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An estrogen response-related signature predicts response to immunotherapy in melanoma
BACKGROUND: Estrogen/estrogen receptor signaling influences the tumor microenvironment and affects the efficacy of immunotherapy in some tumors, including melanoma. This study aimed to construct an estrogen response-related gene signature for predicting response to immunotherapy in melanoma. METHODS...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213284/ https://www.ncbi.nlm.nih.gov/pubmed/37251404 http://dx.doi.org/10.3389/fimmu.2023.1109300 |
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author | Lin, Min Du, Tian Tang, Xiaofeng Liao, Ying Cao, Lan Zhang, Yafang Zheng, Wei Zhou, Jianhua |
author_facet | Lin, Min Du, Tian Tang, Xiaofeng Liao, Ying Cao, Lan Zhang, Yafang Zheng, Wei Zhou, Jianhua |
author_sort | Lin, Min |
collection | PubMed |
description | BACKGROUND: Estrogen/estrogen receptor signaling influences the tumor microenvironment and affects the efficacy of immunotherapy in some tumors, including melanoma. This study aimed to construct an estrogen response-related gene signature for predicting response to immunotherapy in melanoma. METHODS: RNA sequencing data of 4 immunotherapy-treated melanoma datasets and TCGA melanoma was obtained from open access repository. Differential expression analysis and pathway analysis were performed between immunotherapy responders and non-responders. Using dataset GSE91061 as the training group, a multivariate logistic regression model was built from estrogen response-related differential expression genes to predict the response to immunotherapy. The other 3 datasets of immunotherapy-treated melanoma were used as the validation group. The correlation was also examined between the prediction score from the model and immune cell infiltration estimated by xCell in the immunotherapy-treated and TCGA melanoma cases. RESULTS: “Hallmark Estrogen Response Late” was significantly downregulated in immunotherapy responders. 11 estrogen response-related genes were significantly differentially expressed between immunotherapy responders and non-responders, and were included in the multivariate logistic regression model. The AUC was 0.888 in the training group and 0.654–0.720 in the validation group. A higher 11-gene signature score was significantly correlated to increased infiltration of CD8+ T cells (rho=0.32, p=0.02). TCGA melanoma with a high signature score showed a significantly higher proportion of immune-enriched/fibrotic and immune-enriched/non-fibrotic microenvironment subtypes (p<0.001)–subtypes with better response to immunotherapy–and significantly better progression-free interval (p=0.021). CONCLUSION: In this study, we identified and verified an 11-gene signature that could predict response to immunotherapy in melanoma and was correlated with tumor-infiltrating lymphocytes. Our study suggests targeting estrogen-related pathways may serve as a combination strategy for immunotherapy in melanoma. |
format | Online Article Text |
id | pubmed-10213284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102132842023-05-27 An estrogen response-related signature predicts response to immunotherapy in melanoma Lin, Min Du, Tian Tang, Xiaofeng Liao, Ying Cao, Lan Zhang, Yafang Zheng, Wei Zhou, Jianhua Front Immunol Immunology BACKGROUND: Estrogen/estrogen receptor signaling influences the tumor microenvironment and affects the efficacy of immunotherapy in some tumors, including melanoma. This study aimed to construct an estrogen response-related gene signature for predicting response to immunotherapy in melanoma. METHODS: RNA sequencing data of 4 immunotherapy-treated melanoma datasets and TCGA melanoma was obtained from open access repository. Differential expression analysis and pathway analysis were performed between immunotherapy responders and non-responders. Using dataset GSE91061 as the training group, a multivariate logistic regression model was built from estrogen response-related differential expression genes to predict the response to immunotherapy. The other 3 datasets of immunotherapy-treated melanoma were used as the validation group. The correlation was also examined between the prediction score from the model and immune cell infiltration estimated by xCell in the immunotherapy-treated and TCGA melanoma cases. RESULTS: “Hallmark Estrogen Response Late” was significantly downregulated in immunotherapy responders. 11 estrogen response-related genes were significantly differentially expressed between immunotherapy responders and non-responders, and were included in the multivariate logistic regression model. The AUC was 0.888 in the training group and 0.654–0.720 in the validation group. A higher 11-gene signature score was significantly correlated to increased infiltration of CD8+ T cells (rho=0.32, p=0.02). TCGA melanoma with a high signature score showed a significantly higher proportion of immune-enriched/fibrotic and immune-enriched/non-fibrotic microenvironment subtypes (p<0.001)–subtypes with better response to immunotherapy–and significantly better progression-free interval (p=0.021). CONCLUSION: In this study, we identified and verified an 11-gene signature that could predict response to immunotherapy in melanoma and was correlated with tumor-infiltrating lymphocytes. Our study suggests targeting estrogen-related pathways may serve as a combination strategy for immunotherapy in melanoma. Frontiers Media S.A. 2023-05-12 /pmc/articles/PMC10213284/ /pubmed/37251404 http://dx.doi.org/10.3389/fimmu.2023.1109300 Text en Copyright © 2023 Lin, Du, Tang, Liao, Cao, Zhang, Zheng and Zhou https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Lin, Min Du, Tian Tang, Xiaofeng Liao, Ying Cao, Lan Zhang, Yafang Zheng, Wei Zhou, Jianhua An estrogen response-related signature predicts response to immunotherapy in melanoma |
title | An estrogen response-related signature predicts response to immunotherapy in melanoma |
title_full | An estrogen response-related signature predicts response to immunotherapy in melanoma |
title_fullStr | An estrogen response-related signature predicts response to immunotherapy in melanoma |
title_full_unstemmed | An estrogen response-related signature predicts response to immunotherapy in melanoma |
title_short | An estrogen response-related signature predicts response to immunotherapy in melanoma |
title_sort | estrogen response-related signature predicts response to immunotherapy in melanoma |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213284/ https://www.ncbi.nlm.nih.gov/pubmed/37251404 http://dx.doi.org/10.3389/fimmu.2023.1109300 |
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