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Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignancy that is endemic to China and Southeast Asia. Radiotherapy is the usual treatment, however, radioresistance remains a major reason for failure. This study aimed to find key radioresistance regulation models and marker genes of NPC and clarify the mechani...

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Autores principales: Sun, Zhuang, Wang, Xiaohui, Wang, Jingyun, Wang, Jing, Liu, Xiao, Huang, Runda, Chen, Chunyan, Deng, Meiling, Wang, Hanyu, Han, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525106/
https://www.ncbi.nlm.nih.gov/pubmed/34432380
http://dx.doi.org/10.1002/cam4.4228
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author Sun, Zhuang
Wang, Xiaohui
Wang, Jingyun
Wang, Jing
Liu, Xiao
Huang, Runda
Chen, Chunyan
Deng, Meiling
Wang, Hanyu
Han, Fei
author_facet Sun, Zhuang
Wang, Xiaohui
Wang, Jingyun
Wang, Jing
Liu, Xiao
Huang, Runda
Chen, Chunyan
Deng, Meiling
Wang, Hanyu
Han, Fei
author_sort Sun, Zhuang
collection PubMed
description Nasopharyngeal carcinoma (NPC) is a malignancy that is endemic to China and Southeast Asia. Radiotherapy is the usual treatment, however, radioresistance remains a major reason for failure. This study aimed to find key radioresistance regulation models and marker genes of NPC and clarify the mechanism of NPC radioresistance by RNA sequencing and bioinformatics analysis of the differences in gene expression profiles between radioresistant and radiosensitive NPC tissues. A total of 21 NPC biopsy specimens with different radiosensitivity were analyzed by RNA sequencing. Differentially expressed genes in RNA sequencing data were identified using R software. The differentially expressed gene data derived from RNA sequencing as well as prior knowledge in the form of pathway databases were integrated to find sub‐networks of related genes. The data of RNA sequencing with the GSE48501 data from the GEO database were combined to further search for more reliable genes associated with radioresistance of NPC. Survival analyses using the Kaplan–Meier method based on the expression of the genes were conducted to facilitate the understanding of the clinical significance of the differentially expressed genes. RT‐qPCR was performed to validate the expression levels of the differentially expressed genes. We identified 1182 differentially expressed genes between radioresistant and radiosensitive NPC tissue samples. Compared to the radiosensitive group, 22 genes were significantly upregulated and 1160 genes were downregulated in the radioresistant group. In addition, 10 major NPC radiation resistance network models were identified through integration analysis with known NPC radiation resistance‐associated genes and mechanisms. Furthermore, we identified three core genes, DOCK4, MCM9, and POPDC3 among 12 common downregulated genes in the two datasets, which were validated by RT‐qPCR. The findings of this study provide new clues for clarifying the mechanism of NPC radioresistance, and further experimental studies of these core genes are warranted.
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spelling pubmed-85251062021-10-26 Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma Sun, Zhuang Wang, Xiaohui Wang, Jingyun Wang, Jing Liu, Xiao Huang, Runda Chen, Chunyan Deng, Meiling Wang, Hanyu Han, Fei Cancer Med Bioinformatics Nasopharyngeal carcinoma (NPC) is a malignancy that is endemic to China and Southeast Asia. Radiotherapy is the usual treatment, however, radioresistance remains a major reason for failure. This study aimed to find key radioresistance regulation models and marker genes of NPC and clarify the mechanism of NPC radioresistance by RNA sequencing and bioinformatics analysis of the differences in gene expression profiles between radioresistant and radiosensitive NPC tissues. A total of 21 NPC biopsy specimens with different radiosensitivity were analyzed by RNA sequencing. Differentially expressed genes in RNA sequencing data were identified using R software. The differentially expressed gene data derived from RNA sequencing as well as prior knowledge in the form of pathway databases were integrated to find sub‐networks of related genes. The data of RNA sequencing with the GSE48501 data from the GEO database were combined to further search for more reliable genes associated with radioresistance of NPC. Survival analyses using the Kaplan–Meier method based on the expression of the genes were conducted to facilitate the understanding of the clinical significance of the differentially expressed genes. RT‐qPCR was performed to validate the expression levels of the differentially expressed genes. We identified 1182 differentially expressed genes between radioresistant and radiosensitive NPC tissue samples. Compared to the radiosensitive group, 22 genes were significantly upregulated and 1160 genes were downregulated in the radioresistant group. In addition, 10 major NPC radiation resistance network models were identified through integration analysis with known NPC radiation resistance‐associated genes and mechanisms. Furthermore, we identified three core genes, DOCK4, MCM9, and POPDC3 among 12 common downregulated genes in the two datasets, which were validated by RT‐qPCR. The findings of this study provide new clues for clarifying the mechanism of NPC radioresistance, and further experimental studies of these core genes are warranted. John Wiley and Sons Inc. 2021-08-25 /pmc/articles/PMC8525106/ /pubmed/34432380 http://dx.doi.org/10.1002/cam4.4228 Text en © 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Bioinformatics
Sun, Zhuang
Wang, Xiaohui
Wang, Jingyun
Wang, Jing
Liu, Xiao
Huang, Runda
Chen, Chunyan
Deng, Meiling
Wang, Hanyu
Han, Fei
Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma
title Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma
title_full Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma
title_fullStr Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma
title_full_unstemmed Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma
title_short Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma
title_sort key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525106/
https://www.ncbi.nlm.nih.gov/pubmed/34432380
http://dx.doi.org/10.1002/cam4.4228
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