• Journal of Breast Cancer
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• v.21 no.4
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• pp.371-381
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• 2018

Purpose: Immune suppression is common in patients with advanced breast cancer but the mechanisms underlying this phenomenon have not been sufficiently studied. In this study, we aimed to identify B7 family members that were able to predict the immune status of patients, and which may serve as potential targets for the treatment of breast cancer. We also aimed to identify microRNAs that may regulate the expression of B7 family members. Methods: The Cancer Genome Atlas data from 1,092 patients with breast cancer, including gene expression, microRNA expression and survival data, were used for statistical and survival analyses. Polymerase chain reaction and Western blot were used to measure messenger RNA and protein expression, respectively. Luciferase assay was used to investigate direct microRNA target. Results: Bioinformatic analysis predicted that microRNA (miR)-93, miR-195, miR-497, and miR-340 are potential regulators of the immune evasion of breast cancer cells, and that they exert this function by targeting CD274, PDCD1LG2, and NCR3LG1. We chose CD274 for further investigations. We found that miR-195, miR-497, and CD274 expression levels were inversely correlated in MDA-MB-231 cells, and miR-195 and miR-497 expressions mimic inhibited CD274 expression in vitro. Mechanistic investigations demonstrated that miR-195 and miR-497 directly target CD274 3' untranslated region. Conclusion: Our data indicated that the level of B7 family members can predict the prognosis of breast cancer patients, and miR-195/miR-497 regulate CD274 expression in triple negative breast cancer. This regulation may further influence tumor progression and the immune tolerance mechanism in breast cancer and may be able to predict the effect of immunotherapy on patients.

• Biomolecules & Therapeutics
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• v.27 no.4
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• pp.414-422
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• 2019

There is accumulating evidence that microRNAs are emerging as pivotal regulators in the development and progression of neuropathic pain. MicroRNA-15a/16 (miR-15a/16) have been reported to play an important role in various diseases and inflammation response processes. However, whether miR-15a/16 participates in the regulation of neuroinflammation and neuropathic pain development remains unknown. In this study, we established a mouse model of neuropathic pain by chronic constriction injury (CCI) of the sciatic nerves. Our results showed that both miR-15a and miR-16 expression was significantly upregulated in the spinal cord of CCI rats. Downregulation of the expression of miR-15a and miR-16 by intrathecal injection of a specific inhibitor significantly attenuated the mechanical allodynia and thermal hyperalgesia of CCI rats. Furthermore, inhibition of miR-15a and miR-16 downregulated the expression of interleukin-$1{\beta}$ and tumor-necrosis factor-${\alpha}$ in the spinal cord of CCI rats. Bioinformatic analysis predicted that G protein-coupled receptor kinase 2 (GRK2), an important regulator in neuropathic pain and inflammation, was a potential target gene of miR-15a and miR-16. Inhibition of miR-15a and miR-16 markedly increased the expression of GRK2 while downregulating the activation of p38 mitogen-activated protein kinase and $NF-{\kappa}B$ in CCI rats. Notably, the silencing of GRK2 significantly reversed the inhibitory effects of miR-15a/16 inhibition in neuropathic pain. In conclusion, our results suggest that inhibition of miR-15a/16 expression alleviates neuropathic pain development by targeting GRK2. These findings provide novel insights into the molecular pathogenesis of neuropathic pain and suggest potential therapeutic targets for preventing neuropathic pain development.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.425-434
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• 2020

Background: Viral infection outbreaks are emerging public health concerns. They often exhibit seasonal patterns that could be predicted by the application of big data and bioinformatic analyses. Purpose: The purpose of this study was to identify trends in diarrhea-causing viruses such as rotavirus (Gr.A), norovirus G-I, and norovirus G-II in Cheonan, Korea. The identified related factors of diarrhea-causing viruses may be used to predict their trend and prevent their infections. Method: A retrospective analysis of 4,009 fecal samples from June 2010 to December 2019 was carried out at Dankook University Hospital in Cheonan. Reverse transcription-PCR (RT-PCR) was employed to identify virus strains. Information about seasonal patterns of infection was extracted and compared with local weather data. Results: Out of the 4,009 fecal samples tested using multiplex RT-PCR (mRT-PCR), 985 were positive for infection with Gr.A, G-I, and G-II. Out of these 985 cases, 95.3% (n = 939) were under 10 years of age. Gr.A, G-I, and G-II showed high infection rates in patients under 10 years of age. Student's t-test showed a significant correlation between the detection rate of Gr.A and the relative humidity. The detection rate of G-II significantly correlated with wind-chill temperature. Conclusion: Climate factors differentially modulate rotavirus and norovirus infection patterns. These observations provide novel insights into the seasonal impact on the pathogenesis of Gr.A, G-I, and G-II.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

• Journal of Life Science
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• v.22 no.12
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• pp.1644-1650
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• 2012

The aim of this study was to screen the polymorphisms and distribution of each genotype of insertion/ deletion (indel) markers which were found in a preliminary comparative study of bovine genomic sequence databases. Comparative bioinformatic analyses were first performed between the nucleotide sequences of Bovine Genome Project and those of expressed sequence tag (EST) database, and a total of fifty-one species of indel markers were screened. Of these, forty-two indel markers were evaluated, and nine informative indel markers were ultimately selected for population analysis. Nucleotide sequences of each marker were re-sequenced and their polymorphic patterns were typed in six cattle breeds: Holstein, Angus, Charolais, Hereford, and two Korean native cattle breeds (Hanwoo and Jeju Black cattle). Cattle breeds tested in this study showed polymorphic patterns in eight indel markers but not in the Indel-15 marker in Charolais and Holstein. The results of analysis for Jeju Black cattle (JBC) population indicated an observed heterozygosity (Ho) that was highest in HW_G1 (0.600) and the lowest in Indel_29 (0.274). The PIC value was the highest in HW_G4 (0.373) and lowest in Indel_6 (0.305). These polymorphic indel markers will be useful in supplying genetic information for parentage tests and traceability and to develop a molecular breeding system for improvement of animal production in cattle breeds as well as in the JBC population.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.922-929
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• 2019

Objective: Mutations in low-density lipoprotein receptor (LDLR), which encodes a critical protein for cholesterol homeostasis and lipid metabolism in mammals, are involved in cardiometabolic diseases, such as familial hypercholesterolemia in pigs. Whereas microRNAs (miRNAs) can control LDLR regulation, their involvement in circulating cholesterol and lipid levels with respect to cardiometabolic diseases in pigs is unclear. We aimed to identify and analyze LDLR as a potential target gene of SSC-miR-20a. Methods: Bioinformatic analysis predicted that porcine LDLR is a target of SSC-miR-20a. Wild-type and mutant LDLR 3'-untranslated region (UTR) fragments were generated by polymerase chain reaction (PCR) and cloned into the pGL3-Control vector to construct pGL3 Control LDLR wild-3'-UTR and pGL3 Control LDLR mutant-3'-UTR recombinant plasmids, respectively. An miR-20a expression plasmid was constructed by inserting the porcine premiR-20a-coding sequence between the HindIII and BamHI sites in pMR-mCherry, and constructs were confirmed by sequencing. HEK293T cells were co-transfected with the miR-20a expression or pMR-mCherry control plasmids and constructs harboring the corresponding 3'-UTR, and relative luciferase activity was determined. The relative expression levels of miR-20a and LDLR mRNA and their correlation in terms of expression levels in porcine liver tissue were analyzed using reverse-transcription quantitative PCR. Results: Gel electrophoresis and sequencing showed that target gene fragments were successfully cloned, and the three recombinant vectors were successfully constructed. Compared to pMR-mCherry, the miR-20a expression vector significantly inhibited wild-type LDLR3'-UTR-driven (p<0.01), but not mutant LDLR-3'-UTR-driven (p>0.05), luciferase reporter activity. Further, miR-20a and LDLR were expressed at relatively high levels in porcine liver tissues. Pearson correlation analysis revealed that porcine liver miR-20a and LDLR levels were significantly negatively correlated (r = -0.656, p<0.05). Conclusion: LDLR is a potential target of miR-20a, which might directly bind the LDLR 3'-UTR to post-transcriptionally inhibit expression. These results have implications in understanding the pathogenesis and progression of porcine cardiovascular diseases.