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Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis

Hepatocellular carcinoma is recognized as one of the most frequently occurring malignant types of liver cancer globally, making the identification of biomarkers critically important. The aim of the present study was to identify the genes involved in the anticancer effects of flavonoid compounds so t...

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Autores principales: Kim, Seong Min, Rampogu, Shailima, Vetrivel, Preethi, Kulkarni, Apoorva M., Ha, Sang Eun, Kim, Hun Hwan, Lee, Keun Woo, Kim, Gon Sup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7968004/
https://www.ncbi.nlm.nih.gov/pubmed/33747212
http://dx.doi.org/10.3892/ol.2021.12616
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author Kim, Seong Min
Rampogu, Shailima
Vetrivel, Preethi
Kulkarni, Apoorva M.
Ha, Sang Eun
Kim, Hun Hwan
Lee, Keun Woo
Kim, Gon Sup
author_facet Kim, Seong Min
Rampogu, Shailima
Vetrivel, Preethi
Kulkarni, Apoorva M.
Ha, Sang Eun
Kim, Hun Hwan
Lee, Keun Woo
Kim, Gon Sup
author_sort Kim, Seong Min
collection PubMed
description Hepatocellular carcinoma is recognized as one of the most frequently occurring malignant types of liver cancer globally, making the identification of biomarkers critically important. The aim of the present study was to identify the genes involved in the anticancer effects of flavonoid compounds so that they may be used as targets for cancer treatment. Sinensetin (SIN), an isolated polymethoxyflavone monomer compound, possesses broad antitumor activities in vitro. Therefore, the identification of a transcriptome profile on the condition of cells treated with SIN may aid to better understand the genes involved and its mechanism of action. Genomic profiling studies of cancer are increasing rapidly in order to provide gene expression data that can reveal prognostic biomarkers to combat liver cancer. In the present study, high-throughput RNA sequencing (RNA-seq) was performed to reveal differential gene expression patterns between SIN-treated and SIN-untreated human liver cancer HepG2 cells. A total of 43 genes were identified to be differentially expressed (39 downregulated and 4 upregulated in the SIN-treated group compared with the SIN-untreated group). An extensive network analysis for these 43 genes resulted in the identification of 10 upregulated highly interconnected hub genes that contributed to the progression of cancer. Functional enrichment analysis of these 10 hub genes revealed their involvement in the regulation of apoptotic processes, immune response and tumor necrosis factor production. Additionally, the mRNA expression levels of these 10 genes were evaluated using reverse transcription-quantitative PCR, and the results were consistent with the RNA-seq data. Overall, the results of the present study revealed differentially expressed genes involved in cancer after SIN treatment in HepG2 cells and may help to develop strategies targeting these genes for treating liver cancer.
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spelling pubmed-79680042021-03-19 Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis Kim, Seong Min Rampogu, Shailima Vetrivel, Preethi Kulkarni, Apoorva M. Ha, Sang Eun Kim, Hun Hwan Lee, Keun Woo Kim, Gon Sup Oncol Lett Articles Hepatocellular carcinoma is recognized as one of the most frequently occurring malignant types of liver cancer globally, making the identification of biomarkers critically important. The aim of the present study was to identify the genes involved in the anticancer effects of flavonoid compounds so that they may be used as targets for cancer treatment. Sinensetin (SIN), an isolated polymethoxyflavone monomer compound, possesses broad antitumor activities in vitro. Therefore, the identification of a transcriptome profile on the condition of cells treated with SIN may aid to better understand the genes involved and its mechanism of action. Genomic profiling studies of cancer are increasing rapidly in order to provide gene expression data that can reveal prognostic biomarkers to combat liver cancer. In the present study, high-throughput RNA sequencing (RNA-seq) was performed to reveal differential gene expression patterns between SIN-treated and SIN-untreated human liver cancer HepG2 cells. A total of 43 genes were identified to be differentially expressed (39 downregulated and 4 upregulated in the SIN-treated group compared with the SIN-untreated group). An extensive network analysis for these 43 genes resulted in the identification of 10 upregulated highly interconnected hub genes that contributed to the progression of cancer. Functional enrichment analysis of these 10 hub genes revealed their involvement in the regulation of apoptotic processes, immune response and tumor necrosis factor production. Additionally, the mRNA expression levels of these 10 genes were evaluated using reverse transcription-quantitative PCR, and the results were consistent with the RNA-seq data. Overall, the results of the present study revealed differentially expressed genes involved in cancer after SIN treatment in HepG2 cells and may help to develop strategies targeting these genes for treating liver cancer. D.A. Spandidos 2021-05 2021-03-04 /pmc/articles/PMC7968004/ /pubmed/33747212 http://dx.doi.org/10.3892/ol.2021.12616 Text en Copyright: © Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Kim, Seong Min
Rampogu, Shailima
Vetrivel, Preethi
Kulkarni, Apoorva M.
Ha, Sang Eun
Kim, Hun Hwan
Lee, Keun Woo
Kim, Gon Sup
Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis
title Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis
title_full Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis
title_fullStr Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis
title_full_unstemmed Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis
title_short Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis
title_sort transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7968004/
https://www.ncbi.nlm.nih.gov/pubmed/33747212
http://dx.doi.org/10.3892/ol.2021.12616
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