Cargando…

Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes

Objective: Based on TCGA database, a prediction model for 1-, 3-, and 5-year overall survival rates of gastric cancer (GC) patients was constructed by analyzing the critical risk factors affecting the prognosis of gastric cancer patients. Method: Clinicopathological features as well as gene signatur...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Xiaokang, Xu, Kexin, Liao, Xueyi, Rao, Jiaoyu, Huang, Kaiyuan, Gao, Jianlin, Xu, Gengrui, Wang, Dengchuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389082/
https://www.ncbi.nlm.nih.gov/pubmed/35991573
http://dx.doi.org/10.3389/fgene.2022.936658
_version_ 1784770359357079552
author Wang, Xiaokang
Xu, Kexin
Liao, Xueyi
Rao, Jiaoyu
Huang, Kaiyuan
Gao, Jianlin
Xu, Gengrui
Wang, Dengchuan
author_facet Wang, Xiaokang
Xu, Kexin
Liao, Xueyi
Rao, Jiaoyu
Huang, Kaiyuan
Gao, Jianlin
Xu, Gengrui
Wang, Dengchuan
author_sort Wang, Xiaokang
collection PubMed
description Objective: Based on TCGA database, a prediction model for 1-, 3-, and 5-year overall survival rates of gastric cancer (GC) patients was constructed by analyzing the critical risk factors affecting the prognosis of gastric cancer patients. Method: Clinicopathological features as well as gene signature of GC patients were obtained from TCGA database. Patients were randomly divided into a training cohort and an internal validation cohort. Independent predictors of GC prognosis were analyzed by univariate and multivariate Cox analyses to construct nomogram. The accuracy and reliability of the model was further validated by calibration curves, ROC curves, and C-indexes, and the clinical utility of the model was analyzed by decision analysis curves. Result: Age, sex, N stage, M stage, METTL16, RBM15, FMR1, IGFBP1, and FTO were significantly associated with the prognosis of GC patients, and these predictors were further included in the construction of nomogram. The C-indexes for the training cohort and validation set were 0.735 and 0.688, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.6 in training and validation sets at 1, 3, and 5 years. Conclusion: We have constructed and validated a nomogram that provides individual survival condition prediction for GC patients. The prognostic model integrating gene signatures and clinicopathological characteristics would help clinicians determine the prognosis of patients with GC and develop individualized treatment plans.
format Online
Article
Text
id pubmed-9389082
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-93890822022-08-20 Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes Wang, Xiaokang Xu, Kexin Liao, Xueyi Rao, Jiaoyu Huang, Kaiyuan Gao, Jianlin Xu, Gengrui Wang, Dengchuan Front Genet Genetics Objective: Based on TCGA database, a prediction model for 1-, 3-, and 5-year overall survival rates of gastric cancer (GC) patients was constructed by analyzing the critical risk factors affecting the prognosis of gastric cancer patients. Method: Clinicopathological features as well as gene signature of GC patients were obtained from TCGA database. Patients were randomly divided into a training cohort and an internal validation cohort. Independent predictors of GC prognosis were analyzed by univariate and multivariate Cox analyses to construct nomogram. The accuracy and reliability of the model was further validated by calibration curves, ROC curves, and C-indexes, and the clinical utility of the model was analyzed by decision analysis curves. Result: Age, sex, N stage, M stage, METTL16, RBM15, FMR1, IGFBP1, and FTO were significantly associated with the prognosis of GC patients, and these predictors were further included in the construction of nomogram. The C-indexes for the training cohort and validation set were 0.735 and 0.688, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.6 in training and validation sets at 1, 3, and 5 years. Conclusion: We have constructed and validated a nomogram that provides individual survival condition prediction for GC patients. The prognostic model integrating gene signatures and clinicopathological characteristics would help clinicians determine the prognosis of patients with GC and develop individualized treatment plans. Frontiers Media S.A. 2022-08-05 /pmc/articles/PMC9389082/ /pubmed/35991573 http://dx.doi.org/10.3389/fgene.2022.936658 Text en Copyright © 2022 Wang, Xu, Liao, Rao, Huang, Gao, Xu and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wang, Xiaokang
Xu, Kexin
Liao, Xueyi
Rao, Jiaoyu
Huang, Kaiyuan
Gao, Jianlin
Xu, Gengrui
Wang, Dengchuan
Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes
title Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes
title_full Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes
title_fullStr Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes
title_full_unstemmed Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes
title_short Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes
title_sort construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6a-related genes
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389082/
https://www.ncbi.nlm.nih.gov/pubmed/35991573
http://dx.doi.org/10.3389/fgene.2022.936658
work_keys_str_mv AT wangxiaokang constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes
AT xukexin constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes
AT liaoxueyi constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes
AT raojiaoyu constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes
AT huangkaiyuan constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes
AT gaojianlin constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes
AT xugengrui constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes
AT wangdengchuan constructionofasurvivalnomogramforgastriccancerbasedonthecancergenomeatlasofm6arelatedgenes