High Expression of CLEC11A Predicts Favorable Prognosis in Acute Myeloid Leukemia

Chengliang Yin; Junyan Zhang; Wei Guan; Liping Dou; Yuchen Liu; Ming Shen; Xiaodong Jia; Lu Xu; Rilige Wu; Yan Li

doi:10.3389/fonc.2021.608932

High Expression of CLEC11A Predicts Favorable Prognosis in Acute Myeloid Leukemia

Front Oncol. 2021 Mar 2:11:608932. doi: 10.3389/fonc.2021.608932. eCollection 2021.

Authors

Chengliang Yin^{1

2

3}, Junyan Zhang^{1

3}, Wei Guan⁴, Liping Dou⁴, Yuchen Liu⁴, Ming Shen⁵, Xiaodong Jia⁶, Lu Xu⁵, Rilige Wu^{1

3}, Yan Li^{4

7}

Affiliations

¹ Medical Big Data Research Center, Medical Innovation Research Division of Chinese People's Liberation Army General Hospital, Beijing, China.
² Faculty of Medicine, Macau University of Science and Technology, Macau, China.
³ National Engineering Laboratory for Medical Big Data Application Technology, Chinese People's Liberation Army General Hospital, Beijing, China.
⁴ Department of Hematology, Chinese People's Liberation Army General Hospital, Beijing, China.
⁵ Research Center for Translational Medicine Laboratory, Medical Innovation Research Division of Chinese People's Liberation Army General Hospital, Beijing, China.
⁶ Hepatobiliary Surgery Center, The Fifth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China.
⁷ Department of Hematology, Peking University, Third Hospital, Beijing, China.

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Keywords: CLEC11A; acute myeloid leukemia; biomarker; expression; methylation; prognosis.