Advances in predictive biomarkers for melanoma immunotherapy

Abstract Purpose This review primarily discusses the current research advance of predictive biomarkers for melanoma immunotherapy. The aim of the present review is to summarize the biomarkers and evaluate the advantages and disadvantages. Methods All reference can be found through Pubmed. This review mainly focuses on three main directions: tumor-related factors, host factors, and the tumor microenvironment. In the end, there exhibits some unusual aspects of predictive biomarkers and forecasts the future model. Results The mainsteam of predictive biomarkers focuses on PD-L1, TMB, gene mutations, immune cells, IDO1, LDH, tertiary lymphoid structures (TLS), HLA-DR, tumor-associated macrophages (TAMs), tumor-infiltrating lymphocytes (TILs), and Extracellular vesicles (EVs). Conclusion The current research advance of predictive biomarkers for melanoma immunotherapy can be mainly divided into three parts: tumor-related factors, host factors, and the tumor microenvironment. The predictive biomarkers include PD-L1, TMB, gene mutations, immune cells, IDO1, LDH, TLS, HLA-DR, TAMs, TILs, and EVs. A model based on multiple biomarkers is expected to become the answer to predicting prognosis.

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Publication Details

Journal
Holistic Integrative Oncology
Published
2024-10-11
DOI
https://doi.org/10.1007/s44178-024-00121-9
Citations
7
Primary Topic
Immunotherapy and Immune Responses
Type
article
Field-Weighted Citation Impact
1.68

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article

Advances in predictive biomarkers for melanoma immunotherapy

Yu Xu, Tu Hu, Jingqin Zhong, Wanlin Liu et al.
7 citations
Holistic Integrative Oncology
Immunotherapy and Immune Responses
1.68
article

Advances in predictive biomarkers for melanoma immunotherapy

Yu Xu, Tu Hu, Jingqin Zhong, Wanlin Liu, Zijian Zou, Yong Chen, Wei Sun, Xinyi Lin, Wenjie Ma
article en
7 citations

Abstract

Abstract Purpose This review primarily discusses the current research advance of predictive biomarkers for melanoma immunotherapy. The aim of the present review is to summarize the biomarkers and evaluate the advantages and disadvantages. Methods All reference can be found through Pubmed. This review mainly focuses on three main directions: tumor-related factors, host factors, and the tumor microenvironment. In the end, there exhibits some unusual aspects of predictive biomarkers and forecasts the future model. Results The mainsteam of predictive biomarkers focuses on PD-L1, TMB, gene mutations, immune cells, IDO1, LDH, tertiary lymphoid structures (TLS), HLA-DR, tumor-associated macrophages (TAMs), tumor-infiltrating lymphocytes (TILs), and Extracellular vesicles (EVs). Conclusion The current research advance of predictive biomarkers for melanoma immunotherapy can be mainly divided into three parts: tumor-related factors, host factors, and the tumor microenvironment. The predictive biomarkers include PD-L1, TMB, gene mutations, immune cells, IDO1, LDH, TLS, HLA-DR, TAMs, TILs, and EVs. A model based on multiple biomarkers is expected to become the answer to predicting prognosis.

Holistic Integrative OncologyVol. 3(1)
Shanghai Medical College of Fudan University (CN), Fudan University Shanghai Cancer Center (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 16%
Immunotherapy and Immune Responses
1.68
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Advances in predictive biomarkers for melanoma immunotherapy — Yu Xu, Tu Hu, et al. · Holistic Integrative Oncology (2024) | TGRS Research Map | TGRS