Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis
Abstract Aim Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-12-01
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| Series: | BMC Medical Genomics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12920-023-01720-7 |
| _version_ | 1797413708872286208 |
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| author | Fatemeh Abdolahi Ali Shahraki Roghayeh Sheervalilou Sedigheh Sadat Mortazavi |
| author_facet | Fatemeh Abdolahi Ali Shahraki Roghayeh Sheervalilou Sedigheh Sadat Mortazavi |
| author_sort | Fatemeh Abdolahi |
| collection | DOAJ |
| description | Abstract Aim Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgently needed. Methods GSE54129 and GSE26942 datasets were downloaded from Gene Expression Omnibus (GEO) database to detect differentially expressed genes (DEGs). Then, gene set enrichment analyses and protein-protein interactions were investigated. Afterward, ten hub genes were identified from the constructed network of DEGs. Then, the expression of hub genes in GC was validated. Performing survival analysis, the prognostic value of each hub gene in GC samples was investigated. Finally, the databases were used to predict microRNAs that could regulate the hub genes. Eventually, top miRNAs with more interactions with the list of hub genes were introduced. Results In total, 203 overlapping DEGs were identified between both datasets. The main enriched KEGG pathway was “Protein digestion and absorption.” The most significant identified GO terms included “primary alcohol metabolic process,” “basal part of cell,” and “extracellular matrix structural constituent conferring tensile strength.” Identified hub modules were COL1A1, COL1A2, TIMP1, SPP1, COL5A2, THBS2, COL4A1, MUC6, CXCL8, and BGN. The overexpression of seven hub genes was associated with overall survival. Moreover, among the list of selected miRNAs, hsa-miR-27a-3, hsa-miR-941, hsa-miR-129-2-3p, and hsa-miR-1-3p, were introduced as top miRNAs targeting more than five hub genes. Conclusions The present study identified ten genes associated with GC, which may help discover novel prognostic and diagnostic biomarkers as well as therapeutic targets for GC. Our results may advance the understanding of GC occurrence and progression. |
| first_indexed | 2024-03-09T05:21:58Z |
| format | Article |
| id | doaj.art-35159b3afaf847c6b99220a70683f8b3 |
| institution | Directory Open Access Journal |
| issn | 1755-8794 |
| language | English |
| last_indexed | 2024-03-09T05:21:58Z |
| publishDate | 2023-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Genomics |
| spelling | doaj.art-35159b3afaf847c6b99220a70683f8b32023-12-03T12:39:36ZengBMCBMC Medical Genomics1755-87942023-12-0116111510.1186/s12920-023-01720-7Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysisFatemeh Abdolahi0Ali Shahraki1Roghayeh Sheervalilou2Sedigheh Sadat Mortazavi3Department of Biology, Faculty of Science, University of Sistan and BaluchestanDepartment of Biology, Faculty of Science, University of Sistan and BaluchestanPharmacology Research Center, Zahedan University of Medical SciencesDepartment of Biology, Faculty of Sciences, Shahid Bahonar University of KermanAbstract Aim Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgently needed. Methods GSE54129 and GSE26942 datasets were downloaded from Gene Expression Omnibus (GEO) database to detect differentially expressed genes (DEGs). Then, gene set enrichment analyses and protein-protein interactions were investigated. Afterward, ten hub genes were identified from the constructed network of DEGs. Then, the expression of hub genes in GC was validated. Performing survival analysis, the prognostic value of each hub gene in GC samples was investigated. Finally, the databases were used to predict microRNAs that could regulate the hub genes. Eventually, top miRNAs with more interactions with the list of hub genes were introduced. Results In total, 203 overlapping DEGs were identified between both datasets. The main enriched KEGG pathway was “Protein digestion and absorption.” The most significant identified GO terms included “primary alcohol metabolic process,” “basal part of cell,” and “extracellular matrix structural constituent conferring tensile strength.” Identified hub modules were COL1A1, COL1A2, TIMP1, SPP1, COL5A2, THBS2, COL4A1, MUC6, CXCL8, and BGN. The overexpression of seven hub genes was associated with overall survival. Moreover, among the list of selected miRNAs, hsa-miR-27a-3, hsa-miR-941, hsa-miR-129-2-3p, and hsa-miR-1-3p, were introduced as top miRNAs targeting more than five hub genes. Conclusions The present study identified ten genes associated with GC, which may help discover novel prognostic and diagnostic biomarkers as well as therapeutic targets for GC. Our results may advance the understanding of GC occurrence and progression.https://doi.org/10.1186/s12920-023-01720-7Differentially expressed genes (DEGs)Gastric cancer (GC)BioinformaticsmicroRNABiomarkers |
| spellingShingle | Fatemeh Abdolahi Ali Shahraki Roghayeh Sheervalilou Sedigheh Sadat Mortazavi Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis BMC Medical Genomics Differentially expressed genes (DEGs) Gastric cancer (GC) Bioinformatics microRNA Biomarkers |
| title | Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis |
| title_full | Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis |
| title_fullStr | Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis |
| title_full_unstemmed | Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis |
| title_short | Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis |
| title_sort | identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis |
| topic | Differentially expressed genes (DEGs) Gastric cancer (GC) Bioinformatics microRNA Biomarkers |
| url | https://doi.org/10.1186/s12920-023-01720-7 |
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