Cargando…

Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer

METHODS: Two datasets were used as training and validation cohorts to establish the predictive model. We used three types of screening criteria: background analysis, pathway analysis, and functional analysis provided by the cBioportal website. Fisher's exact test and multivariable logistic regr...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Shuxin, Mao, Qianqian, Zhang, Zixuan, Wang, Yuqi, Chen, Duoxuan, Chen, Zhenwen, Lu, Jianyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850031/
https://www.ncbi.nlm.nih.gov/pubmed/35187167
http://dx.doi.org/10.1155/2022/5593619
_version_ 1784652524209307648
author Li, Shuxin
Mao, Qianqian
Zhang, Zixuan
Wang, Yuqi
Chen, Duoxuan
Chen, Zhenwen
Lu, Jianyi
author_facet Li, Shuxin
Mao, Qianqian
Zhang, Zixuan
Wang, Yuqi
Chen, Duoxuan
Chen, Zhenwen
Lu, Jianyi
author_sort Li, Shuxin
collection PubMed
description METHODS: Two datasets were used as training and validation cohorts to establish the predictive model. We used three types of screening criteria: background analysis, pathway analysis, and functional analysis provided by the cBioportal website. Fisher's exact test and multivariable logistic regression were performed to screen out related genes. Furthermore, we performed receiver operating characteristic (ROC) and Kaplan–Meier curve analyses to evaluate the correlation between the selected genes and overall survival. RESULT: We screened five genes (KNL1, NRXN1, C6, CCDC169-SOHLH2, and TTN) that were highly related to recurrence of GC. The area under the receiver operating characteristic (ROC) curve was 0.813, which was much higher than that of the baseline model (AUC = 0.699). This result suggested that the mutation of five selected genes had a significant effect on the prediction of recurrence compared with other factors (age, stages, history, etc.). Furthermore, the Kaplan-Meier estimator also revealed that the mutation of five genes positively correlated with patient survival. CONCLUSIONS: The patients who have mutations in these five genes may experience longer survival than those who do not have mutations. This five-gene panel will likely be a practical tool for prognostic evaluation and will provide another possible way for clinicians to determine therapy.
format Online
Article
Text
id pubmed-8850031
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-88500312022-02-17 Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer Li, Shuxin Mao, Qianqian Zhang, Zixuan Wang, Yuqi Chen, Duoxuan Chen, Zhenwen Lu, Jianyi Biomed Res Int Research Article METHODS: Two datasets were used as training and validation cohorts to establish the predictive model. We used three types of screening criteria: background analysis, pathway analysis, and functional analysis provided by the cBioportal website. Fisher's exact test and multivariable logistic regression were performed to screen out related genes. Furthermore, we performed receiver operating characteristic (ROC) and Kaplan–Meier curve analyses to evaluate the correlation between the selected genes and overall survival. RESULT: We screened five genes (KNL1, NRXN1, C6, CCDC169-SOHLH2, and TTN) that were highly related to recurrence of GC. The area under the receiver operating characteristic (ROC) curve was 0.813, which was much higher than that of the baseline model (AUC = 0.699). This result suggested that the mutation of five selected genes had a significant effect on the prediction of recurrence compared with other factors (age, stages, history, etc.). Furthermore, the Kaplan-Meier estimator also revealed that the mutation of five genes positively correlated with patient survival. CONCLUSIONS: The patients who have mutations in these five genes may experience longer survival than those who do not have mutations. This five-gene panel will likely be a practical tool for prognostic evaluation and will provide another possible way for clinicians to determine therapy. Hindawi 2022-02-09 /pmc/articles/PMC8850031/ /pubmed/35187167 http://dx.doi.org/10.1155/2022/5593619 Text en Copyright © 2022 Shuxin Li 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
Li, Shuxin
Mao, Qianqian
Zhang, Zixuan
Wang, Yuqi
Chen, Duoxuan
Chen, Zhenwen
Lu, Jianyi
Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer
title Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer
title_full Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer
title_fullStr Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer
title_full_unstemmed Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer
title_short Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer
title_sort identification of a five-gene panel to assess prognosis for gastric cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850031/
https://www.ncbi.nlm.nih.gov/pubmed/35187167
http://dx.doi.org/10.1155/2022/5593619
work_keys_str_mv AT lishuxin identificationofafivegenepaneltoassessprognosisforgastriccancer
AT maoqianqian identificationofafivegenepaneltoassessprognosisforgastriccancer
AT zhangzixuan identificationofafivegenepaneltoassessprognosisforgastriccancer
AT wangyuqi identificationofafivegenepaneltoassessprognosisforgastriccancer
AT chenduoxuan identificationofafivegenepaneltoassessprognosisforgastriccancer
AT chenzhenwen identificationofafivegenepaneltoassessprognosisforgastriccancer
AT lujianyi identificationofafivegenepaneltoassessprognosisforgastriccancer