Construction of a microRNA-mRNA Regulatory Network in De Novo Cytogenetically Normal Acute Myeloid Leukemia Patients

Specificity protein 1/3 regulate T-cell acute lymphoblastic leukemia cell proliferation and apoptosis through β-catenin by acting as targets of miR-495-3p

T-cell acute lymphoblastic leukemia (T-ALL) is a hematologic heterogeneous disease. This study explored the mechanism of specificity protein 1/3 (Sp1/3) in T-ALL cells through β-catenin by acting as targets of miR-495-3p. Expression levels of miR-495-3p, Sp1, Sp3, and β-catenin in the serum from T-ALL children patients, healthy controls, and the T-ALL cell lines were measured. The cell proliferation ability and apoptosis rate were detected. Levels of proliferation-related proteins proliferating cell nuclear antigen (PCNA)/cyclinD1 and apoptosis-related proteins B-cell lymphoma-2 associated X protein (Bax)/B-cell lymphoma-2 (Bcl-2) were determined. The binding of Sp1/3 and β-catenin promoter and the targeted relationship between miR-495-3p with Sp1/3 were analyzed. Sp1/3 were upregulated in CD4+ T-cells in T-ALL and were linked with leukocyte count and risk classification. Sp1/3 interference prevented proliferation and promoted apoptosis in T-ALL cells. Sp1/3 transcription factors activated β-catenin expression. Sp1/3 enhanced T-ALL cell proliferation by facilitating β-catenin expression. miR-495-3p targeted and repressed Sp1/3 expressions. miR-495-3p overexpression inhibited T-ALL cell proliferation and promoted apoptosis. Conjointly, Sp1/3, as targets of miR-495-3p limit apoptosis and promote proliferation in T-ALL cells by promoting β-catenin expression.

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a new optimization procedure to identify the top network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression.

Comprehensive analysis of cuproptosis-associated LncRNAs predictive value and related CeRNA network in acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is characterized by a high recurrence and mortality rate. Cuproptosis is involved in cell death regulation in in a variety of solid tumors. Long non-coding RNAs that regulate cuproptosis genes in the pathogenesis of acute leukemia have yet to be explored.

Methods

First, cuproptosis genes with distinct expression levels were discovered by contrasting AML with normal samples from the TCGA and GTEx cohorts. Pearson correlation and univariate Cox-regression analysis were performed to identify cuproptosis-associated lncRNAs with significant prognostic values. Then the least absolute shrinkage and selection operator (LASSO) Cox regression was utilized to establish a multi-gene signature to predict AML prognosis. Next, Kaplan-Meier estimator, receiver operating characteristic curve, and a nomogram were performed to evaluate the predictive capacity of the risk signature. Functional enrichment analyses were employed to assess their function. Moreover, qRT-PCR testing of lncRNA expression in AML samples was conducted. The competing endogenous RNA (ceRNA) network was constructed to find the target genes.

Results

A risk model based on the signature of three cuproptosis-associated lncRNAs was developed. The results showed that the model possessed excellent prognostic potential. The nomogram raised the accuracy in predicting AML survival. In addition, functional enrichment analyses demonstrated an enrichment of inflammatory and immune-related pathways. Moreover, correlations between the risk signature and clinicopathological variables, tumor mutational burden, RNA stemness score, immune profile, and drug sensitivity were observed. Furthermore, we discovered that TRAF3IP2-AS1 may function as a ceRNA to regulate cuproptosis and ferroptosis gene expression.

Conclusion

The risk signature established in this study could serve as a reliable biosignature for AML prognosis. And the findings presented here may facilitate research on cuproptosis in AML.

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a novel optimization procedure to identify the optimal network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression.

The potential role of serum extracellular vesicle derived small RNAs in AML research as non-invasive biomarker

BACKGROUND

Extracellular vesicles (EV) are cell-derived vesicles released by all cells in health and disease. Accordingly, EVs are also released by cells in acute myeloid leukemia (AML), a hematologic malignancy characterized by uncontrolled growth of immature myeloid cells, and these EVs likely carry markers and molecular cargo reflecting the malignant transformation occurring in diseased cells. Monitoring antileukemic or proleukemic processes during disease development and treatment is essential. Therefore, EVs and EV-derived microRNA (miRNA) from AML samples were explored as biomarkers to distinguish disease-related patterns ex vivo or in vivo.

METHODOLOGY

EVs were purified from serum of healthy (H) volunteers and AML patients by immunoaffinity. EV surface protein profiles were analyzed by multiplex bead-based flow cytometry (MBFCM) and total RNA was isolated from EVs prior to miRNA profiling via small RNA sequencing.

RESULTS

MBFCM revealed different surface protein patterns in H versus AML EVs. miRNA analysis showed individual as well as highly dysregulated patterns in H and AML samples.

CONCLUSIONS

In this study, we provide a proof-of-concept for the discriminative potential of EV derived miRNA profiles as biomarkers in H versus AML samples.

MiR-185-5p suppresses acute myeloid leukemia by inhibiting GPX1

Acute myeloid leukemia (AML) has been characterized by the swift development of abnormal cells in the bone marrow. This research aimed to examine the impacts of the miR-185-5p-GPX1 axis on AML progression and differentiation. Findings indicated that miR-185-5p and GPX1 levels were significantly reduced and elevated, respectively. The upregulation of miR-185-5p was observed to restrict the proliferation and invasion abilities of AML cells, and promote differentiate and apoptosis. Moreover, the overexpression of GPX1 was noticed to enhance the growth of AML cells. In conclusion, this research suggested that by targeting GPX1, miR-185-5p inhibited AML progression and downregulated AML cells' proliferation and invasion.