scholarly journals Identification of hub genes associated with adult acute myeloid leukemia progression through weighted gene co-expression network analysis

Aging ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 5686-5697
Author(s):  
Ruiqi Zhu ◽  
Wenyi Lin ◽  
Liang Tang ◽  
Yu Hu
Keyword(s):  
Acute Myeloid Leukemia ◽  
Network Analysis ◽  
Myeloid Leukemia ◽  
Hub Genes ◽  
Acute Myeloid

scholarly journals The role of ARHGAP9: clinical implication and potential function in acute myeloid leukemia

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Caixia Han ◽  
Shujiao He ◽  
Ruiqi Wang ◽  
Xuefeng Gao ◽  
Hong Wang ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Differentially Expressed Genes ◽  
Myeloid Leukemia ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Clinicopathological Parameters ◽  
Hub Genes ◽  
Significant Difference ◽  
Acute Myeloid

Abstract Background Rho GTPase activating protein 9 (ARHGAP9) is expressed in various types of cancers and can inactivate Rho GTPases that mainly regulate cytoskeletal dynamics. However, the exact role of ARHGAP9 in acute myeloid leukemia (AML) has yet to be clarified. Methods We compared the transcriptional expression, prognosis, differentially expressed genes, functional enrichment, and hub genes in AML patients on the basis of the data published in the following databases: UALCAN, GEPIA, Gene Expression Omnibus, the Human Protein Atlas, Cancer Cell Line Encyclopedia, LinkedOmics, Metascape, and String. Data from the Cancer Genome Atlas database was used to evaluate the correlations between ARHGAP9 expression and various clinicopathological parameters, as well as the significantly different genes associated with ARHGAP9 expression. Results We found that ARHGAP9 expression was higher in the tissues and cell lines extracted from patients with AML than corresponding control tissues and other cancer types. ARHGAP9 overexpression was associated with decreased overall survival (OS) in AML. Compared with the ARHGAP9low group, the ARHGAP9high group, which received only chemotherapy, showed significantly worse OS and event-free survival (EFS); however, no significant difference was observed after treatment with autologous or allogeneic hematopoietic stem cell transplantation (auto/allo-HSCT). The ARHGAP9high patients undergoing auto/allo-HSCT also had a significantly better prognosis with respect to OS and EFS than those receiving only chemotherapy. Most overlapping genes of the significantly different genes and co-expression genes exhibited enriched immune functions, suggesting the immune regulation potential of ARHGAP9 in AML. A total of 32 hub genes were identified from the differentially expressed genes, within which the KIF20A had a significant prognostic value for AML. Conclusions ARHGAP9 overexpression was associated with poor OS in AML patients and can be used as a prognostic biomarker. AML patients with ARHGAP9 overexpression can benefit from auto/allo-HSCT rather than chemotherapy.

scholarly journals Novel prognostic genes and subclasses of acute myeloid leukemia revealed by survival analysis of gene expression data

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yanli Lai ◽  
Guifang OuYang ◽  
Lixia Sheng ◽  
Yanli Zhang ◽  
Binbin Lai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Network Analysis ◽  
Risk Score ◽  
Myeloid Leukemia ◽  
The Cancer Genome Atlas ◽  
Prognostic Biomarkers ◽  
High Expression ◽  
Acute Myeloid

Abstract Background Acute myeloid leukemia (AML) is biologically heterogeneous diseases with adverse prognosis. This study was conducted to find prognostic biomarkers that could effectively classify AML patients and provide guidance for treatment decision making. Methods Weighted gene co-expression network analysis was applied to detect co-expression modules and analyze their relationship with clinicopathologic characteristics using RNA sequencing data from The Cancer Genome Atlas database. The associations of gene expression with patients’ mortality were investigated by a variety of statistical methods and validated in an independent dataset of 405 AML patients. A risk score formula was created based on a linear combination of five gene expression levels. Results The weighted gene co-expression network analysis detected 63 co-expression modules. The pink and darkred modules were negatively significantly correlated with overall survival of AML patients. High expression of FNDC3B, VSTM1 and CALR was associated with favourable overall survival, while high expression of PLA2G4A was associated with adverse overall survival. Hierarchical clustering analysis of FNDC3B, VSTM1, PLA2G4A, GOLGA3 and CALR uncovered four subgroups of AML patients. The cluster1 AML patients showed younger age, lower cytogenetics risk, higher frequency of NPM1 mutations and more favourable overall survival than cluster3 patients. The risk score was demonstrated to be an indicator of adverse prognosis in AML patients Conclusions The FNDC3B, VSTM1, PLA2G4A, GOLGA3, CALR and risk score may serve as key prognostic biomarkers for the stratification and ultimately guide rational treatment of AML patients.

scholarly journals Identification of the hub genes and pathways involved in acute myeloid leukemia using bioinformatics analysis

Medicine ◽  
2020 ◽  
Vol 99 (35) ◽  
pp. e22047
Author(s):  
Youping Tan ◽  
Liling Zheng ◽  
Yuanyuan Du ◽  
Qi Zhong ◽  
Yangmin Zhu ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Bioinformatics Analysis ◽  
Hub Genes ◽  
Acute Myeloid

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

2021 ◽  
Vol 10 (1) ◽  
pp. 126-140
Author(s):  
Daxia Cai ◽  
Jiajian Liang ◽  
Xing-Dong Cai ◽  
Ying Yang ◽  
Gexiu Liu ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Drug Sensitivity ◽  
Hub Genes ◽  
Acute Myeloid

scholarly journals In silico analysis of genes and pathways related to acute myeloid leukemia presenting leukopenia

2021 ◽  
Author(s):  
Ajeet Kumar ◽  
Ravi Bhushan ◽  
Pawan K. Dubey ◽  
Vijai Tilak ◽  
Vineeta Gupta ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Cell Signaling ◽  
B Cell ◽  
Myeloid Leukemia ◽  
Expression Profiles ◽  
Differentially Expressed Gene ◽  
Hub Genes ◽  
Hematopoietic Stem ◽  
Acute Myeloid

Abstract Acute myeloid leukemia (AML) is a type of blood cancers that begins from progenitor and hematopoietic stem cell. Chromosomal abnormalities include balanced translocations between two chromosome like t[8;21] and t[15;17]) in malignancies cells. The present study aimed to explore the AML presenting with leukopenia and gene expression changes induced in High-white count B-cell and Low-white count B-cell the total number of samples is ten. The raw gene expression profiles (ID: GSE20482) of bone marrow achieve from AML patient five High-white count B-cell and five Low-white count B-cell were expressed genes used to recognize differentially. These genes that correspond to official gene symbols were select for protein-protein interaction (PPI) and sub-network construction (score > 0.4). The functional annotation of Gene Ontology (GO) and pathways analysis were performed for those genes involve in networking.ResultsThe total number of 846 genes were identified differentially expressed gene and 406 gene were up-regulated another 440 gene were down-regulated. Other 14 genes are interacting with each other significantly identified. Including Hub genes DEGs GNB4, LAMTOR2, ACTN4, HGSNAT, TMED1 are up-regulated while down-regulated DEGs forming hub nodes were UBR4, FBXO30, KLHL21, DCTN6, RNF123, RNF114. AML has a major effect on the expression of genes involved in cell differentiation, apoptosis, cell signaling and modification of protein. AML cells enter the blood quickly and spread to the liver, spleen, and central nervous system. These are total thirteen pathways were enriched and these genes related to oxidative phosphorylation, regulation of actin cytoskeleton, endocytosis, phagocytosis, shigellosis, epithelial cell signaling in helicobacter, adherent junction, pertussis, bile secretion, malaria, African trypanosomiasis were found significantly affected by AML.ConclusionsHub genes like GNB4 and UBR4 provide as a novel biomarker in AML.

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