Correlation of preclinical and clinical biomarkers with efficacy and toxicity of cancer immunotherapy

Immune checkpoint inhibitors (ICIs) have revealed significant clinical values in different solid tumors and hematological malignancy, changing the landscape for the treatment of multiple types of cancer. However, only a subpopulation of patients has obvious tumor response and long-term survival afte...

Full description

Saved in:
Bibliographic Details
Published inTherapeutic Advances in Medical Oncology Vol. 15; p. 17588359231163807
Main Authors Zheng, Lin-Peng, Yang, Jing, Chen, Xie-Wan, Li, Ling-Chen, Sun, Jian-Guo
Format Book Review Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.01.2023
Sage Publications Ltd
SAGE Publishing
Subjects
Artificial intelligence
Biomarkers
Cancer
Cancer immunotherapy
Genomic Biomarkers in Cancer Immunotherapy
Immune checkpoint inhibitors
Malignancy
Patients
Peripheral blood
Solid tumors
Toxicity
Tumor microenvironment
pseudoprogression
immune checkpoint inhibitors
biomarker
immune-related adverse events
hyperprogressive disease
Online AccessGet full text

Cover

More Information
Summary:Immune checkpoint inhibitors (ICIs) have revealed significant clinical values in different solid tumors and hematological malignancy, changing the landscape for the treatment of multiple types of cancer. However, only a subpopulation of patients has obvious tumor response and long-term survival after ICIs treatment, and many patients may experience other undesirable clinical features. Therefore, biomarkers are critical for patients to choose exact optimum therapy. Here, we reviewed existing preclinical and clinical biomarkers of immunotherapeutic efficacy and immune-related adverse events (irAEs). Based on efficacy prediction, pseudoprogression, hyperprogressive disease, or irAEs, these biomarkers were divided into cancer cell-derived biomarkers, tumor microenvironment-derived biomarkers, host-derived biomarkers, peripheral blood biomarkers, and multi-modal model and artificial intelligence assessment-based biomarkers. Furthermore, we describe the relation between ICIs efficacy and irAEs. This review provides the overall perspective of biomarkers of immunotherapeutic outcome and irAEs prediction during ICIs treatment.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-3
content type line 23
ObjectType-Review-1
Lin-Peng Zheng and Jing-Yang contributed equally to this study.
ISSN:1758-8359
1758-8340
1758-8359
DOI:10.1177/17588359231163807