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

Authors :
Zou XL
Li XB
Ke H
Zhang GY
Tang Q
Yuan J
Zhou CJ
Zhang JL
Zhang R
Chen WY
Source :
Frontiers in immunology [Front Immunol] 2021 Dec 21; Vol. 12, pp. 689076. Date of Electronic Publication: 2021 Dec 21 (Print Publication: 2021).
Publication Year :
2021

Abstract

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.<br />Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2021 Zou, Li, Ke, Zhang, Tang, Yuan, Zhou, Zhang, Zhang and Chen.)

Details

Language :
English
ISSN :
1664-3224
Volume :
12
Database :
MEDLINE
Journal :
Frontiers in immunology
Publication Type :
Academic Journal
Accession number :
34992591
Full Text :
https://doi.org/10.3389/fimmu.2021.689076