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Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer
Growing evidence has indicated that prognostic biomarkers have a pivotal role in tumor and immunity biological processes. TP53 mutation can cause a range of changes in immune response, progression, and prognosis of colorectal cancer (CRC). Thus, we aim to build an immunoscore prognostic model that m...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895875/ https://www.ncbi.nlm.nih.gov/pubmed/31689990 http://dx.doi.org/10.3390/cancers11111722 |
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author | Zhao, Xiaojuan Liu, Jianzhong Liu, Shuzhen Yang, Fangfang Chen, Erfei |
author_facet | Zhao, Xiaojuan Liu, Jianzhong Liu, Shuzhen Yang, Fangfang Chen, Erfei |
author_sort | Zhao, Xiaojuan |
collection | PubMed |
description | Growing evidence has indicated that prognostic biomarkers have a pivotal role in tumor and immunity biological processes. TP53 mutation can cause a range of changes in immune response, progression, and prognosis of colorectal cancer (CRC). Thus, we aim to build an immunoscore prognostic model that may enhance the prognosis of CRC from an immunological perspective. We estimated the proportion of immune cells in the GSE39582 public dataset using the CIBERSORT (Cell type identification by estimating relative subset of known RNA transcripts) algorithm. Prognostic genes that were used to establish the immunoscore model were generated by the LASSO (Least absolute shrinkage and selection operator) Cox regression model. We established and validated the immunoscore model in GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) cohorts, respectively; significant differences of overall survival analysis were found between the low and high immunoscore groups or TP53 subgroups. In the multivariable Cox analysis, we observed that the immunoscore was an independent prognostic factor both in the GEO cohort (HR (Hazard ratio) 1.76, 95% CI (confidence intervals): 1.26–2.46) and the TCGA cohort (HR 1.95, 95% CI: 1.20–3.18). Furthermore, we established a nomogram for clinical application, and the results suggest that the nomogram is a better predictive model for prognosis than immunoscore or TNM staging. |
format | Online Article Text |
id | pubmed-6895875 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68958752019-12-24 Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer Zhao, Xiaojuan Liu, Jianzhong Liu, Shuzhen Yang, Fangfang Chen, Erfei Cancers (Basel) Article Growing evidence has indicated that prognostic biomarkers have a pivotal role in tumor and immunity biological processes. TP53 mutation can cause a range of changes in immune response, progression, and prognosis of colorectal cancer (CRC). Thus, we aim to build an immunoscore prognostic model that may enhance the prognosis of CRC from an immunological perspective. We estimated the proportion of immune cells in the GSE39582 public dataset using the CIBERSORT (Cell type identification by estimating relative subset of known RNA transcripts) algorithm. Prognostic genes that were used to establish the immunoscore model were generated by the LASSO (Least absolute shrinkage and selection operator) Cox regression model. We established and validated the immunoscore model in GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) cohorts, respectively; significant differences of overall survival analysis were found between the low and high immunoscore groups or TP53 subgroups. In the multivariable Cox analysis, we observed that the immunoscore was an independent prognostic factor both in the GEO cohort (HR (Hazard ratio) 1.76, 95% CI (confidence intervals): 1.26–2.46) and the TCGA cohort (HR 1.95, 95% CI: 1.20–3.18). Furthermore, we established a nomogram for clinical application, and the results suggest that the nomogram is a better predictive model for prognosis than immunoscore or TNM staging. MDPI 2019-11-04 /pmc/articles/PMC6895875/ /pubmed/31689990 http://dx.doi.org/10.3390/cancers11111722 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhao, Xiaojuan Liu, Jianzhong Liu, Shuzhen Yang, Fangfang Chen, Erfei Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer |
title | Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer |
title_full | Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer |
title_fullStr | Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer |
title_full_unstemmed | Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer |
title_short | Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer |
title_sort | construction and validation of an immune-related prognostic model based on tp53 status in colorectal cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895875/ https://www.ncbi.nlm.nih.gov/pubmed/31689990 http://dx.doi.org/10.3390/cancers11111722 |
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