Identification of MiR-93-5p Targeted Pathogenic Markers in Acute Myeloid Leukemia through Integrative Bioinformatics Analysis and Clinical Validation

Exploration of the mechanism of fraxetin in treating acute myeloid leukemia based on network pharmacology and experimental verification

Objective

To explore the pharmacological mechanism of the effect of fraxetin in treating acute myeloid leukemia (AML) by the network pharmacology method combined with experimental validation.

Methods

The targets of fraxetin were identified through Swisstarget prediction, PhammerMap, and CTDBASE. Disease-related targets of AML were explored using GeneCards and DisGenet databases, and the intersected targets were analyzed in the String website to construct a protein-protein interaction (PPI) network. Subsequently, gene ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were conducted using the DAVID database. Molecular docking of core proteins with drugs was performed using Auto Dock Vina software. Finally, the effect of fraxetin on AML was evaluated by in vitro experiments. The effect of fraxetin on AML cell proliferation was assessed by CCK8, the effect of fraxetin on AML cell apoptosis was assessed by flow cytometry, and the expression of relevant protein targets was detected by Western blotting to evaluate the anti-AML effect of fraxetin.

Results

In this study, fraxetin exerts its effect against AML through 101 intersecting genes. The pathway enrichment analysis revealed that the pharmacological effects of fraxetin on AML were related to the Adenosine 5'-monophosphate (AMP)-activated protein kinase （AMPK） signaling pathway, and the molecular docking results indicated that fraxetin had an excellent binding affinity to both the core target and AMPK. In vitro experiments have demonstrated that fraxetin inhibited the proliferation and induced apoptosis of THP1 and HL60 cells, and the western blotting results indicated that the p-AMPK of the fraxetin intervention group was significantly changed in a dose-dependent manner.

Conclusion

Fraxetin may modulate the AMPK signal pathway by interactine with the core target, thereby potentially therapeutic effect on AML.

mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis

We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following target prediction.We present two use cases applying mirTarRnaSeq. First, to identify miRNA targets, we examined EBV miRNAs for interaction with human and virus transcriptomes of stomach adenocarcinoma. This revealed enrichment of mRNA targets highly expressed in CD105+ endothelial cells, monocytes, CD4+ T cells, NK cells, CD19+ B cells, and CD34 cells. Next, to investigate miRNA-mRNA relationships in SARS-CoV-2 (COVID-19) infection across time, we used paired miRNA and RNA sequenced datasets of SARS-CoV-2 infected lung epithelial cells across three time points (4, 12, and 24 hours post-infection). mirTarRnaSeq identified evidence for human miRNAs targeting cytokine signaling and neutrophil regulation immune pathways from 4 to 24 hours after SARS-CoV-2 infection. Confirming the clinical relevance of these predictions, three of the immune specific mRNA-miRNA relationships identified in human lung epithelial cells after SARS-CoV-2 infection were also observed to be differentially expressed in blood from patients with COVID-19. Overall, mirTarRnaSeq is a robust tool that can address a wide-range of biological questions providing improved prediction of miRNA-mRNA interactions.

Decoding the Mechanism of Shen Qi Sha Bai Decoction in Treating Acute Myeloid Leukemia Based on Network Pharmacology and Molecular Docking

Traditional Chinese Medicine (TCM) has been shown to be efficacious in treating leukemia for thousands of years. It has been shown that Shen Qi Sha Bai Decoction (SQSBD) has been extensively used in the treatment of acute myeloid leukemia (AML). However, the mechanism of SQSBD in treating AML remains unclear. In this study, we employed network pharmacology to analyze the potential active components and elucidate molecular mechanism of SQSBD in treating AML. A total of 268 active components were identified from SQSBD, among which 9 key components (Quercetin, luteolin, kaempferol, licochalcone A, formononetin, wogonin, β-sitosterol, oroxylin A, naringenin, and baicalein) were hit by the 6 hub targets (CDK1, MAPK1, JUN, PCNA, HSB1, STAT3) associated with leukemia. Molecular docking showed that two core active components, quercetin and licochalcone A, exhibited the highest component-like properties (DL), and could bind well to CDK1 and MAPK1 protein. The experimental validation of these two components showed that quercetin inhibited cell growth through CDK1 dephosphorylation-mediated cell cycle arrest at G2/M phase in human AML U937 and HL60 cells, and licochalcone A induced cell differentiation in these leukemia cells via activation of MAPK1 and upregulation of CD11b. All these results indicate that SQSBD is effective in the treatment of AML, and quercetin and licochalcone A are the major candidate compounds for AML treatment.