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A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies

BACKGROUND: There is a lack of molecular markers that effectively predict response to treatment with immune checkpoint inhibitors in patients with uroepithelial bladder carcinoma. The purpose of this study was to explore molecular markers that effectively predict the efficacy of Atezolizumab in the...

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Autores principales: Zhang, Chunlei, Kang, Yindong, Miao, Pengcheng, Chang, Dehui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493780/
https://www.ncbi.nlm.nih.gov/pubmed/37701107
http://dx.doi.org/10.21037/tcr-23-220
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author Zhang, Chunlei
Kang, Yindong
Miao, Pengcheng
Chang, Dehui
author_facet Zhang, Chunlei
Kang, Yindong
Miao, Pengcheng
Chang, Dehui
author_sort Zhang, Chunlei
collection PubMed
description BACKGROUND: There is a lack of molecular markers that effectively predict response to treatment with immune checkpoint inhibitors in patients with uroepithelial bladder carcinoma. The purpose of this study was to explore molecular markers that effectively predict the efficacy of Atezolizumab in the treatment of uroepithelial bladder carcinoma based on real-world clinical trial data. METHODS: Gene expression and clinical information of two groups of patients in two datasets, IMvigor210 and GSE176307, who were treated effectively and ineffectively with the programmed cell death 1 ligand 1 (PD-L1) inhibitor Atezolizumab, were obtained. Bioinformatic methods were used to screen out differentially expressed genes and detect the correlation between their expression and immune-related indicators. Subsequently, we assessed the ability of differentially expressed genes to predict the therapeutic response and prognosis of bladder cancer patients following Atezolizumab treatment. RESULTS: A total of 2 differentially expressed genes, CXC motif chemokine ligand 9 (CXCL9) and CXC motif chemokine ligand 10 (CXCL10) [all P<0.05, log|fold change (FC)| >1], which were co-upregulated, were screened as study targets. In The Cancer Genome Atlas (TCGA) database, CXCL9/10 mRNA expression was positively correlated with both PD-L1 and tumor mutation burden (TMB) (all P<0.05). In the IMvigor210 dataset, the area under the receiver operating characteristic (ROC) curve for CXCL9, CXCL10 and PD-L1 mRNA expression to predict response to treatment with Atezolizumab were 0.645, 0.636 and 0.566, respectively; And CXCL9/10 mRNA was effective in predicting overall survival in patients receiving treatment (all P<0.05). In the GSE176307 dataset, the area under the ROC curve for CXCL9, CXCL10 and PD-L1 mRNA expression to predict response to treatment with Atezolizumab were 0.829, 0.829 and 0.765, respectively; And CXCL9/10 mRNA was not effective in predicting overall survival in patients receiving treatment (all P>0.05). CONCLUSIONS: The mRNA expression levels of CXCL9/10 have the potential to serve as a molecular marker for predicting the therapeutic response and overall survival outcomes of bladder cancer patients treated with Atezolizumab.
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spelling pubmed-104937802023-09-12 A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies Zhang, Chunlei Kang, Yindong Miao, Pengcheng Chang, Dehui Transl Cancer Res Original Article BACKGROUND: There is a lack of molecular markers that effectively predict response to treatment with immune checkpoint inhibitors in patients with uroepithelial bladder carcinoma. The purpose of this study was to explore molecular markers that effectively predict the efficacy of Atezolizumab in the treatment of uroepithelial bladder carcinoma based on real-world clinical trial data. METHODS: Gene expression and clinical information of two groups of patients in two datasets, IMvigor210 and GSE176307, who were treated effectively and ineffectively with the programmed cell death 1 ligand 1 (PD-L1) inhibitor Atezolizumab, were obtained. Bioinformatic methods were used to screen out differentially expressed genes and detect the correlation between their expression and immune-related indicators. Subsequently, we assessed the ability of differentially expressed genes to predict the therapeutic response and prognosis of bladder cancer patients following Atezolizumab treatment. RESULTS: A total of 2 differentially expressed genes, CXC motif chemokine ligand 9 (CXCL9) and CXC motif chemokine ligand 10 (CXCL10) [all P<0.05, log|fold change (FC)| >1], which were co-upregulated, were screened as study targets. In The Cancer Genome Atlas (TCGA) database, CXCL9/10 mRNA expression was positively correlated with both PD-L1 and tumor mutation burden (TMB) (all P<0.05). In the IMvigor210 dataset, the area under the receiver operating characteristic (ROC) curve for CXCL9, CXCL10 and PD-L1 mRNA expression to predict response to treatment with Atezolizumab were 0.645, 0.636 and 0.566, respectively; And CXCL9/10 mRNA was effective in predicting overall survival in patients receiving treatment (all P<0.05). In the GSE176307 dataset, the area under the ROC curve for CXCL9, CXCL10 and PD-L1 mRNA expression to predict response to treatment with Atezolizumab were 0.829, 0.829 and 0.765, respectively; And CXCL9/10 mRNA was not effective in predicting overall survival in patients receiving treatment (all P>0.05). CONCLUSIONS: The mRNA expression levels of CXCL9/10 have the potential to serve as a molecular marker for predicting the therapeutic response and overall survival outcomes of bladder cancer patients treated with Atezolizumab. AME Publishing Company 2023-08-17 2023-08-31 /pmc/articles/PMC10493780/ /pubmed/37701107 http://dx.doi.org/10.21037/tcr-23-220 Text en 2023 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zhang, Chunlei
Kang, Yindong
Miao, Pengcheng
Chang, Dehui
A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies
title A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies
title_full A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies
title_fullStr A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies
title_full_unstemmed A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies
title_short A novel genes-based signature with prognostic value and predictive ability to select patients responsive to Atezolizumab treatment in bladder cancer: an analysis on data from real-world studies
title_sort novel genes-based signature with prognostic value and predictive ability to select patients responsive to atezolizumab treatment in bladder cancer: an analysis on data from real-world studies
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493780/
https://www.ncbi.nlm.nih.gov/pubmed/37701107
http://dx.doi.org/10.21037/tcr-23-220
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