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Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs

BACKGROUND: Copy number variations (CNVs) participate in the development and progression of cancer by altering the expression levels of genes. However, it is unclear whether this correlation exists in diffuse large B-cell lymphoma (DLBCL). METHODS: Differentially expressed genes (DEGs) were identifi...

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Autores principales: Zhang, Shuo, Wang, Hongmin, Liu, Aichun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652577/
https://www.ncbi.nlm.nih.gov/pubmed/36388804
http://dx.doi.org/10.21037/atm-22-4709
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author Zhang, Shuo
Wang, Hongmin
Liu, Aichun
author_facet Zhang, Shuo
Wang, Hongmin
Liu, Aichun
author_sort Zhang, Shuo
collection PubMed
description BACKGROUND: Copy number variations (CNVs) participate in the development and progression of cancer by altering the expression levels of genes. However, it is unclear whether this correlation exists in diffuse large B-cell lymphoma (DLBCL). METHODS: Differentially expressed genes (DEGs) were identified from the GSE25638 and GSE56315 datasets. Modules that were highly related to DLBCL prognosis were obtained by Weighted Gene Co-expression Network Analysis (WGCNA). We performed an integrated analysis between CNV and differential gene expression in The Cancer Genome Atlas (TCGA) DLBCL. The DEGs were then overlapped with the module genes and expression-copy number variations-related (Exp-CNV-related) genes to obtain the common key genes. Time-dependent receiver operating characteristic (ROC) analysis was utilized to evaluate the accuracy of the key gene in predicting the prognosis of DLBCL. Next, we conducted a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to explore the key gene. The potential molecule drugs of the key gene were identified by Connectivity Map (Cmap) analysis. RESULTS: A turquoise module with 160 genes was identified as the signature module. ATP1B1 is overexpressed in DLBCL cell lines, compared to Cluster of Differentiation 19+B (CD19+B) cells. The ROC curve indicated that ATP1B1 could be a biomarker for diagnosing DLBCL, and the forest map suggested that ATP1B1 gene expression levels had a greater impact on the prognosis of patients with DLBCL. The area under curve (AUC) value of the time-dependent ROC curve with values based on the 1-, 3-, and 5-year survivability were 0.576, 0.663, and 0.706, respectively. Pathway analysis demonstrated the relationship between ATP1B1 and focal adhesion, etc. The inhibitory effects of ATP1B1 downregulation on DLBCL cell proliferation, cell migration, invasion, and cell adhesion were also examined. We found out that the higher proliferation ability in ATP1B1-overexpression cells was rescued with roxithromycin. CONCLUSIONS: ATP1B1 is a copy number driver gene that could potentially be adopted as a diagnostic biomarker and therapeutic target of DLBCL.
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spelling pubmed-96525772022-11-15 Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs Zhang, Shuo Wang, Hongmin Liu, Aichun Ann Transl Med Original Article BACKGROUND: Copy number variations (CNVs) participate in the development and progression of cancer by altering the expression levels of genes. However, it is unclear whether this correlation exists in diffuse large B-cell lymphoma (DLBCL). METHODS: Differentially expressed genes (DEGs) were identified from the GSE25638 and GSE56315 datasets. Modules that were highly related to DLBCL prognosis were obtained by Weighted Gene Co-expression Network Analysis (WGCNA). We performed an integrated analysis between CNV and differential gene expression in The Cancer Genome Atlas (TCGA) DLBCL. The DEGs were then overlapped with the module genes and expression-copy number variations-related (Exp-CNV-related) genes to obtain the common key genes. Time-dependent receiver operating characteristic (ROC) analysis was utilized to evaluate the accuracy of the key gene in predicting the prognosis of DLBCL. Next, we conducted a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to explore the key gene. The potential molecule drugs of the key gene were identified by Connectivity Map (Cmap) analysis. RESULTS: A turquoise module with 160 genes was identified as the signature module. ATP1B1 is overexpressed in DLBCL cell lines, compared to Cluster of Differentiation 19+B (CD19+B) cells. The ROC curve indicated that ATP1B1 could be a biomarker for diagnosing DLBCL, and the forest map suggested that ATP1B1 gene expression levels had a greater impact on the prognosis of patients with DLBCL. The area under curve (AUC) value of the time-dependent ROC curve with values based on the 1-, 3-, and 5-year survivability were 0.576, 0.663, and 0.706, respectively. Pathway analysis demonstrated the relationship between ATP1B1 and focal adhesion, etc. The inhibitory effects of ATP1B1 downregulation on DLBCL cell proliferation, cell migration, invasion, and cell adhesion were also examined. We found out that the higher proliferation ability in ATP1B1-overexpression cells was rescued with roxithromycin. CONCLUSIONS: ATP1B1 is a copy number driver gene that could potentially be adopted as a diagnostic biomarker and therapeutic target of DLBCL. AME Publishing Company 2022-10 /pmc/articles/PMC9652577/ /pubmed/36388804 http://dx.doi.org/10.21037/atm-22-4709 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zhang, Shuo
Wang, Hongmin
Liu, Aichun
Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs
title Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs
title_full Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs
title_fullStr Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs
title_full_unstemmed Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs
title_short Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs
title_sort identification of atp1b1, a key copy number driver gene in diffuse large b-cell lymphoma and potential target for drugs
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652577/
https://www.ncbi.nlm.nih.gov/pubmed/36388804
http://dx.doi.org/10.21037/atm-22-4709
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