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A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer
Endometrial carcinoma (EC) is the second major female genital malignancy. Genetic signatures may be an improved choice to predict the prognosis of EC patients. The relationship between pyroptosis and tumours has attracted much attention in recent years. Here, we constructed a new pyroptosis-related...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9806687/ https://www.ncbi.nlm.nih.gov/pubmed/36601599 http://dx.doi.org/10.1155/2022/7570494 |
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author | Liu, Shuguang Zeng, Chao Lv, Huaisheng Zhang, Yan Xiong, Hong Tang, Hongping |
author_facet | Liu, Shuguang Zeng, Chao Lv, Huaisheng Zhang, Yan Xiong, Hong Tang, Hongping |
author_sort | Liu, Shuguang |
collection | PubMed |
description | Endometrial carcinoma (EC) is the second major female genital malignancy. Genetic signatures may be an improved choice to predict the prognosis of EC patients. The relationship between pyroptosis and tumours has attracted much attention in recent years. Here, we constructed a new pyroptosis-related gene (PRG) signature for predicting the prognosis of EC. In this study, gene data and clinical information of EC patients were obtained from The Cancer Genome Atlas (TCGA). Following the identification of PRGs correlated with EC prognosis, we further investigate the bioinformatics functions of these PRGs by univariate Cox regression analysis and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Then, we used the least absolute contraction and selection operator (LASSO) regression and multiple Cox regression analysis to construct a new PRG signature that contains seven PRGs (NFKB1, EEF2K, CTSV, MDM2, GZMB, PANX1, and PTEN) and performed the Kaplan-Meier (K-M) analysis, receiver operating characteristic curve (ROC) analysis, and principal component analysis (PCA) to evaluate the prognostic value of our novel PRG signature. Finally, we assessed the correlations between pyroptosis and immune cells/checkpoints through the CIBERSORT tool and single-sample gene set enrichment analysis (ssGSEA). The result suggested that our signature was powerful in predicting EC prognosis and may play a part in assessing response to immunotherapy in EC patients. In conclusion, our study established a novel PRG signature for EC, which can be used as an effective prognostic marker in clinical practice in the future. |
format | Online Article Text |
id | pubmed-9806687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-98066872023-01-03 A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer Liu, Shuguang Zeng, Chao Lv, Huaisheng Zhang, Yan Xiong, Hong Tang, Hongping Dis Markers Research Article Endometrial carcinoma (EC) is the second major female genital malignancy. Genetic signatures may be an improved choice to predict the prognosis of EC patients. The relationship between pyroptosis and tumours has attracted much attention in recent years. Here, we constructed a new pyroptosis-related gene (PRG) signature for predicting the prognosis of EC. In this study, gene data and clinical information of EC patients were obtained from The Cancer Genome Atlas (TCGA). Following the identification of PRGs correlated with EC prognosis, we further investigate the bioinformatics functions of these PRGs by univariate Cox regression analysis and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Then, we used the least absolute contraction and selection operator (LASSO) regression and multiple Cox regression analysis to construct a new PRG signature that contains seven PRGs (NFKB1, EEF2K, CTSV, MDM2, GZMB, PANX1, and PTEN) and performed the Kaplan-Meier (K-M) analysis, receiver operating characteristic curve (ROC) analysis, and principal component analysis (PCA) to evaluate the prognostic value of our novel PRG signature. Finally, we assessed the correlations between pyroptosis and immune cells/checkpoints through the CIBERSORT tool and single-sample gene set enrichment analysis (ssGSEA). The result suggested that our signature was powerful in predicting EC prognosis and may play a part in assessing response to immunotherapy in EC patients. In conclusion, our study established a novel PRG signature for EC, which can be used as an effective prognostic marker in clinical practice in the future. Hindawi 2022-12-16 /pmc/articles/PMC9806687/ /pubmed/36601599 http://dx.doi.org/10.1155/2022/7570494 Text en Copyright © 2022 Shuguang Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Shuguang Zeng, Chao Lv, Huaisheng Zhang, Yan Xiong, Hong Tang, Hongping A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer |
title | A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer |
title_full | A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer |
title_fullStr | A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer |
title_full_unstemmed | A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer |
title_short | A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer |
title_sort | novel defined pyroptosis-related gene signature for predicting the prognosis of endometrial cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9806687/ https://www.ncbi.nlm.nih.gov/pubmed/36601599 http://dx.doi.org/10.1155/2022/7570494 |
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