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Integrated multiomics revealed adenosine signaling predict immunotherapy response and regulate tumor ecosystem of melanoma

Authors :
Yantao Xu
Poyee Lau
Xiang Chen
Shuang Zhao
Yi He
Zixi Jiang
Guanxiong Zhang
Hong Liu
Source :
Human Genomics, Vol 18, Iss 1, Pp 1-15 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Extracellular adenosine is extensively involved in regulating the tumor microenvironment. Given the disappointing results of adenosine-targeted therapy trials, personalized treatment might be necessary, tailored to the microenvironment status of individual patients. Here, we introduce the adenosine signaling score (ADO-score) model using non-negative matrix fraction identified patient subtypes using publicly available melanoma dataset, which aimed to profile adenosine signaling-related genes and construct a model to predict prognosis. We analyzed 580 malignant melanoma samples and demonstrated its robust value for prognosis. Further investigation in immune checkpoint inhibitor dataset suggests its potential as a stratified factor of immune checkpoint inhibitor efficacy. We validated the power of the ADO-score at the protein level immunofluorescence in a melanoma cohort from Xiangya Hospital. More importantly, single-cell and spatial transcriptomic data highlighted the cell-specific expression patterns of adenosine signaling-related genes and the existence of adenosine signaling-mediated crosstalk between tumor cells and immune cells in melanoma. Our study reveals a robust connection between adenosine signaling and clinical benefits in melanoma patients and proposes a universally applicable adenosine signaling model, the ADO-score, in gene expression profiles and histological sections. This model enables us to more precisely and conveniently select patients who are likely to benefit from immunotherapy.

Details

Language :
English
ISSN :
14797364
Volume :
18
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Human Genomics
Publication Type :
Academic Journal
Accession number :
edsdoj.fa7ae86bfabd4ad595c20006aaa0a822
Document Type :
article
Full Text :
https://doi.org/10.1186/s40246-024-00651-3