Biomarkers for Predicting Response to Immunotherapy with Immune Checkpoint Inhibitors in Cancer Patients

免疫疗法 医学 癌症 癌症免疫疗法 免疫系统 肿瘤科 免疫检查点 免疫学 无容量 癌症研究 内科学
作者
Michael J. Duffy,John Crown
出处
期刊:Clinical Chemistry [Oxford University Press]
卷期号:65 (10): 1228-1238 被引量:206
标识
DOI:10.1373/clinchem.2019.303644
摘要

Abstract BACKGROUND 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. CONTENT 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. SUMMARY 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.
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