miRNA-mRNA Profiling Reveals Prognostic Impact of SMC1A Expression in Acute Myeloid Leukemia

Role of MicroRNAs in Acute Myeloid Leukemia

MicroRNA (miRNA), a significant class of regulatory non-coding RNA (ncRNA), can regulate the expression of numerous protein-coding messenger RNAs (mRNAs). miRNA plays an important part in shaping the human transcriptome. So far, in the human genome, about 2500 miRNAs have been found. Acute myeloid leukemia (AML) belongs to a malignant clonal disorder of hematopoietic stem cells and is characterized by the uncontrolled clonal proliferation of abnormal progenitor cells in the bone marrow and blood. For the past several years, significant scientific attention has been attracted to the role of miRNAs in AML, since alterations in the expression levels of miRNAs may contribute to AML development. This review describes the main functions of non-coding RNA classes and presents miRNA biogenesis. This study aims to review recent reports about altered microRNA expression and their influence on AML cell survival, cell cycle, and apoptotic potential. Additionally, it summarizes the correlations between miRNAs and their target mRNAs in AML and outlines the role of particular miRNAs in AML subtypes according to ELN recommendations.

MicroRNAs Associated with a Bad Prognosis in Acute Myeloid Leukemia and Their Impact on Macrophage Polarization

MicroRNAs (miRNAs) are short, non-coding ribonucleic acids (RNAs) associated with gene expression regulation. Since the discovery of the first miRNA in 1993, thousands of miRNAs have been studied and they have been associated not only with physiological processes, but also with various diseases such as cancer and inflammatory conditions. MiRNAs have proven to be not only significant biomarkers but also an interesting therapeutic target in various diseases, including cancer. In acute myeloid leukemia (AML), miRNAs have been regarded as a welcome addition to the limited therapeutic armamentarium, and there is a vast amount of data on miRNAs and their dysregulation. Macrophages are innate immune cells, present in various tissues involved in both tissue repair and phagocytosis. Based on their polarization, macrophages can be classified into two groups: M1 macrophages with pro-inflammatory functions and M2 macrophages with an anti-inflammatory action. In cancer, M2 macrophages are associated with tumor evasion, metastasis, and a poor outcome. Several miRNAs have been associated with a poor prognosis in AML and with either the M1 or M2 macrophage phenotype. In the present paper, we review miRNAs with a reported negative prognostic significance in cancer with a focus on AML and analyze their potential impact on macrophage polarization.

Biallelic TET2 mutations and canonical ASXL1 mutations are frequent and cooccur in Blastic Plasmacytoid Dendritic Cell Neoplasm (BPDCN): An institutional experience and review of literature

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is recurrently mutated in epigenetic pathway genes. We studied the myeloid-related genetic mutations in a cohort of five patients with BPDCN and one paired relapse case at our institution and identified a high frequency of biallelic TET2 and canonical ASXL1 (c.1934dupG) mutations. The number of cases is small, but the variant allele fraction (VAF) sums of the TET2 mutations, as well as the persistence of TET2 mutations in a case of relapsed BPDCN, suggest an ancestral/founder nature of TET2 clones in the cases. Further literature review shows a high frequency of biallelic TET2 mutations in reported cases of BPDCN.

Cross-Talk between N6-Methyladenosine and Their Related RNAs Defined a Signature and Confirmed m6A Regulators for Diagnosis of Endometriosis

An RNA modification known as N6-methyladenosine (m6A) interacts with a range of coding and non-coding RNAs. The majority of the research has focused on identifying m6A regulators that are differentially expressed in endometriosis, but it has ignored their mechanisms that are derived from the alterations of modifications among RNAs, affecting the disease progression primarily. Here, we aimed to investigate the potential roles of m6A regulators in the diagnostic potency, immune microenvironment, and clinicopathological features of endometriosis through interacting genes. A GEO cohort was incorporated into this study. Variance expression profiling was executed via the "limma" R package. Pearson analysis was performed to investigate the correlations among 767 interacting lncRNAs, 374 interacting mRNAs, and 23 m6A regulators. K-means clustering analysis, based on patterns of mRNA modifications, was applied to perform clinical feature analysis. Infiltrating immune cells and stromal cells were calculated using the Cibersort method. An m6A-related risk model was created and supported by an independent risk assay. LASSO regression analysis and Cox analyses were implemented to determine the diagnostic genes. The diagnostic targets of endometriosis were verified using PCR and the WB method. Results: A thorough investigation of the m6A modification patterns in the GEO database was carried out, based on mRNAs and lncRNAs related to these m6A regulators. Two molecular subtypes were identified using unsupervised clustering analysis, resulting in further complex infiltration levels of immune microenvironment cells in diversified endometriosis pathology types. We identified two m6A regulators, namely METTL3 and YTHDF2, as diagnostic targets of endometriosis following the usage of overlapping genes to construct a diagnostic m6A signature of endometriosis through multivariate logistic regression, and we validated it using independent GSE86534 and GSE105764 cohorts. Finally, we found that m6A alterations might be one of the important reasons for the progression of endometriosis, especially with significant downregulation of the expressions of METTL3 and YTHDF2. Finally, m6A modification patterns have significant effects on the diversity and complexity of the progression and immune microenvironment, and might be key diagnostic markers for endometriosis.

The Cohesin Complex and Its Interplay with Non-Coding RNAs

The cohesin complex is a multi-subunit protein complex initially discovered for its role in sister chromatid cohesion. However, cohesin also has several other functions and plays important roles in transcriptional regulation, DNA double strand break repair, and chromosome architecture thereby influencing gene expression and development in organisms from yeast to man. While most of these functions rely on protein–protein interactions, post-translational protein, as well as DNA modifications, non-coding RNAs are emerging as additional players that facilitate and modulate the function or expression of cohesin and its individual components. This review provides a condensed overview about the architecture as well as the function of the cohesin complex and highlights its multifaceted interplay with both short and long non-coding RNAs.

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

Background: The association between dysregulated microRNAs (miRNAs) and acute myeloid leukemia (AML) is well known. However, our understanding of the regulatory role of miRNAs in the cytogenetically normal AML (CN-AML) subtype pathway is still poor. The current study integrated miRNA and mRNA profiles to explore novel miRNA-mRNA interactions that affect the regulatory patterns of de novo CN-AML. Methods: We utilized a multiplexed nanoString nCounter platform to profile both miRNAs and mRNAs using similar sets of patient samples (n = 24). Correlations were assessed, and an miRNA-mRNA network was constructed. The underlying biological functions of the mRNAs were predicted by gene enrichment. Finally, the interacting pairs were assessed using TargetScan and microT-CDS. We identified 637 significant negative correlations (false discovery rate <0.05). Results: Network analysis revealed a cluster of 12 miRNAs representing the majority of mRNA targets. Within the cluster, five miRNAs (miR-495-3p, miR-185-5p, let-7i-5p, miR-409-3p, and miR-127-3p) were posited to play a pivotal role in the regulation of CN-AML, as they are associated with the negative regulation of myeloid leukocyte differentiation, negative regulation of myeloid cell differentiation, and positive regulation of hematopoiesis. Conclusion: Three novel interactions in CN-AML were predicted as let-7i-5p:HOXA9, miR-495-3p:PIK3R1, and miR-495-3p:CDK6 may be responsible for regulating myeloid cell differentiation in CN-AML.

Characteristics of Cohesin Mutation in Acute Myeloid Leukemia and Its Clinical Significance

The occurrence of gene mutation is a major contributor to the initiation and propagation of acute myeloid leukemia (AML). Accumulating evidence suggests that genes encoding cohesin subunits have a high prevalence of mutations in AML, especially in the t(8;21) subtype. Therefore, it is important to understand how cohesin mutations contribute to leukemogenesis. However, the fundamental understanding of cohesin mutation in clonal expansion and myeloid transformation in hematopoietic cells remains ambiguous. Previous studies briefly introduced the cohesin mutation in AML; however, an in-depth summary of mutations in AML was not provided, and the correlation between cohesin and AML1-ETO in t (8;21) AML was also not analyzed. By summarizing the major findings regarding the cohesin mutation in AML, this review aims to define the characteristics of the cohesin complex mutation, identify its relationships with co-occurring gene mutations, assess its roles in clonal evolution, and discuss its potential for the prognosis of AML. In particular, we focus on the function of cohesin mutations in RUNX1-RUNX1T1 fusion.

A comprehensive study of construction and analysis of competitive endogenous RNA networks in lung adenocarcinoma

BACKGROUND

Long noncoding RNAs (lncRNAs) have gain increasing attention in lung adenocarcinoma. In this study, we aimed at constructing and analyzing the lncRNAs and the related proteins based competitive endogenous RNA (ceRNA) network.

METHODS

RNA expression data of lung adenocarcinoma were extracted from the TCGA database. Differentially expressed (DE) lncRNAs, messenger RNAs (mRNAs) and microRNAs (miRNAs) were identified and then a DElncRNA-DEmiRNA-DEmRNA ceRNA network was constructed for lung adenocarcinoma. We also analyzed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEgenes. Kaplan-Meier survival curves were also been further utilized for exploring the prognostic factors.

RESULTS

After compared and calculated lncRNA, mRNA and miRNA expression profiles between lung adenocarcinoma and normal samples, 1709 differential expressed lncRNAs, 2554 differential expressed mRNAs and 116 differential expressed miRNAs were finally identified. Afterwards, a lncRNA mediated ceRNA network was constructed, according to the interactions among 544 pairs of DElncRNA-DEmiRNA relationships and 47 pairs of DEmiRNA-DEmRNA relationships. As for the survival analyses, we found 10 DElncRNAs, 25 DEmRNAs and 7 miRNAs have statistically prognostic significance for overall survival, respectively.

CONCLUSIONS

This study provides meaningful information for deeper understanding the underlying molecular mechanism of lung adenocarcinoma and for evaluating prognosis, which could monitor recurrence, guide clinical treatment drugs and subsequent related researches.