Up-Regulation of TRIM32 Associated With the Poor Prognosis of Acute Myeloid Leukemia by Integrated Bioinformatics Analysis With External Validation

Abstract

BackgroundAcute myeloid leukemia (AML) is a malignant and molecularly heterogeneous disease. It is essential to clarify the molecular mechanisms of AML and develop targeted treatment strategies to improve patient prognosis.MethodsAML mRNA expression data and survival status were extracted from TCGA and GEO databases (GSE37642, GSE76009, GSE16432, GSE12417, GSE71014). Weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis were performed. Functional enrichment analysis and protein-protein interaction (PPI) network were used to screen out hub genes. In addition, we validated the expression levels of hub genes as well as the prognostic value and externally validated TRIM32 with clinical data from our center. AML cell lines transfected with TRIM32 shRNA were also established to detect the proliferation in vitro.ResultsA total of 2192 AML patients from TCGA and GEO datasets were included in this study and 20 differentially co-expressed genes were screened by WGCNA and differential gene expression analysis methods. These genes were mainly enriched in phospholipid metabolic processes (biological processes, BP), secretory granule membranes (cellular components, CC), and protein serine/threonine kinase activity (molecular functions, MF). In addition, the protein-protein interaction (PPI) network contains 15 nodes and 15 edges and 10 hub genes (TLE1, GLI2, HDAC9, MICALL2, DOCK1, PDPN, RAB27B, SIX3, TRIM32 and TBX1) were identified. The expression of 10 central genes, except TLE1, was associated with survival status in AML patients (p<0.05). High expression of TRIM32 was tightly associated with poor relapse-free survival (RFS) and overall survival (OS) in AML patients, which was verified in the bone marrow samples from our center. In vitro, knockdown of TRIM32 can inhibit the proliferation of AML cell lines.ConclusionTRIM32 was associated with the progression and prognosis of AML patients and could be a potential therapeutic target and biomarker for AML in the future.

Identification of two key biomarkers CD93 and FGL2 associated with survival of acute myeloid leukaemia by weighted gene co‐expression network analysis

“…Yu et al 33 recently used WGCNA to show that high expression of LOC541471, GDAP1, SOD1 and STK25 is associated with poor survival of patients with AML. Xu et al 34 GATA1) and pathways in AML using WGCNA. In the present study, we identified six hub genes related to survival of patients with AML by applying WGCNA.…”

“…recently used WGCNA to show that high expression of LOC541471 , GDAP1 , SOD1 and STK25 is associated with poor survival of patients with AML. Xu et al 34 . also used WGCNA to show that TRIM32 is associated with a poor prognosis in patients with AML.…”