Cargando…

Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm

Different subtypes of gastric cancer differentially respond to immune checkpoint inhibitors (ICI). This study aimed to investigate whether the Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm is related to the classification and prognosis o...

Descripción completa

Detalles Bibliográficos
Autores principales: Yu, Shan, Wang, Yan, Peng, Ke, Lyu, Minzhi, Liu, Fenglin, Liu, Tianshu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8652145/
https://www.ncbi.nlm.nih.gov/pubmed/34900998
http://dx.doi.org/10.3389/fcell.2021.752023
_version_ 1784611531040751616
author Yu, Shan
Wang, Yan
Peng, Ke
Lyu, Minzhi
Liu, Fenglin
Liu, Tianshu
author_facet Yu, Shan
Wang, Yan
Peng, Ke
Lyu, Minzhi
Liu, Fenglin
Liu, Tianshu
author_sort Yu, Shan
collection PubMed
description Different subtypes of gastric cancer differentially respond to immune checkpoint inhibitors (ICI). This study aimed to investigate whether the Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm is related to the classification and prognosis of gastric cancer and to establish an ESTIMATE-based gene signature to predict the prognosis for patients. The immune/stromal scores of 388 gastric cancer patients from TCGA were used in this analysis. The upregulated differentially expressed genes (DEGs) in patients with high stromal/immune scores were identified. The immune-related hub DEGs were selected based on protein-protein interaction (PPI) analysis. The prognostic values of the hub DEGs were evaluated in the TCGA dataset and validated in the GSE15460 dataset using the Kaplan-Meier curves. A prognostic signature was built using the hub DEGs by Cox proportional hazards model, and the accuracy was assessed using receiver operating characteristic (ROC) analysis. Different subtypes of gastric cancer had significantly different immune/stromal scores. High stromal scores but not immune scores were significantly associated with short overall survivals of TCGA patients. Nine hub DEGs were identified in PPI analysisThe expression of these hub DEG negatively correlated with the overall survival in the TCGA cohort, which was validated in the GSE15460 cohort. A 9-gene prognostic signature was constructed. The risk factor of patients was calculated by this signature. High-risk patients had significantly shorter overall survival than low-risk patients. ROC analysis showed that the prognostic model accurately identified high-risk individuals within different time frames. We established an effective 9-gene-based risk signature to predict the prognosis of gastric cancer patients, providing guidance for prognostic stratification.
format Online
Article
Text
id pubmed-8652145
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-86521452021-12-09 Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm Yu, Shan Wang, Yan Peng, Ke Lyu, Minzhi Liu, Fenglin Liu, Tianshu Front Cell Dev Biol Cell and Developmental Biology Different subtypes of gastric cancer differentially respond to immune checkpoint inhibitors (ICI). This study aimed to investigate whether the Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm is related to the classification and prognosis of gastric cancer and to establish an ESTIMATE-based gene signature to predict the prognosis for patients. The immune/stromal scores of 388 gastric cancer patients from TCGA were used in this analysis. The upregulated differentially expressed genes (DEGs) in patients with high stromal/immune scores were identified. The immune-related hub DEGs were selected based on protein-protein interaction (PPI) analysis. The prognostic values of the hub DEGs were evaluated in the TCGA dataset and validated in the GSE15460 dataset using the Kaplan-Meier curves. A prognostic signature was built using the hub DEGs by Cox proportional hazards model, and the accuracy was assessed using receiver operating characteristic (ROC) analysis. Different subtypes of gastric cancer had significantly different immune/stromal scores. High stromal scores but not immune scores were significantly associated with short overall survivals of TCGA patients. Nine hub DEGs were identified in PPI analysisThe expression of these hub DEG negatively correlated with the overall survival in the TCGA cohort, which was validated in the GSE15460 cohort. A 9-gene prognostic signature was constructed. The risk factor of patients was calculated by this signature. High-risk patients had significantly shorter overall survival than low-risk patients. ROC analysis showed that the prognostic model accurately identified high-risk individuals within different time frames. We established an effective 9-gene-based risk signature to predict the prognosis of gastric cancer patients, providing guidance for prognostic stratification. Frontiers Media S.A. 2021-11-24 /pmc/articles/PMC8652145/ /pubmed/34900998 http://dx.doi.org/10.3389/fcell.2021.752023 Text en Copyright © 2021 Yu, Wang, Peng, Lyu, Liu and Liu. 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 Cell and Developmental Biology
Yu, Shan
Wang, Yan
Peng, Ke
Lyu, Minzhi
Liu, Fenglin
Liu, Tianshu
Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm
title Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm
title_full Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm
title_fullStr Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm
title_full_unstemmed Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm
title_short Establishment of a Prognostic Signature of Stromal/Immune-Related Genes for Gastric Adenocarcinoma Based on ESTIMATE Algorithm
title_sort establishment of a prognostic signature of stromal/immune-related genes for gastric adenocarcinoma based on estimate algorithm
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8652145/
https://www.ncbi.nlm.nih.gov/pubmed/34900998
http://dx.doi.org/10.3389/fcell.2021.752023
work_keys_str_mv AT yushan establishmentofaprognosticsignatureofstromalimmunerelatedgenesforgastricadenocarcinomabasedonestimatealgorithm
AT wangyan establishmentofaprognosticsignatureofstromalimmunerelatedgenesforgastricadenocarcinomabasedonestimatealgorithm
AT pengke establishmentofaprognosticsignatureofstromalimmunerelatedgenesforgastricadenocarcinomabasedonestimatealgorithm
AT lyuminzhi establishmentofaprognosticsignatureofstromalimmunerelatedgenesforgastricadenocarcinomabasedonestimatealgorithm
AT liufenglin establishmentofaprognosticsignatureofstromalimmunerelatedgenesforgastricadenocarcinomabasedonestimatealgorithm
AT liutianshu establishmentofaprognosticsignatureofstromalimmunerelatedgenesforgastricadenocarcinomabasedonestimatealgorithm