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Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma

Follicular lymphoma (FL) is the second most prevalent form of non-Hodgkin lymphoma (NHL) and accounts for almost 20% of all NHL cases. Although FL patients' overall survival rates have steadily increased, there is still no accepted standard of care for individuals who experience recurrence or r...

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Autores principales: Zhang, Qing, Wang, Meng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357743/
https://www.ncbi.nlm.nih.gov/pubmed/35965624
http://dx.doi.org/10.1155/2022/5369104
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author Zhang, Qing
Wang, Meng
author_facet Zhang, Qing
Wang, Meng
author_sort Zhang, Qing
collection PubMed
description Follicular lymphoma (FL) is the second most prevalent form of non-Hodgkin lymphoma (NHL) and accounts for almost 20% of all NHL cases. Although FL patients' overall survival rates have steadily increased, there is still no accepted standard of care for individuals who experience recurrence or resistance to treatment. Hence, it is needed to evaluate the precise molecular cascades underlying FL to develop efficient diagnostic and treatment approaches. Herein, we aimed to evaluate variations in gene expression profiles, explore the underlying mechanisms, and find new FL targets. In the present study, Gene Expression Omnibus (GEO) database was employed to evaluate microarray datasets including GSE32018 and GSE55267. R software was employed to evaluate differentially expressed genes (DEGs) between FL and noncancer samples. The DEGs were evaluated using GO, KEGG pathway enrichment analysis, and PPI network to evaluate hub genes, which were then, examined using gene function enrichment analysis. According to the obtained results, a total of 190 upregulated and 162 downregulated DEGs were evaluated. Following the generation of PPI networks, 15 hub genes in highly connected upregulated DEGs were selected including FN1, MMP9, CCL2, CD8A, POSTN, CCR5, COL3A1, CXCL12, VCAM1, COL1A2, CCL5, SPARC, TIMP1, CXCL9, and IL18. The GO enrichment evaluation of the underlined hub genes indicated that the immunological response was the most considerably enriched term. Twelve significant cascades were found using the KEGG pathway analysis, most of which were linked to cellular structure and immunity. Our findings suggested that FN1, SPARC, POSTN, MMP9, and VCAM1 genes are potential biomarkers of FL, and cellular immunity contributes to the pathogenesis of FL. Moreover, the unique DEGs and cascades found in the present study may present new perspectives on the molecular basis of FL's underlying mechanisms as well as a new understanding of FL's future precise management.
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spelling pubmed-93577432022-08-12 Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma Zhang, Qing Wang, Meng Contrast Media Mol Imaging Research Article Follicular lymphoma (FL) is the second most prevalent form of non-Hodgkin lymphoma (NHL) and accounts for almost 20% of all NHL cases. Although FL patients' overall survival rates have steadily increased, there is still no accepted standard of care for individuals who experience recurrence or resistance to treatment. Hence, it is needed to evaluate the precise molecular cascades underlying FL to develop efficient diagnostic and treatment approaches. Herein, we aimed to evaluate variations in gene expression profiles, explore the underlying mechanisms, and find new FL targets. In the present study, Gene Expression Omnibus (GEO) database was employed to evaluate microarray datasets including GSE32018 and GSE55267. R software was employed to evaluate differentially expressed genes (DEGs) between FL and noncancer samples. The DEGs were evaluated using GO, KEGG pathway enrichment analysis, and PPI network to evaluate hub genes, which were then, examined using gene function enrichment analysis. According to the obtained results, a total of 190 upregulated and 162 downregulated DEGs were evaluated. Following the generation of PPI networks, 15 hub genes in highly connected upregulated DEGs were selected including FN1, MMP9, CCL2, CD8A, POSTN, CCR5, COL3A1, CXCL12, VCAM1, COL1A2, CCL5, SPARC, TIMP1, CXCL9, and IL18. The GO enrichment evaluation of the underlined hub genes indicated that the immunological response was the most considerably enriched term. Twelve significant cascades were found using the KEGG pathway analysis, most of which were linked to cellular structure and immunity. Our findings suggested that FN1, SPARC, POSTN, MMP9, and VCAM1 genes are potential biomarkers of FL, and cellular immunity contributes to the pathogenesis of FL. Moreover, the unique DEGs and cascades found in the present study may present new perspectives on the molecular basis of FL's underlying mechanisms as well as a new understanding of FL's future precise management. Hindawi 2022-07-31 /pmc/articles/PMC9357743/ /pubmed/35965624 http://dx.doi.org/10.1155/2022/5369104 Text en Copyright © 2022 Qing Zhang and Meng Wang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Qing
Wang, Meng
Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma
title Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma
title_full Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma
title_fullStr Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma
title_full_unstemmed Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma
title_short Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma
title_sort identification of hub genes and key pathways associated with follicular lymphoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357743/
https://www.ncbi.nlm.nih.gov/pubmed/35965624
http://dx.doi.org/10.1155/2022/5369104
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