Cargando…
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...
Autores principales: | , , , , , , , , , |
---|---|
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 |
_version_ | 1784585623844159488 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8525106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT sunzhuang keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT wangxiaohui keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT wangjingyun keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT wangjing keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT liuxiao keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT huangrunda keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT chenchunyan keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT dengmeiling keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT wanghanyu keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma AT hanfei keyradioresistanceregulationmodelsandmarkergenesidentifiedbyintegratedtranscriptomeanalysisinnasopharyngealcarcinoma |