Search

Sepsis is a systemic inflammatory response caused by infection, and severe sepsis is commonly associated with the development of acute kidney injury (AKI). Accumulating evidence has revealed the implication of circular RNAs in AKI. In this study, we explored the potential engagement and the underlying mechanism of hsa_circ_010157 (circSTRN3) in sepsis-induced AKI. CircSTRN3 levels in HK2 cells and serum samples of patients were determined by RT-PCR. The protein levels of TLR4 (Toll Like Receptor 4), bax (Bcl-2-associated X protein), cleaved caspase 3 and bcl-2 (B-cell lymphoma-2) were detected by Western blotting (WB), and the levels of proinflammatory cytokines were detected by ELISA. The molecular interactions between mir-578/TLR4 and circSTRN3/miR-578 were analyzed by dual luciferase reporter assay as well as RNA pull-down experiment. Lipopolysaccharide (LPS) treated HK2 cells were used as an

Dapper antagonist of catenin-3 (DACT3) is a new tumor-related protein associated with a diverse set of tumors. However, whether DACT3 plays a role in acute myeloid leukemia (AML) is not fully understood. Our findings showed low DACT3 level in AML tissue, which was corrected with shorter survival rates. Upregulation of DACT3 effectively repressed cellular proliferation, and promoted cell cycle arrest and apoptosis of AML cells. Upregulation of DACT3 decreased levels of Dishevelled2 (DVL2), phospho-glycogen synthase kinase-3β (GSK-3β), and active β-catenin, which collectively suppressed Wnt/β-catenin-mediated transcriptional activity. Overexpression of DVL2 reversed DACT3-mediated suppression of Wnt/β-catenin pathway. Reactivation of Wnt/β-catenin abrogated DACT3-upregulation-evoked tumor-suppression in AML cells. Overexpression of DACT3 impeded the formation and growth of AML-derived xenograft tumor. Collectively, our work reveals a tumor-suppressive role of DACT3, a protein that negatively adjusts Wnt/β-catenin pathway via downregulation of DVL2 in AML.

The long noncoding RNA (lncRNA) small nucleolar RNA host gene 1 (SNHG1) is a critical regulator for the development and progression of multiple tumors. Yet, the role of SNHG1 in acute myeloid leukemia (AML) is unknown. The present study demonstrated that SNHG1 expression was upregulated in AML. SNHG1 silencing markedly repressed AML cell growth, whereas SNHG1 overexpression had the opposite effect. MicroRNA-489-3p (miR-489-3p) was identified as a SNHG1-targeting miRNA. SNHG1 knockdown increased miR-489-3p expression. Low expression of miR-489-3p was correlated with high expression of SNHG1 in AML tissues. miR-489-3p overexpression restricted AML cell growth, and SRY-related high-mobility-group box 12 (SOX12) was identified as a miR-489-3p-targeting gene. SNHG1 inhibition or miR-489-3p overexpression inactivated Wnt/β-catenin signaling through downregulation of SOX12. SOX12 overexpression partially reversed the SNHG1 knockdown- or miR-489-3p overexpression-mediated effects. Taken together, these data indicate that suppression of SNHG1 downregulates AML cell growth by inactivating SOX12/Wnt/β-catenin signaling via upregulating miR-489-3p.

Acute myeloid leukemia (AML) is a heterogeneous disease, and survival signatures are urgently needed to better monitor treatment. MiRNAs displayed vital regulatory roles on target genes, which was necessary involved in the complex disease. We therefore examined the expression levels of miRNAs and genes to identify robust signatures for survival benefit analyses. First, we reconstructed subpathway graphs by embedding miRNA components that were derived from low-throughput miRNA-gene interactions. Then, we randomly divided the data sets from The Cancer Genome Atlas (TCGA) into training and testing sets, and further formed 100 subsets based on the training set. Using each subset, we identified survival-related miRNAs and genes, and identified survival subpathways based on the reconstructed subpathway graphs. After statistical analyses of these survival subpathways, the most robust subpathways with the top three ranks were identified, and risk scores were calculated based on these robust subpathways for AML patient prognoses. Among these robust subpathways, three representative subpathways, path: 05200_10 from Pathways in cancer, path: 04110_20 from Cell cycle, and path: 04510_8 from Focal adhesion, were significantly associated with patient survival in the TCGA training and testing sets based on subpathway risk scores. In conclusion, we performed integrated analyses of miRNAs and genes to identify robust prognostic subpathways, and calculated subpathway risk scores to characterize AML patient survival.