Abstract
BackgroundAcute myeloid leukemia (AML) is a heterogeneous disease of the hematopoietic system, for which identification of novel molecular markers is potentially important for clinical prognosis and is an urgent need for treatment optimization.MethodsWe selected C-type lectin domain family 11, member A (CLEC11A) for study via several public databases, comparing expression among a variety of tumors and normal samples as well as different organs and tissues. To investigated the relationship between CLEC11A expression and clinical characteristics, we derived an AML cohort from The Cancer Genome Atlas (TCGA); we also investigated the Bloodspot and HemaExplorer databases. The Kaplan-Meier method and log-rank test were used to evaluate the associations between CLEC11A mRNA expression, as well as DNA methylation, and overall survival (OS), event-free survival (EFS), and relapse-free survival (RFS). DNA methylation levels of CLEC11A from our own 28 de novo AML patients were assessed and related to chemotherapeutic outcomes. Bioinformatics analysis of CLEC11A was carried out using public databases.ResultsMultiple public databases revealed that CLEC11A expression was higher in leukemia. The TCGA data revealed that high CLEC11A expression was linked with favorable prognosis (OS p-value = 2e-04; EFS p-value = 6e-04), which was validated in GSE6891 (OS p-value = 0; EFS p-value = 0; RFS p-value = 2e-03). Methylation of CLEC11A was negatively associated with CLEC11A expression, and high CLEC11A methylation level group was linked to poorer prognosis (OS p-value = 1e-02; EFS p-value = 2e-02). Meanwhile, CLEC11A hypermethylation was associated with poor induction remission rate and dismal survival. Bioinformatic analysis also showed that CLEC11A was an up-regulated gene in leukemogenesis.ConclusionCLEC11A may be used as a prognostic biomarker, and could do benefit for AML patients by providing precise treatment indications, and its unique gene pattern should aid in further understanding the heterogeneous AML mechanisms.
Highlights
Acute myeloid leukemia (AML) is a heterogeneous clonal disorder featured by the accumulation of somatic genetic alterations in hematopoietic progenitor cells, changing normal mechanisms of self-renewal [1, 2], cell proliferation, and differentiation [3] with a highly variable prognosis and a high mortality rate [4, 5]
We studied a Gene Expression Omnibus (GEO) cohort (GSE9476, 38 healthy donors, 26 AML patients), and the relationship between CLEC11A expression and the Kaplan-Meier survival analysis in AML analyzed via the TCGA data was further validated via a GEO database (GSE6891); [5] The Cancer Genome Atlas (TCGA): The Cancer Genome Atlas is a public-funded landmark program that seeks to catalog and discover major cancer-causing genomic alterations to create a comprehensive “atlas” of cancer genomic profiles [32]
This analysis showed that CLEC11A expression was higher in breast, colorectal, gastric, pancreatic cancers and leukemia, lymphoma, sarcoma tumors than in normal tissues (Figure 1A)
Summary
AML is a heterogeneous clonal disorder featured by the accumulation of somatic genetic alterations in hematopoietic progenitor cells, changing normal mechanisms of self-renewal [1, 2], cell proliferation, and differentiation [3] with a highly variable prognosis and a high mortality rate [4, 5]. Several studies have reported that the expression of different panels of genes that include CLEC11A is associated with clinical outcome in patients with AML [16, 17]. The CLEC11A expression level is associated with clinical and biological prognostic outcomes in childhood acute lymphoblastic leukemia [16, 24, 25]. Previous studies have validated CLEC11A as a novel regulator and candidate therapeutic target of multiple myeloma SET domain (MMSET)-related myeloma [16, 26, 27]. These outcomes indicated that CLEC11A plays a vital role in hematopoietic regulation. Acute myeloid leukemia (AML) is a heterogeneous disease of the hematopoietic system, for which identification of novel molecular markers is potentially important for clinical prognosis and is an urgent need for treatment optimization
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