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Prognostic value of eight immune gene signatures in pancreatic cancer patients

BACKGROUND: Pancreatic cancer is one of the most common malignant tumors of the digestive tract, and it has a poor prognosis. Traditional methods are not effective to accurately assess the prognosis of patients with pancreatic cancer. Immunotherapy is a new promising approach for the treatment of pa...

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Autores principales: Wang, Wenting, Xu, Zhijian, Wang, Ning, Yao, Ruyong, Qin, Tao, Lin, Hao, Yue, Lu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863419/
https://www.ncbi.nlm.nih.gov/pubmed/33546693
http://dx.doi.org/10.1186/s12920-020-00868-w
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author Wang, Wenting
Xu, Zhijian
Wang, Ning
Yao, Ruyong
Qin, Tao
Lin, Hao
Yue, Lu
author_facet Wang, Wenting
Xu, Zhijian
Wang, Ning
Yao, Ruyong
Qin, Tao
Lin, Hao
Yue, Lu
author_sort Wang, Wenting
collection PubMed
description BACKGROUND: Pancreatic cancer is one of the most common malignant tumors of the digestive tract, and it has a poor prognosis. Traditional methods are not effective to accurately assess the prognosis of patients with pancreatic cancer. Immunotherapy is a new promising approach for the treatment of pancreatic cancer; however, some patients do not respond well to immunotherapy, which may be related to tumor microenvironment regulation. In this study, we use gene expression database to mine important immune genes and establish a prognostic prediction model for pancreatic cancer patients. We hope to provide a feasible method to evaluate the prognosis of pancreatic cancer and provide valuable targets for pancreatic cancer immunotherapy. RESULTS: We used univariate COX proportional hazard regression analysis, the least absolute shrinkage and selection operator, and multivariate COX regression analysis to screen 8 genes related to prognosis from the 314 immune-related genes, and used them to construct a new clinical prediction model in the TCGA pancreatic cancer cohort. Subsequently, we evaluated the prognostic value of the model. The Kaplan–Meier cumulative curve showed that patients with low risk scores survived significantly longer than patients with high risk scores. The area under the ROC curve (AUC value) of the risk score was 0.755. The univariate COX analysis showed that the risk score was significantly related to overall survival (HR 1.406, 95% CI 1.237–1.598, P < 0.001), and multivariate analysis showed that the risk score was an independent prognostic factor (HR 1.400, 95% CI 1.287–1.522, P < 0.001). Correlation analysis found that immune genes are closely related to tumor immune microenvironment. CONCLUSIONS: Based on the TCGA-PAAD cohort, we identified immune-related markers with independent prognostic significance, validated, and analyzed their biological functions, to provide a feasible method for the prognosis of pancreatic cancer and provide potentially valuable targets for pancreatic cancer immunotherapy.
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spelling pubmed-78634192021-02-05 Prognostic value of eight immune gene signatures in pancreatic cancer patients Wang, Wenting Xu, Zhijian Wang, Ning Yao, Ruyong Qin, Tao Lin, Hao Yue, Lu BMC Med Genomics Research Article BACKGROUND: Pancreatic cancer is one of the most common malignant tumors of the digestive tract, and it has a poor prognosis. Traditional methods are not effective to accurately assess the prognosis of patients with pancreatic cancer. Immunotherapy is a new promising approach for the treatment of pancreatic cancer; however, some patients do not respond well to immunotherapy, which may be related to tumor microenvironment regulation. In this study, we use gene expression database to mine important immune genes and establish a prognostic prediction model for pancreatic cancer patients. We hope to provide a feasible method to evaluate the prognosis of pancreatic cancer and provide valuable targets for pancreatic cancer immunotherapy. RESULTS: We used univariate COX proportional hazard regression analysis, the least absolute shrinkage and selection operator, and multivariate COX regression analysis to screen 8 genes related to prognosis from the 314 immune-related genes, and used them to construct a new clinical prediction model in the TCGA pancreatic cancer cohort. Subsequently, we evaluated the prognostic value of the model. The Kaplan–Meier cumulative curve showed that patients with low risk scores survived significantly longer than patients with high risk scores. The area under the ROC curve (AUC value) of the risk score was 0.755. The univariate COX analysis showed that the risk score was significantly related to overall survival (HR 1.406, 95% CI 1.237–1.598, P < 0.001), and multivariate analysis showed that the risk score was an independent prognostic factor (HR 1.400, 95% CI 1.287–1.522, P < 0.001). Correlation analysis found that immune genes are closely related to tumor immune microenvironment. CONCLUSIONS: Based on the TCGA-PAAD cohort, we identified immune-related markers with independent prognostic significance, validated, and analyzed their biological functions, to provide a feasible method for the prognosis of pancreatic cancer and provide potentially valuable targets for pancreatic cancer immunotherapy. BioMed Central 2021-02-05 /pmc/articles/PMC7863419/ /pubmed/33546693 http://dx.doi.org/10.1186/s12920-020-00868-w Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Wang, Wenting
Xu, Zhijian
Wang, Ning
Yao, Ruyong
Qin, Tao
Lin, Hao
Yue, Lu
Prognostic value of eight immune gene signatures in pancreatic cancer patients
title Prognostic value of eight immune gene signatures in pancreatic cancer patients
title_full Prognostic value of eight immune gene signatures in pancreatic cancer patients
title_fullStr Prognostic value of eight immune gene signatures in pancreatic cancer patients
title_full_unstemmed Prognostic value of eight immune gene signatures in pancreatic cancer patients
title_short Prognostic value of eight immune gene signatures in pancreatic cancer patients
title_sort prognostic value of eight immune gene signatures in pancreatic cancer patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863419/
https://www.ncbi.nlm.nih.gov/pubmed/33546693
http://dx.doi.org/10.1186/s12920-020-00868-w
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