Jungwook Roh’s research while affiliated with Cheongju National University of Education and other places

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Publications (7)


Figure 1. H19 expression levels and effects of H19 on cell viability and migration. (A) Relative mRNA expression levels of H19 in A172 and U87MG cells were quantified by RT-qPCR. (B) Cell counting assays determined the short-term effects of H19 expression levels on glioma cell lines. (C) Colony formation assays determined the long-term effects of H19 expression levels on glioma cell lines. (D) Wound-healing assays determined the motility of H19 expression levels on glioma cell lines. (*p<0.05, **p<0.01, ***p<0.001). NC: Negative control; si-Cont: scrambled siRNA as control; H19-KD: H19-knockdown; H19-OE: H19-overexpression.
Figure 2. Common DEGs in the two glioma cell lines regulated by H19. (A) A total of 242 DEGs were down-regulated by ≤-1.5 log 2 fold change in H19-KD group, while 319 DEGs were up-regulated by ≥1.5 log 2 fold change. (B) A total of 875 DEGs were up-regulated by ≥1.5 log 2 fold change in H19-OE group, while 648 DEGs were down-regulated by ≤-1.5 log 2 fold change. (C) A total of 613 protein-coding genes, showing a positive correlation with H19 expression, were expected to be oncogenes. (D) A total of 766 protein-coding genes, showing a negative correlation with H19 expression, were expected to be tumor-suppressive genes. DEG: Differentially expressed gene; H19-KD: H19-knockdown; H19-OE: H19-overexpression.
Figure 3. Functional analyses performed on selected DEGs. (A) The results of GO enrichment analyses highlighted the most enriched GO terms of DEGs putatively promoting tumorigenesis. (B) KEGG pathway enrichment analyses showed the most enriched pathways of DEGs putatively promoting tumorigenesis. (C) GO enrichment analyses displayed the most enriched terms of DEGs presumed to suppress tumorigenesis. (D) KEGG pathway enrichment analyses presented the most enriched pathways of DEGs presumed to suppress tumorigenesis. The color gradient in the KEGG pathway analysis results indicated p-values. DEG: Differentially expressed gene; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genome.
Gene Expression Profiling Regulated by lncRNA H19 Using Bioinformatic Analyses in Glioma Cell Lines
  • Article
  • Full-text available

October 2024

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14 Reads

Cancer Genomics & Proteomics

YEONSOO CHAE

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JUNGWOOK ROH

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MIJUNG IM

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[...]

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WANYEON KIM

Background/Aim Glioma, the most common type of primary brain tumor, is characterized by high malignancy, recurrence, and mortality. Long non-coding RNA (lncRNA) H19 is a potential biomarker for glioma diagnosis and treatment due to its overexpression in human glioma tissues and its involvement in cell division and metastasis regulation. This study aimed to identify potential therapeutic targets involved in glioma development by analyzing gene expression profiles regulated by H19. Materials and Methods To elucidate the role of H19 in A172 and U87MG glioma cell lines, cell counting, colony formation, and wound healing assays were conducted. RNA-seq data analysis and bioinformatics analyses were performed to reveal the molecular interactions of H19. Results Cell-based experiments showed that elevated H19 levels were related to cancer cell survival, proliferation, and migration. Bioinformatics analyses identified 2,084 differentially expressed genes (DEGs) influenced by H19 which are involved in cancer progression. Specifically, ANXA5, CLEC18B, RAB42, CXCL8, OASL, USP18, and CDCP1 were positively correlated with H19 expression, while CSDC2 and FOXO4 were negatively correlated. These DEGs were predicted to function as oncogenes or tumor suppressors in gliomas, in association with H19. Conclusion These findings highlight H19 and its associated genes as potential diagnostic and therapeutic targets for gliomas, emphasizing their clinical significance in patient survival.

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The effects of MALAT1 on relative expression level and cell viability in NSCLC cell lines. (A) Relative expression levels of MALAT1 in normal lung cell line (MRC5) and NSCLC cell lines (H460, A549, H1299) were quantified by RT-qPCR. (B) Relative expression levels of MALAT1 in the control groups and si-MALAT1 treatment groups were quantified by RT-qPCR. (C) Short-term effects of MALAT1 knockdown on NSCLC cell viability were determined by a cell counting assay. The number of viable cells was compared with control groups. (D) Long-term effects of MALAT1 knockdown on NSCLC cell viability were determined by a colony formation assay. Quantitative analyses of the number of NSCLC cell clones were performed with Image J. *p < 0.05
The effects of MALAT1 on cell motility in NSCLC cell lines. (A) The effects of MALAT1 knockdown on NSCLC cell migration were assessed by a wound healing assay. The graph shows the percentage of covered areas in si-MALAT1 groups compared to control groups. (B) The effects of MALAT1 knockdown on NSCLC cell invasion were assessed by a Transwell invasion assay. The number of invaded cells was compared with control groups. *p < 0.05
DEGs, GO enrichment, and KEGG pathway enrichment analyses in NSCLC cell lines after MALAT1 knockdown. (A) Venn Diagram represents the overlapped upregulated DEGs (log2 fold change ≥ 1.5). (B) Venn Diagram represents the overlapped downregulated DEGs (log2 fold change ≤ -1.5). (C) GO enrichment analysis of the upregulated DEGs shows the abundant terms based on p < 0.05 in the top ranking. (D) KEGG pathway enrichment analysis is shown for the upregulated DEGs. The color gradient from blue to red indicates p-value. (E) GO enrichment analysis of the downregulated DEGs shows the abundant terms based on p < 0.05 in the top ranking. (F) KEGG pathway enrichment analysis is shown for the downregulated DEGs. The color gradient from blue to red indicates p-value
The results of survival analysis of five selected DEGs. (A) PGAM1 (p = 0.002), (B) PGAM4 (p = 0.008), (C) NOL6 (p = 0.04), (D) NAP1L5 (p = 0.01), and (E) SESN1 (p = 0.01). Survival analysis in NSCLC patients was performed using the OncoLnc database
The results of gene expression analysis of five selected DEGs. (A) PGAM1 (p = 4.64e-06), (B) PGAM4 (p = 1.12e-02), (C) NOL6 (p = 1.81e-05), (D) NAP1L5 (p = 3.79e-05), and (E) SESN1 (p = 1.19e-09). Gene expression analysis between NSCLC tissues and adjacent normal tissues was analyzed using the TNMplot database
MALAT1-regulated gene expression profiling in lung cancer cell lines

September 2023

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49 Reads

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9 Citations

BMC Cancer

Background Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and has a poor prognosis. Identifying biomarkers based on molecular mechanisms is critical for early diagnosis, timely treatment, and improved prognosis of lung cancer. MALAT1 has been reported to have overexpressed and tumor-promoting functions in NSCLC. It has been proposed as a potential biomarker for the diagnosis and prognosis of cancer. Therefore, this study was conducted to profile the changes in gene expression according to the regulation of expression of MALAT1 in NSCLC cell lines and to investigate the correlation through bioinformatic analysis of differentially expressed genes (DEGs). Methods MALAT1 expression levels were measured using RT-qPCR. The biological functions of MALAT1 in NSCLC were analyzed by cell counting, colony forming, wound-healing, and Transwell invasion assays. In addition, gene expression profiling in response to the knockdown of MALAT1 was analyzed by transcriptome sequencing, and differentially expressed genes regulated by MALAT1 were performed by GO and KEGG pathway enrichment analyses. Bioinformatic databases were used for gene expression analysis and overall survival analysis. Results Comparative analysis versus MALAT1 expression in MRC5 cells (a normal lung cell line) and the three NSCLC cell lines showed that MALAT1 expression was significantly higher in the NSCLC cells. MALAT1 knockdown decreased cell survival, proliferation, migration, and invasion in all three NSCLC cell lines. RNA-seq analysis of DEGs in NSCLC cells showed 198 DEGs were upregulated and 266 DEGs downregulated by MALAT1 knockdown in all three NSCLC cell lines. Survival analysis on these common DEGs performed using the OncoLnc database resulted in the selection of five DEGs, phosphoglycerate mutase 1 (PGAM1), phosphoglycerate mutase 4 (PGAM4), nucleolar protein 6 (NOL6), nucleosome assembly protein 1 like 5 (NAP1L5), and sestrin1 (SESN1). The gene expression levels of these selected DEGs were proved to gene expression analysis using the TNMplot database. Conclusion MALAT1 might function as an oncogene that enhances NSCLC cell survival, proliferation, colony formation, and invasion. RNA-seq and bioinformatic analyses resulted in the selection of five DEGs, PGAM1, PGAM4, NOL6, NAP1L5, and SESN1, which were found to be closely related to patient survival and tumorigenesis. We believe that further investigation of these five DEGs will provide valuable information on the oncogenic role of MALAT1 in NSCLC.


Figure 2. Therapeutic strategies targeting lncRNAs. Downregulation of risky lncRNAs such as AL606760.2 (Li et al. 2021), H19 (Chen et al. 2020), PVT1 (Chen et al. 2020), MALAT1 (Xiong et al. 2018), and SBF2-AS1 (Zhang et al. 2021) and upregulation of protective lncRNAs such as AC068643.1 (Huang et al. 2020), AC079228.1 (Li et al. 2021), FAM13A-AS1 (Li et al. 2021), HAR1A (Chen et al. 2020), DGCR5 (He et al. 2020), and WDFY3-AS2 (Wu et al. 2018) might help predict prognosis in glioma.
Long non-coding RNA in glioma: novel genetic players in temozolomide resistance

February 2023

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45 Reads

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15 Citations

Glioma is the most common primary malignant brain tumor in adults and accounts for approximately 80% of brain and central nervous system tumors. In 2021, the World Health Organization (WHO) published a new taxonomy for glioma based on its histological features and molecular alterations. Isocitrate dehydrogenase (IDH) catalyzes the decarboxylation of isocitrate, a critical metabolic reaction in energy generation in cells. Mutations in the IDH genes interrupt cell differentiation and serve as molecular biomarkers that can be used to classify gliomas. For example, the mutant IDH is widely detected in low-grade gliomas, whereas the wild type is in high-grade ones, including glioblastomas. Long non-coding RNAs (lncRNAs) are epigenetically involved in gene expression and contribute to glioma development. To investigate the potential use of lncRNAs as biomarkers, we examined lncRNA dysregulation dependent on the IDH mutation status. We found that several lncRNAs, namely, AL606760.2, H19, MALAT1, PVT1 and SBF2-AS1 may function as glioma risk factors, whereas AC068643.1, AC079228.1, DGCR5, FAM13A-AS1, HAR1A and WDFY3-AS2 may have protective effects. Notably, H19, MALAT1, PVT1, and SBF2-AS1 have been associated with temozolomide resistance in glioma patients. This review study suggests that targeting glioma-associated lncRNAs might aid the treatment of glioma.


LncRNAs regulate transporters related to glutamine metabolism.
LncRNAs regulate enzymes related to glutamine metabolism.
The Involvement of Long Non-Coding RNAs in Glutamine-Metabolic Reprogramming and Therapeutic Resistance in Cancer

November 2022

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21 Reads

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8 Citations

International Journal of Molecular Sciences

Metabolic alterations that support the supply of biosynthetic molecules necessary for rapid and sustained proliferation are characteristic of cancer. Some cancer cells rely on glutamine to maintain their energy requirements for growth. Glutamine is an important metabolite in cells because it not only links to the tricarboxylic acid cycle by producing α-ketoglutarate by glutaminase and glutamate dehydrogenase but also supplies other non-essential amino acids, fatty acids, and components of nucleotide synthesis. Altered glutamine metabolism is associated with cancer cell survival, proliferation, metastasis, and aggression. Furthermore, altered glutamine metabolism is known to be involved in therapeutic resistance. In recent studies, lncRNAs were shown to act on amino acid transporters and glutamine-metabolic enzymes, resulting in the regulation of glutamine metabolism. The lncRNAs involved in the expression of the transporters include the abhydrolase domain containing 11 antisense RNA 1, LINC00857, plasmacytoma variant translocation 1, Myc-induced long non-coding RNA, and opa interacting protein 5 antisense RNA 1, all of which play oncogenic roles. When it comes to the regulation of glutamine-metabolic enzymes, several lncRNAs, including nuclear paraspeckle assembly transcript 1, XLOC_006390, urothelial cancer associated 1, and thymopoietin antisense RNA 1, show oncogenic activities, and others such as antisense lncRNA of glutaminase, lincRNA-p21, and ataxin 8 opposite strand serve as tumor suppressors. In addition, glutamine-dependent cancer cells with lncRNA dysregulation promote cell survival, proliferation, and metastasis by increasing chemo- and radio-resistance. Therefore, understanding the roles of lncRNAs in glutamine metabolism will be helpful for the establishment of therapeutic strategies for glutamine-dependent cancer patients.


Gene expression profiling after LINC00472 overexpression in an NSCLC cell line

August 2021

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13 Reads

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9 Citations

Cancer biomarkers: section A of Disease markers

Lung cancer accounts for a large proportion of cancer-related deaths worldwide. Personalized therapeutic medicine based on the genetic characteristics of non-small cell lung cancer (NSCLC) is a promising field, and discovering clinically applicable biomarkers of NSCLC is required. LINC00472 is a long non-coding RNA and has been recently suggested to be a biomarker of NSCLC, but little is known of its mechanism in NSCLC. Thus, the current study was performed to document changes in gene expression after LINC00472 overexpression in NSCLC cells. As a result of cell viability and migration assay, LINC00472 downregulated cell survival, proliferation, and motility. Transcriptome sequencing analysis showed 3,782 genes expression were changed in LINC00472 overexpressing cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed most genes were associated with intracellular metabolism. The PPP1R12B, RGS5, RBM5, RBL2, LDLR and PTPRM genes were upregulated by LINC00472 overexpression and these genes functioned as tumor suppressors in several cancers. In contrast, SPSB1, PCNA, CD24, CDK5, CDC25A, and EIF4EBP1 were downregulated by LINC00472, and they functioned as oncogenes in various cancers. Consequently, the function of LINC00472 in tumorigenesis might be related to changes in the expressions of other oncogenes and tumor suppressors.


Oncogenic lncRNAs upregulated in glioma.
Tumor-suppressive lncRNAs downregulated in glioma.
The Roles Played by Long Non-Coding RNAs in Glioma Resistance

June 2021

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30 Reads

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21 Citations

International Journal of Molecular Sciences

Glioma originates in the central nervous system and is classified based on both histological features and molecular genetic characteristics. Long non-coding RNAs (lncRNAs) are longer than 200 nucleotides and are known to regulate tumorigenesis and tumor progression, and even confer therapeutic resistance to glioma cells. Since oncogenic lncRNAs have been frequently upregulated to promote cell proliferation, migration, and invasion in glioma cells, while tumor-suppressive lncRNAs responsible for the inhibition of apoptosis and decrease in therapeutic sensitivity in glioma cells have been generally downregulated, the dysregulation of lncRNAs affects many features of glioma patients, and the expression profiles associated with these lncRNAs are needed to diagnose the disease stage and to determine suitable therapeutic strategies. Accumulating studies show that the orchestrations of oncogenic lncRNAs and tumor-suppressive lncRNAs in glioma cells result in signaling pathways that influence the pathogenesis and progression of glioma. Furthermore, several lncRNAs are related to the regulation of therapeutic sensitivity in existing anticancer therapies, including radiotherapy, chemotherapy and immunotherapy. Consequently, we undertook this review to improve the understanding of signaling pathways influenced by lncRNAs in glioma and how lncRNAs affect therapeutic resistance.

Citations (6)


... However, they have also been reported to act as competitive endogenous RNAs (ceRNAs) in the cytoplasm, to function as miRNA sponges, and to regulate mRNA expressions (13,15,16). In addition, lncRNAs contribute significantly to cancer development by regulating major signaling pathways, such as NF-ĸB, p53, Notch, and PI3K/AKT (17,18). Dysregulation of lncRNAs is closely associated with tumor progression, metastasis, and metabolic reprogramming (19)(20)(21). ...

Reference:

Gene Expression Profiling Regulated by lncRNA H19 Using Bioinformatic Analyses in Glioma Cell Lines
Hippo-YAP/TAZ pathway regulation: the crucial roles of lncRNAs in cancer
  • Citing Article
  • November 2023

... NOL6 is a protein-coding gene widely distributed in the nucleolus of eukaryotic cells. Previous studies have shown that NOL6 can be considered as a pro-oncogenic molecule in endometrial, breast, gastric, and lung cancers, acting as a promoter of cellular proliferation and migration and inhibitor of apoptosis in their progression [24][25][26][27]. ...

MALAT1-regulated gene expression profiling in lung cancer cell lines

BMC Cancer

... Previous studies have reported that dysregulated PD-1 (Smyth et al. 2021), p53 (Ohashi et al. 2015), and lncRNA SNHG16 (Ren et al. 2022) participated in the carcinogenesis of the esophagus. LncRNA is one type of non-coding RNA with lengths of more than 200 nucleotides and plays critical roles in carcinogenesis (Chen, Wang, et al. 2022;Nair et al. 2020;Roh et al. 2023). A lot of lncRNAs played crucial roles in ESCC. ...

Long non-coding RNA in glioma: novel genetic players in temozolomide resistance

... Higher levels of the protein are associated with a better prognosis, as confirmed by the enhancement of the malignant tumor phenotype following the knockdown of GOT1 [83]. Alterations of glutamine metabolism are involved in cancer cell survival, proliferation, metastasis, and aggression, with Long Non-Coding RNAs playing a role in modulating the enzymes involved, including GOT1, and contributing to the chemo-and radio-resistance of the tumor [84]. ...

The Involvement of Long Non-Coding RNAs in Glutamine-Metabolic Reprogramming and Therapeutic Resistance in Cancer

International Journal of Molecular Sciences

... vector, and incubated in the same conditions as cell culture in a humidified incubator for 7 days. Resulting colonies were washed twice with PBS (WELGENE), fixed with 50% methanol, and stained with 0.5% crystal violet (Sigma, St. Louis, MO, USA) (40). Colonies containing more than 50 cells were then imaged and scored as survivors to assess long-term cell viability. ...

Gene expression profiling after LINC00472 overexpression in an NSCLC cell line
  • Citing Article
  • August 2021

Cancer biomarkers: section A of Disease markers

... In addition, lncRNAs contribute significantly to cancer development by regulating major signaling pathways, such as NF-ĸB, p53, Notch, and PI3K/AKT (17,18). Dysregulation of lncRNAs is closely associated with tumor progression, metastasis, and metabolic reprogramming (19)(20)(21). ...

The Roles Played by Long Non-Coding RNAs in Glioma Resistance

International Journal of Molecular Sciences