的预测生物标志物之一是程序性死亡配体 1(PD-L1)、微卫星不稳定性/错配修复缺陷(MSI/dMMR)和肿瘤突变负担(TMB)。MSI/dMMR 无论肿瘤类型如何都被批准用于临床,而 PD-L1 仅批准用于某些癌症类型(例如,预测对非小细胞肺癌一线帕博利珠单抗单药治疗的反应)。虽然尚未批准用于临床,但 TMB 已被证明可预测多种不同形式的免疫疗法和多种癌症类型的反应。免疫疗法的预测生物标志物研究较少,包括肿瘤浸润 CD8 淋巴细胞和特定的基因特征。尽管已经广泛研究,但 MSI/dMMR、PD-L1 和 TMB 的检测缺乏标准化,并且仍在不断发展。未来研究的一个紧迫重点应该是优化和标准化确定这些生物标志物的方法。
预测免疫治疗反应的生物标志物为不同类型癌症患者的个性化治疗铺平了道路。然而,标准化现有的生物标志物检测方法是当务之急。