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Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics

BACKGROUND: Acute myeloid leukemia (AML) is a common hematopoietic malignancy and have unsatisfactory prognosis. Our study aimed to identify hub genes in AML and explore potential biomarkers through integrated bioinformatics. METHODS: Microarray datasets were analyzed to screen the differentially ex...

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Autores principales: Cai, Daxia, Liang, Jiajian, Cai, Xing-Dong, Yang, Ying, Liu, Gexiu, Zhou, Fenling, He, Dongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798452/
https://www.ncbi.nlm.nih.gov/pubmed/35116245
http://dx.doi.org/10.21037/tcr-20-2712
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author Cai, Daxia
Liang, Jiajian
Cai, Xing-Dong
Yang, Ying
Liu, Gexiu
Zhou, Fenling
He, Dongmei
author_facet Cai, Daxia
Liang, Jiajian
Cai, Xing-Dong
Yang, Ying
Liu, Gexiu
Zhou, Fenling
He, Dongmei
author_sort Cai, Daxia
collection PubMed
description BACKGROUND: Acute myeloid leukemia (AML) is a common hematopoietic malignancy and have unsatisfactory prognosis. Our study aimed to identify hub genes in AML and explore potential biomarkers through integrated bioinformatics. METHODS: Microarray datasets were analyzed to screen the differentially expressed genes (DEGs). Functional enrichment analysis was performed, and protein-protein interaction (PPI) network was generated by the STRING (11.0) database and Cytoscape (3.7.2) software. Hub genes were screened and verified through GEPIA2 and GEO microarray database. Sensitivity of AML cell lines with high expression of hub genes to the small-molecule drugs were identified using GSCA Lite. RESULTS: A total of 456 DEGs were identified and top 100 genes were screened out, of which six genes (FLT3, PF4, CD163, MRC1, CSF2RB, PPBP) were upregulated in AML and individually had a worse prognosis by the overall survival (OS) analysis. AML cell lines with FLT3-overexpression and CSF2RB-overexpression were sensitive to most small-molecule drugs, while, AML cells with CD163-overexpression were only sensitive to a few drugs. However, sensitivity to Erlotinib was correlated with high expression of PF4 and PPBP. CONCLUSIONS: In summary, FLT3, PF4, CD163, MRC1, CSF2RB, PPBP may be potential biomarkers and potential sensitive small-molecule drugs were correlated with overexpression of the biomarkers in AML.
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spelling pubmed-87984522022-02-02 Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics Cai, Daxia Liang, Jiajian Cai, Xing-Dong Yang, Ying Liu, Gexiu Zhou, Fenling He, Dongmei Transl Cancer Res Original Article BACKGROUND: Acute myeloid leukemia (AML) is a common hematopoietic malignancy and have unsatisfactory prognosis. Our study aimed to identify hub genes in AML and explore potential biomarkers through integrated bioinformatics. METHODS: Microarray datasets were analyzed to screen the differentially expressed genes (DEGs). Functional enrichment analysis was performed, and protein-protein interaction (PPI) network was generated by the STRING (11.0) database and Cytoscape (3.7.2) software. Hub genes were screened and verified through GEPIA2 and GEO microarray database. Sensitivity of AML cell lines with high expression of hub genes to the small-molecule drugs were identified using GSCA Lite. RESULTS: A total of 456 DEGs were identified and top 100 genes were screened out, of which six genes (FLT3, PF4, CD163, MRC1, CSF2RB, PPBP) were upregulated in AML and individually had a worse prognosis by the overall survival (OS) analysis. AML cell lines with FLT3-overexpression and CSF2RB-overexpression were sensitive to most small-molecule drugs, while, AML cells with CD163-overexpression were only sensitive to a few drugs. However, sensitivity to Erlotinib was correlated with high expression of PF4 and PPBP. CONCLUSIONS: In summary, FLT3, PF4, CD163, MRC1, CSF2RB, PPBP may be potential biomarkers and potential sensitive small-molecule drugs were correlated with overexpression of the biomarkers in AML. AME Publishing Company 2021-01 /pmc/articles/PMC8798452/ /pubmed/35116245 http://dx.doi.org/10.21037/tcr-20-2712 Text en 2021 Translational Cancer Research. 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/.
spellingShingle Original Article
Cai, Daxia
Liang, Jiajian
Cai, Xing-Dong
Yang, Ying
Liu, Gexiu
Zhou, Fenling
He, Dongmei
Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics
title Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics
title_full Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics
title_fullStr Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics
title_full_unstemmed Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics
title_short Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics
title_sort identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798452/
https://www.ncbi.nlm.nih.gov/pubmed/35116245
http://dx.doi.org/10.21037/tcr-20-2712
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