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Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer

Autophagy has been associated with tumor progression, prognosis, and treatment response. However, an autophagy-related model and their clinical significance have not yet been fully elucidated. In the present study, through the integrative analysis of bulk RNA sequencing and single-cell RNA sequencin...

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Autores principales: Tong, Tianying, Zhang, Jie, Zhu, Xiaoqiang, Hui, Pingping, Wang, Zhimin, Wu, Qiong, Tang, Jiayin, Chen, Haoyan, Tian, Xianglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785981/
https://www.ncbi.nlm.nih.gov/pubmed/35083210
http://dx.doi.org/10.3389/fcell.2021.729485
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author Tong, Tianying
Zhang, Jie
Zhu, Xiaoqiang
Hui, Pingping
Wang, Zhimin
Wu, Qiong
Tang, Jiayin
Chen, Haoyan
Tian, Xianglong
author_facet Tong, Tianying
Zhang, Jie
Zhu, Xiaoqiang
Hui, Pingping
Wang, Zhimin
Wu, Qiong
Tang, Jiayin
Chen, Haoyan
Tian, Xianglong
author_sort Tong, Tianying
collection PubMed
description Autophagy has been associated with tumor progression, prognosis, and treatment response. However, an autophagy-related model and their clinical significance have not yet been fully elucidated. In the present study, through the integrative analysis of bulk RNA sequencing and single-cell RNA sequencing, an autophagy-related risk model was identified. The model was capable of distinguishing the worse prognosis of patients with gastric cancer (GC), which was validated in TCGA and two independent Gene Expression Omnibus cohorts utilizing the survival analysis, and was also independent of other clinical covariates evaluated by multivariable Cox regression. The clinical value of this model was further assessed using a receiver operating characteristic (ROC) and nomogram analysis. Investigation of single-cell RNA sequencing uncovered that this model might act as an indicator of the dysfunctional characteristics of T cells in the high-risk group. Moreover, the high-risk group exhibited the lower expression of immune checkpoint markers (PDCD1 and CTLA4) than the low-risk group, which indicated the potential predictive power to the current immunotherapy response in patients with GC. In conclusion, this autophagy-associated risk model may be a useful tool for prognostic evaluation and will facilitate the potential application of this model as an indicator of the predictive immune checkpoint biomarkers.
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spelling pubmed-87859812022-01-25 Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer Tong, Tianying Zhang, Jie Zhu, Xiaoqiang Hui, Pingping Wang, Zhimin Wu, Qiong Tang, Jiayin Chen, Haoyan Tian, Xianglong Front Cell Dev Biol Cell and Developmental Biology Autophagy has been associated with tumor progression, prognosis, and treatment response. However, an autophagy-related model and their clinical significance have not yet been fully elucidated. In the present study, through the integrative analysis of bulk RNA sequencing and single-cell RNA sequencing, an autophagy-related risk model was identified. The model was capable of distinguishing the worse prognosis of patients with gastric cancer (GC), which was validated in TCGA and two independent Gene Expression Omnibus cohorts utilizing the survival analysis, and was also independent of other clinical covariates evaluated by multivariable Cox regression. The clinical value of this model was further assessed using a receiver operating characteristic (ROC) and nomogram analysis. Investigation of single-cell RNA sequencing uncovered that this model might act as an indicator of the dysfunctional characteristics of T cells in the high-risk group. Moreover, the high-risk group exhibited the lower expression of immune checkpoint markers (PDCD1 and CTLA4) than the low-risk group, which indicated the potential predictive power to the current immunotherapy response in patients with GC. In conclusion, this autophagy-associated risk model may be a useful tool for prognostic evaluation and will facilitate the potential application of this model as an indicator of the predictive immune checkpoint biomarkers. Frontiers Media S.A. 2022-01-10 /pmc/articles/PMC8785981/ /pubmed/35083210 http://dx.doi.org/10.3389/fcell.2021.729485 Text en Copyright © 2022 Tong, Zhang, Zhu, Hui, Wang, Wu, Tang, Chen and Tian. 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
Tong, Tianying
Zhang, Jie
Zhu, Xiaoqiang
Hui, Pingping
Wang, Zhimin
Wu, Qiong
Tang, Jiayin
Chen, Haoyan
Tian, Xianglong
Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer
title Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer
title_full Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer
title_fullStr Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer
title_full_unstemmed Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer
title_short Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer
title_sort prognostic autophagy-related model revealed by integrating single-cell rna sequencing data and bulk gene profiles in gastric cancer
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785981/
https://www.ncbi.nlm.nih.gov/pubmed/35083210
http://dx.doi.org/10.3389/fcell.2021.729485
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