Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer
Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify can...
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| Format: | Article |
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Frontiers Media S.A.
2021-06-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.663787/full |
| _version_ | 1819064020970242048 |
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| author | Maryum Nisar Rehan Zafar Paracha Iqra Arshad Sidra Adil Sabaoon Zeb Rumeza Hanif Mehak Rafiq Zamir Hussain |
| author_facet | Maryum Nisar Rehan Zafar Paracha Iqra Arshad Sidra Adil Sabaoon Zeb Rumeza Hanif Mehak Rafiq Zamir Hussain |
| author_sort | Maryum Nisar |
| collection | DOAJ |
| description | Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFβ1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM–receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa. |
| first_indexed | 2024-12-21T15:23:56Z |
| format | Article |
| id | doaj.art-3aeb5cf184244ec6b929bd5e4570c939 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-21T15:23:56Z |
| publishDate | 2021-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-3aeb5cf184244ec6b929bd5e4570c9392022-12-21T18:58:57ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-06-011210.3389/fgene.2021.663787663787Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic CancerMaryum Nisar0Rehan Zafar Paracha1Iqra Arshad2Sidra Adil3Sabaoon Zeb4Rumeza Hanif5Mehak Rafiq6Zamir Hussain7Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, PakistanResearch Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, PakistanResearch Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, PakistanResearch Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, PakistanResearch Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, PakistanAtta-ur-Rahman School of Applied Biosciences-ASAB, National University of Sciences and Technology (NUST), Islamabad, PakistanResearch Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, PakistanResearch Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, PakistanPancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFβ1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM–receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa.https://www.frontiersin.org/articles/10.3389/fgene.2021.663787/fullpancreatic cancerco-expression networkbiomarkertherapeutic targetdifferential expressionTCGA |
| spellingShingle | Maryum Nisar Rehan Zafar Paracha Iqra Arshad Sidra Adil Sabaoon Zeb Rumeza Hanif Mehak Rafiq Zamir Hussain Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer Frontiers in Genetics pancreatic cancer co-expression network biomarker therapeutic target differential expression TCGA |
| title | Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer |
| title_full | Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer |
| title_fullStr | Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer |
| title_full_unstemmed | Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer |
| title_short | Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer |
| title_sort | integrated analysis of microarray and rna seq data for the identification of hub genes and networks involved in the pancreatic cancer |
| topic | pancreatic cancer co-expression network biomarker therapeutic target differential expression TCGA |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.663787/full |
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