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A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer

BACKGROUND: Triple-negative breast cancer (TNBC) is a highly aggressive subtype and only some of patients could benefit from the immunotherapy. The present study aims to investigate the expression pattern and prognostic value of immune checkpoint genes (ICGs) in TNBC and develop a novel ICGs-signatu...

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Autores principales: Liu, Jingyi, Ling, Yuwei, Su, Ning, Li, Yan, Tian, Siyuan, Hou, Bingxin, Luo, Shanquan, Zhao, Lina, Shi, Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841573/
https://www.ncbi.nlm.nih.gov/pubmed/35261895
http://dx.doi.org/10.21037/tcr-21-1455
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author Liu, Jingyi
Ling, Yuwei
Su, Ning
Li, Yan
Tian, Siyuan
Hou, Bingxin
Luo, Shanquan
Zhao, Lina
Shi, Mei
author_facet Liu, Jingyi
Ling, Yuwei
Su, Ning
Li, Yan
Tian, Siyuan
Hou, Bingxin
Luo, Shanquan
Zhao, Lina
Shi, Mei
author_sort Liu, Jingyi
collection PubMed
description BACKGROUND: Triple-negative breast cancer (TNBC) is a highly aggressive subtype and only some of patients could benefit from the immunotherapy. The present study aims to investigate the expression pattern and prognostic value of immune checkpoint genes (ICGs) in TNBC and develop a novel ICGs-signature to predict the prognosis and immune status in TNBC. METHODS: ICGs expression profiles and clinical characteristics of TNBC samples were obtained from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to construct a multi-gene signature for predicting the prognostic outcome. The risk scores were calculated based on the coefficients of each ICG in LASSO-Cox regression model. The median score was considered as the cut-off value to divide the TNBC patients into a high-risk group and a low-risk group. The Kaplan-Meier survival curves were generated to further explore the association between the risk scores and prognostic outcomes. Finally, single sample gene set enrichment analysis (ssGSEA) was conducted to evaluate the immune status and immunophenoscore (IPS) score was used for the quantitative evaluation of tumor immunogenicity. RESULTS: PDCD1, PDCD1LG2 and KIR3DL2 were included in the ICGs-signature model and the risk scores were calculated for each sample according to the coefficients in LASSO-Cox regression. Patients in high-risk group were associated with unfavorable prognosis. The receiver operating characteristic (ROC) curves showed the area under the curve (AUC) values for predicting 1-, 2- and 3-year overall survival (OS) by ICGs-signature were 0.925,0.822 and 0.835, respectively. The adaptive immunity cells and innate immunity cells were significantly abundant in the low-risk group, and low-risk patients tended to have higher IPS scores of PD-1, CTLA4, PD-L1 and PD-L2. CONCLUSIONS: A novel ICGs-signature was developed and validated, which may be not only served as a robust prognostic marker, but also a potential indicator reflecting immunotherapy response.
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spelling pubmed-88415732022-03-07 A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer Liu, Jingyi Ling, Yuwei Su, Ning Li, Yan Tian, Siyuan Hou, Bingxin Luo, Shanquan Zhao, Lina Shi, Mei Transl Cancer Res Original Article BACKGROUND: Triple-negative breast cancer (TNBC) is a highly aggressive subtype and only some of patients could benefit from the immunotherapy. The present study aims to investigate the expression pattern and prognostic value of immune checkpoint genes (ICGs) in TNBC and develop a novel ICGs-signature to predict the prognosis and immune status in TNBC. METHODS: ICGs expression profiles and clinical characteristics of TNBC samples were obtained from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to construct a multi-gene signature for predicting the prognostic outcome. The risk scores were calculated based on the coefficients of each ICG in LASSO-Cox regression model. The median score was considered as the cut-off value to divide the TNBC patients into a high-risk group and a low-risk group. The Kaplan-Meier survival curves were generated to further explore the association between the risk scores and prognostic outcomes. Finally, single sample gene set enrichment analysis (ssGSEA) was conducted to evaluate the immune status and immunophenoscore (IPS) score was used for the quantitative evaluation of tumor immunogenicity. RESULTS: PDCD1, PDCD1LG2 and KIR3DL2 were included in the ICGs-signature model and the risk scores were calculated for each sample according to the coefficients in LASSO-Cox regression. Patients in high-risk group were associated with unfavorable prognosis. The receiver operating characteristic (ROC) curves showed the area under the curve (AUC) values for predicting 1-, 2- and 3-year overall survival (OS) by ICGs-signature were 0.925,0.822 and 0.835, respectively. The adaptive immunity cells and innate immunity cells were significantly abundant in the low-risk group, and low-risk patients tended to have higher IPS scores of PD-1, CTLA4, PD-L1 and PD-L2. CONCLUSIONS: A novel ICGs-signature was developed and validated, which may be not only served as a robust prognostic marker, but also a potential indicator reflecting immunotherapy response. AME Publishing Company 2022-01 /pmc/articles/PMC8841573/ /pubmed/35261895 http://dx.doi.org/10.21037/tcr-21-1455 Text en 2022 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/.
spellingShingle Original Article
Liu, Jingyi
Ling, Yuwei
Su, Ning
Li, Yan
Tian, Siyuan
Hou, Bingxin
Luo, Shanquan
Zhao, Lina
Shi, Mei
A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer
title A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer
title_full A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer
title_fullStr A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer
title_full_unstemmed A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer
title_short A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer
title_sort novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841573/
https://www.ncbi.nlm.nih.gov/pubmed/35261895
http://dx.doi.org/10.21037/tcr-21-1455
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