02 October 2019 : Laboratory Research
Weighted Gene Coexpression Network Analysis Identifies Cysteine-Rich Intestinal Protein 1 (CRIP1) as a Prognostic Gene Associated with Relapse in Patients with Acute Myeloid LeukemiaChengyu Ye123BC, Shenglin Ma2DE, Bing Xia2F, Cuiping Zheng3AG*
Med Sci Monit 2019; 25:7396-7406
BACKGROUND: Acute myeloid leukemia (AML) is associated with a high relapse rate and poor prognosis. This study aimed to use weighted gene coexpression network analysis (WGCNA) of gene coexpression networks to identify candidate prognostic biomarker genes in patients with AML and to investigate the expression of these genes in the human U937 cell line in vitro.
MATERIAL AND METHODS: RNA-seq data were retrieved from the Cancer Genome Atlas (TCGA) and included bone marrow samples and survival data of patients with AML (N=151), patients who did not relapse after treatment (N=119), and patients with relapse (N=40). Differentially expressed genes were identified, WGCNA was used to detect functional modules, and survival analysis was performed. The Cell Counting Kit-8 (CCK-8) assay investigated the proliferation of U937 cells transfected with short hairpin RNAs (shRNAs), shCRIP1, shHIST1H1C, and shHIST1H1E. RNA-seq analysis identified gene expression following CRIP1 knockdown.
RESULTS: Eighty-two genes were associated with both relapse and prognosis in patients with AML. There were two prognosis-related gene modules in the coexpression network. In the coexpression network, the histone cluster 1 H1 family member gene, HIST1H1C had the maximum relapse fold change, HIST1H1E had the lowest survival p-value, and the cysteine-rich intestinal protein 1 (CRIP1) gene had the most edge numbers and was significantly associated with poor prognosis (P=0.0165786). RNA-seq data showed that there was a significant difference in gene expression after CRIP1 knockdown in U937 cells.
CONCLUSIONS: WGCNA of gene coexpression networks identified CRIP1 as a potential prognostic biomarker gene in patients with AML.
Keywords: Leukemia, Myeloid, Acute, Prognosis, Recurrence, Sequence Analysis, RNA
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