Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer
Background: Gastric cancer (GC) is aggressive cancer with a poor prognosis. Previously bulk transcriptome analysis was utilized to identify key genes correlated with the development, progression and prognosis of GC. However, due to the complexity of the genetic mutations, there is still an urgent ne...
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| Format: | Article |
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Frontiers Media S.A.
2022-01-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2021.801687/full |
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| author | Tingna Chen Tingna Chen Tingna Chen Qiuming He Qiuming He Qiuming He Zhenxian Xiang Zhenxian Xiang Zhenxian Xiang Rongzhang Dou Rongzhang Dou Rongzhang Dou Bin Xiong Bin Xiong Bin Xiong |
| author_facet | Tingna Chen Tingna Chen Tingna Chen Qiuming He Qiuming He Qiuming He Zhenxian Xiang Zhenxian Xiang Zhenxian Xiang Rongzhang Dou Rongzhang Dou Rongzhang Dou Bin Xiong Bin Xiong Bin Xiong |
| author_sort | Tingna Chen |
| collection | DOAJ |
| description | Background: Gastric cancer (GC) is aggressive cancer with a poor prognosis. Previously bulk transcriptome analysis was utilized to identify key genes correlated with the development, progression and prognosis of GC. However, due to the complexity of the genetic mutations, there is still an urgent need to recognize core genes in the regulatory network of GC.Methods: Gene expression profiles (GSE66229) were retrieved from the GEO database. Weighted correlation network analysis (WGCNA) was employed to identify gene modules mostly correlated with GC carcinogenesis. R package ‘DiffCorr’ was applied to identify differentially correlated gene pairs in tumor and normal tissues. Cytoscape was adopted to construct and visualize the gene regulatory network.Results: A total of 15 modules were detected in WGCNA analysis, among which three modules were significantly correlated with GC. Then genes in these modules were analyzed separately by “DiffCorr”. Multiple differentially correlated gene pairs were recognized and the network was visualized by the software Cytoscape. Moreover, GEMIN5 and PFDN2, which were rarely discussed in GC, were identified as key genes in the regulatory network and the differential expression was validated by real-time qPCR, WB and IHC in cell lines and GC patient tissues.Conclusions: Our research has shed light on the carcinogenesis mechanism by revealing differentially correlated gene pairs during transition from normal to tumor. We believe the application of this network-based algorithm holds great potential in inferring relationships and detecting candidate biomarkers. |
| first_indexed | 2024-04-11T17:15:30Z |
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| issn | 2296-634X |
| language | English |
| last_indexed | 2024-04-11T17:15:30Z |
| publishDate | 2022-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj.art-247e63ec7be541c49b13878461277d292022-12-22T04:12:41ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2022-01-01910.3389/fcell.2021.801687801687Identification and Validation of Key Genes of Differential Correlations in Gastric CancerTingna Chen0Tingna Chen1Tingna Chen2Qiuming He3Qiuming He4Qiuming He5Zhenxian Xiang6Zhenxian Xiang7Zhenxian Xiang8Rongzhang Dou9Rongzhang Dou10Rongzhang Dou11Bin Xiong12Bin Xiong13Bin Xiong14Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, ChinaHubei Key Laboratory of Tumor Biological Behaviors, Wuhan, ChinaHubei Cancer Clinical Study Center, Wuhan, ChinaDepartment of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, ChinaHubei Key Laboratory of Tumor Biological Behaviors, Wuhan, ChinaHubei Cancer Clinical Study Center, Wuhan, ChinaDepartment of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, ChinaHubei Key Laboratory of Tumor Biological Behaviors, Wuhan, ChinaHubei Cancer Clinical Study Center, Wuhan, ChinaDepartment of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, ChinaHubei Key Laboratory of Tumor Biological Behaviors, Wuhan, ChinaHubei Cancer Clinical Study Center, Wuhan, ChinaDepartment of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, ChinaHubei Key Laboratory of Tumor Biological Behaviors, Wuhan, ChinaHubei Cancer Clinical Study Center, Wuhan, ChinaBackground: Gastric cancer (GC) is aggressive cancer with a poor prognosis. Previously bulk transcriptome analysis was utilized to identify key genes correlated with the development, progression and prognosis of GC. However, due to the complexity of the genetic mutations, there is still an urgent need to recognize core genes in the regulatory network of GC.Methods: Gene expression profiles (GSE66229) were retrieved from the GEO database. Weighted correlation network analysis (WGCNA) was employed to identify gene modules mostly correlated with GC carcinogenesis. R package ‘DiffCorr’ was applied to identify differentially correlated gene pairs in tumor and normal tissues. Cytoscape was adopted to construct and visualize the gene regulatory network.Results: A total of 15 modules were detected in WGCNA analysis, among which three modules were significantly correlated with GC. Then genes in these modules were analyzed separately by “DiffCorr”. Multiple differentially correlated gene pairs were recognized and the network was visualized by the software Cytoscape. Moreover, GEMIN5 and PFDN2, which were rarely discussed in GC, were identified as key genes in the regulatory network and the differential expression was validated by real-time qPCR, WB and IHC in cell lines and GC patient tissues.Conclusions: Our research has shed light on the carcinogenesis mechanism by revealing differentially correlated gene pairs during transition from normal to tumor. We believe the application of this network-based algorithm holds great potential in inferring relationships and detecting candidate biomarkers.https://www.frontiersin.org/articles/10.3389/fcell.2021.801687/fullgastric cancerdifferential correlationswitching mechanismWGCNAgene network |
| spellingShingle | Tingna Chen Tingna Chen Tingna Chen Qiuming He Qiuming He Qiuming He Zhenxian Xiang Zhenxian Xiang Zhenxian Xiang Rongzhang Dou Rongzhang Dou Rongzhang Dou Bin Xiong Bin Xiong Bin Xiong Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer Frontiers in Cell and Developmental Biology gastric cancer differential correlation switching mechanism WGCNA gene network |
| title | Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer |
| title_full | Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer |
| title_fullStr | Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer |
| title_full_unstemmed | Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer |
| title_short | Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer |
| title_sort | identification and validation of key genes of differential correlations in gastric cancer |
| topic | gastric cancer differential correlation switching mechanism WGCNA gene network |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2021.801687/full |
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