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21 pages, 601 KiB  
Review
Current Insights into Molecular Mechanisms and Potential Biomarkers for Treating Radiation-Induced Liver Damage
by Biki Saha, Sneha Pallatt, Antara Banerjee, Abhijit G. Banerjee, Rupak Pathak and Surajit Pathak
Cells 2024, 13(18), 1560; https://doi.org/10.3390/cells13181560 - 16 Sep 2024
Abstract
Highly conformal delivery of radiation therapy (RT) has revolutionized the treatment landscape for primary and metastatic liver cancers, yet concerns persist regarding radiation-induced liver disease (RILD). Despite advancements, RILD remains a major dose-limiting factor due to the potential damage to normal liver tissues [...] Read more.
Highly conformal delivery of radiation therapy (RT) has revolutionized the treatment landscape for primary and metastatic liver cancers, yet concerns persist regarding radiation-induced liver disease (RILD). Despite advancements, RILD remains a major dose-limiting factor due to the potential damage to normal liver tissues by therapeutic radiation. The toxicity to normal liver tissues is associated with a multitude of physiological and pathological consequences. RILD unfolds as multifaceted processes, intricately linking various responses, such as DNA damage, oxidative stress, inflammation, cellular senescence, fibrosis, and immune reactions, through multiple signaling pathways. The DNA damage caused by ionizing radiation (IR) is a major contributor to the pathogenesis of RILD. Moreover, current treatment options for RILD are limited, with no established biomarker for early detection. RILD diagnosis often occurs at advanced stages, highlighting the critical need for early biomarkers to adjust treatment strategies and prevent liver failure. This review provides an outline of the diverse molecular and cellular mechanisms responsible for the development of RILD and points out all of the available biomarkers for early detection with the aim of helping clinicians decide on advance treatment strategies from a single literature recourse. Full article
(This article belongs to the Section Cellular Pathology)
17 pages, 521 KiB  
Review
The Role of MicroRNA in the Pathogenesis of Acute Kidney Injury
by Estera Bakinowska, Kajetan Kiełbowski and Andrzej Pawlik
Cells 2024, 13(18), 1559; https://doi.org/10.3390/cells13181559 - 16 Sep 2024
Abstract
Acute kidney injury (AKI) describes a condition associated with elevated serum creatinine levels and decreased glomerular filtration rate. AKI can develop as a result of sepsis, the nephrotoxic properties of several drugs, and ischemia/reperfusion injury. Renal damage can be associated with metabolic acidosis, [...] Read more.
Acute kidney injury (AKI) describes a condition associated with elevated serum creatinine levels and decreased glomerular filtration rate. AKI can develop as a result of sepsis, the nephrotoxic properties of several drugs, and ischemia/reperfusion injury. Renal damage can be associated with metabolic acidosis, fluid overload, and ionic disorders. As the molecular background of the pathogenesis of AKI is insufficiently understood, more studies are needed to identify the key signaling pathways and molecules involved in the progression of AKI. Consequently, future treatment methods may be able to restore organ function more rapidly and prevent progression to chronic kidney disease. MicroRNAs (miRNAs) are small molecules that belong to the non-coding RNA family. Recently, numerous studies have demonstrated the altered expression profile of miRNAs in various diseases, including inflammatory and neoplastic conditions. As miRNAs are major regulators of gene expression, their dysregulation is associated with impaired homeostasis and cellular behavior. The aim of this article is to discuss current evidence on the involvement of miRNAs in the pathogenesis of AKI. Full article
(This article belongs to the Special Issue Acute Kidney Injury: From Molecular Mechanisms to Diseases)
25 pages, 3566 KiB  
Article
Characterizing the Cell-Free Transcriptome in a Humanized Diffuse Large B-Cell Lymphoma Patient-Derived Tumor Xenograft Model for RNA-Based Liquid Biopsy in a Preclinical Setting
by Philippe Decruyenaere, Willem Daneels, Annelien Morlion, Kimberly Verniers, Jasper Anckaert, Jan Tavernier, Fritz Offner and Jo Vandesompele
Int. J. Mol. Sci. 2024, 25(18), 9982; https://doi.org/10.3390/ijms25189982 (registering DOI) - 16 Sep 2024
Abstract
The potential of RNA-based liquid biopsy is increasingly being recognized in diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin’s lymphoma. This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n = [...] Read more.
The potential of RNA-based liquid biopsy is increasingly being recognized in diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin’s lymphoma. This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n = 171) derived from a DLBCL PDTX model, including 27 humanized (HIS) PDTX, 8 HIS non-PDTX, and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with CHOP (huCD20-Fc-AFN-CHOP), or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform. RNA sequencing data of the formalin-fixed paraffin-embedded (FFPE) tissue and blood plasma samples of the original patient were included. Flow cytometry was performed on immune cells isolated from whole blood, spleen, and bone marrow. Bulk deconvolution was performed using the Tabula Sapiens v1 basis matrix. Both R-CHOP and huCD20-Fc-AFN-CHOP were able to control tumor growth in most mice. Xenograft tumor volume was strongly associated with circulating tumor RNA (ctRNA) concentration (p < 0.001, R = 0.89), as well as with the number of detected human genes (p < 0.001, R = 0.79). Abundance analysis identified tumor-specific biomarkers that were dynamically tracked during tumor growth or treatment. An 8-gene signature demonstrated high accuracy for assessing therapy response (AUC 0.92). The tumoral gene detectability in the ctRNA of the PDTX-derived plasma was associated with RNA abundance levels in the patient’s tumor tissue and blood plasma (p < 0.001), confirming that tumoral gene abundance contributes to the cell-free RNA (cfRNA) profile. Decomposing the transcriptome, however, revealed high inter- and intra-mouse variability, which was lower in the HIS PDTX mice, indicating an impact of human engraftment on the stability and profile of cfRNA. Immunochemotherapy resulted in B cell depletion, and tumor clearance was reflected by a decrease in the fraction of human CD45+ cells. Lastly, bulk deconvolution provided complementary biological insights into the composition of the tumor and circulating immune system. In conclusion, the blood plasma-derived transcriptome serves as a biomarker source in a preclinical PDTX model, enables the assessment of biological pathways, and enhances the understanding of cfRNA dynamics. Full article
Show Figures

Figure 1

Figure 1
<p>Overview of blood plasma samples in the study derived from both HIS and non-HIS NSG mice. The gray dots in the figure represent a blood draw by tail vein puncture. HIS: human immune system; NSG: NOD-scid IL2Rgnull; PBS: phosphate-buffered saline; PDX: patient-derived xenograft; NSG: NOD-scid IL2Rgnull.</p>
Full article ">Figure 2
<p>Treatment response. Tumor volumes from the start of tumor inoculation in HIS (<b>A</b>) and non-HIS (<b>B</b>) NSG mice. For the grouped analyses in the first graph of each panel, the tumor volume of sacrificed mice was kept at 1500 mm<sup>3</sup> to avoid inappropriate improvement of group averages. For the other graphs, each line represents an individual mouse. Vertical lines indicate IV treatments (C = CHOP; X = Rituximab/huCD20-Fc-AFN/PBS). Error bars represent the standard error of the mean (SEM). HIS: human immune system; NSG: NOD-scid IL2Rgnull; PBS: phosphate-buffered saline.</p>
Full article ">Figure 3
<p>Endogenous human and murine cfRNA concentrations in HIS (<b>A</b>) and non-HIS (<b>B</b>) PDTX NSG mice treated with PBS, R-CHOP, and hu-CD20-FC-AFN-CHOP. Significant <span class="html-italic">p</span>-values are shown. CfRNA: cell-free RNA; HIS: human immune system; NSG: NOD-scid IL2Rgnull; PBS: phosphate-buffered saline; PDTX: patient-derived tumor xenograft. Pre-PDTX: before xenograft implantation; * <span class="html-italic">p</span>-value &lt; 0.05; ** <span class="html-italic">p</span>-value &lt; 0.01.</p>
Full article ">Figure 4
<p>Spearman rank correlation between tumor volume (mm<sup>3</sup>) of non-HIS xenografted PBS-treated NSG mice and human ctRNA concentration (<b>A</b>), murine cfRNA concentration (<b>B</b>), and the fraction of tumor-derived counts over all endogenous counts (<b>C</b>). Log-transformed values are shown. The darker gray region represents the range where the true regression line could lie with 95% confidence. ctRNA: circulating tumor RNA; HIS: human immune system; NSG: NOD-scid IL2Rgnull; PBS: phosphate-buffered saline; PDTX: patient-derived tumor xenograft; R: Spearman correlation coefficient.</p>
Full article ">Figure 5
<p>Principal component analysis for both human- and murine-normalized counts within the non-HIS (<b>A</b>) and the HIS (<b>B</b>) NSG mice. The main drivers of variance of the first two components are shown for each of the comparisons. The symbol † indicates the PBS-treated samples with the highest tumor volumes. The symbol * indicates samples with tumor growth despite immunochemotherapy. HIS: human immune system; NSG: NOD-scid IL2Rgnull; PDTX: patient-derived xenograft model; PBS: phosphate buffered saline, PC: principal component.</p>
Full article ">Figure 6
<p>Venn diagram illustrating the overlap of differentially abundant human and murine genes between the blood plasma of different subgroups. DAGs: differentially abundant genes; HIS: human immune system; PBS: phosphate-buffered saline; PDTX: patient-derived tumor xenograft.</p>
Full article ">Figure 7
<p>Overlap analysis of unique human genes among mice of the non-HIS PDTX (<b>A</b>), HIS non-PDTX (<b>B</b>), and HIS PDTX groups (<b>C</b>). For each group, the top section of each panel shows the number of unique genes for each mouse or combination of mice, the lower left section depicts the number of unique human genes per mouse, and the lower right section indicates which mice (as indicated by the dots) share unique genes. HIS: humanized; PDTX: patient-derived tumor xenograft.</p>
Full article ">Figure 8
<p>Computational deconvolution results on human cfRNA derived from blood plasma demonstrating the relative contribution of each cell type to the circulating immune system, red blood cells and platelets during xenograft growth and treatment in PBS-treated HIS non-PDTX, PBS-treated HIS PDTX, immunochemotherapy-treated HIS PDTX, PBS-treated non-HIS PDTX, and immunochemotherapy-treated non-HIS PDTX NSG mice. CfRNA: cell-free RNA; HIS: human immune system; NSG: NOD-scid IL2Rgnull; PBS: phosphate-buffered saline; pre-tx: pre-treatment; post-tx: post-treatment.</p>
Full article ">
14 pages, 6303 KiB  
Article
The Integrated Analysis of miRNome and Degradome Sequencing Reveals the Regulatory Mechanisms of Seed Development and Oil Biosynthesis in Pecan (Carya illinoinensis)
by Kaikai Zhu, Lu Wei, Wenjuan Ma, Juan Zhao, Mengyun Chen, Guo Wei, Hui Liu, Pengpeng Tan and Fangren Peng
Foods 2024, 13(18), 2934; https://doi.org/10.3390/foods13182934 - 16 Sep 2024
Abstract
Pecan seed oil is a valuable source of essential fatty acids and various bioactive compounds; however, the functions of microRNAs and their targets in oil biosynthesis during seed development are still unknown. Here, we found that the oil content increased rapidly in the [...] Read more.
Pecan seed oil is a valuable source of essential fatty acids and various bioactive compounds; however, the functions of microRNAs and their targets in oil biosynthesis during seed development are still unknown. Here, we found that the oil content increased rapidly in the three early stages in three cultivars, and that oleic acid was the predominant fatty acid component in the mature pecan embryos. We identified, analyzed, and validated the expression levels of miRNAs related to seed development and oil biosynthesis, as well as their potential target genes, using small RNA sequencing data from three stages (120, 135, and 150 days after flowering). During the seed development process, 365 known and 321 novel miRNAs were discovered. In total, 91 known and 181 novel miRNAs were found to be differentially expressed, and 633 target genes were further investigated. The expression trend analysis revealed that the 91 known miRNAs were classified into eight groups, approximately two-thirds of which were up-regulated, whereas most novel miRNAs were down-regulated. The qRT–PCR and degradome sequencing data were used to identify five miRNA- target pairs. Overall, our study provides valuable insights into the molecular regulation of oil biosynthesis in pecan seeds. Full article
(This article belongs to the Section Foodomics)
Show Figures

Figure 1

Figure 1
<p>Oil content and fatty acid composition in developing pecan embryos. (<b>A</b>) Observation of morphological characteristics during five stages of pecan seed development. Bar = 1 cm. (<b>B</b>) Oil contents of seed samples at five stages from three pecan cultivars. (<b>C</b>) Changes in fatty acid composition at different stages in pecan embryos. c16:0, palmitic acid; c16:1, palmitoleic acid; c18:0, stearic acid; c18:1, oleic acid; c18:2, linoleic acid; c18:3n3, α-Linolenic acid; c18:3n6, γ-Linolenic acid; and c20:1, Eicosenoic acid.</p>
Full article ">Figure 2
<p>Length distribution of small RNA from the seeds of the ‘Pawnee’ cultivar of pecan at three developmental stages.</p>
Full article ">Figure 3
<p>Composition of the small RNA in nine libraries.</p>
Full article ">Figure 4
<p>Differentially expressed miRNAs in three developmental stages of pecan seeds. (<b>A</b>) The number of the known DEMs between the different groups. (<b>B</b>) The number of novel DEMs between the different groups. (<b>C</b>) Venn diagrams of the known DEMs. (<b>D</b>) Venn diagrams of the novel DEMs.</p>
Full article ">Figure 5
<p>Expression trends of known DEMs in three developmental stages of pecan seeds. The number of DEMs in each group is listed at the top of each group.</p>
Full article ">Figure 6
<p>qRT–PCR validation of miRNAs during three stages of seed development in pecan seeds. Values are means ± SE of three replicates, and bars with different letters were significantly different at <span class="html-italic">p</span> &lt; 0.05 using Duncan’s multiple range test.</p>
Full article ">Figure 7
<p>Validation of the target genes during three stages of seed development in pecan, showing the expression patterns of five candidate target genes and a prediction of the binding sites of miRNAs in targets using the psRNA Target. Values are means ± SE of three replicates, and bars with different letters were significantly different at <span class="html-italic">p</span> &lt; 0.05 using Duncan’s multiple range test.</p>
Full article ">
17 pages, 8934 KiB  
Article
Identification of Tumor Suppressive miR-144-5p Targets: FAM111B Expression Accelerates the Malignant Phenotypes of Lung Adenocarcinoma
by Yuya Tomioka, Naohiko Seki, Takayuki Suetsugu, Yoko Hagihara, Hiroki Sanada, Yusuke Goto, Naoko Kikkawa, Keiko Mizuno, Kentaro Tanaka and Hiromasa Inoue
Int. J. Mol. Sci. 2024, 25(18), 9974; https://doi.org/10.3390/ijms25189974 (registering DOI) - 16 Sep 2024
Abstract
Accumulating evidence suggests that the passenger strands microRNAs (miRNAs) derived from pre-miRNAs are closely involved in cancer pathogenesis. Analysis of our miRNA expression signature of lung adenocarcinoma (LUAD) and The Cancer Genome Atlas (TCGA) data revealed that miR-144-5p (the passenger strand derived from [...] Read more.
Accumulating evidence suggests that the passenger strands microRNAs (miRNAs) derived from pre-miRNAs are closely involved in cancer pathogenesis. Analysis of our miRNA expression signature of lung adenocarcinoma (LUAD) and The Cancer Genome Atlas (TCGA) data revealed that miR-144-5p (the passenger strand derived from pre-miR-144) was significantly downregulated in LUAD tissues. The aim of this study was to identify therapeutic target molecules controlled by miR-144-5p in LUAD cells. Ectopic expression assays demonstrated that miR-144-5p attenuated LUAD cell aggressiveness, e.g., inhibited cell proliferation, migration and invasion abilities, and induced cell cycle arrest and apoptotic cells. A total of 18 genes were identified as putative cancer-promoting genes controlled by miR-144-5p in LUAD cells based on our in silico analysis. We focused on a family with sequence similarity 111 member B (FAM111B) and investigated its cancer-promoting functions in LUAD cells. Luciferase reporter assay showed that expression of FAM111B was directly regulated by miR-144-5p in LUAD cells. FAM111B knockdown assays showed that LUAD cells significantly suppressed malignant phenotypes, e.g., inhibited cell proliferation, migration and invasion abilities, and induced cell cycle arrest and apoptotic cells. Furthermore, we investigated the FAM111B-mediated molecular networks in LUAD cells. Identifying target genes regulated by passenger strands of miRNAs may aid in the discovery of diagnostic markers and therapeutic targets for LUAD. Full article
(This article belongs to the Special Issue The Role of Non‐coding RNAs in Human Health and Diseases)
Show Figures

Figure 1

Figure 1
<p>Expression levels of <span class="html-italic">miR-144-5p</span> and <span class="html-italic">miR-144-3p</span> in LUAD clinical specimens (<b>A</b>) Volcano plot showing the miRNA expression signature obtained through miRNA sequencing (GEO accession number: GSE230229). The log<sub>2</sub> fold change (FC) in expression is plotted on the x-axis and the log<sub>10</sub> <span class="html-italic">p</span>-value is on the y-axis. The red and blue dots represent the upregulated (log<sub>2</sub> FC &gt; 1.0 and <span class="html-italic">p</span> &lt; 0.05) miRNAs and downregulated (log<sub>2</sub> FC &lt; −1.0 and <span class="html-italic">p</span> &lt; 0.05), respectively. (<b>B</b>) Validation of <span class="html-italic">miR-144-5p</span> and <span class="html-italic">miR-144-3p</span> expression levels in LUAD clinical specimens. The expression levels of both miRNAs were markedly reduced in cancer tissues. (<span class="html-italic">p</span> &lt; 0.001). (<b>C</b>) Positive correlations (Spearman’s rank test) between the expression levels of <span class="html-italic">miR-144-5p</span> and <span class="html-italic">miR-144-3p</span> in clinical specimens (<span class="html-italic">r</span> = 0.882, <span class="html-italic">p</span> &lt; 0.001). (<b>D</b>) The chromosomal position of pre-<span class="html-italic">miR-144</span> within the human genome. The mature sequences of <span class="html-italic">miR-144-5p</span> (passenger strand) and <span class="html-italic">miR-144-3p</span> (guide strand) are shown.</p>
Full article ">Figure 2
<p>Antitumor functions of <span class="html-italic">miR-144-5p</span> in LUAD cells (A549 and H1299). (<b>A</b>) Cell proliferation was evaluated using XTT assay. Cancer cell viability was analyzed 72 h after transient transfection of miRNAs. (<b>B</b>) At 72 h after transient transfection with <span class="html-italic">miR-144-5p</span>, cell cycle status evaluated using flow cytometry. (<b>C</b>) At 72 h after transient transfection with <span class="html-italic">miR-144-5p</span>, apoptotic cells was evaluated using flow cytometry with Annexin V-FITC- and PI-PerCP-Cy5-5-A-stained cells. Cisplatin (30 µM) was used as a positive control for induction of apoptosis. (<b>D</b>) At 72 h after seeding <span class="html-italic">miR-144-5p</span>-transfected cells into the chambers, cell invasion was evaluated using Matrigel invasion assays. (<b>E</b>) At 72 h after seeding <span class="html-italic">miR-144-5p</span> transfected cells into the chambers, cell migration assessed using a membrane culture system. ***, <span class="html-italic">p</span> &lt; 0.001; ****, <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 3
<p>Flowchart for identification of <span class="html-italic">miR-144-5p</span> targets in LUAD cell. To identify putative targets of <span class="html-italic">miR-144-5p</span> in LUAD cells, we used two datasets: the TargetScanHuman database (release 8.0) and our original mRNA expression profile (Upregulated genes in non-small cell lung carcinoma tissues; GEO accession number: GSE19188). A total of 69 genes were identified as candidate targets of <span class="html-italic">miR-144-5p</span>. Furthermore, we searched for genes that were associated with the prognosis of LUAD patients using two databases: OncoLnc (<a href="http://www.oncolnc.org" target="_blank">http://www.oncolnc.org</a>, accessed on 17 May 2024) and GEPIA (<a href="http://gepia2.cancer-pku.cn/#analysis" target="_blank">http://gepia2.cancer-pku.cn/#analysis</a>, accessed on 17 May 2024). Among the <span class="html-italic">miR-144-5p</span> target genes, 18 genes were upregulated in LUAD tissues, and closely associated with poor prognosis in LUAD patients.</p>
Full article ">Figure 4
<p>Expression levels and 5-year overall survival rate of the 18 target genes regulated by <span class="html-italic">miR-144-5p</span> in LUAD (<b>A</b>) The expression levels of the 18 target genes of <span class="html-italic">miR-144-5p</span> (<span class="html-italic">ARHGAP11A</span>, <span class="html-italic">CDCA3</span>, <span class="html-italic">CENPF</span>, <span class="html-italic">CENPN</span>, <span class="html-italic">CHEK1</span>, <span class="html-italic">CP</span>, <span class="html-italic">DEPDC1B</span>, <span class="html-italic">ECT2</span>, <span class="html-italic">FAM111B</span>, <span class="html-italic">FAM64A</span>, <span class="html-italic">HELLS</span>, <span class="html-italic">HJURP</span>, <span class="html-italic">KIF11</span>, <span class="html-italic">NCAPG</span>, <span class="html-italic">RALGPS</span>, <span class="html-italic">SGOL1</span>, <span class="html-italic">SPC24</span>, <span class="html-italic">TRIP13</span>) in LUAD clinical specimens were assessed using the TCGA-LUAD dataset. All genes were upregulated in LUAD tissues (<span class="html-italic">n</span> = 499) compared with normal tissues (<span class="html-italic">n</span> = 58) (<span class="html-italic">p</span> &lt; 0.001). (<b>B</b>) Kaplan–Meier curves of the 5-year overall survival rates based on expression of the 18 target genes (<span class="html-italic">ARHGAP11A</span>, <span class="html-italic">CDCA3</span>, <span class="html-italic">CENPF</span>, <span class="html-italic">CENPN</span>, <span class="html-italic">CHEK1</span>, <span class="html-italic">CP</span>, <span class="html-italic">DEPDC1B</span>, <span class="html-italic">ECT2</span>, <span class="html-italic">FAM111B</span>, <span class="html-italic">FAM64A</span>, <span class="html-italic">HELLS</span>, <span class="html-italic">HJURP</span>, <span class="html-italic">KIF11</span>, <span class="html-italic">NCAPG</span>, <span class="html-italic">RALGPS</span>, <span class="html-italic">SGOL1</span>, <span class="html-italic">SPC24</span>, <span class="html-italic">TRIP13</span>) are shown. Lower expression levels of all 18 genes were significantly associated with poorer overall survival in LUAD patients. The patients (<span class="html-italic">n</span> = 487) were divided into high and low-expression groups based on the median gene expression level. The red and blue lines denote the high and low expression groups, respectively.</p>
Full article ">Figure 4 Cont.
<p>Expression levels and 5-year overall survival rate of the 18 target genes regulated by <span class="html-italic">miR-144-5p</span> in LUAD (<b>A</b>) The expression levels of the 18 target genes of <span class="html-italic">miR-144-5p</span> (<span class="html-italic">ARHGAP11A</span>, <span class="html-italic">CDCA3</span>, <span class="html-italic">CENPF</span>, <span class="html-italic">CENPN</span>, <span class="html-italic">CHEK1</span>, <span class="html-italic">CP</span>, <span class="html-italic">DEPDC1B</span>, <span class="html-italic">ECT2</span>, <span class="html-italic">FAM111B</span>, <span class="html-italic">FAM64A</span>, <span class="html-italic">HELLS</span>, <span class="html-italic">HJURP</span>, <span class="html-italic">KIF11</span>, <span class="html-italic">NCAPG</span>, <span class="html-italic">RALGPS</span>, <span class="html-italic">SGOL1</span>, <span class="html-italic">SPC24</span>, <span class="html-italic">TRIP13</span>) in LUAD clinical specimens were assessed using the TCGA-LUAD dataset. All genes were upregulated in LUAD tissues (<span class="html-italic">n</span> = 499) compared with normal tissues (<span class="html-italic">n</span> = 58) (<span class="html-italic">p</span> &lt; 0.001). (<b>B</b>) Kaplan–Meier curves of the 5-year overall survival rates based on expression of the 18 target genes (<span class="html-italic">ARHGAP11A</span>, <span class="html-italic">CDCA3</span>, <span class="html-italic">CENPF</span>, <span class="html-italic">CENPN</span>, <span class="html-italic">CHEK1</span>, <span class="html-italic">CP</span>, <span class="html-italic">DEPDC1B</span>, <span class="html-italic">ECT2</span>, <span class="html-italic">FAM111B</span>, <span class="html-italic">FAM64A</span>, <span class="html-italic">HELLS</span>, <span class="html-italic">HJURP</span>, <span class="html-italic">KIF11</span>, <span class="html-italic">NCAPG</span>, <span class="html-italic">RALGPS</span>, <span class="html-italic">SGOL1</span>, <span class="html-italic">SPC24</span>, <span class="html-italic">TRIP13</span>) are shown. Lower expression levels of all 18 genes were significantly associated with poorer overall survival in LUAD patients. The patients (<span class="html-italic">n</span> = 487) were divided into high and low-expression groups based on the median gene expression level. The red and blue lines denote the high and low expression groups, respectively.</p>
Full article ">Figure 5
<p><span class="html-italic">MiR-144-5p</span> expression directly regulated <span class="html-italic">FAM111B</span> in LUAD cells. (<b>A</b>) Expression level of <span class="html-italic">FAM111B</span> mRNA is markedly reduced by ectopic expression of <span class="html-italic">miR-144-5p</span> in LUAD cells (A549 and H1299). Total RNA was isolated 72 h after miRNA transfection and quantified by real-time PCR. <span class="html-italic">GAPDH</span> was used as an internal control. (<b>B</b>) Significant reduction of the FAM111B protein level by ectopic expression of <span class="html-italic">miR-144-5p</span> in LUAD cells (A549 and H1299). Proteins were isolated 72 h after <span class="html-italic">miR-144-5p</span> transfection and quantified by Western blotting. GAPDH was used as an internal control. (<b>C</b>) Putative <span class="html-italic">miR-144-5p</span> binding sites in the 3′UTR of the <span class="html-italic">FAM111B</span> gene were detected using the TargetScanHuman database (release 8.0). (<b>D</b>) Dual luciferase reporter assays revealed reduced luminescence activity after co-transfection of <span class="html-italic">miR-144-5p</span> with a vector containing the <span class="html-italic">miR-144-5p</span> binding site (wild-type) in LUAD cells (A549 and H1299). In contrast, no luminescence activity was observed after co-transfection of <span class="html-italic">miR-144-5p</span> with a vector lacking the <span class="html-italic">miR-144-5p</span> binding site (deletion-type) in LUAD cells. ****, <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 6
<p>Effects of knockdown of <span class="html-italic">FAM111B</span> by siRNAs in LUAD cells (A549 and H1299) (<b>A</b>) The inhibitory effects of two different siRNAs targeting <span class="html-italic">FAM111B</span> (si<span class="html-italic">FAM111B</span>-1 and si<span class="html-italic">FAM111B</span>-2) expression were examined. <span class="html-italic">FAM111B</span>- mRNA levels were effectively inhibited by each siRNA in LUAD cells (A549 and H1299). (<b>B</b>) FAM111B protein levels were effectively inhibited by two siRNAs (si<span class="html-italic">FAM111B</span>-1 and si<span class="html-italic">FAM111B</span>-2) in LUAD cells (A549 and H1299). (<b>C</b>) Cell proliferation was evaluated using XTT assays 72 h after siRNA transfection into LUAD cells. (<b>D</b>) At 72 h after transient transfection with si<span class="html-italic">FAM111B</span>-1 and si<span class="html-italic">FAM111B</span>-2, cell cycle status was evaluated using flow cytometry. (<b>E</b>) At 72 h after transient knockdown of <span class="html-italic">FAM111B</span>, apoptotic cells were evaluated using flow cytometry with Annexin V-FITC- and PI-PerCP-Cy5-5-A-stained cells. Cisplatin (30 µM) was used as a positive control for induction of apoptosis. (<b>F</b>) At 72 h after seeding <span class="html-italic">FAM111B</span>-knockdown cells into the chambers, cell invasion assessed using Matrigel invasion assays. (<b>G</b>) At 72 h after seeding <span class="html-italic">FAM111B</span>-knockdown cells into the chambers, cell migration was assessed using a membrane culture system. *, <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; N.S., not significant.</p>
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<p>Effects of knockdown of <span class="html-italic">FAM111B</span> by siRNAs in LUAD cells (A549 and H1299) (<b>A</b>) The inhibitory effects of two different siRNAs targeting <span class="html-italic">FAM111B</span> (si<span class="html-italic">FAM111B</span>-1 and si<span class="html-italic">FAM111B</span>-2) expression were examined. <span class="html-italic">FAM111B</span>- mRNA levels were effectively inhibited by each siRNA in LUAD cells (A549 and H1299). (<b>B</b>) FAM111B protein levels were effectively inhibited by two siRNAs (si<span class="html-italic">FAM111B</span>-1 and si<span class="html-italic">FAM111B</span>-2) in LUAD cells (A549 and H1299). (<b>C</b>) Cell proliferation was evaluated using XTT assays 72 h after siRNA transfection into LUAD cells. (<b>D</b>) At 72 h after transient transfection with si<span class="html-italic">FAM111B</span>-1 and si<span class="html-italic">FAM111B</span>-2, cell cycle status was evaluated using flow cytometry. (<b>E</b>) At 72 h after transient knockdown of <span class="html-italic">FAM111B</span>, apoptotic cells were evaluated using flow cytometry with Annexin V-FITC- and PI-PerCP-Cy5-5-A-stained cells. Cisplatin (30 µM) was used as a positive control for induction of apoptosis. (<b>F</b>) At 72 h after seeding <span class="html-italic">FAM111B</span>-knockdown cells into the chambers, cell invasion assessed using Matrigel invasion assays. (<b>G</b>) At 72 h after seeding <span class="html-italic">FAM111B</span>-knockdown cells into the chambers, cell migration was assessed using a membrane culture system. *, <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; N.S., not significant.</p>
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<p><span class="html-italic">FAM111B</span> expression and its clinical significance in LUAD. (<b>A</b>) Immunohistochemical staining of FAM111B. (<b>B</b>) Cancer tissues showed strong immunostaining, in contrast to the weak staining observed in noncancerous tissues. The data are means and standard errors of the means. Mann–Whitney U-tests. Scale bar: 200 µm (low magnification); 50 µm (high magnification). (<b>C</b>) Forest plot showing the results of multivariate Cox proportional hazards regression analysis of the 5-year overall survival rate. A significantly lower overall survival rate was observed in patients with high <span class="html-italic">FAM111B</span> expression. The data were sourced from TCGA-LUAD datasets. (<b>D</b>) FAM111B-mediated pathways identified by gene set enrichment analysis. The “cell cycle”, “DNA replication” pathways were enriched in patients with high <span class="html-italic">FAM111B</span> expression.</p>
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<p><span class="html-italic">FAM111B</span> expression and its clinical significance in LUAD. (<b>A</b>) Immunohistochemical staining of FAM111B. (<b>B</b>) Cancer tissues showed strong immunostaining, in contrast to the weak staining observed in noncancerous tissues. The data are means and standard errors of the means. Mann–Whitney U-tests. Scale bar: 200 µm (low magnification); 50 µm (high magnification). (<b>C</b>) Forest plot showing the results of multivariate Cox proportional hazards regression analysis of the 5-year overall survival rate. A significantly lower overall survival rate was observed in patients with high <span class="html-italic">FAM111B</span> expression. The data were sourced from TCGA-LUAD datasets. (<b>D</b>) FAM111B-mediated pathways identified by gene set enrichment analysis. The “cell cycle”, “DNA replication” pathways were enriched in patients with high <span class="html-italic">FAM111B</span> expression.</p>
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13 pages, 442 KiB  
Article
microRNAs and Other Serological Markers of Liver Fibrosis in Patients with Alcohol-Related Liver Cirrhosis
by Agata Michalak, Małgorzata Guz, Joanna Kozicka, Marek Cybulski, Witold Jeleniewicz, Karolina Szczygieł, Ewa Tywanek and Halina Cichoż-Lach
Biomedicines 2024, 12(9), 2108; https://doi.org/10.3390/biomedicines12092108 - 16 Sep 2024
Abstract
Background: It is essential to identify novel non-invasive markers of liver fibrosis for clinical and scientific purposes. Thus, the goal of our survey was to assess the serological expression of selected microRNAs (miRNAs) in patients with alcohol-related liver cirrhosis (ALC) and to [...] Read more.
Background: It is essential to identify novel non-invasive markers of liver fibrosis for clinical and scientific purposes. Thus, the goal of our survey was to assess the serological expression of selected microRNAs (miRNAs) in patients with alcohol-related liver cirrhosis (ALC) and to correlate them with other existing markers. Methods: Two hundred and thirty-nine persons were enrolled in the study: one hundred and thirty-nine with ALC and one hundred healthy controls. Serological expression of miR-126-3p, miR-197-3p and miR-1-3p was evaluated in all participants. Direct markers of liver fibrosis (PICP, PIIINP, PDGF-AB, TGF-α and laminin) together with indirect indices (AAR, APRI, FIB-4 and GPR) were also assessed. The additional evaluation concerned hematological parameters: MPV, PDW, PCT, RDW, MPR, RPR NLR, PLR and RLR. Results: The expression of miR-197-3p was lower in ALC compared to controls (p < 0.0001). miR-126-3p correlated negatively with AST (p < 0.05) and positively with miR-197-3p (p < 0.001). miR-197-3p correlated with direct markers of liver fibrosis—positively with PDGF-AB (p < 0.005) and negatively with TGF-α (p < 0.01). Significant negative relationships were noticed between miR-1-3p and the number of neutrophils (p < 0.05), TGF-α (p < 0.05) and laminin (p < 0.05). Conclusions: The achieved results and observed correlations prove the potential involvement of the examined miRNAs in the process of liver fibrosis, giving a novel insight into the diagnostics of liver cirrhosis. Full article
(This article belongs to the Special Issue Novel Insights into Liver Metabolism)
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<p>ROC curve (blue line) for miR-197-3p in the ALC group and random classifier (red line). AUC = 0.691, <span class="html-italic">p</span> &lt; 0.0001. A proposed cut-off &gt; 1.01 amol/µL.</p>
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13 pages, 5167 KiB  
Article
Transcriptome-Wide Evaluation Characterization of microRNAs and Assessment of Their Functional Roles as Regulators of Diapause in Ostrinia furnacalis Larvae (Lepidoptera: Crambidae)
by Hongyue Ma, Ye Liu, Xun Tian, Yujie Chen and Shujing Gao
Insects 2024, 15(9), 702; https://doi.org/10.3390/insects15090702 - 14 Sep 2024
Viewed by 249
Abstract
microRNAs (miRNAs) function as vital regulators of diapause in insects through their ability to post-transcriptionally suppress target gene expression. In this study, the miRNA of Ostrinia furnacalis, an economically important global crop pest species, was characterized. For the included analyses, 9 small RNA [...] Read more.
microRNAs (miRNAs) function as vital regulators of diapause in insects through their ability to post-transcriptionally suppress target gene expression. In this study, the miRNA of Ostrinia furnacalis, an economically important global crop pest species, was characterized. For the included analyses, 9 small RNA libraries were constructed using O. furnacalis larvae in different diapause states (non-diapause, ND; diapause, D; diapause-termination, DT). The results identified 583 total miRNAs, of which 256 had previously been identified, whereas 327 were novel. Furthermore, comparison analysis revealed that 119 and 27 miRNAs were differentially expressed in the D vs. ND and DT vs. D, respectively. Moreover, the expression patterns of their miRNAs were also analyzed. GO and KEGG analysis of the target genes of differentially expressed miRNAs highlighted the importance of these miRNAs as diapause regulators in O. furnacalis, especially through metabolic processes, endocrine processes, 20-hydroxyecdysone, and circadian clock signaling pathways. In summary, this study highlighted the involvement of specific miRNAs in the control of diapause in O. furnacalis. To the best of our knowledge, this is the first study to identify miRNA expression patterns in O. furnacalis, thereby providing reference and novel evidence enhancing our current understanding of how small RNAs influence insect diapause. Full article
(This article belongs to the Section Insect Molecular Biology and Genomics)
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Graphical abstract

Graphical abstract
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<p>Clustering analysis of miRNAs associated with different diapause states in <span class="html-italic">O. furnacalis</span>. Data are presented as the average normalized values of three biological replicates. ND: Non-diapause; D: diapause; DT: diapause-termination.</p>
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<p>Venn diagram analysis of differentially expressed miRNAs between the compared D/ND and DT/D diapause states. ND: Non-diapause; D: diapause; DT: diapause termination.</p>
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<p>The top 20 enriched GO terms are associated with DEM target genes in <span class="html-italic">O. furnacalis</span>. (<b>A</b>) D/ND; (<b>B</b>) DT/D.</p>
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<p>KEGG enrichment analyses of DEM target genes in <span class="html-italic">O. furnacalis</span>. (<b>A</b>) D/ND; (<b>B</b>) DT/D.</p>
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<p>qPCR validation of sRNA-seq results.</p>
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<p>Relative expression profiles of miRNA and target genes in the ND, D, and DT states of <span class="html-italic">O. furnacalis</span>. Relative expression levels of miRNA and target genes were normalized to U6 and <span class="html-italic">β</span>-actin, respectively. Each point represents the mean relative expression level, and the error bars indicate standard error (SE).</p>
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<p>The regulatory model of miRNA in the diapause of <span class="html-italic">O. furnacalis</span>.</p>
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30 pages, 2358 KiB  
Review
Insights into the Role of microRNAs as Clinical Tools for Diagnosis, Prognosis, and as Therapeutic Targets in Alzheimer’s Disease
by Nidhi Puranik and Minseok Song
Int. J. Mol. Sci. 2024, 25(18), 9936; https://doi.org/10.3390/ijms25189936 (registering DOI) - 14 Sep 2024
Viewed by 331
Abstract
Neurodegenerative diseases (NDDs) are a diverse group of neurological disorders characterized by alterations in the structure and function of the central nervous system. Alzheimer’s disease (AD), characterized by impaired memory and cognitive abilities, is the most prevalent type of senile dementia. Loss of [...] Read more.
Neurodegenerative diseases (NDDs) are a diverse group of neurological disorders characterized by alterations in the structure and function of the central nervous system. Alzheimer’s disease (AD), characterized by impaired memory and cognitive abilities, is the most prevalent type of senile dementia. Loss of synapses, intracellular aggregation of hyperphosphorylated tau protein, and extracellular amyloid-β peptide (Aβ) plaques are the hallmarks of AD. MicroRNAs (miRNAs/miRs) are single-stranded ribonucleic acid (RNA) molecules that bind to the 3′ and 5′ untranslated regions of target genes to cause post-transcriptional gene silencing. The brain expresses over 70% of all experimentally detected miRNAs, and these miRNAs are crucial for synaptic function and particular signals during memory formation. Increasing evidence suggests that miRNAs play a role in AD pathogenesis and we provide an overview of the role of miRNAs in synapse formation, Aβ synthesis, tau protein accumulation, and brain-derived neurotrophic factor-associated AD pathogenesis. We further summarize and discuss the role of miRNAs as potential therapeutic targets and biomarkers for AD detection and differentiation between early- and late-stage AD, based on recent research. In conclusion, altered expression of miRNAs in the brain and peripheral circulation demonstrates their potential as biomarkers and therapeutic targets in AD. Full article
(This article belongs to the Special Issue Role of MicroRNAs in Human Diseases)
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<p>Diagrammatic representation of a possible role of miRNAs in diagnosis, prognosis, and therapeutics.</p>
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<p>Therapeutic approaches for manipulating miRNA. (<b>a</b>) The normal mode of action of miRNAs. (<b>b</b>) MiRNA mimics: an increased level of miRNA leads to the downregulation of target mRNA expression. (<b>c</b>) Anti-miRNA: miRNA knockdown leads to the overexpression of target mRNA. (<b>d</b>) Introducing a target-specific miRNA target blocker in a cell that leads to the overexpression of target mRNA. (Created with <a href="http://biorender.com" target="_blank">biorender.com</a>, accessed on 7 May 2024).</p>
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<p>miRNA is associated with various pathophysiologies of Alzheimer’s disease, including tau-, Aβ-, BACE1-, and BDNF signaling-associated pathologies, and is also related to synaptic dysfunction. miRNA associated with AD pathology could be a potential therapeutic target or biomarker for its diagnosis. (Created with BioRender and accessed on 9 September 2024).</p>
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25 pages, 1077 KiB  
Review
Non-Coding RNAs in Myasthenia Gravis: From Immune Regulation to Personalized Medicine
by Nicola Iacomino, Maria Cristina Tarasco, Alessia Berni, Jacopo Ronchi, Renato Mantegazza, Paola Cavalcante and Maria Foti
Cells 2024, 13(18), 1550; https://doi.org/10.3390/cells13181550 - 14 Sep 2024
Viewed by 174
Abstract
Myasthenia gravis (MG) is an antibody-mediated autoimmune disorder characterized by altered neuromuscular transmission, which causes weakness and fatigability in the skeletal muscles. The etiology of MG is complex, being associated with multiple genetic and environmental factors. Over recent years, progress has been made [...] Read more.
Myasthenia gravis (MG) is an antibody-mediated autoimmune disorder characterized by altered neuromuscular transmission, which causes weakness and fatigability in the skeletal muscles. The etiology of MG is complex, being associated with multiple genetic and environmental factors. Over recent years, progress has been made in understanding the immunological alterations implicated in the disease, but the exact pathogenesis still needs to be elucidated. A pathogenic interplay between innate immunity and autoimmunity contributes to the intra-thymic MG development. Epigenetic changes are critically involved in both innate and adaptive immune response regulation. They can act as (i) pathological factors besides genetic predisposition and (ii) co-factors contributing to disease phenotypes or patient-specific disease course/outcomes. This article reviews the role of non-coding RNAs (ncRNAs) as epigenetic factors implicated in MG. Particular attention is dedicated to microRNAs (miRNAs), whose expression is altered in MG patients’ thymuses and circulating blood. The long ncRNA (lncRNA) contribution to MG, although not fully characterized yet, is also discussed. By summarizing the most recent and fast-growing findings on ncRNAs in MG, we highlight the therapeutic potential of these molecules for achieving immune regulation and their value as biomarkers for the development of personalized medicine approaches to improve disease care. Full article
24 pages, 1733 KiB  
Review
Functional Role of Extracellular Vesicles in Skeletal Muscle Physiology and Sarcopenia: The Importance of Physical Exercise and Nutrition
by Mauro Lombardo, Gilda Aiello, Deborah Fratantonio, Sercan Karav and Sara Baldelli
Nutrients 2024, 16(18), 3097; https://doi.org/10.3390/nu16183097 - 13 Sep 2024
Viewed by 349
Abstract
Background/Objectives: Extracellular vesicles (EVs) play a key role in intercellular communication by transferring miRNAs and other macromolecules between cells. Understanding how diet and exercise modulate the release and content of skeletal muscle (SM)-derived EVs could lead to novel therapeutic strategies to prevent age-related [...] Read more.
Background/Objectives: Extracellular vesicles (EVs) play a key role in intercellular communication by transferring miRNAs and other macromolecules between cells. Understanding how diet and exercise modulate the release and content of skeletal muscle (SM)-derived EVs could lead to novel therapeutic strategies to prevent age-related muscle decline and other chronic diseases, such as sarcopenia. This review aims to provide an overview of the role of EVs in muscle function and to explore how nutritional and physical interventions can optimise their release and function. Methods: A literature review of studies examining the impact of exercise and nutritional interventions on MS-derived EVs was conducted. Major scientific databases, including PubMed, Scopus and Web of Science, were searched using keywords such as ‘extracellular vesicles’, ‘muscle’, ‘exercise’, ‘nutrition’ and ‘sarcopenia’. The selected studies included randomised controlled trials (RCTs), clinical trials and cohort studies. Data from these studies were synthesised to identify key findings related to the release of EVs, their composition and their potential role as therapeutic targets. Results: Dietary patterns, specific foods and supplements were found to significantly modulate EV release and composition, affecting muscle health and metabolism. Exercise-induced changes in EV content were observed after both acute and chronic interventions, with a marked impact on miRNAs and proteins related to muscle growth and inflammation. Nutritional interventions, such as the Mediterranean diet and omega-3 fatty acids, have also shown the ability to alter EV profiles, suggesting their potential to improve cardiovascular health and reduce inflammation. Conclusions: EVs are emerging as critical mediators of the beneficial effects of diet and exercise on muscle health. Both exercise and nutritional interventions can modulate the release and content of MS-derived EVs, offering promising avenues for the development of novel therapeutic strategies targeting sarcopenia and other muscle diseases. Future research should focus on large-scale RCT studies with standardised methodologies to better understand the role of EVs as biomarkers and therapeutic targets. Full article
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<p>Formation and release of various types of extracellular vesicles (EVs) from a cell.</p>
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<p>Different roles of some miRNAs implicated in the process of muscle sarcopenia.</p>
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<p>Flowchart of Study Selection Process.</p>
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<p>Summary of the impact of nutritional interventions (diets and supplements) on extracellular vesicles (EVs) and their potential role in improving human health. Specific foods, nutrient-rich diets, and supplements influence the content and function of EVs, leading to improved muscle function, reduced inflammation, and improved metabolic health. The question marks (?) indicate areas where further research is needed to fully understand the mechanisms by which nutritional supplements impact EVs function, including how they enhance the delivery of bioactive molecules and improve EVs stability.</p>
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17 pages, 16291 KiB  
Article
Tumor Heterogeneity in Gastrointestinal Cancer Based on Multimodal Data Analysis
by Dongmei Ai, Yang Du, Hongyu Duan, Juan Qi and Yuduo Wang
Genes 2024, 15(9), 1207; https://doi.org/10.3390/genes15091207 - 13 Sep 2024
Viewed by 279
Abstract
Background: Gastrointestinal cancer cells display both morphology and physiology diversity, thus posing a significant challenge for precise representation by a single data model. We conducted an in-depth study of gastrointestinal cancer heterogeneity by integrating and analyzing data from multiple modalities. Methods: We used [...] Read more.
Background: Gastrointestinal cancer cells display both morphology and physiology diversity, thus posing a significant challenge for precise representation by a single data model. We conducted an in-depth study of gastrointestinal cancer heterogeneity by integrating and analyzing data from multiple modalities. Methods: We used a modified Canny algorithm to identify edges from tumor images, capturing intricate nonlinear interactions between pixels. These edge features were then combined with differentially expressed mRNA, miRNA, and immune cell data. Before data integration, we used the K-medoids algorithm to pre-cluster individual data types. The results of pre-clustering were used to construct the kernel matrix. Finally, we applied spectral clustering to the fusion matrix to identify different tumor subtypes. Furthermore, we identified hub genes linked to these subtypes and their biological roles through the application of Weighted Gene Co-expression Network Analysis (WGCNA) and Gene Ontology (GO) enrichment analysis. Results: Our investigation categorized patients into three distinct tumor subtypes and pinpointed hub genes associated with each. Genes MAGI2-AS3, MALAT1, and SPARC were identified as having a differential impact on the metastatic and invasive capabilities of cancer cells. Conclusion: By harnessing multimodal features, our study enhances the understanding of gastrointestinal tumor heterogeneity and identifies biomarkers for personalized medicine and targeted treatments. Full article
(This article belongs to the Section Bioinformatics)
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<p>Significantly different characteristics between cancer and normal samples: (<b>A</b>) top 10 most significant mRNAs; (<b>B</b>) most significant differential miRNAs; (<b>C</b>) differential boxplots of 22 immune cells.</p>
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<p>Heat maps of the top 20 significantly differentially expressed genes (DEGs): (<b>A</b>) mRNA expression heat map; (<b>B</b>) miRNA expression heat map; (<b>C</b>) mRNA expression heat map after taking the mean for the corresponding feature of the same subtype sample; (<b>D</b>) miRNA expression heat map after taking the mean for the corresponding feature of the same subtype sample.</p>
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<p>Six features with the most significant differences among the three subtypes: (<b>A</b>) Top six most significantly differentially expressed mRNAs; (<b>B</b>) Top six most significantly differentially expressed miRNAs.</p>
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<p>Immune cell characteristics of different subtypes: (<b>A</b>) Heat map of immune cell characteristics of samples of the same subtype after taking the mean value; (<b>B</b>) Difference in the percentage of immune cells in samples of different subtypes.</p>
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<p>Results of Weighted Gene Co-expression Network Analysis (WGCNA): (<b>A</b>) Scale-Free Topology Analysis, frequency distribution of the number of connections (i.e., node degree, k) in the network (<b>left</b>), and a test of the scale-independent nature of the network (<b>right</b>); (<b>B</b>) Clustering of Module Eigengenes; (<b>C</b>) Gene Dendrogram and Module Colors, different colors represent different modules; (<b>D</b>) Module Eigengene Correlation Heatmap.</p>
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<p>Correlation of different modules with different subtypes.</p>
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<p>GO analysis results: (<b>A</b>) subtype I (<b>B</b>) subtype III.</p>
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20 pages, 7076 KiB  
Article
Evolution and Functional Dynamics of TCP Transcription Factor Gene Family in Passion Fruit (Passiflora edulis)
by Munsif Ali Shad, Songguo Wu, Muhammad Junaid Rao, Xiaoying Luo, Xiaojin Huang, Yuxin Wu, Yuhong Zhou, Lingqiang Wang, Chongjian Ma and Lihua Hu
Plants 2024, 13(18), 2568; https://doi.org/10.3390/plants13182568 - 13 Sep 2024
Viewed by 190
Abstract
Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer [...] Read more.
Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer phylogenetic relationships exhibited similar protein and gene structures. Gene members of the TCP family showed developmental-stage- or tissue-specific expression profiles during the passion fruit life cycle. Transcriptome data also demonstrated that many PeTCPs showed induced expression in response to hormonal treatments and cold, heat, and salt stress. Based on transcriptomics data, eight candidate genes were chosen for preferential gene expression confirmation under cold stress conditions. The qRT-PCR assays suggested PeTCP15/16/17/19/23 upregulation, while PeTCP1/11/25 downregulation after cold stress. Additionally, TCP19/20/29/30 exhibited in silico binding with cold-stress-related miRNA319s. GFP subcellular localization assays exhibited PeTCP19/1 were localized at the nucleus. This study will aid in the establishment of novel germplasm, as well as the further investigation of the roles of PeTCPs and their cold stress resistance characteristics. Full article
(This article belongs to the Special Issue Growth, Development, and Stress Response of Horticulture Plants)
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<p>Phylogenetic analysis of <span class="html-italic">TCP</span> gene family proteins among passion fruit and <span class="html-italic">Arabidopsis.</span> The phylogenetic tree was built using MEGA-11 software employing the neighbor-joining tree method with 1000 bootstrap replicates. Passion fruit TCP proteins are designated by “Pe” while <span class="html-italic">Arabidopsis</span> proteins are depicted with the “At” prefix.</p>
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<p>Multiple sequence alignment of passion fruit TCP proteins. Sequences were aligned in the MEGA software and sequence alignment was visualized in the ESPript 3.0 web tool. The residues highlighted in red vertical lines indicate completely conserved while those inside blue verticle lines are highly conserved amino acids.</p>
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<p>TCP protein domain composition and gene structure organization. (<b>A</b>) The phylogenetic tree was generated in MEGA-X software. (<b>B</b>) Domain attributes were downloaded from the NCBI batch CD server. TCP, SKN1, and ACT domains are depicted in green, yellow, and pink, respectively. (<b>C</b>) The gene coordinate information was drawn through the TB tool. CDS, introns, and upstream/downstream regions of gene structure are shown in yellow, black, and blue, respectively.</p>
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<p>Structural modeling and superimposition of bHLH domains of three representative proteins from each subfamily of PeTCP. PeTCP9 depicted in brown, PeTCP17 shown in magenta, and PeTCP25 exhibited in blue represent CYC, CIN, and PCF subfamilies, respectively. Protein 3D modeling was performed using the SWISS-MODEL employing orthologous Arabidopsis TCP proteins as templates. Modeled proteins were visualized and structurally aligned using the Chimera software.</p>
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<p>Distribution of 30 <span class="html-italic">TCP</span> genes in passion fruit genome. The chromosome structures and gene positions were depicted in TBtools employing the genomic information from the Passionfruit Genomics Network database. The scale on the left indicates the chromosome size in Mbps. The colored bars indicate chromosomes, while black dotted lines show the duplicated genes.</p>
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<p><span class="html-italic">Cis</span>-regulatory element (CRE) distribution in the predicted promoter regions of <span class="html-italic">PeTCPs</span>. (<b>A</b>) Hormonal responsiveness. (<b>B</b>) Growth and development related. (<b>C</b>) Stress responsiveness.</p>
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<p>Predicted miRNA319a/b–<span class="html-italic">TCP</span>-binding modules.</p>
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<p>Transcriptome profiling of <span class="html-italic">TCP</span> gene expression levels. (<b>A</b>) Different growth stages and tissues. (<b>B</b>) Hormonal treatments. (<b>C</b>) Cold and heat stress conditions. (<b>D</b>) Salt and drought stress. The scale above each heatmap indicates the levels of relative gene expression, red, yellow, and blue correspond to high, medium, and low expressions, respectively. The vertical bars at the extreme right of each panel and below 8A indicate a phylogenetic subclass and green, red, and blue represent CYC, CIN, and PCF subclasses, respectively.</p>
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<p>GO annotations and KEGG analysis of <span class="html-italic">TCP</span> gene family. The GO enrichment terms’ names are on the X axis while the number of genes belonging to each category is along the Y axis.</p>
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<p>Expression profiles of 8 <span class="html-italic">TCP</span> genes (<span class="html-italic">PeTCP1, 11, 25, 16, 17, 19, 23, 15</span>) in response to the cold stress treatments. Three independent biological replicates’ standard deviations of means are represented by error bars. Significant variations of the transcript levels between treatments and blank control (0 h) are indicated by asterisks (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Subcellular localization of two representative TCP proteins. The top panels represent an empty vector (EV). The PeTCP19-GFP and PeTCP1-GFP fusion proteins were introduced into tobacco leaves for transient expression. After 60 h, confocal microscopy was used to observe the localization of these proteins. Nuclei were visualized using a co-transformed mCherry-labeled nuclear marker (H2B-mCherry). Scale bar, 20 μm.</p>
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25 pages, 5756 KiB  
Article
Impacts of DROSHA (rs10719) and DICER (rs3742330) Variants on Breast Cancer Risk and Their Distribution in Blood and Tissue Samples of Egyptian Patients
by Aly A. M. Shaalan, Essam Al Ageeli, Shahad W. Kattan, Amany I. Almars, Nouf A. Babteen, Abdulmajeed A. A. Sindi, Eman A. Toraih, Manal S. Fawzy and Marwa Hussein Mohamed
Curr. Issues Mol. Biol. 2024, 46(9), 10087-10111; https://doi.org/10.3390/cimb46090602 - 12 Sep 2024
Viewed by 373
Abstract
MicroRNAs (miRNAs) are small, noncoding RNAs that regulate gene expression and play critical roles in tumorigenesis. Genetic variants in miRNA processing genes, DROSHA and DICER, have been implicated in cancer susceptibility and progression in various populations. However, their role in Egyptian patients [...] Read more.
MicroRNAs (miRNAs) are small, noncoding RNAs that regulate gene expression and play critical roles in tumorigenesis. Genetic variants in miRNA processing genes, DROSHA and DICER, have been implicated in cancer susceptibility and progression in various populations. However, their role in Egyptian patients with breast cancer (BC) remains unexplored. This study aims to investigate the association of DROSHA rs10719 and DICER rs3742330 polymorphisms with BC risk and clinical outcomes. This case–control study included 209 BC patients and 106 healthy controls. Genotyping was performed using TaqMan assays in blood, tumor tissue, and adjacent non-cancerous tissue samples. Associations were analyzed using logistic regression and Fisher’s exact test. The DROSHA rs10719 AA genotype was associated with a 3.2-fold increased risk (95%CI = 1.23–9.36, p < 0.001), and the DICER rs3742330 GG genotype was associated with a 3.51-fold increased risk (95%CI = 1.5–8.25, p = 0.001) of BC. Minor allele frequencies were 0.42 for rs10719 A and 0.37 for rs3742330 G alleles. The risk alleles were significantly more prevalent in tumor tissue than adjacent normal tissue (rs10719 A: 40.8% vs. 0%; rs3742330 G: 42.7% vs. 0%; p < 0.001). However, no significant associations were observed with clinicopathological features or survival outcomes over a median follow-up of 17 months. In conclusion, DROSHA rs10719 and DICER rs3742330 polymorphisms are associated with increased BC risk and more prevalent in tumor tissue among our cohort, suggesting a potential role in miRNA dysregulation during breast tumorigenesis. These findings highlight the importance of miRNA processing gene variants in BC susceptibility and warrant further validation in larger cohorts and different ethnic populations. Full article
(This article belongs to the Special Issue Advances in Molecular Pathogenesis Regulation in Cancer 2024)
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<p>The allele frequencies of <span class="html-italic">DROSHA</span> rs10719 and <span class="html-italic">DICER</span> rs3742330 variants in different populations. (<b>A</b>) <span class="html-italic">DROSHA</span> (<b>B</b>) <span class="html-italic">DICER</span>. AMR: American; AFR: African; EAS: East Asian; EUR: European; SAS: South Asians. Data source: 1000 Genomes Project Phase 3 allele frequencies [Ensembl.org] (last accessed on 20 March 2024)”. *rs: reference sequence.</p>
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<p>Analysis of the <span class="html-italic">DROSHA</span> gene structure and its associated 3D interactions with other genes and variants mediated by chromatin loops. (<b>A</b>) The <span class="html-italic">DROSHA</span> gene is on the short arm of chromosome 5 on the forward strand, following the ‘GRCh38.p14’ assembly. The rs10719 variant is positioned at 5:31,401,340 (highlighted), where the ancestral nucleotide ‘A’ is replaced by the alternative (minor) allele ‘G’ (<a href="https://www.ncbi.nlm.nih.gov/snp/rs10719" target="_blank">https://www.ncbi.nlm.nih.gov/snp/rs10719</a>). (<b>B</b>) A Circos plot illustrating the chromatin loops and other 2D characteristics related to the variant of interest, generated using 3DSNP 2.0 (<a href="https://omic.tech/3dsnpv2/" target="_blank">https://omic.tech/3dsnpv2/</a>). The plot displays, from the outer edge to the inner section, the chromatin states, annotated genes, the current SNP of interest and associated SNPs, and 3D chromatin interactions. A color key corresponding to the chromatin states and loops for twelve distinct cell types has been detailed previously [<a href="#B23-cimb-46-00602" class="html-bibr">23</a>]. (<b>C</b>) <span class="html-italic">DROSHA</span>’s subcellular localization can be accessed via <a href="https://www.proteinatlas.org/ENSG00000113360-DROSHA/subcellular" target="_blank">https://www.proteinatlas.org/ENSG00000113360-DROSHA/subcellular</a>. (<b>D</b>) The conservation score for the variant of interest is recorded as 2.277, derived from multiple alignments of vertebrate (<span class="html-italic">n</span> = 46) and mammalian (<span class="html-italic">n</span> = 33) genomes. All databases were last accessed on 30 March 2024.</p>
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<p>Structural analysis of the <span class="html-italic">DICER</span> gene and its associated 3D interactions with other genes and variants mediated by chromatin loops. (<b>A</b>) The DICER gene is situated on the long arm of chromosome 14 on the reverse strand, aligning with the ‘GRCh38.p14’ assembly. The rs3742330 variant is found at position 14: 95,087,025 (highlighted), where the ancestral nucleotide ‘A’ is replaced by the alternative (minor) allele ‘G’ (<a href="https://www.ncbi.nlm.nih.gov/snp/rs3742330" target="_blank">https://www.ncbi.nlm.nih.gov/snp/rs3742330</a>). (<b>B</b>) A Circos plot displaying the chromatin loops and other 2D features related to the variant of interest was created using “3DSNP 2.0 (<a href="https://omic.tech/3dsnpv2/" target="_blank">https://omic.tech/3dsnpv2/</a>)”. The plot illustrates, from the outermost section to the inner, the chromatin states, annotated genes, the currently examined SNP and its associated SNPs, and 3D chromatin interactions. The color key for chromatin states and loops across twelve different cell types is provided in a previous work [<a href="#B23-cimb-46-00602" class="html-bibr">23</a>]. (<b>C</b>) Information regarding the subcellular distribution of <span class="html-italic">DICER</span> can be accessed at <a href="https://www.proteinatlas.org/ENSG00000100697-DICER1/subcellular" target="_blank">https://www.proteinatlas.org/ENSG00000100697-DICER1/subcellular</a>. (<b>D</b>) The conservation score for the variant of interest is reported as −0.023, derived from multiple alignments of vertebrate (<span class="html-italic">n</span> = 46) and mammalian (<span class="html-italic">n</span> = 33) genomes. All databases were last accessed on 30 March 2024.</p>
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<p>Genotype combination analysis of <span class="html-italic">DICER</span> and <span class="html-italic">DROSHA</span> genes in tissues of BC women. (<b>A</b>) Distribution of <span class="html-italic">DROSHA</span> genotypes in patients and controls. (<b>B</b>) Distribution of <span class="html-italic">DICER</span> genotypes in patients and controls. (<b>C</b>) Distribution of combined <span class="html-italic">DROSHA</span> and <span class="html-italic">DICER</span> genotypes in patients and controls. *rs: reference sequence.</p>
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<p>Somatic mutation analyses of <span class="html-italic">DICER</span> and <span class="html-italic">DROSHA</span> polymorphisms in paired tissues of women with BC. (<b>A</b>) Genotype alteration of the <span class="html-italic">DROSHA</span> gene in cancer and non-cancer tissues. The A allele is considered the risky variant. (<b>B</b>) Genotype alteration of <span class="html-italic">DICER</span> gene in cancer and non-cancer tissues. G allele is considered the risky variant. (<b>C</b>) Genotype alteration of combined <span class="html-italic">DROSHA</span> and <span class="html-italic">DICER</span> genes in cancer/non-cancer tissues. *rs: reference sequence.</p>
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<p>Clinical presentation of BC women with blood samples (<span class="html-italic">n</span> = 106). (<b>A</b>) Counts of affected sides. (<b>B</b>) Counts of affected locations. (<b>C</b>) Counts of patients according to the number of masses at the time of presentation. (<b>D</b>) The different histopathological types. (<b>E</b>)Pathology-related data of patients with BC and provided blood samples. G3: Grade 3, T3-4: stage 3-4, LNM: Lymph node metastasis, LVI: lymphovascular infiltration.</p>
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<p>The genotype and allele frequencies of the <span class="html-italic">DICER</span> and <span class="html-italic">DROSHA</span> genes in blood samples of BC and non-cancer women: (<b>A</b>) <span class="html-italic">DROSHA</span> rs10719; (<b>B</b>) <span class="html-italic">DICER</span> rs3742330. Pie charts represented the percentage of each allele in the overall cohorts (cases and controls). The bar chart showed the frequencies (counts) of cohorts per allele or genotype. A two-sided Chi-square test was used. Significance was set at <span class="html-italic">p</span> &lt; 0.05. *rs: reference sequence.</p>
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<p>Genetic association models for disease risk assessment: (<b>A</b>) <span class="html-italic">DROSHA</span> rs10719; (<b>B</b>) <span class="html-italic">DICER</span> rs3742330. Multivariate regression models were performed and shown as odds ratios (ORs) and 95% confidence intervals (95%CI). Adjusted variables were patient age at diagnosis, marital status, occupation, a family history of cancer, prior breast problems, smoking, body mass index, diabetes, hypertension, and hepatitis C virus infection. The red line is a risky genotype, the blue line is a protective genotype, and the black line is insignificant. ** indicate significance at <span class="html-italic">p</span>-value &lt; 0.05.</p>
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16 pages, 1402 KiB  
Review
Research Progress on miRNAs and Artificial miRNAs in Insect and Disease Resistance and Breeding in Plants
by Zengfeng Ma, Jianyu Wang and Changyan Li
Genes 2024, 15(9), 1200; https://doi.org/10.3390/genes15091200 - 12 Sep 2024
Viewed by 409
Abstract
MicroRNAs (miRNAs) are small, non-coding RNAs that are expressed in a tissue- and temporal-specific manner during development. They have been found to be highly conserved during the evolution of different species. miRNAs regulate the expression of several genes in various organisms, with some [...] Read more.
MicroRNAs (miRNAs) are small, non-coding RNAs that are expressed in a tissue- and temporal-specific manner during development. They have been found to be highly conserved during the evolution of different species. miRNAs regulate the expression of several genes in various organisms, with some regulating the expression of multiple genes with similar or completely unrelated functions. Frequent disease and insect pest infestations severely limit agricultural development. Thus, cultivating resistant crops via miRNA-directed gene regulation in plants, insects, and pathogens is an important aspect of modern breeding practices. To strengthen the application of miRNAs in sustainable agriculture, plant endogenous or exogenous miRNAs have been used for plant breeding. Consequently, the development of biological pesticides based on miRNAs has become an important avenue for future pest control methods. However, selecting the appropriate miRNA according to the desired target traits in the target organism is key to successfully using this technology for pest control. This review summarizes the progress in research on miRNAs in plants and other species involved in regulating plant disease and pest resistance pathways. We also discuss the molecular mechanisms of relevant target genes to provide new ideas for future research on pest and disease resistance and breeding in plants. Full article
(This article belongs to the Special Issue Plant Small RNAs: Biogenesis and Functions)
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<p>Molecular mechanisms related to the regulation of endogenous miRNA expression in plants. Primary microRNA (pri-miRNA) is transcribed by Pol II from miRNA-encoding genes. In the nucleus, the RNase III family enzyme DCL1, along with HYL1 and SE, processes pre-miRNA into miRNA/miRNA double strands. The miRNA/miRNA* double strand is methylated at its 3′ end by the miRNA methyltransferase HEN1. Once methylated, the miRNA/miRNA* double strand is transported from the nucleus to the cytoplasm through HASTY. In the cytoplasm, the miRNA/miRNA* double-stranded guide strands are incorporated into RISC. This process is involved in miRNA degradation, as well as miRNA-mediated gene silencing through target cleavage and translational repression [<a href="#B6-genes-15-01200" class="html-bibr">6</a>].</p>
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<p>Functions of exogenous and endogenous miRNAs and amiRNAs in disease and insect resistance in plants. MiRNAs, miRNA target mimetics, and amiRNAs related to plant disease and pest resistance can be synthesized externally or directly transferred into the crop genome to enhance crop disease and pest resistance.</p>
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18 pages, 3787 KiB  
Review
Building a Human Ovarian Antioxidant ceRNA Network “OvAnOx”: A Bioinformatic Perspective for Research on Redox-Related Ovarian Functions and Dysfunctions
by Carla Tatone, Giovanna Di Emidio, Rosalia Battaglia and Cinzia Di Pietro
Antioxidants 2024, 13(9), 1101; https://doi.org/10.3390/antiox13091101 - 12 Sep 2024
Viewed by 271
Abstract
The ovary is a major determinant of female reproductive health. Ovarian functions are mainly related to the primordial follicle pool, which is gradually lost with aging. Ovarian aging and reproductive dysfunctions share oxidative stress as a common underlying mechanism. ROS signaling is essential [...] Read more.
The ovary is a major determinant of female reproductive health. Ovarian functions are mainly related to the primordial follicle pool, which is gradually lost with aging. Ovarian aging and reproductive dysfunctions share oxidative stress as a common underlying mechanism. ROS signaling is essential for normal ovarian processes, yet it can contribute to various ovarian disorders when disrupted. Therefore, balance in the redox system is crucial for proper ovarian functions. In the present study, by focusing on mRNAs and ncRNAs described in the ovary and taking into account only validated ncRNA interactions, we built an ovarian antioxidant ceRNA network, named OvAnOx ceRNA, composed of 5 mRNAs (SOD1, SOD2, CAT, PRDX3, GR), 10 miRNAs and 5 lncRNAs (XIST, FGD5-AS1, MALAT1, NEAT1, SNHG1). Our bioinformatic analysis indicated that the components of OvAnOx ceRNA not only contribute to antioxidant defense but are also involved in other ovarian functions. Indeed, antioxidant enzymes encoded by mRNAs of OvAnOx ceRNA operate within a regulatory network that impacts ovarian reserve, follicular dynamics, and oocyte maturation in normal and pathological conditions. The OvAnOx ceRNA network represents a promising tool to unravel the complex dialog between redox potential and ovarian signaling pathways involved in reproductive health, aging, and diseases. Full article
(This article belongs to the Special Issue Non-Coding RNAs and Reactive Oxygen Species)
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<p>Molecular functions (GO) (<b>A</b>) and associated biological pathways (<b>B</b>) of the 21 antioxidant enzymes-encoding genes selected for this study. The significance is reported as a −log<sub>10</sub> <span class="html-italic">p</span>-value for both panels (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Expression of the selected antioxidant enzymes, in terms of transcripts, within the ovarian tissue.</p>
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<p>Network showing the interactions between miRNAs and antioxidant enzyme mRNAs.</p>
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<p>Network showing the interaction between the miRNAs targeting antioxidant enzymes and lncRNAs. The nodes are ranked according to the degree scoring method, with a color scheme from highly central (red) to central (yellow).</p>
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<p>mRNA-miRNA-lncRNA ceRNA network. (<b>A</b>) Antioxidant ceRNA network. (<b>B</b>) Ovarian antioxidant OvAnOx ceRNA network. miRNAs are red-colored, mRNAs are yellow-colored, and lncRNAs are blue-colored.</p>
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