Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis
Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular m...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2023-07-01
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| Series: | Bioinformatics and Biology Insights |
| Online Access: | https://doi.org/10.1177/11779322231186719 |
| _version_ | 1797771616801783808 |
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| author | Muttanagouda Giriyappagoudar MD Basavaraj Vastrad PhD Rajeshwari Horakeri PhD Chanabasayya Vastrad PhD |
| author_facet | Muttanagouda Giriyappagoudar MD Basavaraj Vastrad PhD Rajeshwari Horakeri PhD Chanabasayya Vastrad PhD |
| author_sort | Muttanagouda Giriyappagoudar MD |
| collection | DOAJ |
| description | Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis. Methods: To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis. Results: A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results. Conclusions: On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation. |
| first_indexed | 2024-03-12T21:40:10Z |
| format | Article |
| id | doaj.art-227e02dc1dea493f810b7dfd596ad077 |
| institution | Directory Open Access Journal |
| issn | 1177-9322 |
| language | English |
| last_indexed | 2024-03-12T21:40:10Z |
| publishDate | 2023-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Bioinformatics and Biology Insights |
| spelling | doaj.art-227e02dc1dea493f810b7dfd596ad0772023-07-27T01:07:47ZengSAGE PublishingBioinformatics and Biology Insights1177-93222023-07-011710.1177/11779322231186719Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data AnalysisMuttanagouda Giriyappagoudar MD0Basavaraj Vastrad PhD1Rajeshwari Horakeri PhD2Chanabasayya Vastrad PhD3Department of Radiation Oncology, Karnataka Institute of Medical Sciences (KIMS), Hubballi, IndiaDepartment of Pharmaceutical Chemistry, K.L.E. Society’s College of Pharmacy, Gadag, IndiaDepartment of Computer Science, Government First Grade College, Hubballi, IndiaBiostatistics and Bioinformatics, Chanabasava Nilaya, Dharwad, IndiaBackground: Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis. Methods: To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis. Results: A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results. Conclusions: On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation.https://doi.org/10.1177/11779322231186719 |
| spellingShingle | Muttanagouda Giriyappagoudar MD Basavaraj Vastrad PhD Rajeshwari Horakeri PhD Chanabasayya Vastrad PhD Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis Bioinformatics and Biology Insights |
| title | Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis |
| title_full | Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis |
| title_fullStr | Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis |
| title_full_unstemmed | Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis |
| title_short | Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis |
| title_sort | identification and interaction analysis of molecular markers in pancreatic ductal adenocarcinoma by bioinformatics and next generation sequencing data analysis |
| url | https://doi.org/10.1177/11779322231186719 |
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