Prognostic Value of Neoantigen Load in Immune Checkpoint Inhibitor Therapy for Cancer

Frontiers in Immunology

Ji-liang Zhang¹  Xue-lin Zou²  Guang-yan Zhang²  Chen-jiao Zhou²  Xiao-bo Li²  Qing Tang²  Jiao Yuan²  Wei-yong Chen²  Hua Ke²  Rui Zhang³ 

[1] Department of Oncology, Chengdu Seventh People’s Hospital, Chengdu, China;Department of Respiratory Medicine, Chengdu Seventh People’s Hospital, Chengdu, China;Department of Thoracic Surgery, Chengdu Seventh People’s Hospital, Chengdu, China;

关键词: cancer;    neoantigen load;    immune checkpoint inhibitor;    biomarker;    prognostic value;   

DOI  :  10.3389/fimmu.2021.689076

来源: DOAJ

【 摘 要 】

Immune checkpoint inhibitors (ICIs) have made great progress in the field of tumors and have become a promising direction of tumor treatment. With advancements in genomics and bioinformatics technology, it is possible to individually analyze the neoantigens produced by somatic mutations of each patient. Neoantigen load (NAL), a promising biomarker for predicting the efficacy of ICIs, has been extensively studied. This article reviews the research progress on NAL as a biomarker for predicting the anti-tumor effects of ICI. First, we provide a definition of NAL, and summarize the detection methods, and their relationship with tumor mutation burden. In addition, we describe the common genomic sources of NAL. Finally, we review the predictive value of NAL as a tumor prediction marker based on various clinical studies. This review focuses on the predictive ability of NAL’s ICI efficacy against tumors. In melanoma, lung cancer, and gynecological tumors, NAL can be considered a predictor of treatment efficacy. In contrast, the use of NAL for urinary system and liver tumors requires further research. When NAL alone is insufficient to predict efficacy, its combination with other indicators can improve prediction efficiency. Evaluating the response of predictive biomarkers before the treatment initiation is essential for guiding the clinical treatment of cancer. The predictive power of NAL has great potential; however, it needs to be based on more accurate sequencing platforms and technologies.

【 授权许可】

Unknown