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. 2021 Feb 11;13(4):5686-5697.
doi: 10.18632/aging.202493. Epub 2021 Feb 11.

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

Affiliations

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

Ruiqi Zhu et al. Aging (Albany NY). .

Abstract

Acute myeloid leukemia (AML) is a malignancy of hematopoietic stem cells. Although many candidate genes such as CEBPA, FLT3, IDH1, and IDH2 have been associated with AML initiation and prognosis, the molecular mechanisms underlying this disease remain unclear. In this study, we used a systemic co-expression analysis method, namely weighted gene co-expression network analysis (WGCNA), to identify new candidate genes associated with adult AML progression and prognosis. We identified around 5,138 differentially expressed genes (DEGs) between AML samples (from The Cancer Genome Atlas database) and normal control samples (from the Genotype-Tissue Expression database). WGCNA identified nine co-expression modules with significant differences based on the DEGs. Among modules, the turquoise and blue ones were the most relevant to AML (P-value: turquoise 0, blue 4.64E-77). GO term and KEGG pathway analyses revealed that pathways that are commonly dysregulated in AML were all enriched in the blue and turquoise modules. A total of 15 hub genes were identified to be crucial for AML progression. PIVOT analysis revealed non-coding RNAs, transcriptional factors, and drugs associated with the hub genes. Finally, survival analysis revealed that one of the hub genes, CEACAM5, was significantly associated with AML prognosis and could serve as a potential target for AML treatment.

Keywords: AML; WGCNA; hub genes.

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Conflict of interest statement

CONFLICTS OF INTEREST: The authors declare there are no conflicts of interest.

Figures

Figure 1
Figure 1
Effects of different soft-threshold values for adult AML co-expression network.
Figure 2
Figure 2
Characterization of adult AML co-expression network. (A) Cluster dendrogram and colored display of the network. (B) Relationship between modules and phenotypes. Turquoise and blue module are the top two modules related with AML phenotype according to P-value. (C) Network heatmap plot for genes in the modules in hierarchical clustering dendrograms. The deeper the red, the more correlated between the genes. (D) Gene expression differences between AML samples and normal control in modules. (E) Gene Significance (GS) and Module Membership (MM) analyses in turquoise and (F) blue module.
Figure 3
Figure 3
Visualization of hub genes network in (A) turquoise and (B) blue modules.
Figure 4
Figure 4
Visualization of part of GO bio-functional analysis results in (A) blue and (C) turquoise module. Visualization of part of KEGG analysis results in (B) blue and (D) turquoise module.
Figure 5
Figure 5
PIVOT analysis revealed TFs and ncRNAs associated with (A) blue and (B) turquoise module.
Figure 6
Figure 6
Kaplan-Meier curve for CEACAM5 low and high expression patients in TCGA database.

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