[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (674)

Search Parameters:
Keywords = mRNA transfection

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
14 pages, 10055 KiB  
Article
MicroRNA Profiling of PRELI-Modulated Exosomes and Effects on Hepatic Cancer Stem Cells
by Boyong Kim
Int. J. Mol. Sci. 2024, 25(24), 13299; https://doi.org/10.3390/ijms252413299 - 11 Dec 2024
Viewed by 281
Abstract
The increasing incidence and mortality rates of liver cancer have heightened the demand for the development of effective anticancer drugs with minimal side effects. In this study, the roles of exosomes derived from liver cancer stem cells (LCSCs) with PRELI (Protein of Relevant [...] Read more.
The increasing incidence and mortality rates of liver cancer have heightened the demand for the development of effective anticancer drugs with minimal side effects. In this study, the roles of exosomes derived from liver cancer stem cells (LCSCs) with PRELI (Protein of Relevant Evolutionary and Lymphoid Interest) modulation and their miRNAs were investigated to explore their therapeutic properties for liver cancer. Various techniques, such as miRNA profiling, microRNA transfection, overexpression, flow cytometry, Western blotting, and immunocytochemistry, were used to evaluate the effects of exosomes under PRELI up- and downregulation. Downregulated PRELI cellular exosomes (DPEs) reduced the levels of five markers—CD133, CD90, CD24, CD13, and EpCAM—in LCSCs, with the exception of OV-6. Conversely, upregulated PRELI cellular exosomes (UPEs) significantly increased the expression of CD90, CD24, and CD133 in NHs, with the maximum increase in CD24. PRELI upregulation altered expression levels of miRNAs, including hsa-miR-378a-3p (involved in stem-like properties), hsa-miR-25-3p (contributing to cell proliferation), and hsa-miR-423-3p (driving invasiveness). Exosomes with downregulated PRELI inhibited the AKT/mTORC1 signaling pathway, whereas LCSCs transfected with the candidate miRNAs activated it. Additionally, under PRELI upregulation, exosomes showed increased surface marker expression, promoting cancer progression. The modulation of PRELI in LCSCs affected miRNA expression significantly, revealing candidate miRNA targets for liver cancer treatment. Exosomes with PRELI downregulation show potential as a novel therapeutic strategy. Consequently, this study proposes the potential of PRELI-induced exosomes and the three miRNAs as a liver anticancer therapeutic candidate. Full article
(This article belongs to the Section Molecular Nanoscience)
Show Figures

Figure 1

Figure 1
<p>Purification of exosomes isolated from PRELI-modulated LCSCs. (<b>a</b>) Marker detection (CD63) and expression levels of PRELI in purified exosomes, as evaluated using Western blotting. Evaluation of purified exosomes with FITC-CD63 antibodies using flow cytometry (<b>b</b>) and fluorescence microscopy (<b>c</b>). CE: control cellular exosome, UPE: upregulated PRELI cellular exosome, DPE: downregulated PRELI cellular exosome, NC: unstained exosome (** <span class="html-italic">p</span> &lt; 0.01), scale bar = 20 µm.</p>
Full article ">Figure 2
<p>Profiling of exosomes from PRELI-modulated LCSCs. (<b>a</b>) Analyzed miRNAs (heat map) and identification of significant miRNAs in the exosomes. (<b>b</b>) Comparison of miRNA levels among three types of exosomes. Biochemical categories of the pie chart (1. aging, 2. angiogenesis, 3. apoptosis, 4. autophagy, 5. cell cycle, 6. cell differentiation, 7. cell migration, 8. cell proliferation, 9. DNA repair, 10. immune response, 11. inflammatory response, 12. neurogeneration, 13. secretion) associated with significant miRNAs in the induced exosomes and alterations of miRNA levels in each of the functional categories. The numbers above bar graphs indicate the number of differentially expressed miRNAs. CE: control cellular exosome, UPE: upregulated PRELI cellular exosome, DPE: downregulated PRELI cellular exosome.</p>
Full article ">Figure 3
<p>Alterations of miRNAs associated with six biochemical categories in three types of exosomes. (CE: control cellular exosome, UPE: upregulated PRELI cellular exosome, DPE: downregulated PRELI cellular exosome) (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>Expression of markers in LCSCs exposed to various exosomes. (CE: control cellular exosomes, UPE: upregulated PRELI cellular exosome, DPE: downregulated PRELI cellular exosome). Fill-patterned bar graphs indicate markers with significant changes. Ns: not significant (* <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 5
<p>Expression of typical LCSC markers in normal hepatocytes exposed to various exosomes. (CE: control cellular exosome, UPE: upregulated PRELI cellular exosome, DPE: downregulated PRELI cellular exosome). Fill-patterned bar graphs indicate markers with significant changes. Ns: not significant (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 6
<p>Levels of AKT signaling molecules (phosphorylated AKT and phosphorylated mTORC1) in normal hepatocytes and LCSCs under various exosomes. (CE: control cellular exosome, UPE: upregulated PRELI cellular exosome, DPEs: downregulated PRELI cellular exosome) (* <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 7
<p>Expression of AKT signaling molecules in LCSCs under miRNA treatment. The merged images show the internalized fluorescence-labeled GAPDH-siRNAs (GFP: green fluorescent proteins) and miRNA (Cy5: cyanine 5) in LCSCs. The expression levels of AKT signaling molecules (phosphorylated AKT and phosphorylated mTORC1) in LCSCs transfected with the fluorescent (Cy5)-labeled miRNAs including hsa-miR378a-3p, hsa-miR25-3p, and hsa-miR423-3p and positive control siRNAs (GFP-GAPDH -siRNA) (* <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) (scale bars = 20 μm).</p>
Full article ">Figure 8
<p>Attenuation of drug resistance and cellular viability in SRHs upon inhibition of three miRNAs. (<b>a</b>) Results from modeling drug resistance. (<b>b</b>) Expression levels of PRELI in SSHs (sorafenib-sensitive hepatocytes) and SRH (sorafenib-resistant hepatocytes). (<b>c</b>) Drug resistance in cells transfected with anti-miRNA siRNAs. Fill-patterned bar graphs indicate sensitivity for Sorafenib.CC<sub>50</sub>: cytotoxic concentration 50; NT: non-transfected; T: transfected, Ns: not significant (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">
22 pages, 7069 KiB  
Article
APOL1 Modulates Renin–Angiotensin System
by Vinod Kumar, Prabhjot Kaur, Kameshwar Ayasolla, Alok Jha, Amen Wiqas, Himanshu Vashistha, Moin A. Saleem, Waldemar Popik, Ashwani Malhotra, Christoph A. Gebeshuber, Karl Skorecki and Pravin C. Singhal
Biomolecules 2024, 14(12), 1575; https://doi.org/10.3390/biom14121575 - 10 Dec 2024
Viewed by 612
Abstract
Patients carrying APOL1 risk alleles (G1 and G2) have a higher risk of developing Focal Segmental Glomerulosclerosis (FSGS); we hypothesized that escalated levels of miR193a contribute to kidney injury by activating renin–angiotensin system (RAS) in the APOL1 milieus. Differentiated podocytes (DPDs) stably expressing [...] Read more.
Patients carrying APOL1 risk alleles (G1 and G2) have a higher risk of developing Focal Segmental Glomerulosclerosis (FSGS); we hypothesized that escalated levels of miR193a contribute to kidney injury by activating renin–angiotensin system (RAS) in the APOL1 milieus. Differentiated podocytes (DPDs) stably expressing vector (V/DPD), G0 (G0/DPDs), G1 (G1/DPDs), and G2 (G2/DPDs) were evaluated for renin, Vitamin D receptor (VDR), and podocyte molecular markers (PDMMs, including WT1, Podocalyxin, Nephrin, and Cluster of Differentiation [CD]2 associated protein [AP]). G0/DPDs displayed attenuated renin but an enhanced expression of VDR and Wilms Tumor [WT]1, including other PDMMs; in contrast, G1/DPDs and G2/DPDs exhibited enhanced expression of renin but decreased expression of VDR and WT1, as well as other PDMMs (at both the protein and mRNA levels). G1/DPDs and G2/DPDs also showed increased mRNA expression for Angiotensinogen and Angiotensin II Type 1 (AT1R) and 2 (AT2R) receptors. Protein concentrations of Brain Acid-Soluble Protein [BASP]1, Enhancer of Zeste Homolog [EZH]2, Histone Deacetylase [HDAC]1, and Histone 3 Lysine27 trimethylated [H3K27me3] in WT1-IP (immunoprecipitated proteins with WT1 antibody) fractions were significantly higher in G0/DPDs vs. G1/DPD and G2/DPDs. Moreover, DPD-silenced BASP1 displayed an increased expression of renin. Notably, VDR agonist-treated DPDs showed escalated levels of VDR and a higher expression of PDMMs, but an attenuated expression of renin. Human Embryonic Kidney (HEK) cells transfected with increasing APOL1(G0) plasmid concentrations showed a corresponding reduction in renin mRNA expression. Bioinformatics studies predicted the miR193a target sites in the VDR 3′UTR (untranslated region), and the luciferase assay confirmed the predicted sites. As expected, podocytes transfected with miR193a plasmid displayed a reduced VDR and an enhanced expression of renin. Renal cortical section immunolabeling in miR193a transgenic (Tr) mice showed renin-expressing podocytes. Kidney tissue extracts from miR193aTr mice also showed reduced expression of VDR and PDMMs, but enhanced expression of Renin. Blood Ang II levels were higher in miR193aTr, APOLG1, and APOL1G1/G2 mice when compared to control mice. Based on these findings, miR193a regulates the activation of RAS and podocyte molecular markers through modulation of VDR and WT1 in the APOL1 milieu. Full article
(This article belongs to the Section Molecular Medicine)
Show Figures

Figure 1

Figure 1
<p>Effect of APOL1 risk and non-risk alleles on podocyte expression of VDR, renin, and PDMMs. (<b>A</b>) Podocytes expressing Vector, G0, G1, and G2 were differentiated for 10 days. Differentiated podocytes (DPD) were harvested, and proteins were extracted and probed for renin and Podocalyxin (PDX) and reprobed for GAPDH (<span class="html-italic">n</span> = 4). Representative gels from two different lysates are shown. (<b>B</b>) Cumulative densitometric data (<span class="html-italic">n</span> = 4) are shown in bar graphs. Renin: * <span class="html-italic">p</span> &lt; 0.05 vs. V/DPD; # <span class="html-italic">p</span> &lt; 0.05 vs. G2/DPD; ## <span class="html-italic">p</span> &lt; 0.01 vs. G0/DPD.PDX: ** <span class="html-italic">p</span> &lt; 0.01 vs. VD/DPD; # <span class="html-italic">p</span> &lt; 0.05 vs. G0/DPD. (<b>C</b>) The lysates mentioned above (<b>A</b>) were also probed for Nephrin, VDR, CD2AP, WT1, and GAPDH (<span class="html-italic">n</span> = 4). Representative gels from two different lysates are displayed. (<b>D</b>) Cumulative densitometric data (<span class="html-italic">n</span> = 4) are shown in a bar diagram. Nephrin: * <span class="html-italic">p</span> &lt; 0.05 vs. V/DPD, G1/DPD, and G2/DPD; # <span class="html-italic">p</span> &lt; 0.05 vs. V/DPD. VDR: ** <span class="html-italic">p</span> &lt; 0.01 vs. V/DPD, G1/DPD, and G2/DPD; * <span class="html-italic">p</span> &lt; 0.05 vs. V/DPD; # <span class="html-italic">p</span> &lt; 0.05 vs. V/DPD; ## <span class="html-italic">p</span> &lt; 0.01 vs. G0/DPD. CD2AP: ** <span class="html-italic">p</span> &lt; 0.01 vs. V/DPD; # <span class="html-italic">p</span> &lt; 0.05 vs. G0/DPD. WT1: * <span class="html-italic">p</span> &lt; 0.05 vs. V/DPD; ## &lt; 0.01 vs. G0/DPD.</p>
Full article ">Figure 2
<p>Podocyte mRNA level alterations in APOL1 milieus. To determine mRNA levels of APOL1-expressing podocytes, RNAs were extracted from cellular lysates V/DPDs, G0/DPDs, G1/DPDs, and G2/DPDs (<span class="html-italic">n</span> = 4). cDNAs were amplified using specific primers (CD2AP, WT1, renin, VDR, and PDX [podocalyxin]). CD2AP: * <span class="html-italic">p</span> &lt; 0.05 with respective V and ** <span class="html-italic">p</span> &lt; 0.01 with respective G1 and G2; WT1: * <span class="html-italic">p</span> &lt; 0.05 with respective V and ** <span class="html-italic">p</span> &lt; 0.01 with respective G1 and G2; Renin: * <span class="html-italic">p</span> &lt; 0.05 with respective G0 and ** <span class="html-italic">p</span> &lt; 0.01 with respective G1 and G2; Nephrin: * <span class="html-italic">p</span> &lt; 0.05 with respective V and G0; VDR: ** <span class="html-italic">p</span> &lt; 0.01 with respective V and *** <span class="html-italic">p</span> &lt; 0.001 with respective G1 and G2; PDX: * <span class="html-italic">p</span> &lt; 0.05 with respective V, G1, and G2.</p>
Full article ">Figure 3
<p>miR1 93a expression in podocytes expressing Vector (V), APOL1G0, APOL1G1, and APOL1G2. Extracted RNAs (<span class="html-italic">n</span> = 4) were assayed for miR193a. Results (means ± SD) are displayed in a bar diagram. * <span class="html-italic">p</span> &lt; 0.05 vs. V; ** <span class="html-italic">p</span> &lt; 0.01 vs. V and G0.</p>
Full article ">Figure 4
<p>Renin-angiotensin status in APOL1 milieus. RNAs were extracted from V/DPD, G0/DPD, G1/DPD, and G2/DPD (<span class="html-italic">n</span> = 4), and cDNAs were amplified with specific primers for APOL1, renin, angiotensinogen, ACE1, AT1R, and AT2R. (<b>A</b>) APOL1: ** <span class="html-italic">p</span> &lt; 0.01 compared to V. (<b>B</b>) Renin: * <span class="html-italic">p</span> &lt; 0.05 compared to V; ** <span class="html-italic">p</span> &lt; 0.01 compared to V and G0; # <span class="html-italic">p</span> &lt; 0.05 compared to V and G1. (<b>C</b>) # <span class="html-italic">p</span> &lt; 0.05 compared to V, G1, and G2; * <span class="html-italic">p</span> &lt; 0.05 compared to V. (<b>D</b>) ** <span class="html-italic">p</span> &lt; 0.01 compared to V, G0, and G1. (<b>E</b>) AT1R: * <span class="html-italic">p</span> &lt; 0.05 compared to V, G0, and G2; ** <span class="html-italic">p</span> &lt; 0.01 compared to V and G0. (<b>F</b>) AT2R: * <span class="html-italic">p</span> &lt; 0.05 compared to V and G0; ** <span class="html-italic">p</span> &lt; 0.01 compared to V, G0, and G1.</p>
Full article ">Figure 5
<p>The structural construct of the WT1-BASP1 repressor complex. (<b>A</b>) Homology modeling and docking studies suggested the binding of WT1-BASP1 repressor complex on the renin promoter. (<b>B</b>) A schematic diagram displays the formation of the WT1-BASP1 repressor complex at the renin promoter. WT1 recruits BASP1, EZH2, and HDAC1, inducing methylation at Lysine 27 residues at Histone (H) 3 tail.</p>
Full article ">Figure 6
<p>Analysis of input lysates of podocytes expressing APOL1 non-risk and risk alleles. (<b>A</b>) Proteins were extracted from the cellular lysates of V/DPDs, G0/DPs, G1/DPDs, and G2/CDPs (<span class="html-italic">n</span> = 3–4). Gels from three independent lysates are displayed. (<b>B</b>) Cumulative densitometric data of proteins displayed in 3A are shown in a bar diagram. APOL1: ** <span class="html-italic">p</span> &lt; 0.01 vs. G1/DPD and G2/DPD; *** <span class="html-italic">p</span> &lt; 0.001 vs. V/DPD; Renin: * <span class="html-italic">p</span> &lt; 0.05 vs. respective variables; WT1: ## <span class="html-italic">p</span> &lt; 0.01 vs. respective variables; BASP1: # <span class="html-italic">p</span> &lt; 0.05 vs. respective variables; EZH2: <sup>a</sup> <span class="html-italic">p</span> &lt; 0.01 vs. V/DPD and G0/DPD; <sup>b</sup> <span class="html-italic">p</span> &lt; 0.01 vs. V/DPD and G0/DPD; HDAC1: <sup>c</sup> <span class="html-italic">p</span> &lt; 0.01 vs. respective other variables; H3K27me<sup>3</sup>: <sup>d</sup> <span class="html-italic">p</span> &lt; 0.01 vs. V/DPD, G1/DPD, and G2/DPD.</p>
Full article ">Figure 7
<p>Analysis of WT1 antibody-bound proteins (output). (<b>A</b>). Cellular lysates from the protocol of <a href="#biomolecules-14-01575-f006" class="html-fig">Figure 6</a>A were immunoprecipitated (IP) with the WT1 antibody. Protein blots of WT1-IP fractions were probed for WT1, renin, EZH2, HDAC1, H3K27me<sup>3</sup>, and IgG (<span class="html-italic">n</span> = 3). Gels from 3 independent cellular lysates are displayed. (<b>B</b>). Cumulative densitometric data from blots of the <a href="#biomolecules-14-01575-f007" class="html-fig">Figure 7</a>A (<span class="html-italic">n</span> = 3). WT1: * <span class="html-italic">p</span> &lt; 0.05 vs. V; ** <span class="html-italic">p</span> &lt; 0.01 vs. G1 and G2. BASP1: ** <span class="html-italic">p</span> &lt; 0.01 vs. respective other variables. EZH2: * <span class="html-italic">p</span> &lt; 0.05 vs. V; ** <span class="html-italic">p</span> &lt; 0.01 vs. G1; *** <span class="html-italic">p</span> &lt; 0.001 vs. G2. HDAC1: * <span class="html-italic">p</span> &lt; 0.05 vs. other variables. H3K27: * <span class="html-italic">p</span> &lt; 0.05 vs. V; ** <span class="html-italic">p</span> &lt; 0.01 vs. G1 and G2.</p>
Full article ">Figure 8
<p>Effect of BASP1 silencing on the podocyte expression of renin. (<b>A</b>) Cellular lysates of control podocytes (C/DPD), scrambled siRNA- (SCR/DPD), and BASP1-SiRNA-transfected podocytes (SiRNA/DPD) were probed for renin and GAPDH (<span class="html-italic">n</span> = 3). Gels of three independent lysates are shown. (<b>B</b>) Cumulative densitometric data (<span class="html-italic">n</span> = 3) are shown in bar graphs. ** <span class="html-italic">p</span> &lt; 0.01 vs. C/DPD and SCR/DPD.</p>
Full article ">Figure 9
<p>Effect of VDR overexpression on renin and podocyte molecular markers (PDMMs). (<b>A</b>) DPDs were incubated in media containing either vehicle (DMSO) or VDA (EB 1089, 10 nM) for 48 h (<span class="html-italic">n</span> = 4). Proteins were extracted and probed for VDR, renin, and PDMMs (WT1, Nephrin, CD2AP, and Synaptopodin) and GAPDH. Gels from two different lysates from V/DPD (vehicle-treated) and VDR/DPD (VDA-treated) are shown. (<b>B</b>) Cumulative densitometric data for different variables are shown in bar graphs. * <span class="html-italic">p</span> &lt; 0.0.5 and ** <span class="html-italic">p</span> &lt; 0.01 vs. respective V/DPD.</p>
Full article ">Figure 10
<p>Dose-response effect of APOL1 induction on renin expression in HEK cells. HEK cells were transfected with either empty vector (control, HEK-Cnt) or APOL1 plasmid (HEK-APOL1) in different concentrations (25, 50, and 100 ng) for 48 h (<span class="html-italic">n</span> = 4). Cells were harvested, and proteins and RNAs were extracted. (<b>A</b>) cDNAs were amplified with specific primers of APOL1 and renin. Cumulative data are shown in a bar diagram. APOL1 expression: # <span class="html-italic">p</span> &lt; 0.05 and ## <span class="html-italic">p</span> &lt; 0.01 vs. HEK-Cnt. Renin: * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 vs. HEK control; <span>$</span><span>$</span> <span class="html-italic">p</span> &lt; 0.01 vs. HEK-APOL1, 25 ng. (<b>B</b>) Proteins were probed for APOL1, renin, and GAPDH. Representative gels are displayed in the upper panel. Cumulative densitometric data are shown in bar graphs. APOL1: # <span class="html-italic">p</span> &lt; 0.05 and ## <span class="html-italic">p</span> &lt; 0.01 vs. HEK-Cnt. Renin: * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 vs. HEK-Cnt; <span>$</span><span>$</span> <span class="html-italic">p</span> &lt; 0.01 vs. HEK-APOL1, 25 ng.</p>
Full article ">Figure 11
<p>Validation of miR193a putative binding sites on VDR. (<b>A</b>) Available online in silico analysis tools (microrna.org; mirdb.org and TargetScan). VDR was predicted as a potential target for miR193a-5p. Predicted binding sites are shown. (<b>B</b>) Podocytes were transiently co-transfected by using Lipofectamine 2000 with wild-type or control reporter 3′-UTR plasmids and miR-193a (pCMV-miR-193a) or negative miR (control, AM17110) in combination. After 48 h of co-transfection, the firefly luciferase activities were measured using the duo-luciferase HS assay. The relative luciferase activity was calculated by normalizing it to Renilla luciferase. The presented results are cumulative values of three independent experiments, each performed in triplicate. *** <span class="html-italic">p</span> &lt; 0.001 vs. other variables.</p>
Full article ">Figure 12
<p>Effect of miR193a on the expression of VDR, renin, and PDMMs. (<b>A</b>) Podocytes were transfected with empty vector or miR19a plasmid and differentiated (<span class="html-italic">n</span> = 4). Cellular lysates were probed for VDR, renin, PDMMs (WT1, PDX, APOL1), and GAPDH. Gels from two different lysates are shown. (<b>B</b>) Cumulative data are shown in bar graphs. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.0.01 vs. respective V/DPD.</p>
Full article ">Figure 13
<p>Renal tissue expression profile of VDR, renin, and PDMMs in control and miR193aTr mice. (<b>A</b>) Renal tissues were harvested from control (Balb/C, wild-type) and miR193aTr mice (<span class="html-italic">n</span> = 3). Proteins were probed for renin, PDMMs (WT1, CD2AP, PDX), and GAPDH. Gels from three different lysates are displayed. (<b>B</b>) Tissue lysates from the above mice were reprobed for VDR, Nephrin, and GAPDH (<span class="html-italic">n</span> = 3). Gels from different lysates are shown. (<b>C</b>) Cumulative densitometric data from gels are shown in panel A in bar graphs. ** <span class="html-italic">p</span> &lt; 0.01 vs. control/Balb C mice. (<b>D</b>) Cumulative densitometric data from gels displayed in Panel B are shown in a bar diagram. ** <span class="html-italic">p</span> &lt; 0.0.01 vs. control/Balb C mice.</p>
Full article ">Figure 14
<p>Renal histology and VDR/renin expression in control (BALB/C) and miR193aTr mice. (<b>A</b>) Representative glomeruli from a control and miR193aTr mice. Sclerosis is displayed by black arrows in a glomerulus from an miR193aTr mouse. (<b>B</b>) Glomeruli were co-labeled with VDR and renin antibodies. Nuclei were stained with DAPI. A representative glomerulus from a control mouse showed co-labeled (VDR and renin) podocytes (white arrows); podocytes predominantly displayed green fluorescence (VDR) and minimal red fluorescence (renin). A representative glomerulus from an miR193aTr mouse displayed both green (VDR) and red (renin) fluorescence in podocytes (white arrows). Parietal epithelial cells showed orange fluorescence (combination of predominant red and mild green fluorescence, indicated by yellow arrows) in glomeruli from both BALB/C and miR193aTr mice. C. Blue square is magnified to display co-labeling of VDR and renin in podocytes. Scale bar = 50 µM.</p>
Full article ">Figure 15
<p>Ang II levels were determined in plasma samples of control (BALB/C, <span class="html-italic">n</span> = 6 and FVBN, <span class="html-italic">n</span> = 9) and experimental (miR193aTR, <span class="html-italic">n</span> = 6; APOL1 G0, <span class="html-italic">n</span> = 10; APOL1 G1, <span class="html-italic">n</span> = 9; and APOL1G1/G2, <span class="html-italic">n</span> = 9) mice. Results (means ± SD) are shown in bar diagrams. (<b>A</b>) Plasma Ang II levels in control (BALB/C) and miR193aTr mice. (<b>B</b>) Plasma Ang II levels in control and APOL1 mice. * <span class="html-italic">p</span> &lt; 0.05 vs. FVBN; # <span class="html-italic">p</span> &lt; 0.05 vs. APOL1G1.</p>
Full article ">Figure 16
<p>A schematic diagram displaying the activation of the RAS contributing to glomerular sclerosis in APOL1 milieus.</p>
Full article ">
22 pages, 16663 KiB  
Article
Gene-Silencing Therapeutic Approaches Targeting PI3K/Akt/mTOR Signaling in Degenerative Intervertebral Disk Cells: An In Vitro Comparative Study Between RNA Interference and CRISPR–Cas9
by Masao Ryu, Takashi Yurube, Yoshiki Takeoka, Yutaro Kanda, Takeru Tsujimoto, Kunihiko Miyazaki, Hiroki Ohnishi, Tomoya Matsuo, Naotoshi Kumagai, Kohei Kuroshima, Yoshiaki Hiranaka, Ryosuke Kuroda and Kenichiro Kakutani
Cells 2024, 13(23), 2030; https://doi.org/10.3390/cells13232030 - 9 Dec 2024
Viewed by 578
Abstract
The mammalian target of rapamycin (mTOR), a serine/threonine kinase, promotes cell growth and inhibits autophagy. The following two complexes contain mTOR: mTORC1 with the regulatory associated protein of mTOR (RAPTOR) and mTORC2 with the rapamycin-insensitive companion of mTOR (RICTOR). The phosphatidylinositol 3-kinase (PI3K)/Akt/mTOR [...] Read more.
The mammalian target of rapamycin (mTOR), a serine/threonine kinase, promotes cell growth and inhibits autophagy. The following two complexes contain mTOR: mTORC1 with the regulatory associated protein of mTOR (RAPTOR) and mTORC2 with the rapamycin-insensitive companion of mTOR (RICTOR). The phosphatidylinositol 3-kinase (PI3K)/Akt/mTOR signaling pathway is important in the intervertebral disk, which is the largest avascular, hypoxic, low-nutrient organ in the body. To examine gene-silencing therapeutic approaches targeting PI3K/Akt/mTOR signaling in degenerative disk cells, an in vitro comparative study was designed between small interfering RNA (siRNA)-mediated RNA interference (RNAi) and clustered regularly interspaced short palindromic repeat (CRISPR)–CRISPR-associated protein 9 (Cas9) gene editing. Surgically obtained human disk nucleus pulposus cells were transfected with a siRNA or CRISPR–Cas9 plasmid targeting mTOR, RAPTOR, or RICTOR. Both of the approaches specifically suppressed target protein expression; however, the 24-h transfection efficiency differed by 53.8–60.3% for RNAi and 88.1–89.3% for CRISPR–Cas9 (p < 0.0001). Targeting mTOR, RAPTOR, and RICTOR all induced autophagy and inhibited apoptosis, senescence, pyroptosis, and matrix catabolism, with the most prominent effects observed with RAPTOR CRISPR–Cas9. In the time-course analysis, the 168-h suppression ratio of RAPTOR protein expression was 83.2% by CRISPR–Cas9 but only 8.8% by RNAi. While RNAi facilitates transient gene knockdown, CRISPR–Cas9 provides extensive gene knockout. Our findings suggest that RAPTOR/mTORC1 is a potential therapeutic target for degenerative disk disease. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic illustration of human disk intracellular PI3K/Akt/mTOR signaling pathway. The mTOR is a serine/threonine kinase that integrates nutrient signals to promote drive cell growth and division. It operates within the following two primary complexes: mTORC1 and mTORC2, which include RAPTOR and RICTOR, respectively. The downstream effectors of mTORC1, such as p70/S6K, are involved in controlling cell proliferation, mRNA translation, and protein synthesis, also associated with senescence and matrix catabolism. Autophagy is tightly suppressed by mTORC1 as well. The regulation of mTORC1 is mediated by the upstream class-I PI3K, with Akt serving as a crucial pro-survival mediator that prevents apoptosis. Furthermore, the negative feedback loop between p70/S6K and the class-I PI3K exists. To analyze the cascade-dependent functions of PI3K/Akt/mTOR signaling, gene suppression was performed using both siRNA-mediated RNAi-based and CRISPR–Cas9-based methods to target <span class="html-italic">mTOR</span> for both mTORC1 and mTORC2, <span class="html-italic">RAPTOR</span> for mTORC1, and <span class="html-italic">RICTOR</span> for mTORC2.</p>
Full article ">Figure 2
<p>Schematic illustration of the in vitro study design. Human degenerative intervertebral disk NP cells were surgically collected from patients who underwent lumbar discectomy or interbody fusion surgery. To retain the phenotype and replicate the physiologically hypoxic intervertebral disk environment, first-passage cells were cultured under 2% O<sub>2</sub> until they reached ~80% confluence. Gene knockdown and knockout targeting <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, and <span class="html-italic">RICTOR</span> were performed using both siRNA-mediated RNAi and CRISPR–Cas9, respectively. After the cells were transfected for 24 h, the suppression of mTOR, RAPTOR, and RICTOR and autophagy were evaluated by Western blotting. The cell number was counted. Cell viability was measured using the CCK-8 assay to evaluate the toxicity associated with RNAi and CRISPR–Cas9. Additionally, to mimic the clinically relevant low-nutrient and inflammatory disease conditions, following siRNA or CRISPR–Cas9 treatment for 24 h, the cells were stimulated with pro-inflammatory IL-1β in serum-free DMEM for an additional 24 h. Subsequent analyses included evaluating the apoptosis, pyroptosis, senescence, and matrix metabolism using Western blotting, TUNEL staining for apoptosis, and SA-β-gal staining for senescence.</p>
Full article ">Figure 3
<p>RNAi and CRISPR–Cas9 enhance the selective suppression of mTOR, RAPTOR, and RICTOR in human disk NP cells. (<b>A</b>) Western blot analysis for brachyury, CD24, and tubulin in the total protein extracts from five different batches of human disk NP cells in DMEM with 10% FBS. (<b>B</b>) Western blot analysis for mTOR, RAPTOR, RICTOR, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA with each of two different sequences (Seq. 1 and Seq. 2) in DMEM with 10% FBS to assess the expression levels of the target protein relative to tubulin. (<b>C</b>) Western blot analysis for mTOR, RAPTOR, RICTOR, and tubulin in the total protein extracts of human disk NP cells 24 h after transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid with each of the three different guide RNA sequences (Seq. 1, Seq. 2, and Seq. 3) in DMEM with 10% FBS to assess the expression levels of the target protein relative to tubulin. (<b>D</b>) Fluorescence for phase contrast (gray), GFP (green), DAPI (blue), and merged signals in human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA containing a GFP sequence in DMEM with 10% FBS to assess the transfection efficiency of the GFP-positive cells relative to the total DAPI-positive cells. (<b>E</b>) Morphological appearance of human disk NP cells 24 h post-transfection with <span class="html-italic">RAPTOR</span> siRNA or <span class="html-italic">RAPTOR</span> CRISPR–Cas9 plasmid in DMEM with 10% FBS to assess the number of adherent cells treated relative to the control. (<b>F</b>) CCK-8 assay in human disk NP cells 24 h post-transfection with control siRNA, control CRISPR–Cas9 plasmid, lipofection only, <span class="html-italic">RAPTOR</span> siRNA, or <span class="html-italic">RAPTOR</span> CRISPR–Cas9 plasmid in DMEM with 10% FBS to assess the viability of the cells treated relative to the control. Cells were counted in duplicated five random low-power fields (100×). Statistical analysis was performed using one-way repeated measures ANOVA with the Tukey–Kramer post hoc test. Data are presented with dot and box plots (<span class="html-italic">n</span> = 6). In (<b>A</b>), the immunoblots shown are all results from experiments with similar outcomes (<span class="html-italic">n</span> = 5). In (<b>B</b>–<b>E</b>), the immunoblots and cellular images shown represent typical results from the experiments with similar outcomes (<span class="html-italic">n</span> = 6).</p>
Full article ">Figure 4
<p>Selective suppression of RAPTOR/mTORC1 inhibits autophagy and p70/S6K but differentially induces Akt activation in human disk NP cells. (<b>A</b>) Western blot analysis for mTOR, RAPTOR, RICTOR, and tubulin in total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA with the sequence showing the highest suppression efficiency in DMEM with 10% FBS to assess the expression levels of the target protein relative to tubulin. (<b>B</b>) Western blot analysis for mTOR, RAPTOR, RICTOR, and tubulin in total protein extracts of human disk NP cells 24 h after transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid with the sequence presenting the highest suppression efficiency in DMEM with 10% FBS to assess the expression levels of the target protein relative to tubulin. (<b>C</b>) Western blot analysis for Akt, phosphorylated Akt (p-Akt), p70/S6K, phosphorylated p70/S6K (p-p70/S6K), and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in DMEM with 10% FBS. (<b>D</b>) Western blot analysis for Akt, p-Akt, p70/S6K, p-p70/S6K, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in DMEM with 10% FBS. (<b>E</b>) Western blot analysis for LC3, p62/SQSTM1, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in DMEM with 10% FBS to assess the expression levels of the target protein relative to tubulin. (<b>F</b>) Western blot analysis for LC3, p62/SQSTM1, and tubulin in the total protein extracts of human disk NP cells 24 h after transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in DMEM with 10% FBS to assess the expression levels of the target protein relative to tubulin. Statistical analysis was performed using the paired <span class="html-italic">t</span>-test or one-way repeated measures ANOVA with the Tukey–Kramer post hoc test. Data are presented with dot and box plots (<span class="html-italic">n</span> = 6). The immunoblots shown represent the typical results from experiments with similar outcomes (<span class="html-italic">n</span> = 6).</p>
Full article ">Figure 5
<p>Selective suppression of RAPTOR/mTORC1 inhibits apoptosis in human disk NP cells. (<b>A</b>) Western blot analysis for PARP, cleaved PARP, cleaved caspase-9, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. (<b>B</b>) Western blot analysis for PARP, cleaved PARP, cleaved caspase-9, and tubulin in the total protein extracts of human disk NP cells 24 h after transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. (<b>C</b>) Fluorescence for TUNEL (green), DAPI (blue), and merged signals in human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS to assess the ratio of TUNEL-positive cells relative to the total DAPI-positive cells. (<b>D</b>) Fluorescence for TUNEL (green), DAPI (blue), and merged signals in human disk NP cells 24 h after transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS to assess the ratio of TUNEL-positive cells relative to the total DAPI-positive cells. Cells were counted in duplicated five random low-power fields (100×). Statistical analysis was performed using one-way repeated measures ANOVA with the Tukey–Kramer post hoc test. Data are presented with dot and box plots (<span class="html-italic">n</span> = 6). The immunoblots and cellular images shown represent typical results from the experiments with similar outcomes (<span class="html-italic">n</span> = 6).</p>
Full article ">Figure 6
<p>Selective suppression of RAPTOR/mTORC1 inhibits pyroptosis in human disk NP cells. (<b>A</b>) Western blot analysis for caspase-1, cleaved caspase-1, GSDMD, N-terminal GSDMD, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS to assess the expression levels of the target protein relative to tubulin. (<b>B</b>) Western blot analysis for caspase-1, cleaved caspase-1, GSDMD, N-terminal GSDMD, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS to assess the expression levels of the target protein relative to tubulin. Statistical analysis was performed using one-way repeated measures ANOVA with the Tukey–Kramer post hoc test. Data are presented with dot and box plots (<span class="html-italic">n</span> = 6). The immunoblots shown represent typical results from the experiments with similar outcomes (<span class="html-italic">n</span> = 6).</p>
Full article ">Figure 7
<p>Selective suppression of RAPTOR/mTORC1 inhibits senescence in human disk NP cells. (<b>A</b>) Western blot analysis for p16/INK4A, p21/WAF1/CIP1, p53, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. (<b>B</b>) Western blot analysis for p16/INK4A, p21/WAF1/CIP1, p53, and tubulin in the total protein extracts of human disk NP cells 24 h after transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. (<b>C</b>) Colorimetric assay for the SA-β-gal signals (blue, indicated by black arrowheads) in human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS to assess the ratio of SA-β-gal-positive cells relative to the total cells. (<b>D</b>) Colorimetric assay for the SA-β-gal signals (blue, indicated by black arrowheads) in human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS to assess the ratio of SA-β-gal-positive cells relative to the total cells. Cells were counted in duplicated five random low-power fields (100×). Statistical analysis was performed using one-way repeated measures ANOVA with the Tukey–Kramer post hoc test. Data are presented with dot and box plots (<span class="html-italic">n</span> = 6). The immunoblots and cellular images shown represent typical results from the experiments with similar outcomes (<span class="html-italic">n</span> = 6).</p>
Full article ">Figure 8
<p>Selective suppression of RAPTOR/mTORC1 increases matrix anabolism through decreased catabolic enzymes in human disk NP cells. (<b>A</b>) Western blot analysis for aggrecan, COL2A1, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. (<b>B</b>) Western blot analysis for aggrecan, COL2A1, and tubulin in the total protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. (<b>C</b>) Western blot analysis for MMP-3, MMP-13, TIMP-1, and TIMP-2 in the supernatant protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control siRNA in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. (<b>D</b>) Western blot analysis for MMP-3, MMP-13, TIMP-1, and TIMP-2 in the supernatant protein extracts of human disk NP cells 24 h post-transfection with <span class="html-italic">mTOR</span>, <span class="html-italic">RAPTOR</span>, <span class="html-italic">RICTOR</span>, or control CRISPR–Cas9 plasmid in 10 ng/mL IL-1β-supplemented DMEM with 0% FBS. The immunoblots shown represent typical results from the experiments with similar outcomes (<span class="html-italic">n</span> = 6).</p>
Full article ">Figure 9
<p>RNAi facilitates transient <span class="html-italic">RAPTOR</span> gene knockdown but CRISPR–Cas9 provides extensive <span class="html-italic">RAPTOR</span> gene knockout in human disk NP cells. Western blot analysis for RAPTOR and tubulin in the total protein extracts from five different batches of human disk NP cells at 0, 24, 48, 72, 120, and 168 h post-transfection with <span class="html-italic">RAPTOR</span> siRNA or CRISPR–Cas9 plasmid in 10% FBS-supplemented DMEM with a media change every 48 h to assess the time-course expression levels of the RAPTOR protein relative to tubulin. Statistical analysis was performed using two-way repeated measures ANOVA with the Tukey–Kramer post hoc test. Data are represented as the mean ± standard deviation (<span class="html-italic">n</span> = 5). The immunoblots shown are all results from the experiments with similar outcomes (<span class="html-italic">n</span> = 5).</p>
Full article ">
16 pages, 5438 KiB  
Article
miR-195-5p Inhibits Colon Cancer Progression via KRT23 Regulation
by Emanuele Piccinno, Viviana Scalavino, Nicoletta Labarile, Raffaele Armentano, Gianluigi Giannelli and Grazia Serino
Pharmaceutics 2024, 16(12), 1554; https://doi.org/10.3390/pharmaceutics16121554 - 4 Dec 2024
Viewed by 480
Abstract
Background/Objectives: KRT23 was recently discovered as an epithelial-specific intermediate filament protein in the type I keratin family. Many studies have underlined keratin’s involvement in several biological processes as well as in the pathogenesis of different diseases. Specifically, KRT23 was reported to affect the [...] Read more.
Background/Objectives: KRT23 was recently discovered as an epithelial-specific intermediate filament protein in the type I keratin family. Many studies have underlined keratin’s involvement in several biological processes as well as in the pathogenesis of different diseases. Specifically, KRT23 was reported to affect the structural integrity of epithelial cells and to trigger cellular signaling leading to the onset of cancer. The aim of this study is to characterize a novel mechanism based on miR-195-5p/KRT23 in colorectal cancer. Methods: KRT23 mRNA and protein expression were characterized in FFPE sections from patients with CRC. The effects of miR-195-5p on KRT23 expression at the mRNA and protein levels were assessed by transient transfection experiments with mimic and inhibitor molecules. Cell attachment/detachment, migration, invasion, clone formation, and apoptosis were evaluated in human CRC cell lines after miR-195-5p mimic transfection. Results: We identified KRT23 as a putative target of miR-195-5p, a microRNA that we previously demonstrated to be reduced in CRC. We have proved the KRT23 expression deregulation in the tumoral section compared to adjacent normal mucosa in patients with CRC, according to the data derived from the public repository. We proved that the gain of miR-195-5p decreased the KRT23 expression. Conversely, we demonstrated that the inhibition of miR-195-5p led to an increase in KRT23 expression levels. We have demonstrated the in vitro effectiveness of miR-195-5p on CRC progression and that the in vivo intraperitoneal delivery of miR-195-5p mimic lowered colonic KRT23 mRNA and protein expression. Conclusions: These findings highlight a new regulatory mechanism by miR-195-5p in CRC affecting the keratin intermediate filaments and underline the miR-195-5p potential clinical properties. Full article
(This article belongs to the Special Issue MicroRNAs in Cancer Therapy: Recent Advances and Prospects)
Show Figures

Figure 1

Figure 1
<p>miR-195-5p targets <span class="html-italic">KRT23</span> binding two specific sequences in CDS mRNA. miRwalk algorithm was used for the analysis founding that miR-195-5p links <span class="html-italic">KRT23</span> CDS in two different sites.</p>
Full article ">Figure 2
<p><span class="html-italic">KRT23</span> expression in CRC. GEPIA tool investigation highlighted a statistically significant deregulation of <span class="html-italic">KRT23</span> between tumor and healthy control status. * <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 3
<p><span class="html-italic">KRT23</span> expression in patients with CRC (n = 30). (<b>A</b>) The RNA was extracted to perform qPCR analysis starting from FFPE tissue blocks that include tumor and adjacent normal colon. Our results demonstrated the crucial increase in expression of <span class="html-italic">KRT23</span> in CRC tissue. ** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) Pearson correlation in CRC tissues demonstrated a negative correlation between miR-195-5p and <span class="html-italic">KRT23</span> expression, indicating that miR-195-5p may be involved in the regulation of <span class="html-italic">KRT23</span>. r = −0.249, <span class="html-italic">p</span> &lt; 0.05. Each point represents a sample.</p>
Full article ">Figure 4
<p>KRT23 protein expression at IHC in FFPE tissues of patients with CRC. (<b>A</b>) Representative images acquired at 4× original magnification showing a strong stain in CRC tissue compared to adjacent normal mucosa. (<b>B</b>) The immunoreactivity score quantified the signal intensity that corresponds to the KRT23 expression in colonic epithelium *** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 5
<p>KRT23 expression in mimic transfected cell lines. (<b>A</b>) KRT23 gene expression was assessed in HCT116 (<b>left</b>) and HT29 (<b>right</b>) transfected cells. The raise of miR-195-5p at 30 nM and 50 nM concentrations by transient transfection led to a valuable reduction of KRT23 in both cell lines. Expression data were normalized on the Gapdh housekeeping gene. Graphs are representative of four independent experiments (mean ± SEM). ** <span class="html-italic">p</span> &lt; 0.001; *** <span class="html-italic">p</span> &lt; 0.0001. (<b>B</b>) KRT23 protein expression in mimic transfected cells. The increase in intracellular levels of miR-195-5p induced an effective decrease in KRT23 levels in both cell lines. KRT23 values were obtained by dividing the normalized transfected sample values by the normalized mock-control sample values. Normalization was performed on the values of β-tubulin housekeeping protein. <a href="#app1-pharmaceutics-16-01554" class="html-app">Supplementary File S1</a> contained the raw data for all Western blot experiments. ** <span class="html-italic">p</span> &lt; 0.001; *** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 6
<p>KRT23 expression after miR-195-5p inhibitor transfection. In HCT116 and HT29 cells, KRT23 mRNA (<b>A</b>) and protein expression (<b>B</b>) levels were significantly increased after transfection compared to mock control confirming the KRT23 regulation by miR-195-5p. mRNA expression data were normalized on the GAPDH housekeeping gene. KRT23 protein values were obtained by dividing the normalized transfected sample values by the normalized mock-control sample values. Data were normalized on the values of β-tubulin housekeeping protein. <a href="#app1-pharmaceutics-16-01554" class="html-app">Supplementary File S1</a> contained the raw data for all Western blot experiments. ** <span class="html-italic">p</span> &lt; 0.001; *** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 7
<p>miR-195-5p mimic inhibits cell attachment and detachment. (<b>A</b>,<b>B</b>) Attachment assay employed on HCT116 (<b>left</b>) and HT29 (<b>right</b>) after mimic transfection. In transfected conditions, the relative attachment of cells was found to be deeply reduced compared to mock control. The values were obtained by dividing the values of the normalized transfected sample with the normalized mock-control sample and derived at least from four independent experiments. ANOVA <span class="html-italic">p</span> &lt; 0.0001 (<b>C</b>,<b>D</b>) Detachment rate of HCT116 and HT29 following mimic transient transfection. The intracellular increase level of miR-195-5p affected the detachment capacity of transfected cells. The data were presented as a percentage of the detached cells to total cells and are presented as the mean  ±  SEM of at least four independent experiments. ANOVA <span class="html-italic">p</span> &lt; 0.001 * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.001, *** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 8
<p>miR-195-5p mimic effectiveness on the formation of HCT-116 cell (<b>A</b>,<b>B</b>) and HT29 cell (<b>C</b>,<b>D</b>) colonies. Transient transfection with molecules of miR-195-5p markedly decreased the cell proliferative rates. After transfection, cell clonogenic potential was significantly declined. For each cell line, the representative images of the colony formation assay and the relative proliferation rate are shown. Magnification 4×. The results are presented as the mean of at least four independent experiments ± SEM. ANOVA <span class="html-italic">p</span> &lt; 0.0001; ** <span class="html-italic">p</span> &lt; 0.001; *** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 9
<p>Impact of miR-195-5p mimic administration on <span class="html-italic">Krt23</span> expression in CRC mice model (n = 14 mice/group). <span class="html-italic">Krt23</span> expression in both medial (<b>A</b>) and distal colon segments (<b>B</b>) was significantly decreased in the miR-195-5p-treated group as compared with vehicle mice. Expression data were normalized on housekeeping gene <span class="html-italic">Gapdh</span> and are shown as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.01, ** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 10
<p>miR-195-5p in vivo effect on KRT23 protein expression in AOM/DSS mice (n = 14 mice/group). According to mRNA data, KRT23 protein expression in the medial and distal colons was strongly reduced in miR-195-5p-treated mice compared to the vehicle group. Each single-channel image derived from DAPI and KRT23 signals is merged. Original magnification: 20×.</p>
Full article ">
15 pages, 2191 KiB  
Article
Macrophage Inhibitor Clodronate Enhances Liver Transduction of Lentiviral but Not Adeno-Associated Viral Vectors or mRNA Lipid Nanoparticles in Neonatal and Juvenile Mice
by Loukia Touramanidou, Sonam Gurung, Claudiu A. Cozmescu, Dany Perocheau, Dale Moulding, Patrick F. Finn, Andrea Frassetto, Simon N. Waddington, Paul Gissen and Julien Baruteau
Cells 2024, 13(23), 1979; https://doi.org/10.3390/cells13231979 - 29 Nov 2024
Viewed by 558
Abstract
Recently approved adeno-associated viral (AAV) vectors for liver monogenic diseases haemophilia A and B are exemplifying the success of liver-directed viral gene therapy. In parallel, additional gene therapy strategies are rapidly emerging to overcome some inherent AAV limitations, such as the non-persistence of [...] Read more.
Recently approved adeno-associated viral (AAV) vectors for liver monogenic diseases haemophilia A and B are exemplifying the success of liver-directed viral gene therapy. In parallel, additional gene therapy strategies are rapidly emerging to overcome some inherent AAV limitations, such as the non-persistence of the episomal transgene in the rapidly growing liver and immune response. Viral integrating vectors such as in vivo lentiviral gene therapy and non-viral vectors such as lipid nanoparticles encapsulating mRNA (LNP-mRNA) are rapidly being developed, currently at the preclinical and clinical stages, respectively. Macrophages are the first effector cells of the innate immune response triggered by gene therapy vectors. Macrophage uptake and activation following administration of viral gene therapy and LNP have been reported. In this study, we assessed the biodistribution of AAV, lentiviral, and LNP-mRNA gene therapy following the depletion of tissue macrophages by clodronate pre-treatment in neonatal and juvenile mice. Both neonatal and adult clodronate-treated mice showed a significant increase in lentiviral-transduced hepatocytes. In contrast, clodronate pre-treatment did not modify hepatocyte transduction mediated by hepatotropic AAV8 but reduced LNP-mRNA transfection in neonatal and juvenile animals. These results highlight the importance of age-specific responses in the liver and will have translational applications for gene therapy programs. Full article
Show Figures

Figure 1

Figure 1
<p>Macrophage depletion in neonatal juvenile mice in liver and spleen following clodronate liposome administration. (<b>A</b>) Schematic representation of the experimental design testing pre-treatment with clodronate liposomes, LPS and PBS liposomes in the depletion of liver macrophages in neonatal and juvenile C57BL/6J mice. (<b>B</b>) Quantification of F8/40 immunostaining, (<b>C</b>) representative images of F8/40 immunostaining in liver sections of neonatal C57BL/6J mice. (<b>D</b>) Quantification of F8/40 immunostaining, (<b>E</b>) representative images of F8/40 immunostaining in spleen sections of neonatal C57BL/6J mice. (<b>F</b>) Quantification of F8/40 immunostaining, (<b>G</b>) representative images of F8/40 immunostaining in liver sections of juvenile C57BL/6J mice. (<b>H</b>) Quantification of F8/40 immunostaining, (<b>I</b>) representative images of F8/40 immunostaining in spleen sections of juvenile C57BL/6J mice. (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>) Horizontal lines display the mean ± standard deviation. One-way ANOVA with Tukey’s multiple comparisons test, ns: not significant, * <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, **** <span class="html-italic">p</span> &lt; 0.0001; LPS (<span class="html-italic">n</span> = 4), PBS LNP (<span class="html-italic">n</span> = 4), clod LNP (<span class="html-italic">n</span> = 4). (<b>C</b>,<b>E</b>,<b>G</b>,<b>I</b>) Scale bars are 100 μm for ×10 magnification. Clod: clodronate liposomes; LPS: lipopolysaccharide; PBS: Phosphate Buffer Solution.</p>
Full article ">Figure 2
<p>Macrophage depletion enhances lentiviral liver transduction in neonatal and juvenile mice. (<b>A</b>) Schematic representation of the experimental design testing lentiviral vector transduction following pre-treatment with clodronate liposomes in CD1 mice. (<b>B</b>) Lentiviral vector genome copies per cell in liver, (<b>C</b>) quantification of GFP immunostaining, (<b>D</b>) representative images of GFP immunostaining in liver sections of neonatally injected CD1 mice. (<b>E</b>) Lentiviral vector genome copies per cell in liver, (<b>F</b>) quantification of GFP immunostaining, (<b>G</b>) representative images of GFP immunostaining in liver sections of 2.5-week-old injected CD1 mice. (<b>B</b>,<b>C</b>,<b>E</b>,<b>F</b>) Horizontal lines display the mean ± standard deviation. One-way ANOVA with Tukey’s multiple comparisons tests, ns: not significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01; untreated (<span class="html-italic">n</span> = 3–5), PBS + LV (<span class="html-italic">n</span> = 6), clod + LV (<span class="html-italic">n</span> = 5–7). (<b>D</b>,<b>G</b>) Scale bars are 100 μm and 50 μm for ×10 and ×20 magnification, respectively. Clod: clodronate liposomes; LV: lentivirus; PBS: Phosphate Buffer Solution; VCN: vector copy number.</p>
Full article ">Figure 3
<p>Macrophage depletion decreases splenic transduction and enhances lentiviral-mediated liver transduction; a reproducible finding between outbred and inbred mouse strains. (<b>A</b>) Schematic representation of the experimental design testing lentiviral vector transduction following pre-treatment with clodronate liposomes in C57BL/6J mice. (<b>B</b>) Lentiviral vector genome copies per cell in liver, (<b>C</b>) vector genome copies per cell in spleen; (<b>D</b>) quantification of GFP immunostaining, (<b>E</b>) representative images of GFP immunostaining in liver sections of neonatally injected C57BL/6J mice. (<b>F</b>) Lentiviral vector genome copies per cell in liver, (<b>G</b>) vector genome copies per cell in spleen; (<b>H</b>) quantification of GFP immunostaining, (<b>I</b>) representative images of GFP immunostaining in liver sections of 2.5-week-old injected C57BL/6J mice. (<b>B</b>–<b>H</b>) Horizontal lines display the mean ± standard deviation. One-way ANOVA with Tukey’s multiple comparisons test, ns: not significant, * <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, **** <span class="html-italic">p</span> &lt; 0.0001; untreated (<span class="html-italic">n</span> = 4–5), PBS + LV (<span class="html-italic">n</span> = 6), clod + LV (<span class="html-italic">n</span> = 6). (<b>E</b>,<b>I</b>) Scale bars are 100 μm and 50 μm for ×10 and ×20 magnification, respectively. Clod: clodronate liposomes; LV: lentivirus; PBS: Phosphate Buffer Solution; VCN: vector copy number.</p>
Full article ">Figure 4
<p>Macrophage depletion does not influence AAV-mediated liver transduction. (<b>A</b>) Schematic representation of the experimental design testing AAV vector transduction following pre-treatment with clodronate liposomes in CD1 mice. (<b>B</b>) AAV vector genome copies per cell in liver, (<b>C</b>) quantification of GFP immunostaining, (<b>D</b>) representative images of GFP immunostaining in liver sections of neonatally injected CD1 mice. (<b>E</b>) AAV vector genome copies per cell in liver, (<b>F</b>) quantification of GFP immunostaining, (<b>G</b>) representative images of GFP immunostaining in liver sections of 2.5-week-old injected CD1 mice. (<b>B</b>,<b>C</b>,<b>E</b>,<b>F</b>) Horizontal lines display the mean ± standard deviation. One-way ANOVA with Tukey’s multiple comparison test, ns: not significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01; untreated (<span class="html-italic">n</span> = 4–5), PBS + AAV (<span class="html-italic">n</span> = 6), clod + AAV (<span class="html-italic">n</span> = 6), AAV control (<span class="html-italic">n</span> = 4). (<b>D</b>,<b>G</b>) Scale bars are 100 μm and 50 μm for ×10 and ×20 magnification, respectively. AAV: adeno-associated virus, clod: clodronate liposomes; PBS: Phosphate Buffer Solution; VCN: vector copy number.</p>
Full article ">Figure 5
<p>LNP-mRNA-mediated liver transduction does not benefit from macrophage depletion. (<b>A</b>) Schematic representation of the experimental design testing liver uptake of LNP.GFP following pre-treatment with clodronate liposomes in CD1 mice. (<b>B</b>) GFP western blot at 24 h post-LNP-mRNA administration (<span class="html-italic">n</span> = 3), (<b>C</b>) quantification of GFP western blot of livers against housekeeping control GAPDH. (<b>D</b>) quantification of GFP immunostaining, (<b>E</b>) representative images of GFP immunostaining in liver sections of neonatally injected CD1 mice. (<b>F</b>) GFP western blot at 24 h post-LNP-mRNA administration (<span class="html-italic">n</span> = 3), (<b>G</b>) quantification of GFP western blot of livers against housekeeping control GAPDH. (<b>H</b>) Quantification of GFP immunostaining, (<b>I</b>) representative images of GFP immunostaining in liver sections of juvenile-injected CD1 mice. (<b>C</b>,<b>D</b>,<b>G</b>,<b>H</b>) Horizontal lines display the mean ± standard deviation. One-way ANOVA with Tukey’s multiple comparisons test, ns: not significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01; untreated (<span class="html-italic">n</span> = 3–5), PBS + LNP (<span class="html-italic">n</span> = 5–6), clod + LNP (<span class="html-italic">n</span> = 6), LNP control (<span class="html-italic">n</span> = 4). (<b>E</b>,<b>I</b>) Scale bars are 100 μm and 50 μm for ×10 and ×20 magnification, respectively. Clod: clodronate liposomes; LNP: Lipid nanoparticles; PBS: Phosphate Buffer Solution.</p>
Full article ">
14 pages, 3474 KiB  
Article
Enhancing the Chemosensitivity of MKN-45 Gastric Cancer Cells to Docetaxel via B7H6 Suppression: A Novel Therapeutic Strategy
by Elif Sibel Aslan, Nermin Akcali, Cuneyd Yavas, Sajjad Eslamkhah, Savas Gur and Lutfiye Karcioglu Batur
Life 2024, 14(12), 1546; https://doi.org/10.3390/life14121546 - 26 Nov 2024
Viewed by 502
Abstract
Purpose: Although chemotherapy is one of the standard treatments for gastric cancer, the disease’s resistance mechanisms continue to limit the survival rates. B7H6 (NCR3LG1), an immune checkpoint belonging to the B7 family, is significantly overexpressed in gastric cancer. This work investigated [...] Read more.
Purpose: Although chemotherapy is one of the standard treatments for gastric cancer, the disease’s resistance mechanisms continue to limit the survival rates. B7H6 (NCR3LG1), an immune checkpoint belonging to the B7 family, is significantly overexpressed in gastric cancer. This work investigated the possibility of using B7H6 suppression to improve the effectiveness of the widely used chemotherapy medication docetaxel. Materials and Methods: In this study, MKN-45 gastric cancer cells were transfected for 24 h with siRNA targeting B7H6, and then, docetaxel was added at optimal inhibitory doses (IC25 and IC50). To assess the impact of this combination therapy, cellular viability, proliferation, and migration were assessed using MTT assay, colony-forming unit assay, and wound-healing assay, respectively. Additionally, apoptosis and cell cycle status were evaluated by flow cytometry. Moreover, using qRT-PCR, the gene expression of B7H6 and indicators associated with apoptosis was also examined. Results: The sensitivity of MKN-45 cells to docetaxel was greatly increased by the siRNA-mediated knockdown of B7H6, resulting in a decrease in the drug’s IC50 value. When compared to each therapy alone, the combination of B7H6 siRNA plus docetaxel at IC50 levels exhibited a significant increase in apoptosis rate. The volume of cells arrested at the sub-G1 and G2-M phase was shown to rise when B7H6 siRNA transfection was combined with docetaxel. Furthermore, the combination treatment significantly decreased the ability of cells to migrate and form colonies. Conclusions: B7H6 suppression increases the susceptibility of MKN-45 gastric cancer cells to docetaxel treatment, resulting in decreased cellular proliferation and increased rates of apoptosis. The present work underscores the possibility of enhancing treatment results in gastric cancer by merging conventional chemotherapy with gene-silencing approaches. Full article
(This article belongs to the Section Physiology and Pathology)
Show Figures

Figure 1

Figure 1
<p>Analysis of the B7H6 immune checkpoint gene expression in gastric cancer cell lines. The MKN-45 cell line has the most significant level of expression (*** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 2
<p>The expression of the <span class="html-italic">B7H6</span> gene in MKN-45 cells was inhibited in a dose-dependent manner using particular siRNAs at concentrations of 40, 60, 80, and 100 pmol for 24 h. The data indicate a significant reduction in <span class="html-italic">B7H6</span> expression, with the most prominent decline found at a concentration of 60 pmol siRNA (*** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 3
<p>The MTT test findings demonstrate the suppressive effects of docetaxel on the vitality of MKN-45 cells. At concentrations of 15 μg/mL and 9.8 μg/mL, docetaxel decreased cell viability to 50% (IC50) and 25% (IC25), respectively. Following transfection, the IC50 and IC25 values exhibited a drop to 5.6 μg/mL and 2.35 μg/mL, respectively, suggesting an improved responsiveness to docetaxel.</p>
Full article ">Figure 4
<p>Wound-healing assay showing the impact of <span class="html-italic">B7H6</span> siRNA and docetaxel on MKN-45 cell migration at 0, 24, and 48 h. Cells treated with the combination of <span class="html-italic">B7H6</span> siRNA and docetaxel, especially at IC50, exhibited significantly reduced migration compared to those treated with either treatment alone.</p>
Full article ">Figure 5
<p>Colony-forming unit assay showing colony formation was reduced with <span class="html-italic">B7H6</span> siRNA, further decreased with docetaxel, and nearly eliminated with the combination treatment.</p>
Full article ">Figure 6
<p>(<b>A</b>) Apoptosis in MKN-45 cells treated with docetaxel at IC25 and IC50 doses. When docetaxel was applied alone at IC25 and IC50, the apoptosis rates observed were 13.89% and 31.8%, respectively. This indicates that while docetaxel independently promotes apoptosis, the effect is limited compared to combination treatments. (<b>B</b>) Apoptosis in MKN-45 cells treated with a combination of <span class="html-italic">B7H6</span> siRNA and docetaxel at IC25 and IC50 doses. The combination treatment significantly enhanced apoptosis rates, reaching 36.4% for the IC25 dose and 63.8% for the IC50 dose. This substantial increase highlights the synergistic effect of <span class="html-italic">B7H6</span> siRNA in enhancing the chemosensitivity of MKN-45 cells to docetaxel. Statistical analysis confirmed that these differences were highly significant (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 7
<p>(<b>A</b>) Flow cytometry plots for the control group and cells treated with IC25 and IC50 doses of docetaxel. (<b>B</b>) Flow cytometry plots for cells treated with siRNA alone and in combination with IC25 and IC50 doses of docetaxel. Flow cytometry analysis of MKN-45 cells treated with docetaxel and <span class="html-italic">B7H6</span> siRNA demonstrates significant changes in cell cycle distribution across various treatment groups, including control, IC25, IC50, siRNA alone, and combinations of siRNA with IC25 and IC50 doses of docetaxel. Notably, treatment with docetaxel, especially when combined with <span class="html-italic">B7H6</span> siRNA, led to marked increases in sub-G1 (apoptotic) and G2-M phase arrest, indicative of enhanced apoptosis and cell cycle disruption. The combined treatment with IC25 and IC50 doses of docetaxel and siRNA significantly elevated the sub-G1 and G2-M phase cell populations compared to treatment with docetaxel alone.</p>
Full article ">Figure 8
<p>qRT-PCR analysis of apoptosis-related gene expression in MKN-45 cells. The combined treatment with <span class="html-italic">B7H6</span> siRNA and docetaxel significantly modulated the expression of key apoptotic markers. <span class="html-italic">Bax</span> (<b>A</b>) and caspase-3 (<b>B</b>) levels were notably increased, indicating enhanced pro-apoptotic activity, while <span class="html-italic">Bcl-2</span> expression (<b>C</b>) was significantly reduced, suggesting a decrease in anti-apoptotic signaling. These changes compared to individual treatments and control groups highlight the potentiation of apoptosis induced by the combination therapy. Asterisks (*, ***, ****) in the graph represent varying levels of statistical significance, with * indicating <span class="html-italic">p</span> &lt; 0.05, *** indicating <span class="html-italic">p</span> &lt; 0.001 and **** indicating <span class="html-italic">p</span> &lt; 0.0001 reflecting progressively higher levels of confidence in the observed differences.</p>
Full article ">
21 pages, 2785 KiB  
Article
Impact of Circadian Clock PER2 Gene Overexpression on Rumen Epithelial Cell Dynamics and VFA Transport Protein Expression
by Rahmat Ali, Yongkang Zhen, Xi Zanna, Jiaqi Lin, Chong Zhang, Jianjun Ma, Yuhong Zhong, Hosameldeen Mohamed Husien, Ahmad A. Saleh and Mengzhi Wang
Int. J. Mol. Sci. 2024, 25(22), 12428; https://doi.org/10.3390/ijms252212428 - 19 Nov 2024
Viewed by 837
Abstract
The circadian gene PER2 is recognized for its regulatory effects on cell proliferation and lipid metabolism across various non-ruminant cells. This study investigates the influence of PER2 gene overexpression on goat rumen epithelial cells using a constructed pcDNA3.1-PER2 plasmid, assessing its impact [...] Read more.
The circadian gene PER2 is recognized for its regulatory effects on cell proliferation and lipid metabolism across various non-ruminant cells. This study investigates the influence of PER2 gene overexpression on goat rumen epithelial cells using a constructed pcDNA3.1-PER2 plasmid, assessing its impact on circadian gene expression, cell proliferation, and mRNA levels of short-chain fatty acid (SCFA) transporters, alongside genes related to lipid metabolism, cell proliferation, and apoptosis. Rumen epithelial cells were obtained every four hours from healthy dairy goats (n = 3; aged 1.5 years; average weight 45.34 ± 4.28 kg), cultured for 48 h in vitro, and segregated into control (pcDNA3.1) and overexpressed (pcDNA3.1-PER2) groups, each with four biological replicates. The study examined the potential connection between circadian rhythms and nutrient assimilation in ruminant, including cell proliferation, apoptosis, cell cycle dynamics, and antioxidant activity and the expression of circadian-related genes, VFA transporter genes and regulatory factors. The introduction of the pcDNA3.1-PER2 plasmid drastically elevated PER2 expression levels by 3471.48-fold compared to controls (p < 0.01), confirming effective overexpression. PER2 overexpression resulted in a significant increase in apoptosis rates (p < 0.05) and a notable reduction in cell proliferation at 24 and 48 h post-transfection (p < 0.05), illustrating an inhibitory effect on rumen epithelial cell growth. PER2 elevation significantly boosted the expression of CCND1, WEE1, p21, and p16 (p < 0.05) while diminishing CDK4 expression (p < 0.05). While the general expression of intracellular inflammation genes remained stable, TNF-α expression notably increased. Antioxidant marker levels (SOD, MDA, GSH-Px, CAT, and T-AOC) exhibited no significant change, suggesting no oxidative damage due to PER2 overexpression. Furthermore, PER2 overexpression significantly downregulated AE2, NHE1, MCT1, and MCT4 mRNA expressions while upregulating PAT1 and VH+ ATPase. These results suggest that PER2 overexpression impairs cell proliferation, enhances apoptosis, and modulates VFA transporter-related factors in the rumen epithelium. This study implies that the PER2 gene may regulate VFA absorption through modulation of VFA transporters in rumen epithelial cells, necessitating further research into its specific regulatory mechanisms. Full article
(This article belongs to the Special Issue Molecular Advances in Circadian Rhythm and Metabolism)
Show Figures

Figure 1

Figure 1
<p>Relative expression of <span class="html-italic">PER2</span> gene in goat rumen epithelial cells. The data of each group were mean ± SEM (n = 3), ** showed significant difference (<span class="html-italic">p</span> ≤ 0.01).</p>
Full article ">Figure 2
<p>Influence of <span class="html-italic">PER2</span> overexpression on goat rumen epithelial cell proliferation and apoptosis. (<b>A</b>,<b>B</b>) Consequences of <span class="html-italic">PER2</span> overexpression on goat rumen epithelial cell apoptosis; (<b>C</b>) consequences of <span class="html-italic">PER2</span> overexpression on goat rumen epithelial cell proliferation. Each group’s data are represented as mean <span class="html-italic">±</span> SEM (n = 3), ** indicates a significant difference (<span class="html-italic">p</span> ≤ 0.01), * indicates a significant difference (<span class="html-italic">p</span> ≤ 0.05).</p>
Full article ">Figure 3
<p>Effect of <span class="html-italic">PER2</span> overexpression on membrane damage in goat rumen epithelial cells.</p>
Full article ">Figure 4
<p>Effect of <span class="html-italic">PER2</span> overexpression on ROS levels in goat rumen epithelial cells.</p>
Full article ">Figure 5
<p>Effect of <span class="html-italic">PER2</span> overexpression on antioxidant markers in goat rumen epithelial cells.</p>
Full article ">Figure 6
<p>(<b>a</b>) Construction model of overexpression vector, (<b>b</b>) <span class="html-italic">PER2</span> CDS amplification results, and (<b>c</b>) pcDNA3.1 double enzyme cut results. M; 5 kb.</p>
Full article ">
14 pages, 1407 KiB  
Article
Acid Sphingomyelinase Activation and ROS Generation Potentiate Antiproliferative Effects of Mitomycin in HCC
by Sirkka Buitkamp, Stephanie Schwalm, Katja Jakobi, Nerea Ferreiros, Christin Wünsche, Stefan Zeuzem, Erich Gulbins, Christoph Sarrazin, Josef Pfeilschifter and Georgios Grammatikos
Int. J. Mol. Sci. 2024, 25(22), 12175; https://doi.org/10.3390/ijms252212175 - 13 Nov 2024
Viewed by 560
Abstract
Sphingolipids play a major role in the regulation of hepatocellular apoptosis and proliferation. We have previously identified sphingolipid metabolites as biomarkers of chronic liver disease and hepatocellular carcinoma. Human hepatocellular carcinoma cell lines were transfected with a plasmid vector encoding for acid sphingomyelinase. [...] Read more.
Sphingolipids play a major role in the regulation of hepatocellular apoptosis and proliferation. We have previously identified sphingolipid metabolites as biomarkers of chronic liver disease and hepatocellular carcinoma. Human hepatocellular carcinoma cell lines were transfected with a plasmid vector encoding for acid sphingomyelinase. Overexpressing cells were subsequently treated with mitomycin and cell proliferation, acid sphingomyelinase activity, sphingolipid concentrations, and generation of reactive oxygen species were assessed. The stimulation of acid sphingomyelinase-overexpressing cell lines with mitomycin showed a significant activation of the enzyme (p < 0.001) followed by an accumulation of various ceramide species (p < 0.001) and reactive oxygen radicals (p < 0.001) as compared to control transfected cells. Consequently, a significant reduction in cell proliferation was observed in acid sphingomyelinase-overexpressing cells (p < 0.05) which could be diminished by the simultaneous application of antioxidant agents. Moreover, the application of mitomycin induced significant alterations in mRNA expression levels of ceramidases and sphingosine kinases (p < 0.05). Our data suggest that the overexpression of the acid sphingomyelinase in human hepatoma cell lines enhances the in vitro antiproliferative potential of mitomycin via accumulation of ceramide and reactive oxygen species. The selective activation of acid sphingomyelinase might offer a novel therapeutic approach in the treatment of hepatocellular carcinoma. Full article
Show Figures

Figure 1

Figure 1
<p>Mitomycin C upregulates the expression and activity of ASM. mRNA-expression and enzyme activity after transfection with either an empty vector (pJK) or a plasmid encoding for ASM (<b>A</b>,<b>B</b>). The transfected Huh7.5 and HepG2 cells were treated for 48 h either with or without 3 µM mitomycin C (MMC) (<b>C</b>,<b>D</b>). The data are expressed in % of the basic expression level (<b>A</b>) or in % of untreated control (<b>C</b>). Given the specific activity of [<sup>14</sup>C] Sphingomyelin of 52 mCi/mmol, the activity of 100 cpm/μg/h corresponds to 1 pmol/μg/h specific activity of the acid sphingomyelinase. Shown are means +/− SD of three independent experiments (<span class="html-italic">n</span> = 3). *** <span class="html-italic">p</span> &lt; 0.0001, ** <span class="html-italic">p</span> &lt; 0.001, and * <span class="html-italic">p</span> &lt; 0.05 indicate statistical significance when compared to the control values (<b>B</b>,<b>D</b>). The results are expressed in counts normalized on extracted protein (<b>B</b>) or in % of untreated control (<b>D</b>) and are means ± SD (<span class="html-italic">n</span> = 3, *** <span class="html-italic">p</span> &lt; 0.0001, ** <span class="html-italic">p</span> &lt; 0.001, and * <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 2
<p>Mitomycin C causes enhanced cleavage of sphingomyeline and upregulates cellular levels of the ceramide species in ASM-overexpressing cells. The ceramide levels in ASM transfected (ASM) and control transfected (pJK) Huh7.5 after treatment with 3 µM mitomycin C (MMC) for 48 h. The data are expressed in % of the untreated control and are means ± SD from a total of three independent experiments (<span class="html-italic">n</span> = 3). *** <span class="html-italic">p</span> &lt; 0.0001, ** <span class="html-italic">p</span> &lt; 0.001, and * <span class="html-italic">p</span> &lt; 0.05 are considered significantly different when compared to the control group.</p>
Full article ">Figure 3
<p>The effect of Mitomycin C on cell viability and ROS production is abrogated by antioxidants. The cells were either pretreated for 1 h with or without 25 µM imipramine prior to stimulation for 48 h either with or without 0.3 µM mitomycin C (MMC) (<b>A</b>). The data of cell counts are expressed as % of control and are means ± SD (<span class="html-italic">n</span> = 3). *** <span class="html-italic">p</span> &lt; 0.0001, ** <span class="html-italic">p</span> &lt; 0.001, and * <span class="html-italic">p</span> &lt; 0.05 indicate statistical significance when compared to the control group. (<b>B</b>) The cells were incubated for 48 h either with or without 0.3 µM MMC C. The data are expressed in % of the untreated control and are means ± SD of at least three (<span class="html-italic">n</span> = 3) independent experiments. (<b>C</b>) The cells were treated for 48 h with either 0.3 µM MMC C (MMC), 3 mM N-acetyl-Cysteine (NAC), 100 µM Tiron, or combined. The results are expressed as % of control and are means ± SD (<span class="html-italic">n</span> = 3). *** <span class="html-italic">p</span> &lt; 0.0001, ** <span class="html-italic">p</span> &lt; 0.001, and * <span class="html-italic">p</span> &lt; 0.05 are significantly different when compared to the control group.</p>
Full article ">Figure 4
<p>The effect of Mitomycin C on levels of sphingosine, S1P, and sphinganine-1-p. The ASM transfected (ASM) and control transfected (pJK) cells were treated for 48 h either with or without 3 µM mitomycin C (MMC). The results are expressed in % of the untreated control and are means ± SD (<span class="html-italic">n</span> = 3). *** <span class="html-italic">p</span> &lt; 0.0001, ** <span class="html-italic">p</span> &lt; 0.001, and * <span class="html-italic">p</span> &lt; 0.05 indicate statistical significance when compared to the control group.</p>
Full article ">Figure 5
<p>The mRNA expression of various enzymes of the sphingolipid metabolism upon Mitomycin C treatment. The ASM transfected (ASM) and control transfected (pJK) Huh7.5 und HepG2 cells were incubated for 48 h either with or without 3 µM mitomycin C (MMC). The data were obtained by the ΔΔCt method as described in the methods section and are expressed in % of untreated control, shown are means ± SD (<span class="html-italic">n</span> = 3). *** <span class="html-italic">p</span> &lt; 0.0001, ** <span class="html-italic">p</span> &lt; 0.001, and * <span class="html-italic">p</span> &lt; 0.05 are considered significantly different when compared to the control group.</p>
Full article ">
17 pages, 4356 KiB  
Article
Effect of Culture Supernatant of Clostridium butyricum TO-A on Human DNA-Repair-Factor-Encoding Gene Promoters
by Shunsuke Takaoka, Takuro Ishii, Yuriko Umihara, Ryuji Otani, Sota Akazawa, Takahiro Oda, Yoko Ogino, Yoichi Okino, Dian-Sheng Wang and Fumiaki Uchiumi
Int. J. Mol. Sci. 2024, 25(22), 12151; https://doi.org/10.3390/ijms252212151 - 12 Nov 2024
Viewed by 807
Abstract
In this study, Clostridium butyricum TO-A culture supernatant (CBCS) or butyric acid was added to a culture medium of human cervical carcinoma HeLa S3 cells, and changes in DNA-repair-related gene promoter activities were investigated. The HeLa S3 cells were transfected with a luciferase [...] Read more.
In this study, Clostridium butyricum TO-A culture supernatant (CBCS) or butyric acid was added to a culture medium of human cervical carcinoma HeLa S3 cells, and changes in DNA-repair-related gene promoter activities were investigated. The HeLa S3 cells were transfected with a luciferase (Luc) expression vector containing approximately 500 bp of the 5′-upstream region of several human DNA-repair-related genes and cultured with a medium containing the CBCS (10%) or butyric acid (2.5 mM). The cells were harvested after 19 to 42 h of incubation. A Luc assay revealed that the human ATM, PARG, PARP1, and RB1 gene promoter activities were significantly increased. A Western blot analysis showed that the amounts of the proteins encoded by these genes markedly increased. Furthermore, 8, 24, and 48 h after the addition of the CBCS (10%), total RNA was extracted and subjected to RNAseq analysis. The results showed that the expression of several inflammation- and DNA-replication/repair-related genes, including NFKB and the MCM gene groups, decreased markedly after 8 h. However, the expression of the histone genes increased after 24 h. Elucidation of the mechanism by which the CBCS and butyrate affect the expression of genes that encode DNA-repair-associated proteins may contribute to the prevention of carcinogenesis, the risk of which rises in accordance with aging. Full article
(This article belongs to the Section Biochemistry)
Show Figures

Figure 1

Figure 1
<p>Responses of human gene promoters to bacteria-cultivated supernatants in HeLa S3 cells. (<b>A</b>) Screening of bacteria-cultivated supernatants (BCSs) that could activate human DNA-repair-factor-encoding gene promoters. BSCS: <span class="html-italic">Bacillus subtilis</span> TO-A culture supernatant; EFCS: <span class="html-italic">Enterococcus faecium</span> T-110 culture supernatant; CBCS: <span class="html-italic">Clostridium butyricum</span> TO-A culture supernatant; BACS: <span class="html-italic">Bacillus amyloliquefaciens</span> TOA5001 culture supernatant. (<b>B</b>) Effect of CBCS on human DNA-repair-factor-encoding gene promoters. Three independent experiments were carried out. Results show relative Luc activities compared with those of the pGL4-PIF1-transfected cells untreated with BCS. Asterisks indicate values that were not determined.</p>
Full article ">Figure 2
<p>Morphological changes in the HeLa S3 cells after treatment with BCSs. (<b>A</b>) HeLa S3 cells were cultured in a medium containing 10% CBCS or CBCS/BSCS/EFCS mixture (CSM) for 19 h (lower panels). The upper panels indicate HeLa S3 cells that were cultured in a medium with 10% control supernatant for 19 h. (<b>B</b>) HeLa S3 cells were cultured in a medium containing 10% CBCS for 28 and 42 h (lower panels). The upper panels indicate HeLa S3 cells that were cultured in a medium with 10% control supernatant for 28 and 42 h. (<b>C</b>) HeLa S3 cells were cultured in a medium containing 0 (upper left), 1.25 (upper right), 2.5 (lower left), and 5 mM (lower right) of n-butyric acid for 25 h.</p>
Full article ">Figure 3
<p>The inhibitory effect of the CBCS on HeLa S3 cell proliferation. HeLa S3 cells (2500 cells/well) were cultivated in a 96-well plate for 24 h. Then, the culture medium was changed to that containing 0 to 20% of the CBCS (orange columns) or a control bacterial culture medium (blue columns), and a CCK-8 assay was carried out after 48 h of incubation at 37 °C with 5% of CO<sub>2</sub>. The results are shown as means ± SD from three independent experiments. Statistical analysis was performed with Student’s <span class="html-italic">t</span>-test, and asterisks (**) indicate a value of ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 4
<p>Responses of the human gene promoters to n-butyric acid in HeLa S3 cells. HeLa S3 cells were transfected with Luc reporter plasmids, including pGL4.10[<span class="html-italic">luc</span>2] and pGL4-PIF1 as negative and positive control vectors, respectively. After 4 h of transfection, the culture medium was changed to that containing 2.5 mM of n-butyric acid. After further incubation, the cells were corrected, and the Luc assay was carried out. Averages from three independent experiments with or without n-butyric acid were calculated. Fold activation indicates the ratio of the results for the average Luc activity of the butyrate-containing culture medium to those for the culture medium that did not contain butyrate.</p>
Full article ">Figure 5
<p>Levels of ATM, RB1, and PARP1 proteins in HeLa S3 cells. The HeLa S3 cells (1 × 10<sup>6</sup>) were cultivated with a DMEM containing 10% FBS for 24 h. Then, the culture medium was changed to that containing (<b>A</b>) 10% CBCS or (<b>B</b>) n-butyric acid (2.5 mM). Zero to forty-eight hours after the medium exchange, the cells were corrected, and RIPA buffer extracts were subjected to SDS-PAGE and Western blotting.</p>
Full article ">Figure 6
<p>n-Butyric acid response elements in the human <span class="html-italic">RB1</span> and <span class="html-italic">PARP1</span> gene promoters. (<b>A</b>) Deletion experiments on the human <span class="html-italic">RB1</span> and <span class="html-italic">PARP1</span> promoters. HeLa S3 cells were transfected with Luc reporter plasmids. After 4 h of transfection, the culture medium was changed to that containing 5 mM of n-butyric acid, and similar experiments were carried out. Averages from three independent experiments with or without n-butyric acid were calculated. Fold activation indicates the ratio of the results for the average Luc activity of the butyrate-containing culture medium to those for the culture medium that did not contain butyrate. (<b>B</b>) n-Butyric acid-responsive core sequences in the 5′-upstream regions of human <span class="html-italic">RB1</span> and <span class="html-italic">PARP1</span>. The n-butyric acid-responsive sequences in pGL4-RB1Δ3 and pGL4-PARP1Δ 2 were applied in the JASPAR-2020 program (with a threshold &gt; 95%). Restriction sites for <span class="html-italic">Kpn</span>I and <span class="html-italic">Xho</span>I enzymes are highlighted in yellow and pale blue, respectively. The green-highlighted GGAA and TTCC are the core motifs that are recognized by transcription factors, including ETS family proteins.</p>
Full article ">Figure 7
<p>Heat map for the RNAseq cluster analysis of differentially expressed genes (DEGs) between samples. HeLa S3 cells that were cultivated with or without CBCS (10%) for 0, 8, 24, and 48 h. Red and green represent up- and down-regulated genes, respectively.</p>
Full article ">Figure 8
<p>Classification of genes by protein coding. The up- (<b>left</b>) and down-regulated (<b>right</b>) genes of HeLa S3 cells cultivated for 8 (<b>upper</b>), 24 (<b>middle</b>), and 48 h (<b>lower</b>) were classified further as protein-coding (white pie portions) or non-coding RNAs (black pie portions).</p>
Full article ">Figure 9
<p>GO enrichment analysis comparing differential genes between CBCS-treated and non-treated HeLa S3 cells. RNA samples were obtained after (<b>A</b>) 8, (<b>B</b>) 24, and (<b>C</b>) 48 h of cultivation with or without CBCS (10%).</p>
Full article ">Figure 10
<p>KEGG enrichment analysis comparing differential genes between CBCS-treated and non-treated HeLa S3 cells. RNA samples were obtained after (<b>A</b>) 8, (<b>B</b>) 24, and (<b>C</b>) 48 h of cultivation with or without CBCS (10%).</p>
Full article ">
10 pages, 2514 KiB  
Article
Potential Involvement of miR-144 in the Regulation of Hair Follicle Development and Cycle Through Interaction with Lhx2
by Guangxian Zhou, Xiaolong Wang, Yulin Chen and Danju Kang
Genes 2024, 15(11), 1454; https://doi.org/10.3390/genes15111454 - 11 Nov 2024
Viewed by 739
Abstract
Background: Cashmere, known as “soft gold”, is a highly prized fiber from Cashmere goats, produced by secondary hair follicles. Dermal papilla cells, located at the base of these follicles, regulate the proliferation and differentiation of hair matrix cells, which are essential for hair [...] Read more.
Background: Cashmere, known as “soft gold”, is a highly prized fiber from Cashmere goats, produced by secondary hair follicles. Dermal papilla cells, located at the base of these follicles, regulate the proliferation and differentiation of hair matrix cells, which are essential for hair growth and cashmere formation. Recent studies emphasize the role of microRNAs (miRNAs) in controlling gene expression within these processes. Methods: This study centered on exploring the targeted regulatory interaction between miR-144 and the Lhx2 gene. Utilizing methodologies like miRNA target prediction, luciferase reporter assays, and quantitative PCR, they assessed the interplay between miR-144 and Lhx2. Dermal papilla cells derived from Cashmere goats were cultured and transfected with either miR-144 mimics or inhibitors to observe the subsequent effects on Lhx2 expression. Results: The results demonstrated that miR-144 directly targets the Lhx2 gene by binding to its mRNA, leading to a decrease in Lhx2 expression. This modulation of Lhx2 levels influenced the behavior of dermal papilla cells, affecting their ability to regulate hair matrix cell proliferation and differentiation. Consequently, the manipulation of miR-144 levels had a significant impact on the growth cycle of cashmere wool. Conclusions: The findings suggest miR-144 regulates hair follicle dynamics by targeting Lhx2, offering insights into hair growth mechanisms. This could lead to innovations in enhancing cashmere production, fleece quality, and addressing hair growth disorders. Future research may focus on adjusting miR-144 levels to optimize Lhx2 expression and promote hair follicle activity. Full article
(This article belongs to the Special Issue Genetics and Genomics of Sheep and Goat)
Show Figures

Figure 1

Figure 1
<p>The expression of <span class="html-italic">Lhx2</span> and miR-144 in goat tissues. (<b>A</b>) The expression of <span class="html-italic">Lhx2</span> in nine different goat tissues. Different letters represent significant differences <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) The relative expression of <span class="html-italic">Lhx2</span> in goat skin tissue at different times (1–2: catagen; 3–4: telogen; 9–10: anagen). (<b>C</b>) The relative expression of miR-144-3p in goat skin tissues at 2 (catagen), 4 (telogen) and 10 (anagen) months. ** represents <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 2
<p>MiR-144-3p target sites in <span class="html-italic">Lhx2</span> 3′ UTR. (<b>A</b>) Three predicted target sites for miR-144 on <span class="html-italic">Lhx2</span> 3′ UTR fragment. The red bases indicate the mutant sites. (<b>B</b>) A sketch map of the 3′ UTR fragment of Lhx2 cloned into the psiCheckTM-2 vector. The green block is the wild or mutant fragment. (<b>C</b>) Dual Luciferase results. The control group contained synthetic oligonucleotides. psiCheck2-WT represents the wild type, psiCheck2-MA is the mutant with the three target sites for miR-144, psiCheck2-MB represents mutant MB and MC, and psiCheck2-MC represents the mutant (MC). * Represents <span class="html-italic">p</span> &lt; 0.05, and ** represents <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 3
<p>Validation of the targeting regulatory relationship to the Lhx2 gene by the adenoviruses system. (<b>A</b>) DPCs transfected with nothing for 48 h, CK group. (<b>B</b>) DPCs transfected with CMV for 48 h, CMV group. (<b>C</b>) DPCs transfected with Ad-miR-144 for 48 h, Ad-miR-144 group. (<b>D</b>) The expression of miR-144-3p in DPCs transfected with Ad-miR-144. (<b>E</b>) The expression of <span class="html-italic">Lhx2</span> in DPCs transfected with Ad-miR-144. (<b>F</b>) Western blot results for LHX2 protein. * Represents <span class="html-italic">p</span> &lt; 0.05, ** represents <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 4
<p>The effect of miR-144 on <span class="html-italic">Lhx2</span> expression in DPCs. (<b>A</b>) The relative expression of genes (<span class="html-italic">Lhx2</span>, <span class="html-italic">Sox9</span>, and <span class="html-italic">Lgr5</span> or <span class="html-italic">Bmp2</span>, <span class="html-italic">Bmp4</span>, <span class="html-italic">Fgf10</span>, Tgf<span class="html-italic">β</span>1 and <span class="html-italic">β-catenin</span>) on DPCs. (<b>B</b>) A sketch map for the function of miR-144 on the hair follicle. The continuous line indicates the direct effect, and the dotted line indicates the direct or indirect effect on hair follicle. * Represents <span class="html-italic">p</span> &lt; 0.05, ** represents <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">
15 pages, 4067 KiB  
Article
p21Waf1/Cip1 Is a Novel Downstream Target of 40S Ribosomal S6 Kinase 2
by Alakananda Basu and Zhenyu Xuan
Cancers 2024, 16(22), 3783; https://doi.org/10.3390/cancers16223783 - 10 Nov 2024
Viewed by 614
Abstract
Background/Objectives: The ribosomal S6 kinase 2 (S6K2) acts downstream of the mechanistic target of rapamycin complex 1 and is a homolog of S6K1 but little is known about its downstream effectors. The objective of this study was to use an unbiased transcriptome [...] Read more.
Background/Objectives: The ribosomal S6 kinase 2 (S6K2) acts downstream of the mechanistic target of rapamycin complex 1 and is a homolog of S6K1 but little is known about its downstream effectors. The objective of this study was to use an unbiased transcriptome profiling to uncover how S6K2 promotes breast cancer cell survival. Methods: RNA-Seq analysis was performed to identify novel S6K2 targets. Cells were transfected with siRNAs or plasmids containing genes of interest. Western blot analyses were performed to quantify total and phosphorylated proteins. Apoptosis was monitored by treating cells with different concentrations of doxorubicin. Results: Silencing of S6K2, but not S6K1, decreased p21 in MCF-7 and T47D breast cancer cells. Knockdown of Akt1 but not Akt2 decreased p21 in MCF-7 cells whereas both Akt1 and Akt2 knockdown attenuated p21 in T47D cells. While Akt1 overexpression enhanced p21 and partially reversed the effect of S6K2 deficiency on p21 downregulation in MCF-7 cells, it had little effect in T47D cells. S6K2 knockdown increased JUN mRNA and knockdown of cJun enhanced p21. Low concentrations of doxorubicin increased, and high concentrations decreased p21 levels in T47D cells. Silencing of S6K2 or p21 sensitized T47D cells to doxorubicin via c-Jun N-terminal kinase (JNK)-mediated downregulation of Mcl-1. Conclusions: S6K2 knockdown enhanced doxorubicin-induced apoptosis by downregulating the cell cycle inhibitor p21 and the anti-apoptotic protein Mcl-1 via Akt and/or JNK. Full article
(This article belongs to the Section Molecular Cancer Biology)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>RNA-Seq analysis. (<b>A</b>). Venn graph of DEGs detected using both Cuffdiff and DESeq following S6K2 KD. FDR &lt; 0.05 was applied for each method. (<b>B</b>). The representative gene ontology terms of functional annotation clusters, which are significantly enriched in 118 shared DEGs (FDR &lt; 0.05). (<b>C</b>). Densitometric quantification of <span class="html-italic">CDKN1A</span> mRNA normalized with GAPDH control. The asterisk (*) indicates a significant difference from control siRNA-transfected cells (<span class="html-italic">p</span> &lt; 0.05) using paired Student’s <span class="html-italic">t</span>-test.</p>
Full article ">Figure 2
<p>T47D (<b>A</b>,<b>B</b>) or MCF-7 (<b>C</b>,<b>D</b>) cells were transfected with or without control non-targeting siRNA or SMARTpool (SP) S6K1 or S6K2 siRNA. Western blot analyses were performed with indicated antibodies. The intensity of p21 was determined using ImageJ and normalized with respect to loading control. Each bar represents mean ± S.E. <span class="html-italic">p</span> values were calculated using a paired Student’s <span class="html-italic">t</span> test. (<b>E</b>). Different concentrations of cell lysates from MCF-7 cells transfected with an empty vector pcDNA3 (PC) or a vector containing S6K2 construct were subjected to Western blot analyses with indicated antibodies.</p>
Full article ">Figure 3
<p>T47D (<b>A</b>,<b>B</b>) or MCF-7 (<b>C</b>,<b>D</b>) cells were transfected with indicated siRNAs and Western blot analyses were performed with indicated antibodies. Each bar represents the mean ± S.E of four independent experiments. <span class="html-italic">p</span> values were calculated using paired Student’s <span class="html-italic">t</span> test of control versus individual siRNA as described under <a href="#cancers-16-03783-f002" class="html-fig">Figure 2</a>. ***, <span class="html-italic">p</span> ≤ 0.0005; **, <span class="html-italic">p</span> ≤ 0.005; *, <span class="html-italic">p</span> ≤ 0.05.</p>
Full article ">Figure 4
<p>T47D (<b>A</b>,<b>B</b>) or MCF-7 (<b>C</b>,<b>D</b>) cells were transfected with indicated siRNAs and Western blot analyses were performed with indicated antibodies. Each bar represents mean ± S.E of at least six independent experiments. <span class="html-italic">p</span> values were calculated using paired Student’s <span class="html-italic">t</span> test.</p>
Full article ">Figure 5
<p>T47D (<b>A</b>,<b>B</b>) or MCF-7 (<b>C</b>,<b>D</b>) cells were transfected with control or S6K2 siRNA and then infected with or without adenoviral vectors containing Akt1. Western blot analyses were performed with indicated antibodies. Each bar represents mean ± S.E of six independent experiments. <span class="html-italic">p</span> values calculated using paired <span class="html-italic">t</span> test of control versus Akt1 overexpressing cells: T47D, <span class="html-italic">p</span> = 0.0007; MCF-7, <span class="html-italic">p</span> = 0.0005; Light gray bar, control siRNA; black bar, S6K2 siRNA.</p>
Full article ">Figure 6
<p>T47D cells were transfected with indicated siRNAs. Western blot analyses were performed with indicated antibodies (<b>A</b>,<b>C</b>,<b>E</b>). The intensities of cJun (<b>B</b>) and p21 (<b>D</b>) were determined using ImageJ and normalized with respect to loading controls. Each bar represents mean ± S.E. <span class="html-italic">p</span> values were calculated using paired Student’s <span class="html-italic">t</span> test.</p>
Full article ">Figure 7
<p>T47D cells were transfected with control non-targeting siRNA or S6K2 siRNA and then treated with indicated concentrations of doxorubicin (Dox). Western blot analyses were performed with indicated antibodies. The band corresponding to cleaved caspase-7 was quantified using ImageJ and the intensities of bands normalized with loading controls are shown.</p>
Full article ">Figure 8
<p>T47D cells were transfected with control non-targeting siRNA or p21 siRNA and then treated with indicated concentrations of doxorubicin. Western blot analyses were performed with indicated antibodies. The bands corresponding to p21, cleaved caspase-3, caspase-7, and PARP were quantified using ImageJ, and the intensities of bands normalized with loading controls are shown.</p>
Full article ">Figure 9
<p>T47D cells were transfected with control non-targeting siRNA, S6K2 and/or c-Jun siRNA and then treated with or without 0.3 and 1.0 µM (<b>A</b>) or 10 µM (<b>B</b>) doxorubicin. Western blot analysis was performed with indicated antibodies. The band corresponding to cleaved caspase-7 or PARP was quantified using ImageJ and the intensities of bands were normalized with tubulin.</p>
Full article ">Figure 10
<p>T47D cells were transfected with control non-targeting siRNA or JNK1 siRNA and then treated with indicated concentrations of doxorubicin. Western blot analyses were performed with indicated antibodies.</p>
Full article ">
21 pages, 3331 KiB  
Article
Characterization of HTLV-1 Infectious Molecular Clone Isolated from Patient with HAM/TSP and Immortalization of Human Primary T-Cell Lines
by Marcia Bellon, Pooja Jain and Christophe Nicot
Viruses 2024, 16(11), 1755; https://doi.org/10.3390/v16111755 - 9 Nov 2024
Viewed by 794
Abstract
Human T-cell leukemia virus (HTLV-1) is the etiological agent of lymphoproliferative diseases such as adult T-cell leukemia and T-cell lymphoma (ATL) and a neurodegenerative disease known as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). While several molecular clones of HTLV-1 have been published, all were [...] Read more.
Human T-cell leukemia virus (HTLV-1) is the etiological agent of lymphoproliferative diseases such as adult T-cell leukemia and T-cell lymphoma (ATL) and a neurodegenerative disease known as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). While several molecular clones of HTLV-1 have been published, all were isolated from samples derived from patients with adult T-cell leukemia. Here, we report the characterization of an HTLV-1 infectious molecular clone isolated from a sample of a patient with HAM/TSP disease. Genetic comparative analyses of the HAM/TSP molecular clone (pBST) revealed unique genetic alterations and specific viral mRNA expression patterns. Interestingly, our clone also harbors characteristics previously published to favor the development of HAM/TSP disease. The molecular clone is capable of infection and immortalization of human primary T cells in vitro. Our studies further demonstrate that the HTLV-1 virus produced from primary T cells transfected with pBST or ACH molecular clones cannot sustain long-term expansion, and cells cease to proliferate after 3–4 months in culture. In contrast, long-term proliferation and immortalization were achieved if the virus was transmitted from dendritic cells to primary T cells, and secondary infection of 729B cells in vitro was demonstrated. In both primary T cells and 729B cells, pBST and ACH were latent, and only hbz viral RNA was detected. This study suggests that HTLV-1 transmission from DC to T cells favors the immortalization of latently infected cells. Full article
(This article belongs to the Special Issue Chronic Infection by Oncogenic Viruses)
Show Figures

Figure 1

Figure 1
<p>Cloning pBST into pBR327. (<b>A</b>) Agarose gel of p.4.39 DNA digested with 1-Sac1+BstEII. 2- BstEII. 3- Sac1. 4- Lambda HindIII DNA marker. Schematic representation of p4.39 with restriction sites for Sac1 (S) or BstEII (B) and pBR327 digested with EcoR1 and Sal1 for cloning. (<b>B</b>–<b>D</b>) Alignment between pBST and MT-2 sequences of different regions of the viral LTR. (<b>E</b>) Alignment between pBST and MT-2 sequence of RexRE REM3 loop. (<b>F</b>) The enhancer region conserved sites for transcription factors SRF and ELK-1 in HTLV-1 ACH (<b>top</b>) and pBST sequence (<b>bottom</b>).</p>
Full article ">Figure 2
<p>Schematic representation of pBST mutations present in viral proteins. (<b>A</b>) Phylogenetic tree analysis, generated with the maximum likelihood (PhyML) method on a 710-nt-long fragment of the LTR. The numbers at the nodes correspond to the bootstrap value, obtained after 1000 repeats. The branch lengths are drawn to scale. HTLV-1c strains were used as outgroup. (<b>B</b>) Phylogenetic tree generated by the maximum likelihood method (PhyML) on 6366 nt corresponding to the concatenation of gag-pol-env-tax ORFs. The numbers at the nodes correspond to the bootstrap value, obtained after 1000 repeats. The branch lengths are drawn to scale. HTLV-1c strains were used as outgroup. (<b>C</b>) Amino acid sequence of structural and enzymatic proteins GAG, PRO, POL, and ENV TAX, HBZ, p12, p30, and p13 from pBST and HTLV-1A prototype ATK. Mutation positions are indicated. (<b>D</b>) Amino acid sequence alignment compared to full-length genome sequences from Japanese HAM/TSP (n = 12) or Brazilian HAM/TSP (n = 10) (Supplemental S4–S12). See material and methods. Red triangle and (*) indicate stop codon.</p>
Full article ">Figure 3
<p>Expression of viral mRNAs from pBST. (<b>A</b>) Schematic representation of HTLV-1 mRNAs with positions of splice donors and splice acceptor sites noted. (<b>B</b>) pBST was transfected into 293T cells, and total RNAs were extracted after 48 h. “(-)” represents control, pCDNA 3.1 transfected 293T cells, and “PBST” represents pBST transfected 293T cells. Specific primers (<a href="#viruses-16-01755-t001" class="html-table">Table 1</a>) were used, and RT-PCR products were resolved onto agarose gels. p13 PCR products are approximately 130 bp. HTLV-1 transformed cells LAF, MT4, and HUT102 were used as controls. (<b>C</b>) Schematic of the pBST LTR cloned into the luciferase vector. Luciferase assays representing fold change activation of pBST-LTR-Luciferase activated by Tax produced in the context of the molecular clone. (<b>D</b>) The pBST envelope gene was cloned into pCDNA 3.1 expression vector and transfected into high-density HeLa cells. Syncytia were visualized after 48 h by staining with Crystal Violet.</p>
Full article ">Figure 4
<p>pBST produces infectious virus particles. (<b>A</b>) Electron microscopy images of 293T cells transfected with ACH or pBST. Digital images were acquired with an AMT digital camera, with magnification scale bars indicated in the figures. White triangles indicate virus particles, with size in nanometers (nm). (<b>B</b>) 293T cells were transfected with increasing amounts of pBST molecular clones. After 48 h, supernatant was cleared by centrifugation for 5 min at 10,000 rpm, and supernatant was tested for GAG p19 by ELISA. (<b>C</b>) 729B cells were transfected with pBST by Amaxa, and after 48 h, cells were co-cultivated with BHK1E6 HTLV-1LTR-LacZ reporter cells for 48 h. Cells were washed, fixed, and stained with X-Gal to reveal HTLV-1-infected beta-galactosidase-positive cells.</p>
Full article ">Figure 5
<p>Immortalization of primary human T cell lines and secondary transmission to 729B cells. (<b>A</b>) Images of cultures from PBMCs at 3 weeks of culture and pBST immortalized T cell lines. (<b>B</b>) FACS analyses of cell surface markers for CD4, CD8, and CD25 expression on activated PBMCs or pBST immortalized cells. Cells were blocked for 30 min in BSA buffer and incubated for 2 h with the appropriate conjugated antibody. Cells were washed and fixed in 1% PFA overnight before analyses. CD4-APC (cat#551980) BD Pharmingen; IgG1-k-Isotype control-APC (cat#550854) BD Pharmingen. CD8-PE (cat#555367) BD Pharmingen; IgG1-k-Isotype control-PE (cat#555749) BD Pharmingen. Results were acquired on instrument BC-Accuri C6 Plus Flow Cytometer (BD Biosciences). (<b>C</b>) PCR analyses of genomic DNA from PBMC controls or PBMCs immortalized with pBST. HTLV-1 LAF cell line was used as a control. Chromatograms show specific genetic variations (black arrow) present in the pBST immortalized cell lines. The ACH sequence was used as a control. (<b>D</b>) RT-PCR analysis of <span class="html-italic">hbz</span> expression from 729B cell controls or 729B cells chronically infected with pBST. The HTLV-1 LAF cell line was used as a control.</p>
Full article ">
17 pages, 2379 KiB  
Article
The Knob Domain of the Fiber-1 Protein Affects the Replication of Fowl Adenovirus Serotype 4
by Xiaofeng Li, Zhixun Xie, You Wei, Zhiqin Xie, Aiqiong Wu, Sisi Luo, Liji Xie, Meng Li and Yanfang Zhang
Microorganisms 2024, 12(11), 2265; https://doi.org/10.3390/microorganisms12112265 - 8 Nov 2024
Viewed by 611
Abstract
Fowl adenovirus serotype 4 (FAdV-4) outbreaks have caused significant economic losses in the Chinese poultry industry since 2015. The relationships among viral structural proteins in infected hosts are relatively unknown. To explore the role of different parts of the fiber-1 protein in FAdV-4-infected [...] Read more.
Fowl adenovirus serotype 4 (FAdV-4) outbreaks have caused significant economic losses in the Chinese poultry industry since 2015. The relationships among viral structural proteins in infected hosts are relatively unknown. To explore the role of different parts of the fiber-1 protein in FAdV-4-infected hosts, we truncated fiber-1 into fiber-1-Δ1 (73–205 aa) and fiber-1-Δ2 (211–412 aa), constructed pEF1α-HA-fiber-1-Δ1 and pEF1α-HA-fiber-1-Δ2 and then transfected them into leghorn male hepatocyte (LMH) cells. After FAdV-4 infection, the roles of fiber-1-Δ1 and fiber-1-Δ2 in the replication of FAdV-4 were investigated, and transcriptome sequencing was performed. The results showed that the fiber-1-Δ1 and fiber-1-Δ2 proteins were the shaft and knob domains, respectively, of fiber-1, with molecular weights of 21.4 kDa and 29.6 kDa, respectively. The fiber-1-Δ1 and fiber-1-Δ2 proteins were mainly localized in the cytoplasm of LMH cells. Fiber-1-Δ2 has a greater ability to inhibit FAdV-4 replication than fiber-1-Δ1, and 933 differentially expressed genes (DEGs) were detected between the fiber-1-Δ1 and fiber-1-Δ2 groups. Functional analysis revealed these DEGs in a variety of biological functions and pathways, such as the phosphoinositide 3-kinase–protein kinase b (PI3K–Akt) signaling pathway, the mitogen-activated protein kinase (MAPK) signaling pathway, cytokine–cytokine receptor interactions, Toll-like receptors (TLRs), the Janus tyrosine kinase–signal transducer and activator of transcription (Jak–STAT) signaling pathway, the nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) signaling pathway, and other innate immune pathways. The mRNA expression levels of type I interferons (IFN-α and INF-β) and proinflammatory cytokines (IL-1β, IL-6 and IL-8) were significantly increased in cells overexpressing the fiber-1-Δ2 protein. These results demonstrate the role of the knob domain of the fiber-1 (fiber-1-Δ2) protein in FAdV-4 infection and provide a theoretical basis for analyzing the function of the fiber-1 protein of FAdV-4. Full article
(This article belongs to the Section Molecular Microbiology and Immunology)
Show Figures

Figure 1

Figure 1
<p>Prediction of fiber-1 major structural domains, PCR amplification and antigenic peptide prediction analysis. (<b>A</b>) Prediction of the fiber-1 protein domain. (<b>B</b>) Schematic of the amino acids of the full-length or truncated fiber-1 molecule, fiber-1 (1–431 aa), fiber-1-Δ1 (73–205 aa), and fiber-1-Δ2 (211–412 aa). (<b>C</b>) Analysis of the PCR products of the fiber-1-Δ1 and fiber-1-Δ2 genes via agarose gel electrophoresis. (<b>a</b>) The results for fiber-1-Δ1. Lane 1: DL2 000 DNA marker. Lanes 2~4: fiber-1-Δ1 gene PCR amplification products. The size of the fiber-1-Δ1 gene fragment is 399 bp. (<b>b</b>) The results for fiber-1-Δ2. Lane 1: DL2 000 DNA marker; lanes 2~4: fiber-1-Δ2 gene PCR amplification products. The size of the fiber-1-Δ2 gene fragment was 606 bp. (<b>D</b>) Complete fibre-1 protein map and prediction of the hydrophilicity, antigenicity, flexibility and surface accessibility of potential dominant B-cell epitopes of fiber-1-Δ1 and fiber-1-Δ2. Red boxes represent the highest scoring antigenic epitopes.</p>
Full article ">Figure 2
<p>Fiber-1-Δ1 and fiber-1-Δ2 were expressed in LMH cells. (<b>A</b>) Replication curves of FAdV-4 on LMH, MOI = 0.01. (<b>B</b>) LMH cells were transfected with different plasmid concentrations (10×). The plasmid concentrations were 1, 1.25, and 2.0 µg per well, and the transfection efficiency increased with increasing concentration of the transfected plasmid. (<b>C</b>) The results for fiber-1-Δ1 and fiber-1-Δ2 were verified by Western blotting. (<b>a</b>) The results of fiber-1-Δ1. Lane 1: protein marker (11–245 kDa). Lane 2: LMH cells transfected with the empty pEF1α-HA plasmid as a control. Lane 3: fiber-1-Δ1 protein was overexpressed in LMH cells. The size of the fiber-1-Δ1 protein containing the HA label was approximately 21.4 kDa. (<b>b</b>) The results for fiber-1-Δ2. Lane 1: protein marker (11–245 kDa). Lane 2: LMH cells transfected with the empty pEF1α-HA plasmid as a control. Lane 3: fiber-1-Δ2 protein was overexpressed in LMH cells. The size of the fiber-1-Δ2 protein containing the HA label was approximately 29.6 kDa. (<b>D</b>) The fiber-1, fiber-1-Δ1 and fiber-1-Δ2 proteins were localized mainly in the cytoplasm of LMH cells (60×), the scale bar was 20 µm. (<b>E</b>) Prediction of cellular sublocalization of fiber-1, fiber-1-Δ1 and fiber-1-Δ2 proteins.</p>
Full article ">Figure 3
<p>Fiber-1-Δ1 and fiber-1-Δ2 inhibit FAdV-4 replication in LMH cells. LMH cells were transfected with pEF1α-HA, pEF1α-HA-fiber-1-Δ1 or pEF1α-HA-fiber-1-Δ2 and then infected with FAdV-4 (MOI = 0.01). Viral replication was determined at 6, 12, 18, 24, 36, and 48 hpi via absolute quantitative PCR. The results are expressed as the means ± SDs of three independent experiments. pEF1α-HA-fiber-1-Δ2 compared with the mock group, significant differences are denoted by blue<span style="color:#9CC2E5">*</span> pEF1α-HA-fiber-1-Δ2 compared with pEF1α-HA-fiber-1-Δ1, significant differences are denoted by black*. One * indicates <span class="html-italic">p</span> &lt; 0.05, and two * indicate <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 4
<p>DEGs between fiber-1-Δ1 (A) and fiber-1-Δ2 (B) overexpression in LMH cells. The red dots (<span style="color:red">●</span>) indicate upregulated genes and the green dots (<span style="color:#00B050">●</span>) indicate downregulated genes. The black dots (●) indicate that the genes are not differentially expressed.</p>
Full article ">Figure 5
<p>GO and KEGG enrichment analyses of DEGs. (<b>A</b>) The top 30 enriched GO categories. (<b>B</b>) The top 30 enriched KEGG categories. The vertical axis represents the functional annotation information, and the horizontal axis represents the enrichment factor corresponding to the function (the number of DEGs annotated to the function divided by all the genes). In terms of the number of genes annotated to a function, the size of the q value is indicated by the color of the dot, so the smaller the q value, the redder it is. The number of DEGs associated with each function is indicated by the size of the dots (only the 30 GO terms with the highest enrichment were selected).</p>
Full article ">Figure 6
<p>Effects of fiber-1-Δ1 and fiber-1-Δ2 on the expression of innate immune signaling pathway-related genes during FAdV-4 infection. The results are expressed as the means ± SDs of three independent experiments. * indicates <span class="html-italic">p</span> &lt; 0.05 and ** indicates <span class="html-italic">p</span> &lt; 0.01. In the mock group, LMH cells were transfected with the pEF1α-HA plasmid; in the fiber-1-Δ1 group, LMH cells were transfected with the pEF1α-HA-fiber-1-Δ1 plasmid; and in the fiber-1-Δ2 group, LMH cells were transfected with the pEF1α-HA-fiber-1-Δ2 plasmid.</p>
Full article ">
32 pages, 9671 KiB  
Article
Ten Hypermethylated lncRNA Genes Are Specifically Involved in the Initiation, Progression, and Lymphatic and Peritoneal Metastasis of Epithelial Ovarian Cancer
by Eleonora A. Braga, Alexey M. Burdennyy, Leonid A. Uroshlev, Danila M. Zaichenko, Elena A. Filippova, Svetlana S. Lukina, Irina V. Pronina, Iana R. Astafeva, Marina V. Fridman, Tatiana P. Kazubskaya, Vitaly I. Loginov, Alexey A. Dmitriev, Aleksey A. Moskovtsev and Nikolay E. Kushlinskii
Int. J. Mol. Sci. 2024, 25(21), 11843; https://doi.org/10.3390/ijms252111843 - 4 Nov 2024
Viewed by 973
Abstract
Abstract: Our work aimed to evaluate and differentiate the role of ten lncRNA genes (GAS5, HAND2-AS1, KCNK15-AS1, MAGI2-AS3, MEG3, SEMA3B-AS1, SNHG6, SSTR5-AS1, ZEB1-AS1, and ZNF667-AS1) in the development and progression of epithelial [...] Read more.
Abstract: Our work aimed to evaluate and differentiate the role of ten lncRNA genes (GAS5, HAND2-AS1, KCNK15-AS1, MAGI2-AS3, MEG3, SEMA3B-AS1, SNHG6, SSTR5-AS1, ZEB1-AS1, and ZNF667-AS1) in the development and progression of epithelial ovarian cancer (EOC). A representative set of clinical samples was used: 140 primary tumors from patients without and with metastases and 59 peritoneal metastases. Using MS-qPCR, we demonstrated an increase in methylation levels of all ten lncRNA genes in tumors compared to normal tissues (p < 0.001). Using RT-qPCR, we showed downregulation and an inverse relationship between methylation and expression levels for ten lncRNAs (rs < −0.5). We further identified lncRNA genes that were specifically hypermethylated in tumors from patients with metastases to lymph nodes (HAND2-AS1), peritoneum (KCNK15-AS1, MEG3, and SEMA3B-AS1), and greater omentum (MEG3, SEMA3B-AS1, and ZNF667-AS1). The same four lncRNA genes involved in peritoneal spread were associated with clinical stage and tumor extent (p < 0.001). Interestingly, we found a reversion from increase to decrease in the hypermethylation level of five metastasis-related lncRNA genes (MEG3, SEMA3B-AS1, SSTR5-AS1, ZEB1-AS1, and ZNF667-AS1) in 59 peritoneal metastases. This reversion may be associated with partial epithelial–mesenchymal transition (EMT) in metastatic cells, as indicated by a decrease in the level of the EMT marker, CDH1 mRNA (p < 0.01). Furthermore, novel mRNA targets and regulated miRNAs were predicted for a number of the studied lncRNAs using the NCBI GEO datasets and analyzed by RT-qPCR and transfection of SKOV3 and OVCAR3 cells. In addition, hypermethylation of SEMA3B-AS1, SSTR5-AS1, and ZNF667-AS1 genes was proposed as a marker for overall survival in patients with EOC. Full article
(This article belongs to the Special Issue Molecular Diagnostics and Genomics of Tumors)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Methylation levels of ten lncRNA genes in 18 samples from donors (D), 123 histologically normal ovarian tissues from EOC patients (N), 140 primary ovarian tumors (T), and 59 peritoneal macroscopic metastases (PM); (<b>b</b>) methylation levels of ten lncRNA genes in 43 primary ovarian tumors from patients without metastases (T) and 43 matched histologically normal ovarian tissues (N). * <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, # <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 2
<p>(<b>a</b>) Hypermethylated lncRNA genes associated with advanced clinical stages of EOC; 47 samples of stages I + II and 93 samples of stages III + IV; (<b>b</b>) hypermethylated lncRNA genes associated with advanced histological grade of EOC; 72 G1–G2 samples and 68 G3–G4 samples. * <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, # <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 3
<p>Hypermethylated lncRNA genes associated with different types of EOC metastases: (<b>a</b>) metastases to the great omentum (70 patients—without, 70 patients—with); (<b>b</b>) dissemination through the peritoneum (70 patients—without, 70 patients—with); (<b>c</b>) metastases to the lymph nodes (110 patients—N0, 30 patients—N1–N3); (<b>d</b>) samples from patients with metastases of any type were considered (44 patients—without, 96 patients—with). ** <span class="html-italic">p</span> &lt; 0.01, # <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 4
<p>Methylation levels of six lncRNA genes in 59 peritoneal metastases (PM) vs. 59 primary tumors from the same EOC patients. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, # <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 5
<p>Changes in the levels of ten lncRNAs in primary tumors compared to matched histologically normal tissues. The lncRNAs HAND2-AS1, MEG3, and ZEB1-AS1 were tested in the subset of 73 paired (T/N) samples, GAS5 in 68 samples, and the remaining six lncRNAs in 56 samples. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, # <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 6
<p>Changes in expression levels of four lncRNAs (GAS5, HAND2-AS1, MAGI2-AS3, MEG3) in serous ovarian cystadenocarcinoma according to the GEPIA 2.0 data (red—tumor, gray—normal); 426 tumor samples, 88 normal tissues; red asterisk corresponds to <span class="html-italic">p</span> &lt; 0.01; TPM—transcripts per million.</p>
Full article ">Figure 7
<p>Statistically significant negative correlation between the changes in methylation and expression levels of ten lncRNA genes in the subset of 90 paired (T/N) samples of EOC. The lncRNAs HAND2-AS1, MEG3, and ZEB1-AS1 were tested in the subset of 73 samples, GAS5 in 68 samples, and the other six lncRNAs in 56 samples. Spearman’s correlation coefficients (<span class="html-italic">r<sub>s</sub></span>) are given.</p>
Full article ">Figure 8
<p>(<b>a</b>) Decreased relative expression level of lncRNA HAND2-AS1 in primary ovarian tumors from patients with lymphatic metastases (21 samples, T/N) compared to primary tumors without lymphatic metastases (52 samples, T/N); (<b>b</b>) decreased relative expression level of lncRNA HAND2-AS1 in primary ovarian tumors from patients with any metastases (50 samples, T/N) compared to primary tumors without any metastases (23 samples, T/N); (<b>c</b>) increased relative expression level of lncRNAs HAND2-AS1 and MEG3 in peritoneal metastases compared to primary tumors from the same EOC patients (31 PM samples vs. 31 tumor samples).</p>
Full article ">Figure 9
<p>Changes in mRNA levels of five EMT markers (CDH1, SNAI2/SLUG, ZEB1, ZEB2, VIM mRNAs) in 30 peritoneal metastases (PM) compared to 46 primary ovarian tumors (T).</p>
Full article ">Figure 10
<p>(<b>a</b>) Relative expression levels of FKBP14 and SERPINF1 mRNAs in the subset of 44 EOC samples (27 T/N +17 PM/N); (<b>b</b>–<b>d</b>) positive correlations of expression levels of lncRNAs MAGI2-AS3 and HAND2-AS1 with expression levels of FKBP14 and SERPINF1 mRNAs in 44 EOC samples (27 T/N +17 PM/N).</p>
Full article ">Figure 11
<p>(<b>a</b>) Relative expression levels of four miRNAs (miR-124-3p, miR-124-5p, miR-137-3p, miR-33b-5p); (<b>b</b>) correlation plot to analyze possible correlations between four miRNAs and ten lncRNAs in the subset of 41 paired (T/N) EOC samples.</p>
Full article ">Figure 12
<p>Changes in the levels of lncRNA GAS5 in (<b>a</b>) SKOV3 and (<b>b</b>) OVCAR3 cells transfected with miRNA mimics: c.el-67—cel-miR-67-3p, hsa-124—hsa-miR-124-3p, hsa-137—hsa-miR-137-3p. SKOV3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.13, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.32, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.99; OVCAR3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.99. Data are presented as the median and 25–75% percentiles (n = 4).</p>
Full article ">Figure 13
<p>Changes in the levels of lncRNA ZNF667-AS1 in (<b>a</b>) SKOV3 and (<b>b</b>) OVCAR3 cells transfected with miRNA mimics: c.el-67—cel-miR-67-3p, hsa-124—hsa-miR-124-3p, hsa-137—hsa-miR-137-3p. SKOV3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.25, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.55; OVCAR3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.057, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.99. Data are presented as the median and 25–75% percentiles (n = 4).</p>
Full article ">Figure 14
<p>Changes in the levels of lncRNA ZEB1-AS1 in (<b>a</b>) SKOV3 and (<b>b</b>) OVCAR3 cells transfected with miRNA mimics: c.el-67—cel-miR-67-3p, hsa-124—hsa-miR-124-3p, hsa-137—hsa-miR-137-3p. SKOV3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.72, OVCAR3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.99. Data are presented as the median and 25–75% percentiles (n = 4).</p>
Full article ">Figure 15
<p>Changes in the levels of lncRNA KCNK15-AS1 in (<b>a</b>) SKOV3 and (<b>b</b>) OVCAR3 cells transfected with miRNA mimics: c.el-67—cel-miR-67-3p, hsa-124—hsa-miR-124-3p, hsa-137—hsa-miR-137-3p. SKOV3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.78, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.10; OVCAR3: <span class="html-italic">p</span> (hsa-124 vs. mock) = 0.69, <span class="html-italic">p</span> (hsa-137 vs. mock) = 0.99, <span class="html-italic">p</span> (hsa-221 vs. mock) = 0.99. Data are presented as the median and 25–75% percentiles (n = 4).</p>
Full article ">Figure 16
<p>Analysis of overall survival and overall hazard in OC patients based on methylation status of (<b>a</b>) <span class="html-italic">ZNF667-AS1</span>, (<b>b</b>) <span class="html-italic">SEMA3B-AS1</span>, and (<b>c</b>) <span class="html-italic">SSTR5-AS1</span> genes.</p>
Full article ">Figure 17
<p>Comparison of the functional significance of the studied lncRNAs; (<b>a</b>) potential mRNA targets of nine lncRNAs according to the analysis of co-expressed mRNAs at <span class="html-italic">r<sub>s</sub></span> &gt; 0.4 in the GSE211669 dataset; KCNK15-AS1 had 41 target mRNAs; (<b>b</b>) EMT-associated genes among the identified mRNA targets according to GeneCards; 8 of 41 target mRNAs for KCNK15-AS1 were EMT-associated.</p>
Full article ">
16 pages, 3890 KiB  
Article
miR-193b-5p and miR-374b-5p Are Aberrantly Expressed in Endometriosis and Suppress Endometrial Cell Migration In Vitro
by Caroline Frisendahl, Yiqun Tang, Nageswara Rao Boggavarapu, Maire Peters, Parameswaran Grace Lalitkumar, Terhi T. Piltonen, Riikka K. Arffman, Andres Salumets, Martin Götte, Eberhard Korsching and Kristina Gemzell-Danielsson
Biomolecules 2024, 14(11), 1400; https://doi.org/10.3390/biom14111400 - 3 Nov 2024
Viewed by 1101
Abstract
(1) Background: Endometriosis is a highly prevalent gynecological disease affecting 10% of women of reproductive age worldwide. miRNAs may play a role in endometriosis, though their exact function remains unclear. This study aimed to identify differentially expressed miRNAs in endometriosis and study their [...] Read more.
(1) Background: Endometriosis is a highly prevalent gynecological disease affecting 10% of women of reproductive age worldwide. miRNAs may play a role in endometriosis, though their exact function remains unclear. This study aimed to identify differentially expressed miRNAs in endometriosis and study their functions in the disease. (2) Methods: Endometrial tissue was collected from women with endometriosis (n = 15) and non-endometriosis controls (n = 17). Dysregulated miRNAs were identified through small RNA-sequencing, and their biological significance was explored by target gene prediction and pathway analysis. Selected miRNAs were examined in paired ectopic endometriomas and eutopic endometrium (n = 10) using qRT-PCR. Their roles in cell migration and proliferation were further examined in vitro using functional assays. To identify potential target genes, we performed mRNA sequencing on transfected cells and the endometrioma cohort. (3) Results: We identified 14 dysregulated miRNAs in the eutopic endometrium of women with endometriosis compared to endometrial tissue from women without endometriosis. Pathway analysis indicated enrichment in cell migration and proliferation-associated pathways. Further ex vivo studies of miR-193b-5p and miR-374b-5p showed that both miRNAs were upregulated in endometrioma. Overexpression of these two miRNAs in vitro inhibited cell migration, and mRNA sequencing revealed several migration-related genes that are targeted by these miRNAs. (4) Conclusions: Our study identified two key endometrial miRNAs that may be involved in the pathogenesis of endometriosis by regulating cell migration. Full article
(This article belongs to the Special Issue Cellular and Molecular Mechanisms of Endometriosis)
Show Figures

Figure 1

Figure 1
<p>Overall study design flowchart. DE-miRNAs: differentially expressed miRNAs; DEGs: differentially expressed genes.</p>
Full article ">Figure 2
<p>Selected KEGG signaling pathways significantly enriched for the upregulated (<b>A</b>) and downregulated (<b>B</b>) miRNA’s target genes. The pathways presented have been selected based on involvement in endometriosis, according to the published literature. In <a href="#biomolecules-14-01400-f002" class="html-fig">Figure 2</a>A, the pathways have been further sorted based on involvement in cell migration and proliferation. A <span class="html-italic">p</span>-value of 0.05 was considered statistically significant.</p>
Full article ">Figure 3
<p>Relative gene expression level of miR-193b-5p and miR-374b-5p in endometrioma (n = 10) compared to paired endometrium (n = 10). Data are presented using a line plot. Wilcoxon matched-pairs signed-rank test was used in the statistical analysis; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 4
<p>Wound healing assays. (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>) The representative images of the unclosed wound area at each timepoint. (<b>B</b>) In comparison to the mimic control group, the percentage of wound closure was significantly reduced after transfection with miR-193b-5p mimic in 12Z cells. (<b>D</b>) No statistical difference in cell migratory ability was observed between miR-374b-5p transfection and control groups in 12Z cells. (<b>F</b>) In comparison to the mimic control group, the percentage of wound closure was significantly reduced after transfection with miR-193b-5p mimics in HESC cells at the time point of 24 h. (<b>H</b>) In comparison to the mimic control group, the percentage of wound closure was significantly reduced after transfection with miR-374b-5p mimics in HESC cells at time points of 12 h and 24 h. <span class="html-italic">p</span> &lt; 0.05 is considered statistically significant. All experiments were repeated three times.</p>
Full article ">Figure 5
<p>Transwell cell migration assay. (<b>A</b>) The migration ability of 12Z cells after hsa-miR-193b-5p mimics transfection compared to the control group. (<b>C</b>) The migration ability of 12Z cells after hsa-miR-374b-5p mimics transfection compared to the control group. (<b>E</b>) The migration ability of HESC cells after hsa-miR-193b-5p mimics transfection compared to the control group. (<b>G</b>) The migration ability of HESC cells after hsa-miR-374b-5p mimics transfection compared to the control group. (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>) Representative images of the transwell membranes with the migrated cells (5x). n = 9 independent replicates, * <span class="html-italic">p</span> &lt; 0.5, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001; Mann–Whitney U-test.</p>
Full article ">
Back to TopTop