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Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma

BACKGROUND: The mitochondrion and its associated genes were heavily implicated in developing and therapy tumors as the primary cellular organelle in charge of metabolic reprogramming and ferroptosis. Our work focuses on discovering new potential targets while analyzing the multi-omics data of mitoch...

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Autores principales: Jin, Xing, Zhang, Huan, Sui, Qihai, Li, Ming, Liang, Jiaqi, Hu, Zhengyang, Cheng, Ye, Zheng, Yuansheng, Chen, Zhencong, Lin, Miao, Wang, Hao, Zhan, Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732315/
https://www.ncbi.nlm.nih.gov/pubmed/36506395
http://dx.doi.org/10.1016/j.heliyon.2022.e11966
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author Jin, Xing
Zhang, Huan
Sui, Qihai
Li, Ming
Liang, Jiaqi
Hu, Zhengyang
Cheng, Ye
Zheng, Yuansheng
Chen, Zhencong
Lin, Miao
Wang, Hao
Zhan, Cheng
author_facet Jin, Xing
Zhang, Huan
Sui, Qihai
Li, Ming
Liang, Jiaqi
Hu, Zhengyang
Cheng, Ye
Zheng, Yuansheng
Chen, Zhencong
Lin, Miao
Wang, Hao
Zhan, Cheng
author_sort Jin, Xing
collection PubMed
description BACKGROUND: The mitochondrion and its associated genes were heavily implicated in developing and therapy tumors as the primary cellular organelle in charge of metabolic reprogramming and ferroptosis. Our work focuses on discovering new potential targets while analyzing the multi-omics data of mitochondria-related genes in lung adenocarcinoma (LUAD). METHODS: The Cancer Genome Atlas (TCGA) database provided multi-omics data for LUAD patients. Based on the expression profile of the genes associated with mitochondria, the patients were grouped by the unsupervised clustering method. R was used to explore the differential expressed protein-code gene, miRNA, and lncRNA, as well as their enriched functions and ceRNA networks. Additionally, the discrepancy between immune infiltration and genetic variation was comprehensively characterized. Our clinical samples and in vitro experiments investigated the hub gene determined by LASSO and batch analysis. RESULTS: Two clusters are distinguished using unsupervised consensus clustering based on mitochondrial heterogeneity. The integrated analysis emphasized that patients in cluster B had a worse prognosis, higher mutation frequencies, and less immune cell infiltration. The hub genes DARS2 and COX5B are identified by further analysis using LASSO penalization. In vitro experiments indicated that DARS2 and COX5B knockdown inhibited tumor cell proliferation. The specimen of our hospital cohort conducted the immunohistochemistry analysis and validated that DARS2 and COX5B's expression was significantly higher in the tumor than in adjacent normal tissue and correlated to LUAD patients' prognosis. CONCLUSION: Our observations implied that LUAD patients' tumors had distinct mitochondrial function heterogeneity with different clinical and molecular characteristics. DARS2 and COX5B might be critical genes involved in mitochondrial alterations and potential therapeutic targets.
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spelling pubmed-97323152022-12-10 Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma Jin, Xing Zhang, Huan Sui, Qihai Li, Ming Liang, Jiaqi Hu, Zhengyang Cheng, Ye Zheng, Yuansheng Chen, Zhencong Lin, Miao Wang, Hao Zhan, Cheng Heliyon Research Article BACKGROUND: The mitochondrion and its associated genes were heavily implicated in developing and therapy tumors as the primary cellular organelle in charge of metabolic reprogramming and ferroptosis. Our work focuses on discovering new potential targets while analyzing the multi-omics data of mitochondria-related genes in lung adenocarcinoma (LUAD). METHODS: The Cancer Genome Atlas (TCGA) database provided multi-omics data for LUAD patients. Based on the expression profile of the genes associated with mitochondria, the patients were grouped by the unsupervised clustering method. R was used to explore the differential expressed protein-code gene, miRNA, and lncRNA, as well as their enriched functions and ceRNA networks. Additionally, the discrepancy between immune infiltration and genetic variation was comprehensively characterized. Our clinical samples and in vitro experiments investigated the hub gene determined by LASSO and batch analysis. RESULTS: Two clusters are distinguished using unsupervised consensus clustering based on mitochondrial heterogeneity. The integrated analysis emphasized that patients in cluster B had a worse prognosis, higher mutation frequencies, and less immune cell infiltration. The hub genes DARS2 and COX5B are identified by further analysis using LASSO penalization. In vitro experiments indicated that DARS2 and COX5B knockdown inhibited tumor cell proliferation. The specimen of our hospital cohort conducted the immunohistochemistry analysis and validated that DARS2 and COX5B's expression was significantly higher in the tumor than in adjacent normal tissue and correlated to LUAD patients' prognosis. CONCLUSION: Our observations implied that LUAD patients' tumors had distinct mitochondrial function heterogeneity with different clinical and molecular characteristics. DARS2 and COX5B might be critical genes involved in mitochondrial alterations and potential therapeutic targets. Elsevier 2022-12-01 /pmc/articles/PMC9732315/ /pubmed/36506395 http://dx.doi.org/10.1016/j.heliyon.2022.e11966 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Jin, Xing
Zhang, Huan
Sui, Qihai
Li, Ming
Liang, Jiaqi
Hu, Zhengyang
Cheng, Ye
Zheng, Yuansheng
Chen, Zhencong
Lin, Miao
Wang, Hao
Zhan, Cheng
Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma
title Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma
title_full Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma
title_fullStr Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma
title_full_unstemmed Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma
title_short Identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma
title_sort identification and validation of the mitochondrial function related hub genes by unsupervised machine learning and multi-omics analyses in lung adenocarcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732315/
https://www.ncbi.nlm.nih.gov/pubmed/36506395
http://dx.doi.org/10.1016/j.heliyon.2022.e11966
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