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HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells
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LYPD3, a New Biomarker and Therapeutic Target for Acute Myelogenous Leukemia
Tingting Hu1, Yingjie Zhang2, Tianqing Yang1
1Department of Pediatrics, Third Xiangya Hospital, Central South University, Changsha, China.
Abstract:
Background: Acute myelogenous leukemia (AML) is nosocomial with the highest pediatric mortality rates and a relatively poor prognosis. C4.4A(LYPD3) is a tumorigenic and high-glycosylated cell surface protein that has been proven to be linked with the carcinogenic effects in solid tumors, but no hematologic tumors have been reported. We focus on exploring the molecular mechanism of LYPD3 in the regulation of the occurrence and development of AML to provide a research basis for the screening of markers related to the treatment and prognosis. Methods: Datasets on RNA Sequencing (RNA-seq) and mRNA expression profiles of 510 samples were obtained from The Cancer Genome Atlas Program/The Genotype-Tissue Expression (Tcga-gtex) on 10 March 2021, which included the information on 173 AML tumorous tissue samples and 337 normal blood samples. The differential expression, identification of prognostic genes based on the COX regression model, and LASSO regression were analyzed. In order to better verify, experiments including gene knockdown mediated by small interfering RNA (siRNA), cell proliferation assays, and Western blot were prefomed. We studied the possible associated pathways through which LYPD3 may have an impact on the pathogenesis and prognosis of AML by gene set enrichment analysis (GSEA). Results: A total of 11,490 differential expression genes (DEGs) were identified. Among them, 4,164 genes were upregulated, and 7,756 genes were downregulated. The univariate Cox regression analysis and LASSO regression analysis found that 28 genes including LYPD3, DNAJC8, and other genes were associated with overall survival (OS). After multivariate Cox analysis, a total of 10 genes were considered significantly correlated with OS in AML including LYPD3, which had a poor impact on AML (p <0.05). The experiment results also supported the above conclusion. We identified 25 pathways, including the E2F signaling pathway, p53 signaling pathway, and PI3K_AKT signaling pathway, that were significantly upregulated in AML samples with high LYPD3 expression (p < 0.05) by GSEA. Further, the results of the experiment suggested that LYPD3 participates in the development of AML through the p53 signaling pathway or/and PI3K/AKT signaling pathway. Conclusion: This study first proved that the expression of LYPD3 was elevated in AML, which was correlated with poor clinical characteristics and prognosis. In addition, LYPD3 participates in the development of AML through p53 or/and the PI3K/AKT signaling pathway.
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