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An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer
PURPOSE: Gastric cancer (GC) has substantial biological differences between Asian and non-Asian populations, which makes it difficult to have a unified predictive measure for all people. We aimed to identify novel prognostic biomarkers to help predict the prognosis of Asian GC patients. MATERIALS AN...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Cancer Association
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812008/ https://www.ncbi.nlm.nih.gov/pubmed/32878427 http://dx.doi.org/10.4143/crt.2020.424 |
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author | Chen, Jiahui Wang, Anqiang Ji, Jun Zhou, Kai Bu, Zhaode Lyu, Guoqing Ji, Jiafu |
author_facet | Chen, Jiahui Wang, Anqiang Ji, Jun Zhou, Kai Bu, Zhaode Lyu, Guoqing Ji, Jiafu |
author_sort | Chen, Jiahui |
collection | PubMed |
description | PURPOSE: Gastric cancer (GC) has substantial biological differences between Asian and non-Asian populations, which makes it difficult to have a unified predictive measure for all people. We aimed to identify novel prognostic biomarkers to help predict the prognosis of Asian GC patients. MATERIALS AND METHODS: We investigated the differential gene expression between GC and normal tissues of GSE66229. Univariate, multivariate and Lasso Cox regression analyses were conducted to establish a four-gene-related prognostic model based on the risk score. The risk score was based on a linear combination of the expression levels of individual genes multiplied by their multivariate Cox regression coefficients. Validation of the prognostic model was conducted using The Cancer Genome Atlas (TCGA) database. A nomogram containing clinical characteristics and the prognostic model was established to predict the prognosis of Asian GC patients. RESULTS: Four genes (RBPMS2, RGN, PLEKHS1, and CT83) were selected to establish the prognostic model, and it was validated in the TCGA Asian cohort. Receiver operating characteristic analysis confirmed the sensitivity and specificity of the prognostic model. Based on the prognostic model, a nomogram containing clinical characteristics and the prognostic model was established, and Harrell’s concordance index of the nomogram for evaluating the overall survival significantly higher than the model only focuses on the pathologic stage (0.74 vs. 0.64, p < 0.001). CONCLUSION: The four-gene-related prognostic model and the nomogram based on it are reliable tools for predicting the overall survival of Asian GC patients. |
format | Online Article Text |
id | pubmed-7812008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Korean Cancer Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-78120082021-01-26 An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer Chen, Jiahui Wang, Anqiang Ji, Jun Zhou, Kai Bu, Zhaode Lyu, Guoqing Ji, Jiafu Cancer Res Treat Original Article PURPOSE: Gastric cancer (GC) has substantial biological differences between Asian and non-Asian populations, which makes it difficult to have a unified predictive measure for all people. We aimed to identify novel prognostic biomarkers to help predict the prognosis of Asian GC patients. MATERIALS AND METHODS: We investigated the differential gene expression between GC and normal tissues of GSE66229. Univariate, multivariate and Lasso Cox regression analyses were conducted to establish a four-gene-related prognostic model based on the risk score. The risk score was based on a linear combination of the expression levels of individual genes multiplied by their multivariate Cox regression coefficients. Validation of the prognostic model was conducted using The Cancer Genome Atlas (TCGA) database. A nomogram containing clinical characteristics and the prognostic model was established to predict the prognosis of Asian GC patients. RESULTS: Four genes (RBPMS2, RGN, PLEKHS1, and CT83) were selected to establish the prognostic model, and it was validated in the TCGA Asian cohort. Receiver operating characteristic analysis confirmed the sensitivity and specificity of the prognostic model. Based on the prognostic model, a nomogram containing clinical characteristics and the prognostic model was established, and Harrell’s concordance index of the nomogram for evaluating the overall survival significantly higher than the model only focuses on the pathologic stage (0.74 vs. 0.64, p < 0.001). CONCLUSION: The four-gene-related prognostic model and the nomogram based on it are reliable tools for predicting the overall survival of Asian GC patients. Korean Cancer Association 2021-01 2020-08-31 /pmc/articles/PMC7812008/ /pubmed/32878427 http://dx.doi.org/10.4143/crt.2020.424 Text en Copyright © 2021 by the Korean Cancer Association This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Chen, Jiahui Wang, Anqiang Ji, Jun Zhou, Kai Bu, Zhaode Lyu, Guoqing Ji, Jiafu An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer |
title | An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer |
title_full | An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer |
title_fullStr | An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer |
title_full_unstemmed | An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer |
title_short | An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer |
title_sort | innovative prognostic model based on four genes in asian patient with gastric cancer |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812008/ https://www.ncbi.nlm.nih.gov/pubmed/32878427 http://dx.doi.org/10.4143/crt.2020.424 |
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