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Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer
AIM: This study aimed to identify key genes, non-coding RNAs, and their possible regulatory interactions during gallbladder cancer (GBC). BACKGROUND: The early detection of GBC, i.e. before metastasis, is restricted by our limited knowledge of molecular markers and mechanism(s) involved during carci...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Shaheed Beheshti University of Medical Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9876761/ https://www.ncbi.nlm.nih.gov/pubmed/36762219 http://dx.doi.org/10.22037/ghfbb.v15i4.2292 |
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author | Singh, Nidhi Sharma, Rinku Bose, Sujoy |
author_facet | Singh, Nidhi Sharma, Rinku Bose, Sujoy |
author_sort | Singh, Nidhi |
collection | PubMed |
description | AIM: This study aimed to identify key genes, non-coding RNAs, and their possible regulatory interactions during gallbladder cancer (GBC). BACKGROUND: The early detection of GBC, i.e. before metastasis, is restricted by our limited knowledge of molecular markers and mechanism(s) involved during carcinogenesis. Therefore, identifying important disease-associated transcriptome-level alterations can be of clinical importance. METHODS: In this study, six NCBI-GEO microarray dataseries of GBC and control tissue samples were analyzed to identify differentially expressed genes (DEGs) and non-coding RNAs {microRNAs (DEmiRNAs) and long non-coding RNAs (DElncRNAs)} with a computational meta-analysis approach. A series of bioinformatic methods were applied to enrich functional pathways, create protein-protein interaction networks, identify hub genes, and screen potential targets of DEmiRNAs and DElncRNAs. Expression and interaction data were consolidated to reveal putative DElncRNAs:DEmiRNAs:DEGs interactions. RESULTS: In total, 351 DEGs (185 downregulated, 166 upregulated), 787 DEmiRNAs (299 downregulated, 488 upregulated), and 7436 DElncRNAs (3127 downregulated, 4309 upregulated) were identified. Eight genes (FGF, CDK1, RPN2, SEC61A1, SOX2, CALR, NGFR, and NCAM) were identified as hub genes. Genes associated with ubiquitin ligase activity, N-linked glycosylation, and blood coagulation were upregulated, while those for cell-cell adhesion, cell differentiation, and surface receptor-linked signaling were downregulated. DEGs-DEmiRNAs-DElncRNAs interaction network identified 46 DElncRNAs to be associated with 28 DEmiRNAs, consecutively regulating 27 DEGs. DEmiRNAs-hsa-miR-26b-5p and hsa-miR-335-5p; and DElnRNAs-LINC00657 and CTB-89H12.4 regulated the highest number of DEGs and DEmiRNAs, respectively. CONCLUSION: The current study has identified meaningful transcriptome-level changes and gene-miRNA-lncRNA interactions during GBC and laid a platform for future studies on novel prognostic and diagnostic markers in GBC. |
format | Online Article Text |
id | pubmed-9876761 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Shaheed Beheshti University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-98767612023-02-08 Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer Singh, Nidhi Sharma, Rinku Bose, Sujoy Gastroenterol Hepatol Bed Bench Meta-Analysis AIM: This study aimed to identify key genes, non-coding RNAs, and their possible regulatory interactions during gallbladder cancer (GBC). BACKGROUND: The early detection of GBC, i.e. before metastasis, is restricted by our limited knowledge of molecular markers and mechanism(s) involved during carcinogenesis. Therefore, identifying important disease-associated transcriptome-level alterations can be of clinical importance. METHODS: In this study, six NCBI-GEO microarray dataseries of GBC and control tissue samples were analyzed to identify differentially expressed genes (DEGs) and non-coding RNAs {microRNAs (DEmiRNAs) and long non-coding RNAs (DElncRNAs)} with a computational meta-analysis approach. A series of bioinformatic methods were applied to enrich functional pathways, create protein-protein interaction networks, identify hub genes, and screen potential targets of DEmiRNAs and DElncRNAs. Expression and interaction data were consolidated to reveal putative DElncRNAs:DEmiRNAs:DEGs interactions. RESULTS: In total, 351 DEGs (185 downregulated, 166 upregulated), 787 DEmiRNAs (299 downregulated, 488 upregulated), and 7436 DElncRNAs (3127 downregulated, 4309 upregulated) were identified. Eight genes (FGF, CDK1, RPN2, SEC61A1, SOX2, CALR, NGFR, and NCAM) were identified as hub genes. Genes associated with ubiquitin ligase activity, N-linked glycosylation, and blood coagulation were upregulated, while those for cell-cell adhesion, cell differentiation, and surface receptor-linked signaling were downregulated. DEGs-DEmiRNAs-DElncRNAs interaction network identified 46 DElncRNAs to be associated with 28 DEmiRNAs, consecutively regulating 27 DEGs. DEmiRNAs-hsa-miR-26b-5p and hsa-miR-335-5p; and DElnRNAs-LINC00657 and CTB-89H12.4 regulated the highest number of DEGs and DEmiRNAs, respectively. CONCLUSION: The current study has identified meaningful transcriptome-level changes and gene-miRNA-lncRNA interactions during GBC and laid a platform for future studies on novel prognostic and diagnostic markers in GBC. Shaheed Beheshti University of Medical Sciences 2022 /pmc/articles/PMC9876761/ /pubmed/36762219 http://dx.doi.org/10.22037/ghfbb.v15i4.2292 Text en https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article, distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) which permits others to copy and redistribute the material just in noncommercial usages, provided the original work is properly cited. |
spellingShingle | Meta-Analysis Singh, Nidhi Sharma, Rinku Bose, Sujoy Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer |
title | Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer |
title_full | Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer |
title_fullStr | Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer |
title_full_unstemmed | Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer |
title_short | Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer |
title_sort | meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer |
topic | Meta-Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9876761/ https://www.ncbi.nlm.nih.gov/pubmed/36762219 http://dx.doi.org/10.22037/ghfbb.v15i4.2292 |
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