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Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets
Although hepatoblastoma is the most common pediatric liver cancer, its genetic heterogeneity and therapeutic targets are not well elucidated. Therefore, we conducted a multiomics analysis, including mutatome, DNA methylome, and transcriptome analyses, of 59 hepatoblastoma samples. Based on DNA methy...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341754/ https://www.ncbi.nlm.nih.gov/pubmed/32656360 http://dx.doi.org/10.1038/s41698-020-0125-y |
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author | Sekiguchi, Masahiro Seki, Masafumi Kawai, Tomoko Yoshida, Kenichi Yoshida, Misa Isobe, Tomoya Hoshino, Noriko Shirai, Ryota Tanaka, Mio Souzaki, Ryota Watanabe, Kentaro Arakawa, Yuki Nannya, Yasuhito Suzuki, Hiromichi Fujii, Yoichi Kataoka, Keisuke Shiraishi, Yuichi Chiba, Kenichi Tanaka, Hiroko Shimamura, Teppei Sato, Yusuke Sato-Otsubo, Aiko Kimura, Shunsuke Kubota, Yasuo Hiwatari, Mitsuteru Koh, Katsuyoshi Hayashi, Yasuhide Kanamori, Yutaka Kasahara, Mureo Kohashi, Kenichi Kato, Motohiro Yoshioka, Takako Matsumoto, Kimikazu Oka, Akira Taguchi, Tomoaki Sanada, Masashi Tanaka, Yukichi Miyano, Satoru Hata, Kenichiro Ogawa, Seishi Takita, Junko |
author_facet | Sekiguchi, Masahiro Seki, Masafumi Kawai, Tomoko Yoshida, Kenichi Yoshida, Misa Isobe, Tomoya Hoshino, Noriko Shirai, Ryota Tanaka, Mio Souzaki, Ryota Watanabe, Kentaro Arakawa, Yuki Nannya, Yasuhito Suzuki, Hiromichi Fujii, Yoichi Kataoka, Keisuke Shiraishi, Yuichi Chiba, Kenichi Tanaka, Hiroko Shimamura, Teppei Sato, Yusuke Sato-Otsubo, Aiko Kimura, Shunsuke Kubota, Yasuo Hiwatari, Mitsuteru Koh, Katsuyoshi Hayashi, Yasuhide Kanamori, Yutaka Kasahara, Mureo Kohashi, Kenichi Kato, Motohiro Yoshioka, Takako Matsumoto, Kimikazu Oka, Akira Taguchi, Tomoaki Sanada, Masashi Tanaka, Yukichi Miyano, Satoru Hata, Kenichiro Ogawa, Seishi Takita, Junko |
author_sort | Sekiguchi, Masahiro |
collection | PubMed |
description | Although hepatoblastoma is the most common pediatric liver cancer, its genetic heterogeneity and therapeutic targets are not well elucidated. Therefore, we conducted a multiomics analysis, including mutatome, DNA methylome, and transcriptome analyses, of 59 hepatoblastoma samples. Based on DNA methylation patterns, hepatoblastoma was classified into three clusters exhibiting remarkable correlation with clinical, histological, and genetic features. Cluster F was largely composed of cases with fetal histology and good outcomes, whereas clusters E1 and E2 corresponded primarily to embryonal/combined histology and poor outcomes. E1 and E2, albeit distinguishable by different patient age distributions, were genetically characterized by hypermethylation of the HNF4A/CEBPA-binding regions, fetal liver-like expression patterns, upregulation of the cell cycle pathway, and overexpression of NQO1 and ODC1. Inhibition of NQO1 and ODC1 in hepatoblastoma cells induced chemosensitization and growth suppression, respectively. Our results provide a comprehensive description of the molecular basis of hepatoblastoma and rational therapeutic strategies for high-risk cases. |
format | Online Article Text |
id | pubmed-7341754 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73417542020-07-09 Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets Sekiguchi, Masahiro Seki, Masafumi Kawai, Tomoko Yoshida, Kenichi Yoshida, Misa Isobe, Tomoya Hoshino, Noriko Shirai, Ryota Tanaka, Mio Souzaki, Ryota Watanabe, Kentaro Arakawa, Yuki Nannya, Yasuhito Suzuki, Hiromichi Fujii, Yoichi Kataoka, Keisuke Shiraishi, Yuichi Chiba, Kenichi Tanaka, Hiroko Shimamura, Teppei Sato, Yusuke Sato-Otsubo, Aiko Kimura, Shunsuke Kubota, Yasuo Hiwatari, Mitsuteru Koh, Katsuyoshi Hayashi, Yasuhide Kanamori, Yutaka Kasahara, Mureo Kohashi, Kenichi Kato, Motohiro Yoshioka, Takako Matsumoto, Kimikazu Oka, Akira Taguchi, Tomoaki Sanada, Masashi Tanaka, Yukichi Miyano, Satoru Hata, Kenichiro Ogawa, Seishi Takita, Junko NPJ Precis Oncol Article Although hepatoblastoma is the most common pediatric liver cancer, its genetic heterogeneity and therapeutic targets are not well elucidated. Therefore, we conducted a multiomics analysis, including mutatome, DNA methylome, and transcriptome analyses, of 59 hepatoblastoma samples. Based on DNA methylation patterns, hepatoblastoma was classified into three clusters exhibiting remarkable correlation with clinical, histological, and genetic features. Cluster F was largely composed of cases with fetal histology and good outcomes, whereas clusters E1 and E2 corresponded primarily to embryonal/combined histology and poor outcomes. E1 and E2, albeit distinguishable by different patient age distributions, were genetically characterized by hypermethylation of the HNF4A/CEBPA-binding regions, fetal liver-like expression patterns, upregulation of the cell cycle pathway, and overexpression of NQO1 and ODC1. Inhibition of NQO1 and ODC1 in hepatoblastoma cells induced chemosensitization and growth suppression, respectively. Our results provide a comprehensive description of the molecular basis of hepatoblastoma and rational therapeutic strategies for high-risk cases. Nature Publishing Group UK 2020-07-07 /pmc/articles/PMC7341754/ /pubmed/32656360 http://dx.doi.org/10.1038/s41698-020-0125-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Sekiguchi, Masahiro Seki, Masafumi Kawai, Tomoko Yoshida, Kenichi Yoshida, Misa Isobe, Tomoya Hoshino, Noriko Shirai, Ryota Tanaka, Mio Souzaki, Ryota Watanabe, Kentaro Arakawa, Yuki Nannya, Yasuhito Suzuki, Hiromichi Fujii, Yoichi Kataoka, Keisuke Shiraishi, Yuichi Chiba, Kenichi Tanaka, Hiroko Shimamura, Teppei Sato, Yusuke Sato-Otsubo, Aiko Kimura, Shunsuke Kubota, Yasuo Hiwatari, Mitsuteru Koh, Katsuyoshi Hayashi, Yasuhide Kanamori, Yutaka Kasahara, Mureo Kohashi, Kenichi Kato, Motohiro Yoshioka, Takako Matsumoto, Kimikazu Oka, Akira Taguchi, Tomoaki Sanada, Masashi Tanaka, Yukichi Miyano, Satoru Hata, Kenichiro Ogawa, Seishi Takita, Junko Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets |
title | Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets |
title_full | Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets |
title_fullStr | Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets |
title_full_unstemmed | Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets |
title_short | Integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets |
title_sort | integrated multiomics analysis of hepatoblastoma unravels its heterogeneity and provides novel druggable targets |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341754/ https://www.ncbi.nlm.nih.gov/pubmed/32656360 http://dx.doi.org/10.1038/s41698-020-0125-y |
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