MicroRNA let-7b downregulates AML1-ETO oncogene expression in t(8;21) AML by targeting its 3'UTR

MicroRNA mediated gene regulatory circuits leads to machine learning based preliminary detection of Acute Myeloid Leukemia

Acute Myeloid Leukemia (AML) can be detected based on morphology, cytochemistry, immunological markers, and cytogenetics. MicroRNAs (miRNAs) influence key biological pathways in multiple haematological malignancies including AML. In this work, we have analysed the miRNome and the transcriptome of normal and AML samples and have identified the significant set of miRNA-target mRNA pairs present within AML- Peripheral Blood and AML- Bone Marrow samples from both tissue and cell lines. The miRNA target genes are further filtered based on their functional significance in AML system. These filtered genes constitute the set of selected miRNA target features, which have been finally used for developing machine learning based prediction tool, 'TbAMLPred' for preliminary detection of AML. This model implements both unsupervised clustering and supervised classification algorithms that would increase the reliability of prediction. Our results show that the selected miRNA target-based features can separate the control and disease samples linearly. Overall, we put forward 'TbAMLPred' for a non-invasive mode of preliminary AML diagnosis in future. Github link for accessing TbAMLPred: https://github.com/zglabDIB/TbAMLPred.

Competing endogenous RNA networks related to prognosis in chronic lymphocytic leukemia: comprehensive analyses and construction of a novel risk score model

BACKGROUND

Chronic lymphocytic leukemia (CLL) is a heterogeneous B-cell malignancy that lacks specific biomarkers and drug targets. Competing endogenous RNAs (ceRNAs) play vital roles in oncogenesis and tumor progression by sponging microRNAs (miRNAs). Nevertheless, the regulatory mechanisms of survival-related ceRNA networks in CLL remain to be uncovered.

METHODS

We included 865 de novo CLL patients to investigate RNA expression profiles and Illumina sequencing was performed on four CLL patients, two CLL cell lines and six healthy donors in our center. According to univariate Cox regression, LASSO regression as well as multivariate Cox regression analyses, we established a novel risk score model in CLL patients. Immune signatures were compared between the low- and high-risk groups with CIBERSORT and ESTIMATE program. Afterwards, we analyzed the relationship between differentially expressed miRNAs (DEmiRNAs) and IGHV mutational status, p53 mutation status and del17p. Based on the survival analyses and differentially expressed RNAs with targeting relationships, the lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed. In addition, the circRNA circ_0002078/miR-185-3p/TCF7L1 axis was verified and their interrelations were delineated by dual-luciferase reporter gene assay.

RESULTS

Totally, 57 differentially expressed mRNAs (DEmRNAs) and 335 DEmiRNAs were identified between CLL patient specimens and normal B cells. A novel risk score model consisting of HTN3, IL3RA and NCK1 was established and validated. The concordance indexes of the model were 0.825, 0.719 and 0.773 in the training, test and total sets, respectively. The high-risk group was related to del(13q14) as well as shorter overall survival (OS). Moreover, we identified DEmiRNAs that related to cytogenetic abnormality of CLL patients, which revealed that miR-324-3p was associated with IGHV mutation, p53 mutation and del17p. The survival-related lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed to further facilitate the development of potential predictive biomarkers. Besides, the expression of circ_0002078 and TCF7L1 were significantly elevated and miR-185-3p was obviously decreased in CLL patients. Circ_0002078 regulated TCF7L1 expression by competing with TCF7L1 for miR-185-3p.

CONCLUSIONS

The comprehensive analyses of RNA expression profiles provide pioneering insights into the molecular mechanisms of CLL. The novel risk score model and survival-related ceRNA networks promote the development of prognostic biomarkers and potential therapeutic vulnerabilities for CLL.

Prognostic value and potential mechanism of long non-coding RNA Lnc-SMIM20-1 in acute myeloid leukemia

OBJECTIVES

Acute myeloid leukemia (AML) is a common hematologic malignancy with high heterogeneity and poor prognosis. Although long non-coding RNAs (lncRNAs) have been used as biomarkers for tumors, the clinical relevance of numerous lncRNAs in AML remains to be investigated.

RESEARCH DESIGN AND METHODS

Differentially expressed lncRNAs between AML and normal peripheral blood samples were identified using DESeq2. Pan-cancer analysis was performed by GEPIA tool. Kaplan-Meier survival curve was applied for prognosis analysis. KEGG pathway analysis and GSEA were used for functional enrichment. The ceRNA network was constructed by GDCRNAtools.

RESULTS

Lnc-SMIM20-1 was most highly expressed in AML and up-regulated in the TCGA-AML cohort compared to normal tissues. Patients with high expression of Lnc-SMIM20-1 had poor overall prognosis both in the TCGA adult AML cohort and the TARGET pediatric AML cohort, no matter whether they were treated with chemotherapy or allo-HSCT. Lnc-SMIM20-1 might participate in cancer-associated signaling pathways and immune-related signaling pathways by interacting with four microRNAs and 20 mRNAs.

CONCLUSION

Lnc-SMIM20-1 was up-regulated in AML acting as a stable poor prognostic factor. The prognostic impact of Lnc-SMIM20-1 cannot be overcome by allo-HSCT. Our findings provide insight into the clinical relevance of Lnc-SMIM20-1 in AML; aiming to progress the development of novel therapeutics.

Acute Myeloid Leukemia: New Multiomics Molecular Signatures and Implications for Systems Medicine Diagnostics and Therapeutics Innovation

Acute myeloid leukemia (AML) is a common, complex, and multifactorial malignancy of the hematopoietic system. AML diagnosis and treatment outcomes display marked heterogeneity and patient-to-patient variations. To date, AML-related biomarker discovery research has employed single omics inquiries. Multiomics analyses that reconcile and integrate the data streams from multiple levels of the cellular hierarchy, from genes to proteins to metabolites, offer much promise for innovation in AML diagnostics and therapeutics. We report, in this study, a systems medicine and multiomics approach to integrate the AML transcriptome data and reporter biomolecules at the RNA, protein, and metabolite levels using genome-scale biological networks. We utilized two independent transcriptome datasets (GSE5122, GSE8970) in the Gene Expression Omnibus database. We identified new multiomics molecular signatures of relevance to AML: miRNAs (e.g., mir-484 and miR-519d-3p), receptors (ACVR1 and PTPRG), transcription factors (PRDM14 and GATA3), and metabolites (in particular, amino acid derivatives). The differential expression profiles of all reporter biomolecules were crossvalidated in independent RNA-Seq and miRNA-Seq datasets. Notably, we found that PTPRG holds important prognostication potential as evaluated by Kaplan-Meier survival analyses. The multiomics relationships unraveled in this analysis point toward the genomic pathogenesis of AML. These multiomics molecular leads warrant further research and development as potential diagnostic and therapeutic targets.

Alternative polyadenylation dysregulation contributes to the differentiation block of acute myeloid leukemia

Posttranscriptional regulation has emerged as a driver for leukemia development and an avenue for therapeutic targeting. Among posttranscriptional processes, alternative polyadenylation (APA) is globally dysregulated across cancer types. However, limited studies have focused on the prevalence and role of APA in myeloid leukemia. Furthermore, it is poorly understood how altered poly(A) site usage of individual genes contributes to malignancy or whether targeting global APA patterns might alter oncogenic potential. In this study, we examined global APA dysregulation in patients with acute myeloid leukemia (AML) by performing 3' region extraction and deep sequencing (3'READS) on a subset of AML patient samples along with healthy hematopoietic stem and progenitor cells (HSPCs) and by analyzing publicly available data from a broad AML patient cohort. We show that patient cells exhibit global 3' untranslated region (UTR) shortening and coding sequence lengthening due to differences in poly(A) site (PAS) usage. Among APA regulators, expression of FIP1L1, one of the core cleavage and polyadenylation factors, correlated with the degree of APA dysregulation in our 3'READS data set. Targeting global APA by FIP1L1 knockdown reversed the global trends seen in patients. Importantly, FIP1L1 knockdown induced differentiation of t(8;21) cells by promoting 3'UTR lengthening and downregulation of the fusion oncoprotein AML1-ETO. In non-t(8;21) cells, FIP1L1 knockdown also promoted differentiation by attenuating mechanistic target of rapamycin complex 1 (mTORC1) signaling and reducing MYC protein levels. Our study provides mechanistic insights into the role of APA in AML pathogenesis and indicates that targeting global APA patterns can overcome the differentiation block in patients with AML.

Emerging role of let-7 family in the pathogenesis of hematological malignancies

Let-7 includes a family of miRNA which are implicated in the developmental processes as well as carcinogenesis. This miRNA family has been shown to influence pathogenesis of a variety of hematological malignancies through changing expression of a number of oncogenic pathways, particularly those related with MYC. Expression of these miRNAs has been found to be different between distinct hematological malignancies or even between cytogenetically-defined subgroups of a certain malignancy. In the current review, we summarize the data regarding biogenesis, genomic locations, targets and regulatory network of this miRNA family in the context of hematological malignancies.

Transcription Factors, R-Loops and Deubiquitinating Enzymes: Emerging Targets in Myelodysplastic Syndromes and Acute Myeloid Leukemia

Simple Summary

The advent of DNA massive sequencing technologies has allowed for the first time an extensive look into the heterogeneous spectrum of genes and mutations underpinning myelodysplastic syndromes (MDSs) and acute myeloid leukemia (AML). In this review, we wish to explore the most recent advances and the rationale for the potential therapeutic interest of three main actors in myelo-leukemic transformation: transcription factors that govern myeloid differentiation; RNA splicing factors, which ensure proper mRNA maturation and whose mutations increase R-loops formation; and deubiquitinating enzymes, which contribute to genome stability in hematopoietic stem cells (HSCs).

Abstract

Myeloid neoplasms encompass a very heterogeneous family of diseases characterized by the failure of the molecular mechanisms that ensure a balanced equilibrium between hematopoietic stem cells (HSCs) self-renewal and the proper production of differentiated cells. The origin of the driver mutations leading to preleukemia can be traced back to HSC/progenitor cells. Many properties typical to normal HSCs are exploited by leukemic stem cells (LSCs) to their advantage, leading to the emergence of a clonal population that can eventually progress to leukemia with variable latency and evolution. In fact, different subclones might in turn develop from the original malignant clone through accumulation of additional mutations, increasing their competitive fitness. This process ultimately leads to a complex cancer architecture where a mosaic of cellular clones—each carrying a unique set of mutations—coexists. The repertoire of genes whose mutations contribute to the progression toward leukemogenesis is broad. It encompasses genes involved in different cellular processes, including transcriptional regulation, epigenetics (DNA and histones modifications), DNA damage signaling and repair, chromosome segregation and replication (cohesin complex), RNA splicing, and signal transduction. Among these many players, transcription factors, RNA splicing proteins, and deubiquitinating enzymes are emerging as potential targets for therapeutic intervention.

Gene Transcription as a Therapeutic Target in Leukemia

Blood malignancies often arise from undifferentiated hematopoietic stem cells or partially differentiated stem-like cells. A tight balance of multipotency and differentiation, cell division, and quiescence underlying normal hematopoiesis requires a special program governed by the transcriptional machinery. Acquisition of drug resistance by tumor cells also involves reprogramming of their transcriptional landscape. Limiting tumor cell plasticity by disabling reprogramming of the gene transcription is a promising strategy for improvement of treatment outcomes. Herein, we review the molecular mechanisms of action of transcription-targeted drugs in hematological malignancies (largely in leukemia) with particular respect to the results of clinical trials.