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microRNA as Therapeutic Target

A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Cell and Gene Therapy".

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 79020

Special Issue Editor

Special Issue Information

Dear Colleagues,

It is known that miRNAs can play critical roles during disease progression. However, it is not frequent that they are treated as a therapeutic target. However, because of the advent of RNA drug discovery, more and more miRNAs are expected to be therapeutic targets. The submission of any kind of studies related to the identification of novel miRNAs as drug targets, the proposal of possible therapeutic targets of miRNAs, and experimental validations of therapeutic application of miRNA in vivo as well as in vitro, are welcome for this Special Issue.

Prof. Y-H. Taguchi
Guest Editor

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Keywords

  • Epigenetic therapy
  • RNA drug
  • drug delivery
  • exosome miRNA
  • miRNA based therapy
  • drug target miRNA
  • miRNA based therapy
  • RNA editing
  • epitrancripotome

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Published Papers (12 papers)

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22 pages, 10349 KiB  
Article
FAM64A: A Novel Oncogenic Target of Lung Adenocarcinoma Regulated by Both Strands of miR-99a (miR-99a-5p and miR-99a-3p)
by Keiko Mizuno, Kengo Tanigawa, Nijiro Nohata, Shunsuke Misono, Reona Okada, Shunichi Asai, Shogo Moriya, Takayuki Suetsugu, Hiromasa Inoue and Naohiko Seki
Cells 2020, 9(9), 2083; https://doi.org/10.3390/cells9092083 - 11 Sep 2020
Cited by 16 | Viewed by 2851
Abstract
Lung adenocarcinoma (LUAD) is the most aggressive cancer and the prognosis of these patients is unfavorable. We revealed that the expression levels of both strands of miR-99a (miR-99a-5p and miR-99a-3p) were significantly suppressed in several cancer tissues. Analyses of large The [...] Read more.
Lung adenocarcinoma (LUAD) is the most aggressive cancer and the prognosis of these patients is unfavorable. We revealed that the expression levels of both strands of miR-99a (miR-99a-5p and miR-99a-3p) were significantly suppressed in several cancer tissues. Analyses of large The Cancer Genome Atlas (TCGA) datasets showed that reduced miR-99a-5p or miR-99a-3p expression is associated with worse prognoses in LUAD patients (disease-free survival (DFS): p = 0.1264 and 0.0316; overall survival (OS): p = 0.0176 and 0.0756, respectively). Ectopic expression of these miRNAs attenuated LUAD cell proliferation, suggesting their tumor-suppressive roles. Our in silico analysis revealed 23 putative target genes of pre-miR-99a in LUAD cells. Among these targets, high expressions of 19 genes were associated with worse prognoses in LUAD patients (OS: p < 0.05). Notably, FAM64A was regulated by both miR-99a-5p and miR-99a-3p in LUAD cells, and its aberrant expression was significantly associated with poor prognosis in LUAD patients (OS: p = 0.0175; DFS: p = 0.0276). FAM64A knockdown using siRNAs suggested that elevated FAM64A expression contributes to cancer progression. Aberrant FAM64A expression was detected in LUAD tissues by immunostaining. Taken together, our miRNA-based analysis might be effective for identifying prognostic and therapeutic molecules in LUAD. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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Figure 1

Figure 1
<p>Downregulation of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> in LUAD. (<b>A</b>) Comparison of the expression levels of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> between tumor and non-tumor tissues in paired (left) and non-paired (right) LUAD clinical specimens from TCGA datasets. (<b>B</b>) Positive correlation between the relative expression level of <span class="html-italic">miR-99a-5p</span> and that of <span class="html-italic">miR-99a-3p</span> in clinical specimens according to Spearman’s rank tests.</p>
Full article ">Figure 2
<p>Clinical significance of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> expression in LUAD. (<b>A</b>) The patients were divided into two groups according to the median expression level of <span class="html-italic">miR-99a-5p</span> or <span class="html-italic">miR-99a-3p</span>: high (red lines) and low (blue lines) expression groups. (<b>B</b>) The patients were divided into two groups, top 25% and low 25%. High expression of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> is represented by red lines; low expression of these miRNAs is represented by blue lines.</p>
Full article ">Figure 3
<p>Functional assays of cell proliferation and cell cycle arrest following ectopic expression of <span class="html-italic">miR-99a-5p</span> or <span class="html-italic">miR-99a-3p</span> in LUAD cell lines (A549 and H1299 cells). (<b>A</b>) Cell proliferation assessed using XTT assays at 72 h after miRNA transfection (* <span class="html-italic">p</span> &lt; 0.0001). (<b>B</b>) Flow cytometric analysis of the cell cycle phase distribution of control cells and cells transfected with <span class="html-italic">miR-99a-5p</span> or <span class="html-italic">miR-99a-3p</span>. Cells were evaluated at 72 h after miRNA transfection (* <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 4
<p>Identification of putative targets of <span class="html-italic">miR-99a-5p</span> or <span class="html-italic">miR-99a-3p</span> regulation in LUAD cells. Prediction of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> target genes using the TargetScanHuman, cBioportal and LinkedOmics databases. Venn diagrams represent the number of putative target genes regulated by <span class="html-italic">miR-99a-5p</span> or <span class="html-italic">miR-99a-3p</span>.</p>
Full article ">Figure 5
<p>Clinical significance of pre-<span class="html-italic">miR-99a</span> target genes in TCGA database. Kaplan–Meier survival curves and log-rank comparisons of patients with LUAD using TCGA datasets. Patients were divided into two groups according to the median expression of each pre-<span class="html-italic">miR-99a</span> target gene evaluated: high and low expression groups. The red and blue lines represent the high and low expression groups, respectively. High expression mRNA of 18 genes (<span class="html-italic">CKS1B</span>, <span class="html-italic">KCMF1</span>, <span class="html-italic">CENPF</span>, <span class="html-italic">CASC5</span>, <span class="html-italic">MKI67</span>, <span class="html-italic">ESCO2</span>, <span class="html-italic">FANCI</span>, <span class="html-italic">SGOL1</span>, <span class="html-italic">MCM4</span>, <span class="html-italic">KIF11</span>, <span class="html-italic">NEK2</span>, <span class="html-italic">MTHFD2</span>, <span class="html-italic">NCAPG</span>, <span class="html-italic">RRM2</span>, <span class="html-italic">FAM136A</span>, <span class="html-italic">ZWINT</span>, <span class="html-italic">CDK1</span> and <span class="html-italic">CDKN3</span>) significantly predicted worse survival (5-year overall survival rate) in patients with LUAD. The expression data were downloaded from <a href="http://www.oncolnc.org" target="_blank">http://www.oncolnc.org</a>.</p>
Full article ">Figure 5 Cont.
<p>Clinical significance of pre-<span class="html-italic">miR-99a</span> target genes in TCGA database. Kaplan–Meier survival curves and log-rank comparisons of patients with LUAD using TCGA datasets. Patients were divided into two groups according to the median expression of each pre-<span class="html-italic">miR-99a</span> target gene evaluated: high and low expression groups. The red and blue lines represent the high and low expression groups, respectively. High expression mRNA of 18 genes (<span class="html-italic">CKS1B</span>, <span class="html-italic">KCMF1</span>, <span class="html-italic">CENPF</span>, <span class="html-italic">CASC5</span>, <span class="html-italic">MKI67</span>, <span class="html-italic">ESCO2</span>, <span class="html-italic">FANCI</span>, <span class="html-italic">SGOL1</span>, <span class="html-italic">MCM4</span>, <span class="html-italic">KIF11</span>, <span class="html-italic">NEK2</span>, <span class="html-italic">MTHFD2</span>, <span class="html-italic">NCAPG</span>, <span class="html-italic">RRM2</span>, <span class="html-italic">FAM136A</span>, <span class="html-italic">ZWINT</span>, <span class="html-italic">CDK1</span> and <span class="html-italic">CDKN3</span>) significantly predicted worse survival (5-year overall survival rate) in patients with LUAD. The expression data were downloaded from <a href="http://www.oncolnc.org" target="_blank">http://www.oncolnc.org</a>.</p>
Full article ">Figure 6
<p>Expression levels of pre-<span class="html-italic">miR-99a</span> target genes in LUAD clinical specimens. Using TCGA datasets, the expression levels of all 22 pre-<span class="html-italic">miR-99a</span> target genes evaluated were upregulated in LUAD clinical specimens (<span class="html-italic">n</span> = 475) compared with normal lung tissues (<span class="html-italic">n</span> = 54). The expression data were downloaded from <a href="http://firebrowse.org/" target="_blank">http://firebrowse.org/</a>.</p>
Full article ">Figure 6 Cont.
<p>Expression levels of pre-<span class="html-italic">miR-99a</span> target genes in LUAD clinical specimens. Using TCGA datasets, the expression levels of all 22 pre-<span class="html-italic">miR-99a</span> target genes evaluated were upregulated in LUAD clinical specimens (<span class="html-italic">n</span> = 475) compared with normal lung tissues (<span class="html-italic">n</span> = 54). The expression data were downloaded from <a href="http://firebrowse.org/" target="_blank">http://firebrowse.org/</a>.</p>
Full article ">Figure 7
<p>Clinical significance of <span class="html-italic">FAM64A</span> expression in LUAD. (<b>A</b>) Comparison of <span class="html-italic">FAM64A</span> expression levels between tumor and non-tumor tissues in paired (left) and non-paired (right) LUAD clinical specimens from TCGA datasets. Upregulation of <span class="html-italic">FAM64A</span> was detected in LUAD tissues. (<b>B</b>) Correlations between the relative expression level of <span class="html-italic">FAM64A</span> and that of <span class="html-italic">miR-99a-5p</span> or <span class="html-italic">miR-99a-3p</span>. Spearman’s rank test showed a negative correlation between <span class="html-italic">FAM64A</span> and <span class="html-italic">miR-99a-5p</span> or <span class="html-italic">miR-99a-3p</span> expression levels in clinical specimens. (<b>C</b>) Kaplan–Meier survival curves and log-rank comparisons of patients with LUAD using TCGA database. Patients were divided into two groups according to the median <span class="html-italic">FAM64A</span> expression level: high and low expression groups. The red and blue lines represent the high and low expression groups, respectively. (<b>D</b>) Forest plot of the multivariate analysis results assessing independent prognostic factors for disease-free and overall survival, including <span class="html-italic">FAM64A</span> expression (high vs. low) (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 8
<p>Overexpression of FAM64A in LUAD clinical specimens. (<b>A</b>–<b>C</b>) Immunohistochemical staining of FAM64A in LUAD tissues. Overexpression of FAM64A was detected in the cytoplasm and/or nuclei of cancer cells. On the other hand, expression of FAM64A was low in normal lung cells (<b>D</b>).</p>
Full article ">Figure 9
<p>Direct regulation of <span class="html-italic">FAM64A</span> by <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> in LUAD cells. (<b>A</b>) Significantly reduced expression of <span class="html-italic">FAM64A</span> mRNA by <span class="html-italic">miR-99s-5p</span> or <span class="html-italic">miR-99a-3p</span> transfection in A549 cells (at 72 h after transfection; * <span class="html-italic">p</span> &lt; 0.0001). (<b>B</b>) Predictions of <span class="html-italic">miR-99a</span>-binding sites using TargetScanHuman database analyses. Each miRNA strand (<span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span>) had one binding site in the 3′UTR of <span class="html-italic">FAM64A.</span> Dual-luciferase reporter assays showed that luminescence activity was reduced by co-transfection of the <span class="html-italic">FAM64A</span> wild-type vector (containing the <span class="html-italic">miR-99a-5</span>p-binding site) with <span class="html-italic">miR-99a-5</span><span class="html-italic">p</span> or of the <span class="html-italic">FAM64A</span> wild-type vector (containing the <span class="html-italic">miR-99a-3</span>p-binding site) with <span class="html-italic">miR-99a-3</span><span class="html-italic">p</span> in A549 cells. Normalized data were calculated as <span class="html-italic">Renilla</span>/firefly luciferase activity ratios (* <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 10
<p>Effect of <span class="html-italic">FAM64A</span> knockdown on cell proliferation and cell cycle arrest in LUAD cells. (<b>A</b>) Successful suppression of <span class="html-italic">FAM64A</span> expression by si<span class="html-italic">FAM64A</span>-1 or si<span class="html-italic">FAM64A</span>-2 transfection in A549 and H1299 cells. (<b>B</b>) Cell proliferation assessed by XTT assay at 72 h after miRNA transfection (* <span class="html-italic">p</span> &lt; 0.0001). (<b>C</b>) Flow cytometric analyses of cell cycle phase distributions in control cells and cells transfected with si<span class="html-italic">FAM64A</span>. The cells were assessed at 72 h after miRNA transfection (* <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 11
<p>TCGA database analysis of the clinical significance and function of <span class="html-italic">FAM64A</span> in LUAD clinical specimens. The bar graph shows the results of gene set enrichment analysis (GSEA) of the genes differentially expressed between high and low <span class="html-italic">FAM64A</span> expression groups in LUAD patients. Four representative GSEA plots are shown below for E2F targets, G2/M checkpoint, MYC target 1 variant 1 and mitotic spindle assembly with q-values &lt; 0.05. These pathway terms were significantly enriched in the high <span class="html-italic">FAM64A</span> expression group.</p>
Full article ">Figure 11 Cont.
<p>TCGA database analysis of the clinical significance and function of <span class="html-italic">FAM64A</span> in LUAD clinical specimens. The bar graph shows the results of gene set enrichment analysis (GSEA) of the genes differentially expressed between high and low <span class="html-italic">FAM64A</span> expression groups in LUAD patients. Four representative GSEA plots are shown below for E2F targets, G2/M checkpoint, MYC target 1 variant 1 and mitotic spindle assembly with q-values &lt; 0.05. These pathway terms were significantly enriched in the high <span class="html-italic">FAM64A</span> expression group.</p>
Full article ">Figure 12
<p>Associations of genome alterations and mutation counts with <span class="html-italic">FAM64A</span> expression in LUAD clinical specimens. Proportion of genome alterations (percentage of chromosome regions with copy number alterations relative to all regions evaluated; (<b>left</b>)) and the mutation count (number of mutational events per case; (<b>right</b>)) were significantly increased in the high compared with the low <span class="html-italic">FAM64A</span> expression group (*** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">
15 pages, 3696 KiB  
Article
The miR-28-5p Targetome Discovery Identified SREBF2 as One of the Mediators of the miR-28-5p Tumor Suppressor Activity in Prostate Cancer Cells
by Sofia Fazio, Gabriele Berti, Francesco Russo, Monica Evangelista, Romina D’Aurizio, Alberto Mercatanti, Marco Pellegrini and Milena Rizzo
Cells 2020, 9(2), 354; https://doi.org/10.3390/cells9020354 - 3 Feb 2020
Cited by 23 | Viewed by 3560
Abstract
miR-28-5p is downregulated in some tumor tissues in which it has been demonstrated to have tumor suppressor (TS) activity. Here, we demonstrate that miR-28-5p acts as a TS in prostate cancer (PCa) cells affecting cell proliferation/survival, as well as migration and invasion. Using [...] Read more.
miR-28-5p is downregulated in some tumor tissues in which it has been demonstrated to have tumor suppressor (TS) activity. Here, we demonstrate that miR-28-5p acts as a TS in prostate cancer (PCa) cells affecting cell proliferation/survival, as well as migration and invasion. Using the miRNA pull out assay and next generation sequencing, we collected the complete repertoire of miR-28-5p targets, obtaining a data set (miR-28-5p targetome) of 191 mRNAs. Filtering the targetome with TargetScan 7, PITA and RNA22, we found that 61% of the transcripts had miR-28-5p binding sites. To assign a functional value to the captured transcripts, we grouped the miR-28-5p targets into gene families with annotated function and showed that six transcripts belong to the transcription factor category. Among them we selected SREBF2, a gene with an important role in PCa. We validated miR-28-5p/SREBF2 interaction, demonstrating that SREBF2 inhibition affects almost all the tumor processes altered by miR-28-5p re-expression, suggesting that SREBF2 is an important mediator of miR-28-5p TS activity. Our findings support the identification of the targetome of cancer-related miRNAs as a tool to discover genes and pathways fundamental for tumor development, and potential new targets for anti-tumor therapy. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
Show Figures

Figure 1

Figure 1
<p>Effect of miR-28-5p re-expression in PCa cells. (<b>A</b>) Analysis of the miR-28-5p expression level by qRT-PCR in prostate cancer cell lines with respect to the normal cells RNA. (<b>B</b>) Relative expression level of miR-28-5p, evaluated by qRT-PCR, after miR-28-5p transfection in DU-145 cells. Cell migration (<b>C</b>,<b>D</b>) and invasion (<b>E</b>) of DU-145 cells after miR-28-5p overexpression evaluated by wound healing assay (<b>C</b>) and trans-well assay (<b>D</b>,<b>E</b>). (<b>F</b>) Relative expression of E-cadherin 1 (CDH1) and vimentin (VIM) in miR-28-5p overexpressing versus normal DU-145 cells. (<b>G</b>) Number of colonies formed in soft agar in DU-145 cells after miR-28-5p or CT overexpression. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, unpaired <span class="html-italic">t</span>-test.</p>
Full article ">Figure 2
<p>Association of miR-28-5p expression with clinical parameters in PCa patients. (<b>A</b>) Analysis of miR-28-5p expression level data of the Memorial Sloan Kettering Cancer Center (MSKCC) study’s patients. The significances according to the Kruskal–Wallis and Wilcoxon test are indicated. (<b>B</b>) Kaplan–Meier curves for recurrence-free survival events between MSKCC patients after dividing samples into two groups according to the 25st quartile of miR-28-5p expression level. Log-rank test’s <span class="html-italic">p</span>-value is shown. The miR-28-5p expression levels (log2RPMK) of TGCA PRAD samples are shown and grouped by pathological T stage (<b>C</b>) and Gleason score (<b>D</b>) with <span class="html-italic">p</span>-value from the Spearman’s test of association.</p>
Full article ">Figure 3
<p>Analysis of miR-28-5p targetome. (<b>A</b>) Evaluation of the enrichment of miR-28-5p selected targets in the miR-28<sub>BIO</sub> compared to miR-28<sub>CT</sub> pull out samples by qRT-PCR. (<b>B</b>) Pie chart representing the percentage of the predicted/non-predicted targets (upper panel) and the percentage of the targets predicted by one, two or three algorithms (lower panel) in the miR-28-5p targetome. (<b>C</b>) Results of the MSigDB gene sets analyses showing the identified genes families. (<b>D</b>) Enrichment of the miR-28-5p targets belonging to the “transcription factors” family in the miR-28<sub>BIO</sub> compared to miR-28<sub>CT</sub> pull out samples by qRT-PCR. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, unpaired <span class="html-italic">t</span>-test.</p>
Full article ">Figure 4
<p>Evaluation of the SREBF2 role in DU-145 PCa cells. (<b>A</b>) SREBF2 inhibition by siR-SREBF2 transfection in DU-145 cells analyzed by qRT-PCR and western blot analysis. Evaluation of SREBF2 silencing effect on proliferation (<b>B</b>), survival (<b>D</b>) migration (<b>E</b>,<b>F</b>) and invasion (<b>G</b>) in DU-145 cells. Relative expression of proliferation (Ki-67, c-MYC and cyclin D1 (CCND1)) (<b>C</b>), epithelial (E-cadherin 1 (CDH1)) and mesenchymal markers (Vimentin (VIM)) (<b>H</b>) in miR-28-5p overexpressing versus normal DU-145 cells. (<b>I</b>) Number of colonies formed in soft agar in DU-145 cells after miR-28-5p overexpression or SREBF2 silencing. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, unpaired <span class="html-italic">t</span>-test. ns, not significant.</p>
Full article ">Figure 5
<p>Analysis of miR-28-5p/SREBF2 interaction in PCa cells. (<b>A</b>) Quantification of SREBF2 mRNA and protein level in miR-28-5p versus CT transfected DU-145 cells. Relative luciferase activity after the cotransfection of pSREBF2<sub>3′UTR</sub> (<b>B</b>), pSREBF2<sub>5’UTR-ORFI</sub> (<b>C</b>), pSREBF2<sub>ORFII</sub> (<b>D</b>) and either CT or miR-28-5p. (<b>E</b>) Relative luciferase mRNA level, analyzed with qRT-PCR, in DU-145 cotransfected with miR-28-5p sensor and miR-28-5p mimic or inhibitor versus miR-28-5p sensor/CT cotransfected cells. (<b>F</b>) Relative luciferase mRNA level, analyzed by qRT-PCR, in DU-145 cotransfected with miR-28-5p sensor/siR-SREBF2 versus miR-28-5p sensor/CT cotransfected cells. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, unpaired <span class="html-italic">t</span>-test. ns, not significant.</p>
Full article ">
18 pages, 5907 KiB  
Article
Regulation of Oncogenic Targets by miR-99a-3p (Passenger Strand of miR-99a-Duplex) in Head and Neck Squamous Cell Carcinoma
by Reona Okada, Keiichi Koshizuka, Yasutaka Yamada, Shogo Moriya, Naoko Kikkawa, Takashi Kinoshita, Toyoyuki Hanazawa and Naohiko Seki
Cells 2019, 8(12), 1535; https://doi.org/10.3390/cells8121535 - 28 Nov 2019
Cited by 28 | Viewed by 4076
Abstract
To identify novel oncogenic targets in head and neck squamous cell carcinoma (HNSCC), we have analyzed antitumor microRNAs (miRNAs) and their controlled molecular networks in HNSCC cells. Based on our miRNA signature in HNSCC, both strands of the miR-99a-duplex (miR-99a-5p: [...] Read more.
To identify novel oncogenic targets in head and neck squamous cell carcinoma (HNSCC), we have analyzed antitumor microRNAs (miRNAs) and their controlled molecular networks in HNSCC cells. Based on our miRNA signature in HNSCC, both strands of the miR-99a-duplex (miR-99a-5p: the guide strand, and miR-99a-3p: the passenger strand) are downregulated in cancer tissues. Moreover, low expression of miR-99a-5p and miR-99a-3p significantly predicts poor prognosis in HNSCC, and these miRNAs regulate cancer cell migration and invasion. We previously showed that passenger strands of miRNAs have antitumor functions. Here, we screened miR-99a-3p-controlled oncogenes involved in HNSCC pathogenesis. Thirty-two genes were identified as miR-99a-3p-regulated genes, and 10 genes (STAMBP, TIMP4, TMEM14C, CANX, SUV420H1, HSP90B1, PDIA3, MTHFD2, BCAT1, and SLC22A15) significantly predicted 5-year overall survival. Notably, among these genes, STAMBP, TIMP4, TMEM14C, CANX, and SUV420H1 were independent prognostic markers of HNSCC by multivariate analyses. We further investigated the oncogenic function of STAMBP in HNSCC cells using knockdown assays. Our data demonstrated that the aggressiveness of phenotypes in HNSCC cells was attenuated by siSTAMBP transfection. Moreover, aberrant STAMBP expression was detected in HNSCC clinical specimens by immunohistochemistry. This strategy may contribute to the clarification of the molecular pathogenesis of this disease. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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Figure 1

Figure 1
<p>Expression and clinical significance of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> in HNSCC clinical specimens. (<b>A</b>) Expression of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> was significantly reduced in HNSCC clinical specimens and cell lines (FaDu and SAS cells). Data were normalized to the expression of RNU48. (<b>B</b>) Spearman’s rank tests showed positive correlations between expression levels of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> in clinical specimens. (<b>C</b>) Kaplan-Meier survival curve analyses of patients with HNSCC using data from The Cancer Genome Atlas (TCGA) database. Patients were divided into two groups according to miRNA expression, high group and low group (according to median expression). The red line shows the high expression group, and the blue line shows the low expression group.</p>
Full article ">Figure 2
<p>Functional assays of cell proliferation, migration, and invasion following ectopic expression of <span class="html-italic">miR-99a-5p</span> and <span class="html-italic">miR-99a-3p</span> in HNSCC cell lines (FaDu and SAS cells). (<b>A</b>) Cell proliferation was assessed using XTT assays. Data were collected 72 h after miRNA transfection (* <span class="html-italic">p</span> &lt; 0.0001). (<b>B</b>) Cell migration was assessed with membrane culture system. Data were collected 48 h after seeding the cells into the chambers (* <span class="html-italic">p</span> &lt; 0.0001). (<b>C</b>) Cell invasion was determined 48 h after seeding miRNA-transfected cells into chambers using Matrigel invasion assays (* <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Clinical significance of <span class="html-italic">miR-99a-3p</span> target genes in TCGA database. Among putative targets of <span class="html-italic">miR-99a-3p</span> in HNSCC cells, high expression of 10 genes (<span class="html-italic">STAMBP, TIMP4, TMEM14C, CANX, SUV420H1, HSP90B1, PDIA3, MTHFD2, BCAT1,</span> and <span class="html-italic">SLC22A15</span>) was significantly associated with poor prognosis in patients with HNSCC. Kaplan-Meier curves of 5-year overall survival for each gene are shown.</p>
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<p>Forest plot of multivariate analysis of five genes (<span class="html-italic">STAMBP, TIMP4, TMEM14C, SUV420H1,</span> and <span class="html-italic">CANX</span>), which were independent prognostic factors for overall survival after adjustment for patient age, disease, stage, and pathological grade.</p>
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<p>Expression of <span class="html-italic">STAMBP</span>/STAMBP was directly regulated by <span class="html-italic">miR-99a-3p</span> in HNSCC cells. (<b>A</b>) Expression of <span class="html-italic">STAMBP</span> mRNA was significantly reduced by <span class="html-italic">miR-99a-3p</span> transfection into FaDu and SAS cells (72 h after transfection; * <span class="html-italic">p</span> &lt; 0.0001, N.S.: Not significant). Expression of <span class="html-italic">GAPDH</span> was used as an internal control. (<b>B</b>) Expression of STAMBP protein was reduced by <span class="html-italic">miR-99a-3p</span> transfection into HNSCC cells (72 h after transfection). Expression of GAPDH was used as an internal control. (<b>C</b>) TargetScanHuman database analyses predicted one putative <span class="html-italic">miR-99a-3p</span> binding site in the 3′-UTR of <span class="html-italic">STAMBP</span>. (<b>D</b>) Dual luciferase reporter assays showed that luminescence activities were reduced by cotransfection with wild-type (<span class="html-italic">miR-99a-3p</span> binding site) vectors and <span class="html-italic">miR-99a-3p</span> in FaDu and SAS cells. Normalized data were calculated as Renilla/firefly luciferase activity ratios (N.S.: Not significant).</p>
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<p>Effects of <span class="html-italic">STAMBP</span> knockdown on cell proliferation, migration, and invasion in HNSCC cells. (<b>A</b>) Expression of <span class="html-italic">STAMBP</span> mRNA was significantly reduced by siRNA transfection into HNSCC cells (* <span class="html-italic">p</span> &lt; 0.0001). Expression of <span class="html-italic">GAPDH</span> was used as an internal control. (<b>B</b>) Expression of STAMBP protein was markedly reduced by siRNA transfection into HNSCC cells. Expression of GAPDH was used as an internal control. (<b>C</b>) Cell proliferation was assessed using XTT assays. Data were collected 72 h after miRNA transfection (* <span class="html-italic">p</span> &lt; 0.0001). (<b>D</b>) Cell migration was assessed with a membrane culture system. Data were collected 48 h after seeding the cells into the chambers (* <span class="html-italic">p</span> &lt; 0.0001). (<b>E</b>) Cell invasion was determined 48 h after seeding miRNA-transfected cells into chambers using Matrigel invasion assays (* <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Overexpression of STAMBP in HNSCC clinical specimens. (<b>A</b>–<b>I</b>) Expression of STAMBP was investigated by immunohistochemical staining of HNSCC clinical specimens. Overexpression of STAMBP was detected in the nuclei and/or cytoplasm of cancer cells. (<b>J</b>) Extremely weak expression of STAMBP in normal mucosa of larynx and pharynx.</p>
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Review

Jump to: Research

26 pages, 1117 KiB  
Review
Current Status of microRNA-Based Therapeutic Approaches in Neurodegenerative Disorders
by Sujay Paul, Luis Alberto Bravo Vázquez, Samantha Pérez Uribe, Paula Roxana Reyes-Pérez and Ashutosh Sharma
Cells 2020, 9(7), 1698; https://doi.org/10.3390/cells9071698 - 15 Jul 2020
Cited by 72 | Viewed by 7607
Abstract
MicroRNAs (miRNAs) are a key gene regulator and play essential roles in several biological and pathological mechanisms in the human system. In recent years, plenty of miRNAs have been identified to be involved in the development of neurodegenerative disorders (NDDs), thus making them [...] Read more.
MicroRNAs (miRNAs) are a key gene regulator and play essential roles in several biological and pathological mechanisms in the human system. In recent years, plenty of miRNAs have been identified to be involved in the development of neurodegenerative disorders (NDDs), thus making them an attractive option for therapeutic approaches. Hence, in this review, we provide an overview of the current research of miRNA-based therapeutics for a selected set of NDDs, either for their high prevalence or lethality, such as Alzheimer’s, Parkinson’s, Huntington’s, Amyotrophic Lateral Sclerosis, Friedreich’s Ataxia, Spinal Muscular Atrophy, and Frontotemporal Dementia. We also discuss the relevant delivery techniques, pertinent outcomes, their limitations, and their potential to become a new generation of human therapeutic drugs in the near future. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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Figure 1

Figure 1
<p>Scheme of miRNA biogenesis and the mode of action of RISC. The pri-miRNA is obtained in the nucleus by the translation of a specific gene and then transformed into pre-miRNA by the microprocessor complex conformed by DGCR8 and Drosha. Afterward, it is transported to the cytoplasm, where the DICER protein removes the loop of the molecule resulting in the miRNA duplex, thereafter, it joins the RISC by the AGO protein. When the RISC has total complementarity, the mRNA target is deadenylated, decapped, and completely degraded. Otherwise, partial complementarity can reduce or inhibit the translation and eventually cause mRNA degradation.</p>
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<p>The general flow for designing and testing a miRNA-based therapeutic approach to treat neurodegenerative diseases. Firstly, abnormally expressed miRNAs are detected in patients’ tissues, and are then later regulated by inhibiting or enhancing their function. Otherwise, specific synthetic miRNAs can be designed to target genes of interest. Later, these miRs must enter cells by an appropriate delivery system. The effect of administered miRNAs is then assessed in biologic models.</p>
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23 pages, 1374 KiB  
Review
The Promise and Challenges of Developing miRNA-Based Therapeutics for Parkinson’s Disease
by Simoneide S. Titze-de-Almeida, Cristina Soto-Sánchez, Eduardo Fernandez, James B. Koprich, Jonathan M. Brotchie and Ricardo Titze-de-Almeida
Cells 2020, 9(4), 841; https://doi.org/10.3390/cells9040841 - 31 Mar 2020
Cited by 52 | Viewed by 5821
Abstract
MicroRNAs (miRNAs) are small double-stranded RNAs that exert a fine-tuning sequence-specific regulation of cell transcriptome. While one unique miRNA regulates hundreds of mRNAs, each mRNA molecule is commonly regulated by various miRNAs that bind to complementary sequences at 3’-untranslated regions for triggering the [...] Read more.
MicroRNAs (miRNAs) are small double-stranded RNAs that exert a fine-tuning sequence-specific regulation of cell transcriptome. While one unique miRNA regulates hundreds of mRNAs, each mRNA molecule is commonly regulated by various miRNAs that bind to complementary sequences at 3’-untranslated regions for triggering the mechanism of RNA interference. Unfortunately, dysregulated miRNAs play critical roles in many disorders, including Parkinson’s disease (PD), the second most prevalent neurodegenerative disease in the world. Treatment of this slowly, progressive, and yet incurable pathology challenges neurologists. In addition to L-DOPA that restores dopaminergic transmission and ameliorate motor signs (i.e., bradykinesia, rigidity, tremors), patients commonly receive medication for mood disorders and autonomic dysfunctions. However, the effectiveness of L-DOPA declines over time, and the L-DOPA-induced dyskinesias commonly appear and become highly disabling. The discovery of more effective therapies capable of slowing disease progression –a neuroprotective agent–remains a critical need in PD. The present review focus on miRNAs as promising drug targets for PD, examining their role in underlying mechanisms of the disease, the strategies for controlling aberrant expressions, and, finally, the current technologies for translating these small molecules from bench to clinics. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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Figure 1
<p>Biological synthesis of endogenous microRNAs (miRNAs) and modulation by synthetic oligonucleotides. miRNAs are coded in mammalian DNA genes and transcribed by RNA polymerase II (Pol II) to form the primary miRNA (pri-miRNA). This long RNA receives the first processing by Drosha and DGCR8 enzymes in cell nucleus, with remotion of nucleotides outside the hairpin. The resulting miRNA precursor (pre-miRNA) moves to cytoplasm carried by Exportin 5. Dicer and TRBP enzymes execute the second round of processing, resulting in miRNA duplexes with 18–25 nucleotides. Sense strand is removed. The guide (or antisense) strand is the mature miRNA that will guide the RISC complex (miRISC) to target mRNAs bearing partially complementary sequences in 3’-UTR region. Silencing of miRNA-targeted mRNAs occurs through translational repression or degradation. AGO—Argonaute 2; CDS—Coding sequence region of mRNA; 3’-UTR-3’ untranslated region; DGCR8—DiGeorge syndrome critical region gene 8; Dicer—a ribonuclease enzyme; Drosha—a ribonuclease enzyme; miRISC—RISC complex associated with a miRNA; Pol II—RNA polymerase II; pre-miRNA—miRNA precursor; pri-miRNA—primary miRNA; RISC—RNA-induced silencing complex; TRBP—HIV-1 Trans-activation response (TAR) RNA-binding protein. Reprinted with permission from Titze-de-Almeida and Titze-de-Almeida 2018, with modifications [<a href="#B34-cells-09-00841" class="html-bibr">34</a>].</p>
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<p>Schematic representation of miRNAs in the healthy and Parkinsonian brain. MicroRNAs expressed in the central nervous system contributes to brain development and cell physiology. Instead, aberrantly expressed miRNAs play a role in pathological mechanisms in a parkinsonian brain (PD brain). Translating to clinics, miRNAs are candidate biomarkers of disease progression and promising targets for miRNA-based therapeutics.</p>
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14 pages, 743 KiB  
Review
Nanoparticle-Based Delivery of Tumor Suppressor microRNA for Cancer Therapy
by Clodagh P. O’Neill and Róisín M. Dwyer
Cells 2020, 9(2), 521; https://doi.org/10.3390/cells9020521 - 24 Feb 2020
Cited by 66 | Viewed by 7475
Abstract
Improved understanding of microRNA expression and function in cancer has revealed a range of microRNAs that negatively regulate many oncogenic pathways, thus representing potent tumor suppressors. Therapeutic targeting of the expression of these microRNAs to the site of tumors and metastases provides a [...] Read more.
Improved understanding of microRNA expression and function in cancer has revealed a range of microRNAs that negatively regulate many oncogenic pathways, thus representing potent tumor suppressors. Therapeutic targeting of the expression of these microRNAs to the site of tumors and metastases provides a promising avenue for cancer therapy. To overcome challenges associated with microRNA degradation, transient expression and poor targeting, novel nanoparticles are being developed and employed to shield microRNAs for tumor-targeted delivery. This review focuses on studies describing a variety of both natural and synthetic nanoparticle delivery vehicles that have been engineered for tumor-targeted delivery of tumor suppressor microRNAs in vivo. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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<p>Tumor suppressor miRNA encapsulation in nanoparticle formulations for delivery to primary tumors and metastases (image created using <a href="http://Biorender.com" target="_blank">Biorender.com</a>—paid subscription).</p>
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27 pages, 1939 KiB  
Review
RNA-Based Therapeutics: From Antisense Oligonucleotides to miRNAs
by Sarah Bajan and Gyorgy Hutvagner
Cells 2020, 9(1), 137; https://doi.org/10.3390/cells9010137 - 7 Jan 2020
Cited by 245 | Viewed by 17693
Abstract
The first therapeutic nucleic acid, a DNA oligonucleotide, was approved for clinical use in 1998. Twenty years later, in 2018, the first therapeutic RNA-based oligonucleotide was United States Food and Drug Administration (FDA) approved. This promises to be a rapidly expanding market, as [...] Read more.
The first therapeutic nucleic acid, a DNA oligonucleotide, was approved for clinical use in 1998. Twenty years later, in 2018, the first therapeutic RNA-based oligonucleotide was United States Food and Drug Administration (FDA) approved. This promises to be a rapidly expanding market, as many emerging biopharmaceutical companies are developing RNA interference (RNAi)-based, and RNA-based antisense oligonucleotide therapies. However, miRNA therapeutics are noticeably absent. miRNAs are regulatory RNAs that regulate gene expression. In disease states, the expression of many miRNAs is measurably altered. The potential of miRNAs as therapies and therapeutic targets has long been discussed and in the context of a wide variety of infections and diseases. Despite the great number of studies identifying miRNAs as potential therapeutic targets, only a handful of miRNA-targeting drugs (mimics or inhibitors) have entered clinical trials. In this review, we will discuss whether the investment in finding potential miRNA therapeutic targets has yielded feasible and practicable results, the benefits and obstacles of miRNAs as therapeutic targets, and the potential future of the field. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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Figure 1
<p>Mechanisms of RNA-based therapeutics that are dependent on the endogenous microRNA (miRNA) pathway. (<b>A</b>) miRNAs are encoded in the genome, often in the intron of protein-coding genes. The transcript, produced by RNA polymerase II, containing the miRNA forms a characteristic stem-loop structure which is processed in the nucleus by an RNases III enzyme, Drosha, to form an RNA hairpin (approx. 70 nucleotides) called the pre-miRNA. Pre-miRNA moves into the cytoplasm via exportin-5 (XPO-5), where it is further processed by Dicer, producing a double-stranded miRNA–miRNA* duplex. One strand of this duplex is loaded onto an Argonaute (Ago protein) to from the RNA-induced silencing complex (RISC). The other strand of the duplex (the passenger strand) is degraded. RISC is guided by the loaded miRNA strand which imperfectly binds to complementary sites commonly found in the 3’ untranslated region (UTR) of target mRNAs. RISC inhibits the translation of the bound mRNA and can cause deadenylation and degradation of the targeted transcript. Therapeutic miRNA mimics (<b>B</b>) are synthesized as miRNA duplexes. Upon entry into the cell, one strand binds to an endogenous Ago protein forming RISC, while the passenger strand degrades. The synthesized miRNA acts as a guide, directing the RISC to the therapeutic target, and inhibiting its translation. (<b>C</b>) AntagomiRs are single-stranded, synthesized, modified RNA molecules which are complementary to an endogenous miRNA. Upon entry into the cell, the antagomiR will bind to its target miRNA, preventing the miRNA from being loaded onto an Ago protein and forming RISC. (<b>D)</b> Once therapeutic siRNA duplexes enter the cell, one strand is loaded onto an Ago2 protein forming RISC. RISC is directed to the target mRNA by the loaded siRNA which binds with 100% complementarity to its target, Ago2 then cleaves the transcript. (<b>E</b>) DNA plasmids designed to encode short hairpin (sh) RNA enter the cell nucleus, where they are transcribed, producing an RNA with a characteristic stem-loop structure, allowing the RNA to enter the endogenous miRNA biogenesis pathway.</p>
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<p>Common Delivery Methods for RNA-based Therapeutics. (<b>A</b>) RNA-based therapeutics are often encapsulated, or attached on the surface of, nanoparticles to aid delivery of the drug into the cell. These nanoparticles are often modified with moieties such as cholesterol or polyethylene glycol (PEG) which aid uptake of the nanoparticle via the cell membrane. Some nanoparticles are directed to particular cells by the addition of a targeting moiety, often a ligand for a cell surface receptor specifically expressed on the target cell. Commonly, the nanoparticle enters the cell via endocytosis, forming an endosome, which, after environmental changes (e.g., lowered pH), degrades, releasing the RNA therapeutic into the cell. (<b>B</b>) Alternatively, some RNA therapeutics are directly conjugated to moieties to aid their transport across the cell membrane, e.g., cholesterol (<b>C</b>) Synthesized RNA therapeutics can be chemically modified to increase their stability and binding affinity and decrease their toxicity. LNA: locked nucleic acid (2′4′-methylene; 2′<span class="html-italic">O</span>Me: 2′-<span class="html-italic">O</span>-methyl; 2′MOE: 2′-<span class="html-italic">O</span>-methoxyethyl.</p>
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<p>Mechanism of approved therapeutics. (<b>A</b>) Nusinersen regulates splicing of the Survival Motor Neuron (<span class="html-italic">SMN)</span> 2 gene to treat patients with spinal muscular atrophy (SMA). Due to weak splice site, masked by the binding of hnRNP, the <span class="html-italic">SMN2</span> gene usually produces a truncated transcript lacking exon 7, which, when translated, produces a non-functional and unstable protein (SMN2∆7). Nusinersen (Spinraza<sup>TM</sup>, Biogen) is an antisense oligonucleotide (ASO) therapy that binds, via complementarity, to SMN2 pre-mRNA, displacing hnRNP, exposing the splice site and increasing the inclusion of exon 7, forming a full-length, mature SMN2 transcript. Once translated, this produces a full-length, functional SMN protein, which improves patient’s motor neuron function and slows disease progression. (<b>B</b>) Patisiran (Onpattro) reduces the production of transthyrethin (TTR) protein to reduce the formation of amyloid fibrils in hereditary transthyretin-mediated (hATTR) amyloidosis. Mutations in the <span class="html-italic">TTR</span> gene causes misfolding of the TTR protein, the misfolded protein aggregates into amyloid fibrils. Patisiran is a synthesized siRNA therapy, which is 100% complementary to a specific sequence in the 3′ UTR of the TTR mRNA. Once Patisiran enters the cell, one strand of the short interfering RNA (siRNA) duplex is loaded onto an Ago2 protein, forming RISC. RISC binds to the TTR transcript, which is subsequently cleaved by Ago2, therefore reducing TTR protein production, preventing further amyloidosis and improving patient’s quality of life.</p>
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39 pages, 3490 KiB  
Review
Dissimilar Appearances Are Deceptive–Common microRNAs and Therapeutic Strategies in Liver Cancer and Melanoma
by Lisa Linck-Paulus, Claus Hellerbrand, Anja K. Bosserhoff and Peter Dietrich
Cells 2020, 9(1), 114; https://doi.org/10.3390/cells9010114 - 2 Jan 2020
Cited by 15 | Viewed by 5255
Abstract
In this review, we summarize the current knowledge on miRNAs as therapeutic targets in two cancer types that were frequently described to be driven by miRNAs—melanoma and hepatocellular carcinoma (HCC). By focusing on common microRNAs and associated pathways in these—at first sight—dissimilar cancer [...] Read more.
In this review, we summarize the current knowledge on miRNAs as therapeutic targets in two cancer types that were frequently described to be driven by miRNAs—melanoma and hepatocellular carcinoma (HCC). By focusing on common microRNAs and associated pathways in these—at first sight—dissimilar cancer types, we aim at revealing similar molecular mechanisms that are evolved in microRNA-biology to drive cancer progression. Thereby, we also want to outlay potential novel therapeutic strategies. After providing a brief introduction to general miRNA biology and basic information about HCC and melanoma, this review depicts prominent examples of potent oncomiRs and tumor-suppressor miRNAs, which have been proven to drive diverse cancer types including melanoma and HCC. To develop and apply miRNA-based therapeutics for cancer treatment in the future, it is essential to understand how miRNA dysregulation evolves during malignant transformation. Therefore, we highlight important aspects such as genetic alterations, miRNA editing and transcriptional regulation based on concrete examples. Furthermore, we expand our illustration by focusing on miRNA-associated proteins as well as other regulators of miRNAs which could also provide therapeutic targets. Finally, design and delivery strategies of miRNA-associated therapeutic agents as well as potential drawbacks are discussed to address the question of how miRNAs might contribute to cancer therapy in the future. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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<p>MiRNA processing pathway. Long primary miRNA transcripts (pri-miRNA) are processed in the nucleus by Drosha and DGCR8 [<a href="#B43-cells-09-00114" class="html-bibr">43</a>,<a href="#B44-cells-09-00114" class="html-bibr">44</a>,<a href="#B45-cells-09-00114" class="html-bibr">45</a>,<a href="#B46-cells-09-00114" class="html-bibr">46</a>]. The pre-miRNA is transferred into the cytoplasm by Exportin 5 (XPO5) and further processed by Dicer and TRBP [<a href="#B47-cells-09-00114" class="html-bibr">47</a>,<a href="#B48-cells-09-00114" class="html-bibr">48</a>]. The resulting miRNA duplex is loaded onto AGO at which point one strand is degraded [<a href="#B51-cells-09-00114" class="html-bibr">51</a>,<a href="#B52-cells-09-00114" class="html-bibr">52</a>]. The remaining mature miRNA strand forms the “RNA induced silencing complex” (RISC) together with AGO and GW182 [<a href="#B51-cells-09-00114" class="html-bibr">51</a>,<a href="#B53-cells-09-00114" class="html-bibr">53</a>]. The main function of the RISC is the translational repression of complementary target mRNAs [<a href="#B54-cells-09-00114" class="html-bibr">54</a>].</p>
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<p><span class="html-italic">Let-7</span> members are strongly downregulated and function as potent tumor-suppressors in melanoma and hepatocellular carcinoma (HCC). References (numbers in brackets indicate according references of studies) showing differential expression (indicated by arrows) of single <span class="html-italic">let-7</span> family members in melanoma and HCC.</p>
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<p>Important tumor suppressive miRNAs and their impact on cancer cells. MiRNAs <span class="html-italic">let-7</span>, <span class="html-italic">miR-622</span> and <span class="html-italic">miR-26a</span> are downregulated during tumor development in both melanoma and HCC (and also many other cancer types) (indicated by red arrows), thereby influencing major target genes and according cellular pathways. Downregulation of <span class="html-italic">let-7</span> induces de-repression of integrin β3 promoting cancer cell migration and invasion [<a href="#B92-cells-09-00114" class="html-bibr">92</a>]. It further releases cell cycle promoting cyclins and CDKs [<a href="#B93-cells-09-00114" class="html-bibr">93</a>] and inhibits the cell cycle inhibitor p16 [<a href="#B133-cells-09-00114" class="html-bibr">133</a>]. Low expression of <span class="html-italic">let-7</span> interferes with apoptosis via induction of the antiapoptotic protein BCL-XL [<a href="#B132-cells-09-00114" class="html-bibr">132</a>]. Furthermore, cancer associated downregulation of <span class="html-italic">let-7</span> results in reduced oxidative phosphorylation, glycolysis and production of ROS [<a href="#B94-cells-09-00114" class="html-bibr">94</a>]. Downregulation of <span class="html-italic">miR-622</span> results in an increase of its target KRAS [<a href="#B5-cells-09-00114" class="html-bibr">5</a>,<a href="#B109-cells-09-00114" class="html-bibr">109</a>]. KRAS can also interfere with the apoptosis pathway via upregulation of BCL-XL [<a href="#B109-cells-09-00114" class="html-bibr">109</a>]. <span class="html-italic">MiR-622</span> downregulation also unreleases its target CXCR4 which mediates migration of tumor cells [<a href="#B141-cells-09-00114" class="html-bibr">141</a>]. Further, low <span class="html-italic">miR-622</span> expression induces de-repression of MAP4K4 promoting epithelial to mesenchymal transition (EMT) and invasiveness [<a href="#B142-cells-09-00114" class="html-bibr">142</a>,<a href="#B143-cells-09-00114" class="html-bibr">143</a>]. Low levels of <span class="html-italic">miR-26a</span> in tumor cells lead to increased integrin α5 expression and reduced E-cadherin expression inducing EMT [<a href="#B144-cells-09-00114" class="html-bibr">144</a>,<a href="#B145-cells-09-00114" class="html-bibr">145</a>,<a href="#B146-cells-09-00114" class="html-bibr">146</a>]. It further induces the release of anti-apoptotic SODD [<a href="#B147-cells-09-00114" class="html-bibr">147</a>]. Moreover, both <span class="html-italic">mir-622</span> and <span class="html-italic">miR-26a</span> are suppressed by EZH2 in tumor cells [<a href="#B141-cells-09-00114" class="html-bibr">141</a>,<a href="#B148-cells-09-00114" class="html-bibr">148</a>,<a href="#B149-cells-09-00114" class="html-bibr">149</a>]. Simultaneously, decreased <span class="html-italic">miR-26a</span> expression releases its target EZH2, creating a regulatory feedback loop [<a href="#B148-cells-09-00114" class="html-bibr">148</a>,<a href="#B149-cells-09-00114" class="html-bibr">149</a>,<a href="#B150-cells-09-00114" class="html-bibr">150</a>,<a href="#B151-cells-09-00114" class="html-bibr">151</a>].</p>
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<p><span class="html-italic">MiR-622</span> is a strongly downregulated tumor-suppressive miRNA in melanoma, HCC and also in other cancer types. Several studies (numbers in brackets indicate according references) showed differential expression (indicated by arrows) of <span class="html-italic">miR-622</span> in melanoma, HCC and other further cancer types.</p>
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<p>Downregulation of tumor-suppressor <span class="html-italic">miR-26a</span> in melanoma and HCC. Several studies (numbers in brackets indicate according references) showed differential expression of <span class="html-italic">miR-26a</span> in melanoma and HCC.</p>
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<p>Upregulation of OncomiR <span class="html-italic">miR-221</span> in melanoma and HCC. References (numbers in brackets indicate according references of studies) showing differential expression (indicated by arrows) of <span class="html-italic">miR-221</span> in melanoma and HCC.</p>
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<p>OncomiRs <span class="html-italic">miR-221</span> and <span class="html-italic">miR-210</span> and their impact on cancer cells. The miRNAs <span class="html-italic">miR-221</span> and <span class="html-italic">miR-210</span> are significantly upregulated during tumor development of melanoma and HCC (indicated by red arrows) which leads to interference with important cellular pathways. <span class="html-italic">MiR-221</span> downregulates the transcription factors c-FOS [<a href="#B196-cells-09-00114" class="html-bibr">196</a>] and AP2α [<a href="#B191-cells-09-00114" class="html-bibr">191</a>] and is regulated itself by c-Jun and the NFκB pathway [<a href="#B213-cells-09-00114" class="html-bibr">213</a>]. NFκB regulation also leads to suppression of the <span class="html-italic">miR-221</span> downstream genes Bcl-2, VEGF and MMP-9 thus inhibiting apoptosis [<a href="#B196-cells-09-00114" class="html-bibr">196</a>]. <span class="html-italic">MiR-221</span>-associated anti-apoptotic activity is further mediated by targeting caspase-3 [<a href="#B209-cells-09-00114" class="html-bibr">209</a>]. Regulation of Bcl-2, VEGF and MMP-9 by <span class="html-italic">miR-221</span> can also induce an invasive phenotype which is further mediated by <span class="html-italic">miR-221</span> suppressing SCD5 and thereby promoting EMT [<a href="#B193-cells-09-00114" class="html-bibr">193</a>]. Additional <span class="html-italic">miR-221</span> targets are c-Kit, p27Kip1/CDKN1B and CDKN1A whose downregulation in cancer induces cell proliferation [<a href="#B194-cells-09-00114" class="html-bibr">194</a>,<a href="#B195-cells-09-00114" class="html-bibr">195</a>,<a href="#B212-cells-09-00114" class="html-bibr">212</a>]. <span class="html-italic">MiR-210</span> can also influence EMT and migration via inhibition of TIMP2 [<a href="#B215-cells-09-00114" class="html-bibr">215</a>] and activation of VMP1 [<a href="#B216-cells-09-00114" class="html-bibr">216</a>]. Downregulation of <span class="html-italic">SMAD4</span> and <span class="html-italic">STAT6</span> by <span class="html-italic">miR-210</span> promotes angiogenesis [<a href="#B217-cells-09-00114" class="html-bibr">217</a>]. Further important targets of <span class="html-italic">miR-210</span> in tumor cells are HOX1A and PTPN1 interfering with the immune response [<a href="#B218-cells-09-00114" class="html-bibr">218</a>]. <span class="html-italic">MiR-210</span> expression is induced during hypoxia [<a href="#B219-cells-09-00114" class="html-bibr">219</a>,<a href="#B220-cells-09-00114" class="html-bibr">220</a>] through regulation by HIF1α [<a href="#B221-cells-09-00114" class="html-bibr">221</a>].</p>
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<p><span class="html-italic">MiR-210</span> is strongly upregulated and has oncogenic function in melanoma and HCC. References (numbers in brackets indicate according references of studies) showing differential expression (indicated by arrows) of <span class="html-italic">miR-210</span> in melanoma and HCC.</p>
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<p>Potential ways to therapeutically target miRNAs and miRNA-related enzymes. Red arrows indicate multiple approaches for targeting miRNAs for therapeutic purposes. Small molecule targeting of epigenetic enzymes, for example, histone deacetylases (HDACs) or specific transcription factors (TF) can reactivate the expression of tumor-suppressive miRNAs [<a href="#B196-cells-09-00114" class="html-bibr">196</a>,<a href="#B258-cells-09-00114" class="html-bibr">258</a>,<a href="#B266-cells-09-00114" class="html-bibr">266</a>,<a href="#B270-cells-09-00114" class="html-bibr">270</a>]. Drosha expression could be induced or <span class="html-italic">XPO5</span> expression could be inhibited by siRNA leading to induction or repression of tumorigenic miRNAs [<a href="#B271-cells-09-00114" class="html-bibr">271</a>,<a href="#B272-cells-09-00114" class="html-bibr">272</a>]. To inhibit binding of the negative regulator LIN28 to the tumor-suppressive miRNA <span class="html-italic">let-7</span>, short, loop-targeting “looptomiRs” can be used [<a href="#B273-cells-09-00114" class="html-bibr">273</a>]. Targeting Dicer could be a potentially promising approach for specific tumor conditions such as hypoxia [<a href="#B274-cells-09-00114" class="html-bibr">274</a>]. MiRNA modifying enzymes, such as ADAR or METTL, could also be approached by therapeutic strategies [<a href="#B261-cells-09-00114" class="html-bibr">261</a>,<a href="#B262-cells-09-00114" class="html-bibr">262</a>,<a href="#B263-cells-09-00114" class="html-bibr">263</a>,<a href="#B264-cells-09-00114" class="html-bibr">264</a>]. AGO is strongly downregulated in melanoma and re-expression could represent a therapeutic option [<a href="#B275-cells-09-00114" class="html-bibr">275</a>,<a href="#B276-cells-09-00114" class="html-bibr">276</a>]. The inhibitory effect of tumor-specific miRNAs on their target mRNAs could be inhibited by sequestering the miRNAs using, for example, lncRNAs as competing endogenous RNAs (ceRNAs) [<a href="#B277-cells-09-00114" class="html-bibr">277</a>,<a href="#B278-cells-09-00114" class="html-bibr">278</a>,<a href="#B279-cells-09-00114" class="html-bibr">279</a>], by small-molecule inhibitors [<a href="#B280-cells-09-00114" class="html-bibr">280</a>] or modified oligoribonucleotides (e.g., LNAs) [<a href="#B281-cells-09-00114" class="html-bibr">281</a>]. Those can be specifically delivered into tumor cells using a nanoparticle based system [<a href="#B282-cells-09-00114" class="html-bibr">282</a>]. Modified RNA molecules can also be taken up via endocytosis [<a href="#B33-cells-09-00114" class="html-bibr">33</a>].</p>
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19 pages, 2749 KiB  
Review
Precision Medicine in Neurodegenerative Diseases: Some Promising Tips Coming from the microRNAs’ World
by Nicoletta Nuzziello, Loredana Ciaccia and Maria Liguori
Cells 2020, 9(1), 75; https://doi.org/10.3390/cells9010075 - 27 Dec 2019
Cited by 11 | Viewed by 4611
Abstract
Novel insights in the development of a precision medicine approach for treating the neurodegenerative diseases (NDDs) are provided by emerging advances in the field of pharmacoepigenomics. In this context, microRNAs (miRNAs) have been extensively studied because of their implication in several disorders related [...] Read more.
Novel insights in the development of a precision medicine approach for treating the neurodegenerative diseases (NDDs) are provided by emerging advances in the field of pharmacoepigenomics. In this context, microRNAs (miRNAs) have been extensively studied because of their implication in several disorders related to the central nervous system, as well as for their potential role as biomarkers of diagnosis, prognosis, and response to treatment. Recent studies in the field of neurodegeneration reported evidence that drug response and efficacy can be modulated by miRNA-mediated mechanisms. In fact, miRNAs seem to regulate the expression of pharmacology target genes, while approved (conventional and non-conventional) therapies can restore altered miRNAs observed in NDDs. The knowledge of miRNA pharmacoepigenomics may offers new clues to develop more effective treatments by providing novel insights into interindividual variability in drug disposition and response. Recently, the therapeutic potential of miRNAs is gaining increasing attention, and miRNA-based drugs (for cancer) have been under observation in clinical trials. However, the effective use of miRNAs as therapeutic target still needs to be investigated. Here, we report a brief review of representative studies in which miRNAs related to therapeutic effects have been investigated in NDDs, providing exciting potential prospects of miRNAs in pharmacoepigenomics and translational medicine. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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<p>Circular view of microRNAs (miRNAs) and related drugs. Yellow nodes represent miRNAs, green nodes represent multiple sclerosis (MS) disease-modifying therapies, blue nodes represent Parkinson’s disease (PD) treatments, and red nodes represent AD treatments. The color of edges is associated to neurodegenerative diseases (NDDs), and the size of the nodes is proportional to the degree of the nodes (number of incoming and outcoming edges). The network is visualized using Cytoscape v3.7.1. (Institute for Systems Biology, Seattle, WA, USA).</p>
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<p>Schematic representation of miRNA pharmacoepigenomics reported in MS by Cytoscape v3.7.1. Yellow nodes represent miRNAs. Fingolimod, Natalizumab, Glatiramer Acetate, Interferon-β, and Dimethyl fumarate, are shown in green, blue, purple, orange, and brown, respectively. The size of the nodes is proportional to the degree of the nodes. It is worthy to mention that, among the more frequently used disease-modifying therapies (DMTs) in relapsing-remitting course (RRMS), Fingolimod, Glutiramer Acetate, and Natalizumab seem to significantly impact the expression levels of common miRNAs (and possibly target genes), while their mechanisms of action are quite different (see the text). Indeed, this observation may suffer from some biases due to e.g., the selection of the investigated miRNAs, the molecular methods used, etc., so more definitive conclusions can be drawn after planned studies.</p>
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32 pages, 1696 KiB  
Review
MicroRNA-Based Combinatorial Cancer Therapy: Effects of MicroRNAs on the Efficacy of Anti-Cancer Therapies
by Hyun Ah Seo, Sokviseth Moeng, Seokmin Sim, Hyo Jeong Kuh, Soo Young Choi and Jong Kook Park
Cells 2020, 9(1), 29; https://doi.org/10.3390/cells9010029 - 20 Dec 2019
Cited by 45 | Viewed by 7818
Abstract
The susceptibility of cancer cells to different types of treatments can be restricted by intrinsic and acquired therapeutic resistance, leading to the failure of cancer regression and remission. To overcome this problem, a combination therapy has been proposed as a fundamental strategy to [...] Read more.
The susceptibility of cancer cells to different types of treatments can be restricted by intrinsic and acquired therapeutic resistance, leading to the failure of cancer regression and remission. To overcome this problem, a combination therapy has been proposed as a fundamental strategy to improve therapeutic responses; however, resistance is still unavoidable. MicroRNA (miRNAs) are associated with cancer therapeutic resistance. The modulation of dysregulated miRNA levels through miRNA-based therapy comprising a replacement or inhibition approach has been proposed to sensitize cancer cells to other anti-cancer therapies. The combination of miRNA-based therapy with other anti-cancer therapies (miRNA-based combinatorial cancer therapy) is attractive, due to the ability of miRNAs to target multiple genes associated with the signaling pathways controlling therapeutic resistance. In this article, we present an overview of recent findings on the role of therapeutic resistance-related miRNAs in different types of cancer. We review the feasibility of utilizing dysregulated miRNAs in cancer cells and extracellular vesicles as potential candidates for miRNA-based combinatorial cancer therapy. We also discuss innate properties of miRNAs that need to be considered for more effective combinatorial cancer therapy. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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<p>Micro-RNA (MiRNA)-mediated regulation of the expression of drug transporters. Rounded rectangles indicate miRNAs (light green), transcription factors (orange), cytoplasmic signaling molecules (light blue), and a transmembrane receptor (red). Activation is denoted by solid line arrows, and inhibitory effects are indicated by perpendicular lines. Dashed arrows represent the nuclear translocation of transcription factors. Several miRNAs impact the efficacy of cancer therapeutic agents by transcriptionally regulating the levels of drug transporters, as described in <a href="#sec2dot3-cells-09-00029" class="html-sec">Section 2.3</a>.</p>
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<p>MiRNA-mediated regulation of the factors associated with cancer stemness. Rounded rectangles denote miRNAs (light green), stemness factors (orange), and upstream regulators of stemness factors (light blue, red, and green). Inhibitory effects are indicated by perpendicular lines. The positive regulation of stemness factors by each upstream factor is represented by solid lines. The effects of miRNAs on anti-cancer therapies are described in <a href="#sec5dot7dot2-cells-09-00029" class="html-sec">Section 5.7.2</a> and <a href="#cells-09-00029-t004" class="html-table">Table 4</a>.</p>
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<p>Extracellular vesicle miRNAs are responsible for therapeutic resistance. Exosomes and microvesicles (EVs), derived from cancer-associated cells, drug-resistant cancer cells, and cancer stem cells (CSCs), confer neighboring cells resistance to various anti-cancer treatments via transferring miRNAs, which regulate several factors associated with resistance mechanisms. Rounded rectangles represent miRNAs (light green), miRNA targets (orange), and signaling factors/cellular events affected by miRNA targets (light orange). Activation is indicated by solid line arrows, and inhibitory effects are demonstrated by perpendicular lines. The secretion of extracellular vesicles is denoted by dashed arrows. Potential mechanisms underlying the role of extracellular vesicle miRNAs in therapeutic resistance are explained in <a href="#sec7-cells-09-00029" class="html-sec">Section 7</a>.</p>
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40 pages, 1243 KiB  
Review
TGF-β and microRNA Interplay in Genitourinary Cancers
by Joanna Boguslawska, Piotr Kryst, Slawomir Poletajew and Agnieszka Piekielko-Witkowska
Cells 2019, 8(12), 1619; https://doi.org/10.3390/cells8121619 - 12 Dec 2019
Cited by 19 | Viewed by 5490
Abstract
Genitourinary cancers (GCs) include a large group of different types of tumors localizing to the kidney, bladder, prostate, testis, and penis. Despite highly divergent molecular patterns, most GCs share commonly disturbed signaling pathways that involve the activity of TGF-β (transforming growth factor beta). [...] Read more.
Genitourinary cancers (GCs) include a large group of different types of tumors localizing to the kidney, bladder, prostate, testis, and penis. Despite highly divergent molecular patterns, most GCs share commonly disturbed signaling pathways that involve the activity of TGF-β (transforming growth factor beta). TGF-β is a pleiotropic cytokine that regulates key cancer-related molecular and cellular processes, including proliferation, migration, invasion, apoptosis, and chemoresistance. The understanding of the mechanisms of TGF-β actions in cancer is hindered by the “TGF-β paradox” in which early stages of cancerogenic process are suppressed by TGF-β while advanced stages are stimulated by its activity. A growing body of evidence suggests that these paradoxical TGF-β actions could result from the interplay with microRNAs: Short, non-coding RNAs that regulate gene expression by binding to target transcripts and inducing mRNA degradation or inhibition of translation. Here, we discuss the current knowledge of TGF-β signaling in GCs. Importantly, TGF-β signaling and microRNA-mediated regulation of gene expression often act in complicated feedback circuits that involve other crucial regulators of cancer progression (e.g., androgen receptor). Furthermore, recently published in vitro and in vivo studies clearly indicate that the interplay between microRNAs and the TGF-β signaling pathway offers new potential treatment options for GC patients. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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<p>TGF-β maturation. The inactive TGF-β precursor dimerizes and the resulting dimer is cleaved by furin endopeptidase resulting in mature TGF-β and the latency-associated peptide (LAP) that bind non-covalently to produce small latent complex. The latter is next bound by latent TGF-β binding protein (LTBP), resulting in a large latent complex.</p>
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<p>MicroRNAs regulating key genes of the TGF-β signaling pathway. MicroRNAs acting in bladder, prostate, and renal cancer are shown in colors (yellow, purple, and red, respectively). The details of miRNA-mediated regulation of the TGF-β signaling pathway are provided in the text</p>
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19 pages, 3039 KiB  
Review
Mapping Research in the Obesity, Adipose Tissue, and MicroRNA Field: A Bibliometric Analysis
by João Manoel Alves, Ramon Handerson Gomes Teles, Camila do Valle Gomes Gatto, Vitor Rosetto Muñoz, Márcia Regina Cominetti and Ana Cláudia Garcia de Oliveira Duarte
Cells 2019, 8(12), 1581; https://doi.org/10.3390/cells8121581 - 6 Dec 2019
Cited by 16 | Viewed by 5459
Abstract
Recent studies have investigated the control of adipose tissue expansion and inflammatory process by microRNAs (miRNAs). These two processes are of great interest because both are associated with obesity and metabolic syndrome. However, despite the great relevance of the role of miRNAs in [...] Read more.
Recent studies have investigated the control of adipose tissue expansion and inflammatory process by microRNAs (miRNAs). These two processes are of great interest because both are associated with obesity and metabolic syndrome. However, despite the great relevance of the role of miRNAs in obesity and adipose tissue, no qualitative and quantitative analysis on the subject has been performed. Thus, we aimed to examine global research activity and current trends with respect to the interaction between obesity, adipose tissue and miRNAs through a bibliometric analysis. This research was performed on the Scopus database for publications containing miRNA, obesity, and adipose tissue keyword combinations. In total, 898 articles were analyzed and the most frequently occurring keywords were selected and clustered into three well-defined groups. As a result, first group of keywords pointed to the research area on miRNAs expressed in obesity-associated diseases. The second group demonstrated the regulation of the adipogenesis process by miRNAs, while the third group highlighted brown adipose tissue and thermogenesis as one of the latest global research trends related to the theme. The studies selected in this paper describe the expression and performance of different miRNAs in obesity and comorbidities. Most studies have focused on identifying miRNAs and signaling pathways associated with obesity, type 2 diabetes mellitus, and cardiovascular disease. Thus, the miRNA profile for these diseases may be used as biomarkers and therapeutic targets in the prevention and treatment of obesity-associated diseases. Full article
(This article belongs to the Special Issue microRNA as Therapeutic Target)
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<p>Flowchart of the article selection process used in the study. Notes: * Document and source type include only the articles published in Journals. Conference papers, short surveys, editorials, notes, letters, book chapters, and articles “in press” were excluded.</p>
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<p>Number of publications on the theme from 2005 to 2019.</p>
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<p>Keywords clusters overview related to obesity and miRNA.</p>
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<p>Density map of the most cited miRNAs associated with obesity research.</p>
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<p>miRNAs associated with obesity-disorders.</p>
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<p>Some miRNAs that control the adipogenic process, glucose uptake, remodeling and thermogenesis in brown adipose tissue (BAT). The action and role of miRNAs are described in the text.</p>
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