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Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is the third leading cause of cancer-related deaths and the fifth most prevalent malignancy worldwide. Mitochondrial respiratory chain complexes play a crucial role in STAD pathogenesis. However, how mitochondrial respiratory chain complex genes (MRCCGs) affect the prog...

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Autores principales: Yang, Jing, Jin, Feifan, Li, Huanjuan, Shen, Yuhuan, Shi, Weilin, Wang, Lina, Zhong, Lei, Wu, Gongqiang, Wu, Qiaoliang, Li, Yanchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105960/
https://www.ncbi.nlm.nih.gov/pubmed/37062830
http://dx.doi.org/10.1186/s12935-023-02913-x
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author Yang, Jing
Jin, Feifan
Li, Huanjuan
Shen, Yuhuan
Shi, Weilin
Wang, Lina
Zhong, Lei
Wu, Gongqiang
Wu, Qiaoliang
Li, Yanchun
author_facet Yang, Jing
Jin, Feifan
Li, Huanjuan
Shen, Yuhuan
Shi, Weilin
Wang, Lina
Zhong, Lei
Wu, Gongqiang
Wu, Qiaoliang
Li, Yanchun
author_sort Yang, Jing
collection PubMed
description Stomach adenocarcinoma (STAD) is the third leading cause of cancer-related deaths and the fifth most prevalent malignancy worldwide. Mitochondrial respiratory chain complexes play a crucial role in STAD pathogenesis. However, how mitochondrial respiratory chain complex genes (MRCCGs) affect the prognosis and tumor microenvironment in STAD remains unclear. In this study, we systematically analyzed genetic alterations and copy number variations of different expression densities of MRCCGs, based on 806 samples from two independent STAD cohorts. Then we employed the unsupervised clustering method to classify the samples into three expression patterns based on the prognostic MRCCG expressions, and found that they were involved in different biological pathways and correlated with the clinicopathological characteristics, immune cell infiltration, and prognosis of STAD. Subsequently, we conducted a univariate Cox regression analysis to identify the prognostic value of 1175 subtype-related differentially expressed genes (DEGs) and screened out 555 prognostic-related genes. Principal component analysis was performed and developed the MG score system to quantify MRCCG patterns of STAD. The prognostic significance of MG Score was validated in three cohorts. The low MG score group, characterized by increased microsatellite instability-high (MSI-H), tumor mutation burden (TMB), PD-L1 expression, had a better prognosis. Interestingly, we demonstrated MRCCG patterns score could predict the sensitivity to ferroptosis inducing therapy. Our comprehensive analysis of MRCCGs in STAD demonstrated their potential roles in the tumor-immune-stromal microenvironment, clinicopathological features, and prognosis. Our findings highlight that MRCCGs may provide a new understanding of immunotherapy strategies for gastric cancer and provide a new perspective on the development of personalized immune therapeutic strategies for patients with STAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-023-02913-x.
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spelling pubmed-101059602023-04-17 Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma Yang, Jing Jin, Feifan Li, Huanjuan Shen, Yuhuan Shi, Weilin Wang, Lina Zhong, Lei Wu, Gongqiang Wu, Qiaoliang Li, Yanchun Cancer Cell Int Research Stomach adenocarcinoma (STAD) is the third leading cause of cancer-related deaths and the fifth most prevalent malignancy worldwide. Mitochondrial respiratory chain complexes play a crucial role in STAD pathogenesis. However, how mitochondrial respiratory chain complex genes (MRCCGs) affect the prognosis and tumor microenvironment in STAD remains unclear. In this study, we systematically analyzed genetic alterations and copy number variations of different expression densities of MRCCGs, based on 806 samples from two independent STAD cohorts. Then we employed the unsupervised clustering method to classify the samples into three expression patterns based on the prognostic MRCCG expressions, and found that they were involved in different biological pathways and correlated with the clinicopathological characteristics, immune cell infiltration, and prognosis of STAD. Subsequently, we conducted a univariate Cox regression analysis to identify the prognostic value of 1175 subtype-related differentially expressed genes (DEGs) and screened out 555 prognostic-related genes. Principal component analysis was performed and developed the MG score system to quantify MRCCG patterns of STAD. The prognostic significance of MG Score was validated in three cohorts. The low MG score group, characterized by increased microsatellite instability-high (MSI-H), tumor mutation burden (TMB), PD-L1 expression, had a better prognosis. Interestingly, we demonstrated MRCCG patterns score could predict the sensitivity to ferroptosis inducing therapy. Our comprehensive analysis of MRCCGs in STAD demonstrated their potential roles in the tumor-immune-stromal microenvironment, clinicopathological features, and prognosis. Our findings highlight that MRCCGs may provide a new understanding of immunotherapy strategies for gastric cancer and provide a new perspective on the development of personalized immune therapeutic strategies for patients with STAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-023-02913-x. BioMed Central 2023-04-16 /pmc/articles/PMC10105960/ /pubmed/37062830 http://dx.doi.org/10.1186/s12935-023-02913-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yang, Jing
Jin, Feifan
Li, Huanjuan
Shen, Yuhuan
Shi, Weilin
Wang, Lina
Zhong, Lei
Wu, Gongqiang
Wu, Qiaoliang
Li, Yanchun
Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma
title Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma
title_full Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma
title_fullStr Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma
title_full_unstemmed Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma
title_short Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma
title_sort identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105960/
https://www.ncbi.nlm.nih.gov/pubmed/37062830
http://dx.doi.org/10.1186/s12935-023-02913-x
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