miR-181a is a novel player in the STAT3-mediated survival network of TCRαβ+ CD8+ T large granular lymphocyte leukemia

Assmann, Jorn L.J.C.; León, Leticia G.; Stavast, Christiaan J.; Bogaerdt, Sanne E. van den; Schilperoord-Vermeulen, Joyce; Sandberg, Yorick; Bellido, Mar; Erkeland, Stefan J.; Feith, David J.; Loughran, Thomas P.; Langerak, Anton W.

doi:10.1038/s41375-021-01480-2

Cited by 11 publications

(5 citation statements)

References 40 publications

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“…It is possible that miR-181a might regulate the expression of transcription factors that affect BMPR2 level. This is in agreement with published results demonstrating that STAT3 is transcription factor regulating BMPR2 expression ( 42 ) while miR-181 regulates the expression of STAT3 ( 43 ). TGF-β can regulate the expression of miRNAs by regulating several cellular processes, including transcription and post-transcriptional maturation of miRNA precursors.…”

Section: Discussionsupporting

confidence: 93%

TGF‑β1 affects the renal cancer miRNome and regulates tumor cells proliferation

et al. 2022

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TGF-β1 is a pleiotropic cytokine that can either promote or inhibit cancer development and progression. It was previously found that TGF-β1 can regulate the expression of several microRNAs (miR or miRNA) involved in the progression of renal cell carcinoma (Rcc). Therefore, the present study aimed to analyze the effects of TGF-β1 on the global Rcc miRNome. It was found that TGF-β1 can regulate a complex network consisting of miRNAs and mRNAs involved in Rcc transformation. In particular, TGF-β1 was revealed to regulate the proliferation of Rcc cells while concomitantly modifying the expression of oncogenic regulators, including avian erythroblastosis virus E26 (V-Ets) oncogene homolog-1 (ETS1). In addition, TGF-β1 was demonstrated to regulate the expression of a number of miRNAs including miR-30c-5p, miR-155-5p, miR-181a-5p and miR-181b-5p. By contrast, TGF-β1 reciprocally modified the expression of genes encoding TGF-β1 receptors and SMAds, indicating a novel regulatory feedback mechanism mediated through the miRNAs. These data suggested that ETS1 served different roles in different subtypes of RCC tumors, specifically by functioning as an oncogene in clear cell Rcc while as a tumor suppressor in papillary Rcc.

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Section: Discussionsupporting

confidence: 93%

TGF‑β1 affects the renal cancer miRNome and regulates tumor cells proliferation

et al. 2022

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“…miR-145a-5p and miR-181-5p, which play key roles promoting granulopoiesis [ 45 ] and CD4+ T-cell maturation [ 16 , 46 ] respectively, were upregulated in this cluster. Steroids downregulated genes involved in lymphocyte activation, but upregulated the JAK/STAT pathway in CTP1, which can promote further overexpression of miR-181 family members [ 47 , 48 ]. JAK/STAT pathway can be activated by IL-6 and has been related to mortality in COVID-19 patients [ 49 , 50 ].…”

Section: Discussionmentioning

confidence: 99%

Transcriptomic clustering of critically ill COVID-19 patients

et al. 2022

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Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation has shown a mortality benefit.In a cohort of 56 critically-ill COVID-19 patients, peripheral blood transcriptomes were obtained at admission in an Intensive Care Unit (ICU) and clustered using an unsupervised algorithm. Differences in gene expression, circulating microRNAs (c-miRNA) and clinical data between clusters were assessed, and circulating cell populations estimated from sequencing data. A transcriptomic signature was defined and applied to an external cohort to validate the findings.We identified two transcriptomic clusters characterised by expression of either interferon-related or immune checkpoint genes, respectively. Steroids have cluster-specific effects, decreasing lymphocyte activation in the former but promoting B-cell activation in the latter. These profiles have different ICU outcome, in spite of no major clinical differences at ICU admission. A transcriptomic signature was used to identify these clusters in two external validation cohorts (with 50 and 60 patients), yielding similar results.These results reveal different underlying pathogenetic mechanisms and illustrate the potential of transcriptomics to identify patient endotypes in severe COVID-19, aimed to ultimately personalise their therapies.

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“…miR-181a has been shown to target PTEN , a gene responsible for apoptosis regulation [ 25 ]. It has also been shown to play a role in the regulation of the Wnt, STAT3 and RAS/MAPK pathways, which have been implicated in leukemia development [ 26 , 27 , 28 ]. miR-181a has been shown to increase cell sensitivity to chemotherapeutic drugs by targeting several antiapoptotic genes [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

MicroRNAs in Leukemias: A Clinically Annotated Compendium

Turk

Calin

Kunej

2022

IJMS

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Leukemias are a group of malignancies of the blood and bone marrow. Multiple types of leukemia are known, however reliable treatments have not been developed for most leukemia types. Furthermore, even relatively reliable treatments can result in relapses. MicroRNAs (miRNAs) are a class of short, noncoding RNAs responsible for epigenetic regulation of gene expression and have been proposed as a source of potential novel therapeutic targets for leukemias. In order to identify central miRNAs for leukemia, we conducted data synthesis using two databases: miRTarBase and DISNOR. A total of 137 unique miRNAs associated with 16 types of leukemia were retrieved from miRTarBase and 86 protein-coding genes associated with leukemia were retrieved from the DISNOR database. Based on these data, we formed a visual network of 248 miRNA-target interactions (MTI) between leukemia-associated genes and miRNAs associated with ≥4 leukemia types. We then manually reviewed the literature describing these 248 MTIs for interactions identified in leukemia studies. This manually curated data was then used to visualize a network of 64 MTIs identified in leukemia patients, cell lines and animal models. We also formed a visual network of miRNA-leukemia associations. Finally, we compiled leukemia clinical trials from the ClinicalTrials database. miRNAs with the highest number of MTIs were miR-125b-5p, miR-155-5p, miR-181a-5p and miR-19a-3p, while target genes with the highest number of MTIs were TP53, BCL2, KIT, ATM, RUNX1 and ABL1. The analysis of 248 MTIs revealed a large, highly interconnected network. Additionally, a large MTI subnetwork was present in the network visualized from manually reviewed data. The interconnectedness of the MTI subnetwork suggests that certain miRNAs represent central disease molecules for multiple leukemia types. Additional studies on miRNAs, their target genes and associated biological pathways are required to elucidate the therapeutic potential of miRNAs in leukemia.

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miR-181a is a novel player in the STAT3-mediated survival network of TCRαβ+ CD8+ T large granular lymphocyte leukemia

Cited by 11 publications

References 40 publications

TGF‑β1 affects the renal cancer miRNome and regulates tumor cells proliferation

TGF‑β1 affects the renal cancer miRNome and regulates tumor cells proliferation

Transcriptomic clustering of critically ill COVID-19 patients

MicroRNAs in Leukemias: A Clinically Annotated Compendium

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