High Expression of CLEC11A Predicts Favorable Prognosis in Acute Myeloid Leukemia

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.

We 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.

Multiple 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.

CLEC11A 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.