Cargando…

Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis

Objective: Immune cells infiltrating has been proved to be associated with prognosis in gastric cancer (GC) by studies. This study aims to explore the prognosis value of infiltrating immune cells in gastric cancer. Methods: In our study, the CIBERSORT algorithm was used to calculate the fraction of...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Wenjie, Li, Mengting, Wang, Haizhou, Peng, Yanan, Dong, Shouquan, Lu, Yuanyuan, Wang, Fan, Xu, Fei, Liu, Lan, Zhao, Qiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797666/
https://www.ncbi.nlm.nih.gov/pubmed/33442396
http://dx.doi.org/10.7150/jca.51079
_version_ 1783634919536197632
author Li, Wenjie
Li, Mengting
Wang, Haizhou
Peng, Yanan
Dong, Shouquan
Lu, Yuanyuan
Wang, Fan
Xu, Fei
Liu, Lan
Zhao, Qiu
author_facet Li, Wenjie
Li, Mengting
Wang, Haizhou
Peng, Yanan
Dong, Shouquan
Lu, Yuanyuan
Wang, Fan
Xu, Fei
Liu, Lan
Zhao, Qiu
author_sort Li, Wenjie
collection PubMed
description Objective: Immune cells infiltrating has been proved to be associated with prognosis in gastric cancer (GC) by studies. This study aims to explore the prognosis value of infiltrating immune cells in gastric cancer. Methods: In our study, the CIBERSORT algorithm was used to calculate the fraction of 22 tumor-infiltrating immune cells (TIIC) in 100 normal and 300 tumor samples from the GEO cohort and 30 normal and 344 tumor samples from the TCGA cohort. Univariate and multivariate Cox regression were used to construct an immune risk score model. Multivariate cox regression was also used to validate whether our risk score model could predict prognosis in GC independently. Furthermore, the model was validated in different patient subgroups to test its independence. P<0.05 was considered statistically significant. Results: The results showed that the fraction of 3 immune cells increased in tumor tissues compared with normal tissues in both the GEO and TCGA cohort. Univariate cox regression analysis showed four cells significantly correlated with survival rate in GC (P<0.05). The immune risk score model was constructed based on the four cells through multivariate cox regression and further validated. The KM survival curve suggested that patients with high risk had poor prognosis than patients with low risk (P<0.05). ROC curve indicated the model was reliable (AUC= 0.67 in the GEO cohort, AUC = 0.65 in the TCGA cohort). Furthermore, multivariate Cox regression showed the model was an independent factor for overall survival predicting in GC (hazard ratio (HR) = 2.35, 95% confidence interval (CI) = 1.63~3.40 in the GEO cohort, HR = 2.87, 95% CI = 1.94~4.25 in the TCGA cohort). Finally, we validated the model in patient subgroups by the KM survival curve. Conclusion: In summary, tumor-infiltrating immune cells play an essential role in GC progression and affect the outcome of GC patients. The immune risk score can predict overall survival for GC independently, and high immune risk score is associated with poor prognosis.
format Online
Article
Text
id pubmed-7797666
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Ivyspring International Publisher
record_format MEDLINE/PubMed
spelling pubmed-77976662021-01-12 Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis Li, Wenjie Li, Mengting Wang, Haizhou Peng, Yanan Dong, Shouquan Lu, Yuanyuan Wang, Fan Xu, Fei Liu, Lan Zhao, Qiu J Cancer Research Paper Objective: Immune cells infiltrating has been proved to be associated with prognosis in gastric cancer (GC) by studies. This study aims to explore the prognosis value of infiltrating immune cells in gastric cancer. Methods: In our study, the CIBERSORT algorithm was used to calculate the fraction of 22 tumor-infiltrating immune cells (TIIC) in 100 normal and 300 tumor samples from the GEO cohort and 30 normal and 344 tumor samples from the TCGA cohort. Univariate and multivariate Cox regression were used to construct an immune risk score model. Multivariate cox regression was also used to validate whether our risk score model could predict prognosis in GC independently. Furthermore, the model was validated in different patient subgroups to test its independence. P<0.05 was considered statistically significant. Results: The results showed that the fraction of 3 immune cells increased in tumor tissues compared with normal tissues in both the GEO and TCGA cohort. Univariate cox regression analysis showed four cells significantly correlated with survival rate in GC (P<0.05). The immune risk score model was constructed based on the four cells through multivariate cox regression and further validated. The KM survival curve suggested that patients with high risk had poor prognosis than patients with low risk (P<0.05). ROC curve indicated the model was reliable (AUC= 0.67 in the GEO cohort, AUC = 0.65 in the TCGA cohort). Furthermore, multivariate Cox regression showed the model was an independent factor for overall survival predicting in GC (hazard ratio (HR) = 2.35, 95% confidence interval (CI) = 1.63~3.40 in the GEO cohort, HR = 2.87, 95% CI = 1.94~4.25 in the TCGA cohort). Finally, we validated the model in patient subgroups by the KM survival curve. Conclusion: In summary, tumor-infiltrating immune cells play an essential role in GC progression and affect the outcome of GC patients. The immune risk score can predict overall survival for GC independently, and high immune risk score is associated with poor prognosis. Ivyspring International Publisher 2021-01-01 /pmc/articles/PMC7797666/ /pubmed/33442396 http://dx.doi.org/10.7150/jca.51079 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Li, Wenjie
Li, Mengting
Wang, Haizhou
Peng, Yanan
Dong, Shouquan
Lu, Yuanyuan
Wang, Fan
Xu, Fei
Liu, Lan
Zhao, Qiu
Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis
title Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis
title_full Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis
title_fullStr Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis
title_full_unstemmed Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis
title_short Infiltrating Immune Cells in Gastric Cancer: A Novel Predicting Model for Prognosis
title_sort infiltrating immune cells in gastric cancer: a novel predicting model for prognosis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797666/
https://www.ncbi.nlm.nih.gov/pubmed/33442396
http://dx.doi.org/10.7150/jca.51079
work_keys_str_mv AT liwenjie infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT limengting infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT wanghaizhou infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT pengyanan infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT dongshouquan infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT luyuanyuan infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT wangfan infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT xufei infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT liulan infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis
AT zhaoqiu infiltratingimmunecellsingastriccanceranovelpredictingmodelforprognosis