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Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer

Ovarian cancer (OC) is the most lethal gynecological cancer in women. Studies had reported that immune-related lncRNAs signatures were valuable in predicting the survival and prognosis of patients with various cancers. In our study, the prognostic value of immune-related lncRNAs was investigated in...

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Autores principales: Li, He, Liu, Zhao-Yi, Chen, Yong-Chang, Zhang, Xiao-Ye, Wu, Nayiyuan, Wang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9596922/
https://www.ncbi.nlm.nih.gov/pubmed/36313727
http://dx.doi.org/10.3389/fonc.2022.999654
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author Li, He
Liu, Zhao-Yi
Chen, Yong-Chang
Zhang, Xiao-Ye
Wu, Nayiyuan
Wang, Jing
author_facet Li, He
Liu, Zhao-Yi
Chen, Yong-Chang
Zhang, Xiao-Ye
Wu, Nayiyuan
Wang, Jing
author_sort Li, He
collection PubMed
description Ovarian cancer (OC) is the most lethal gynecological cancer in women. Studies had reported that immune-related lncRNAs signatures were valuable in predicting the survival and prognosis of patients with various cancers. In our study, the prognostic value of immune-related lncRNAs was investigated in OC patients from TCGA-RNA-seq cohort (n=378) and HG-U133_Plus_2 cohort (n=590), respectively. Pearson correlation analysis was implemented to screen the immune-related lncRNA and then univariate Cox regression analysis was performed to explore their prognostic value in OC patients. Five prognostic immune-related lncRNAs were identified as prognostic lncRNAs. Besides, they were inputted into a LASSO Cox regression to establish and validate an immune-related lncRNA prognostic signature in TCGA-RNA-Seq cohort and HG-U133_Plus_2 cohort, respectively. Based on the best cut-off value of risk score, patients were divided into high- and low-risk groups. Survival analysis suggested that patients in the high-risk group had a worse overall survival (OS) than those in the low-risk group in both cohorts. The association between clinicopathological feathers and risk score was then evaluated by using stratification analysis. Moreover, we constructed a nomogram based on risk score, age and stage, which had a strong ability to forecast the OS of the OC patients. The influence of risk score on immune infiltration and immunotherapy response were assessed and the results suggested that patients with high-risk score might recruit multiple immune cells and stromal cells, leading to facilitating immune surveillance evasive. Ultimately, we demonstrated that the risk model was associated with chemotherapy response of multiple antitumor drugs, especially for paclitaxel, metformin and veliparib, which are commonly used in treating OC patients. In conclusion, we constructed a novel immune-related lncRNA signature, which had a potential prognostic value for OC patients and might facilitate personalized counselling for immunotherapy and chemotherapy.
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spelling pubmed-95969222022-10-27 Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer Li, He Liu, Zhao-Yi Chen, Yong-Chang Zhang, Xiao-Ye Wu, Nayiyuan Wang, Jing Front Oncol Oncology Ovarian cancer (OC) is the most lethal gynecological cancer in women. Studies had reported that immune-related lncRNAs signatures were valuable in predicting the survival and prognosis of patients with various cancers. In our study, the prognostic value of immune-related lncRNAs was investigated in OC patients from TCGA-RNA-seq cohort (n=378) and HG-U133_Plus_2 cohort (n=590), respectively. Pearson correlation analysis was implemented to screen the immune-related lncRNA and then univariate Cox regression analysis was performed to explore their prognostic value in OC patients. Five prognostic immune-related lncRNAs were identified as prognostic lncRNAs. Besides, they were inputted into a LASSO Cox regression to establish and validate an immune-related lncRNA prognostic signature in TCGA-RNA-Seq cohort and HG-U133_Plus_2 cohort, respectively. Based on the best cut-off value of risk score, patients were divided into high- and low-risk groups. Survival analysis suggested that patients in the high-risk group had a worse overall survival (OS) than those in the low-risk group in both cohorts. The association between clinicopathological feathers and risk score was then evaluated by using stratification analysis. Moreover, we constructed a nomogram based on risk score, age and stage, which had a strong ability to forecast the OS of the OC patients. The influence of risk score on immune infiltration and immunotherapy response were assessed and the results suggested that patients with high-risk score might recruit multiple immune cells and stromal cells, leading to facilitating immune surveillance evasive. Ultimately, we demonstrated that the risk model was associated with chemotherapy response of multiple antitumor drugs, especially for paclitaxel, metformin and veliparib, which are commonly used in treating OC patients. In conclusion, we constructed a novel immune-related lncRNA signature, which had a potential prognostic value for OC patients and might facilitate personalized counselling for immunotherapy and chemotherapy. Frontiers Media S.A. 2022-10-12 /pmc/articles/PMC9596922/ /pubmed/36313727 http://dx.doi.org/10.3389/fonc.2022.999654 Text en Copyright © 2022 Li, Liu, Chen, Zhang, Wu and Wang 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 Oncology
Li, He
Liu, Zhao-Yi
Chen, Yong-Chang
Zhang, Xiao-Ye
Wu, Nayiyuan
Wang, Jing
Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer
title Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer
title_full Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer
title_fullStr Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer
title_full_unstemmed Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer
title_short Identification and validation of an immune-related lncRNAs signature to predict the overall survival of ovarian cancer
title_sort identification and validation of an immune-related lncrnas signature to predict the overall survival of ovarian cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9596922/
https://www.ncbi.nlm.nih.gov/pubmed/36313727
http://dx.doi.org/10.3389/fonc.2022.999654
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