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A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes

Metabolic reprogramming is a hallmark of malignancy. Understanding the characteristics of metabolic reprogramming in esophageal squamous cell carcinoma (ESCC) helps uncover novel targets for cancer progression. In this study, 880 metabolism-related genes were identified from microarray data and then...

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Autores principales: Liu, Yu, Wang, Liyu, Fang, Lingling, Liu, Hengchang, Tian, He, Zheng, Yujia, Fan, Tao, Li, Chunxiang, He, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573269/
https://www.ncbi.nlm.nih.gov/pubmed/34760709
http://dx.doi.org/10.3389/fonc.2021.772145
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author Liu, Yu
Wang, Liyu
Fang, Lingling
Liu, Hengchang
Tian, He
Zheng, Yujia
Fan, Tao
Li, Chunxiang
He, Jie
author_facet Liu, Yu
Wang, Liyu
Fang, Lingling
Liu, Hengchang
Tian, He
Zheng, Yujia
Fan, Tao
Li, Chunxiang
He, Jie
author_sort Liu, Yu
collection PubMed
description Metabolic reprogramming is a hallmark of malignancy. Understanding the characteristics of metabolic reprogramming in esophageal squamous cell carcinoma (ESCC) helps uncover novel targets for cancer progression. In this study, 880 metabolism-related genes were identified from microarray data and then filtered to divide patients into two subgroups using consensus clustering, which exhibits significantly different overall survival. After a differential analysis between two subtypes, 3 genes were screened out to construct a two subtypes decision model on the training cohort (GSE53624), defined as high-risk and low-risk subtypes. These risk models were then verified in two public databases (GSE53622 and TCGA-ESCC), an independent cohort of 49 ESCC patients by RT-qPCR and an external cohort of 95 ESCC patients by immunohistochemistry analysis (IHC). Furthermore, the immune cell infiltration of regulatory T cells (Tregs) and plasma cells showed a significant difference between the high and low-risk subtypes in the IHC experiment with 119 ESCC patients. In conclusion, our study indicated that three metabolism-related prognostic genes could stratify patients into subgroups and were associated with immune infiltration, clinical features and clinical outcomes.
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spelling pubmed-85732692021-11-09 A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes Liu, Yu Wang, Liyu Fang, Lingling Liu, Hengchang Tian, He Zheng, Yujia Fan, Tao Li, Chunxiang He, Jie Front Oncol Oncology Metabolic reprogramming is a hallmark of malignancy. Understanding the characteristics of metabolic reprogramming in esophageal squamous cell carcinoma (ESCC) helps uncover novel targets for cancer progression. In this study, 880 metabolism-related genes were identified from microarray data and then filtered to divide patients into two subgroups using consensus clustering, which exhibits significantly different overall survival. After a differential analysis between two subtypes, 3 genes were screened out to construct a two subtypes decision model on the training cohort (GSE53624), defined as high-risk and low-risk subtypes. These risk models were then verified in two public databases (GSE53622 and TCGA-ESCC), an independent cohort of 49 ESCC patients by RT-qPCR and an external cohort of 95 ESCC patients by immunohistochemistry analysis (IHC). Furthermore, the immune cell infiltration of regulatory T cells (Tregs) and plasma cells showed a significant difference between the high and low-risk subtypes in the IHC experiment with 119 ESCC patients. In conclusion, our study indicated that three metabolism-related prognostic genes could stratify patients into subgroups and were associated with immune infiltration, clinical features and clinical outcomes. Frontiers Media S.A. 2021-10-25 /pmc/articles/PMC8573269/ /pubmed/34760709 http://dx.doi.org/10.3389/fonc.2021.772145 Text en Copyright © 2021 Liu, Wang, Fang, Liu, Tian, Zheng, Fan, Li and He 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 Oncology
Liu, Yu
Wang, Liyu
Fang, Lingling
Liu, Hengchang
Tian, He
Zheng, Yujia
Fan, Tao
Li, Chunxiang
He, Jie
A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes
title A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes
title_full A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes
title_fullStr A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes
title_full_unstemmed A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes
title_short A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes
title_sort multi-center validated subtyping model of esophageal cancer based on three metabolism-related genes
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573269/
https://www.ncbi.nlm.nih.gov/pubmed/34760709
http://dx.doi.org/10.3389/fonc.2021.772145
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