Literature DB >> 35195779

DNA methylation marker to estimate ovarian cancer cell fraction.

Takahiro Ebata1, Satoshi Yamashita1, Hideyuki Takeshima1, Hiroshi Yoshida2, Yoshiko Kawata3, Nao Kino3, Toshiharu Yasugi3, Yasuhisa Terao4, Kan Yonemori5, Tomoyasu Kato6, Toshikazu Ushijima7.   

Abstract

Evaluation of a cancer cell fraction is important for accurate molecular analysis, and pathological analysis is the gold standard for evaluation. Despite the potential convenience, no established molecular markers for evaluation are available. In this study, we aimed to identify ovarian cancer cell fraction markers using DNA methylation highly specific to ovarian cancer cells. Using genome-wide DNA methylation data, we screened candidate marker genes methylated in 30 ovarian cancer FFPE samples and 12 high-grade serous ovarian cancer cell lines, and unmethylated in two female leucocytes and two normal fallopian epithelial cell samples. Methylation levels of two genes, SIM1, and ZNF154, showed high correlation with pathological cancer cell fractions among the 30 ovarian cancer FFPE samples (R = 0.61 for SIM1, 0.71 for ZNF154). For cost-effective analysis of FFPE samples, pyrosequencing primers were designed, and successfully established for SIM1 and ZNF154. Correlation between a pathological cancer cell fraction and methylation levels obtained by pyrosequencing was confirmed to be high (R = 0.53 for SIM1, 0.64 for ZNF154). Finally, an independent validation cohort of 29 ovarian cancer FFPE samples was analyzed. ZNF154 methylation showed a high correlation with the pathological cancer cell fraction (R = 0.77, P < 0.0001). Therefore, the ZNF154 methylation level was considered to be useful for the estimation of ovarian cancer cell fraction, and is expected to help accurate molecular analysis.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Biomarker; DNA methylation; Epigenetic; Serous ovarian cancer

Mesh:

Substances:

Year:  2022        PMID: 35195779     DOI: 10.1007/s12032-022-01679-y

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.064


  18 in total

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Authors:  Hiroki Ishihara; Satoshi Yamashita; Satoshi Fujii; Kazunari Tanabe; Hirofumi Mukai; Toshikazu Ushijima
Journal:  Med Oncol       Date:  2018-09-14       Impact factor: 3.064

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Authors:  Panagiotis A Konstantinopoulos; Raphael Ceccaldi; Geoffrey I Shapiro; Alan D D'Andrea
Journal:  Cancer Discov       Date:  2015-10-13       Impact factor: 39.397

Review 3.  Clinical cancer genomic profiling.

Authors:  Debyani Chakravarty; David B Solit
Journal:  Nat Rev Genet       Date:  2021-03-24       Impact factor: 53.242

4.  Epigenetic profiling to classify cancer of unknown primary: a multicentre, retrospective analysis.

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Journal:  Lancet Oncol       Date:  2016-08-27       Impact factor: 41.316

5.  Pancreatic Cancer Cell Fraction Estimation in a DNA Sample.

Authors:  Hiroki Ishihara; Satoshi Yamashita; Ryosuke Amano; Kenjiro Kimura; Kosei Hirakawa; Takako Ueda; Yoshiki Murakami; Akihiro Tamori; Kazunari Tanabe; Norifumi Kawada; Atsushi Hagihara; Toshikazu Ushijima
Journal:  Oncology       Date:  2018-08-27       Impact factor: 2.935

6.  Influence of degree of DNA degradation in formalin-fixed and paraffin-embedded tissue samples on accuracy of genome-wide DNA methylation analysis.

Authors:  Sho Ueda; Satoshi Yamashita; Shun-Ichi Watanabe; Mika Wakabayashi; Noriko Motoi; Masayuki Noguchi; Shigeki Sekine; Yukio Sato; Toshikazu Ushijima
Journal:  Epigenomics       Date:  2021-04-06       Impact factor: 4.778

7.  Estimation of the fraction of cancer cells in a tumor DNA sample using DNA methylation.

Authors:  Takamasa Takahashi; Yasunori Matsuda; Satoshi Yamashita; Naoko Hattori; Ryoji Kushima; Yi-Chia Lee; Hiroyasu Igaki; Yuji Tachimori; Masato Nagino; Toshikazu Ushijima
Journal:  PLoS One       Date:  2013-12-02       Impact factor: 3.240

8.  A Landscape of Pharmacogenomic Interactions in Cancer.

Authors:  Francesco Iorio; Theo A Knijnenburg; Daniel J Vis; Graham R Bignell; Michael P Menden; Michael Schubert; Nanne Aben; Emanuel Gonçalves; Syd Barthorpe; Howard Lightfoot; Thomas Cokelaer; Patricia Greninger; Ewald van Dyk; Han Chang; Heshani de Silva; Holger Heyn; Xianming Deng; Regina K Egan; Qingsong Liu; Tatiana Mironenko; Xeni Mitropoulos; Laura Richardson; Jinhua Wang; Tinghu Zhang; Sebastian Moran; Sergi Sayols; Maryam Soleimani; David Tamborero; Nuria Lopez-Bigas; Petra Ross-Macdonald; Manel Esteller; Nathanael S Gray; Daniel A Haber; Michael R Stratton; Cyril H Benes; Lodewyk F A Wessels; Julio Saez-Rodriguez; Ultan McDermott; Mathew J Garnett
Journal:  Cell       Date:  2016-07-07       Impact factor: 41.582

9.  A comprehensive analysis of 195 DNA methylomes reveals shared and cell-specific features of partially methylated domains.

Authors:  Abdulrahman Salhab; Karl Nordström; Gilles Gasparoni; Kathrin Kattler; Peter Ebert; Fidel Ramirez; Laura Arrigoni; Fabian Müller; Julia K Polansky; Cristina Cadenas; Jan G Hengstler; Thomas Lengauer; Thomas Manke; Jörn Walter
Journal:  Genome Biol       Date:  2018-09-28       Impact factor: 13.583

10.  Genome-Wide DNA Methylation Pattern in Whole Blood Associated With Primary Intracerebral Hemorrhage.

Authors:  Yupeng Zhang; Hongyu Long; Sai Wang; Wenbiao Xiao; Meishan Xiong; Jianyi Liu; Lei Chen; Ruijuan Chen; Xueli Wei; Yi Shu; Yi Zeng; Le Zhang
Journal:  Front Immunol       Date:  2021-08-13       Impact factor: 7.561

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