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DNA methylation marker to estimate ovarian cancer cell fraction
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...
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| Published in: | Medical oncology (Northwood, London, England) London, England), 2022-05, Vol.39 (5), p.78-78, Article 78 |
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| container_end_page | 78 |
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| container_title | Medical oncology (Northwood, London, England) |
| container_volume | 39 |
| creator | Ebata, Takahiro Yamashita, Satoshi Takeshima, Hideyuki Yoshida, Hiroshi Kawata, Yoshiko Kino, Nao Yasugi, Toshiharu Terao, Yasuhisa Yonemori, Kan Kato, Tomoyasu Ushijima, Toshikazu |
| description | 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
|
| doi_str_mv | 10.1007/s12032-022-01679-y |
| format | article |
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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.</description><identifier>ISSN: 1357-0560</identifier><identifier>EISSN: 1559-131X</identifier><identifier>DOI: 10.1007/s12032-022-01679-y</identifier><identifier>PMID: 35195779</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Biomarkers, Tumor - genetics ; Cell Line, Tumor ; DNA Methylation ; DNA, Neoplasm - genetics ; Female ; Genetic Markers ; Hematology ; Humans ; Internal Medicine ; Kruppel-Like Transcription Factors - genetics ; Medicine ; Medicine & Public Health ; Oncology ; Original Paper ; Ovarian cancer ; Ovarian Neoplasms - genetics ; Ovarian Neoplasms - pathology ; Pathology</subject><ispartof>Medical oncology (Northwood, London, England), 2022-05, Vol.39 (5), p.78-78, Article 78</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022</rights><rights>2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c485t-56de16fe360b51fea6b78b2cbb9f74d352eb327bfcaa70dbde0bbf2bec5c54c3</citedby><cites>FETCH-LOGICAL-c485t-56de16fe360b51fea6b78b2cbb9f74d352eb327bfcaa70dbde0bbf2bec5c54c3</cites><orcidid>0000-0003-3405-7817</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35195779$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ebata, Takahiro</creatorcontrib><creatorcontrib>Yamashita, Satoshi</creatorcontrib><creatorcontrib>Takeshima, Hideyuki</creatorcontrib><creatorcontrib>Yoshida, Hiroshi</creatorcontrib><creatorcontrib>Kawata, Yoshiko</creatorcontrib><creatorcontrib>Kino, Nao</creatorcontrib><creatorcontrib>Yasugi, Toshiharu</creatorcontrib><creatorcontrib>Terao, Yasuhisa</creatorcontrib><creatorcontrib>Yonemori, Kan</creatorcontrib><creatorcontrib>Kato, Tomoyasu</creatorcontrib><creatorcontrib>Ushijima, Toshikazu</creatorcontrib><title>DNA methylation marker to estimate ovarian cancer cell fraction</title><title>Medical oncology (Northwood, London, England)</title><addtitle>Med Oncol</addtitle><addtitle>Med Oncol</addtitle><description>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.</description><subject>Biomarkers, Tumor - genetics</subject><subject>Cell Line, Tumor</subject><subject>DNA Methylation</subject><subject>DNA, Neoplasm - genetics</subject><subject>Female</subject><subject>Genetic Markers</subject><subject>Hematology</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Kruppel-Like Transcription Factors - genetics</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Oncology</subject><subject>Original Paper</subject><subject>Ovarian cancer</subject><subject>Ovarian Neoplasms - genetics</subject><subject>Ovarian Neoplasms - pathology</subject><subject>Pathology</subject><issn>1357-0560</issn><issn>1559-131X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kMtOwzAQRS0EoqXwAyxQJDZsAn7EcbNCVXlKFWy6YGfZzhhS8ih2gpS_x20KSCxYWGNpzty5cxE6JfiSYCyuPKGY0RjT8EgqsrjfQ2PCeRYTRl72w59xEWOe4hE68n6FMSWcZodoxDjJuBDZGF3fPM2iCtq3vlRt0dRRpdw7uKhtIvBtUakWouZTuULVkVG1CS0DZRlZp8yGP0YHVpUeTnZ1gpZ3t8v5Q7x4vn-czxaxSaa8jXmaA0ktsBRrTiyoVIuppkbrzIokZ5yCZlRoa5QSONc5YK0t1WC44YlhE3QxyK5d89EFZ7Iq_MaIqqHpvKQpoySZpkQE9PwPumo6VwdzWwqzKUuyQNGBMq7x3oGVaxeudb0kWG7SlUO6MqQrt-nKPgyd7aQ7XUH-M_IdZwDYAPjQql_B_e7-R_YLGd-GPA</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Ebata, Takahiro</creator><creator>Yamashita, Satoshi</creator><creator>Takeshima, Hideyuki</creator><creator>Yoshida, Hiroshi</creator><creator>Kawata, Yoshiko</creator><creator>Kino, Nao</creator><creator>Yasugi, Toshiharu</creator><creator>Terao, Yasuhisa</creator><creator>Yonemori, Kan</creator><creator>Kato, Tomoyasu</creator><creator>Ushijima, Toshikazu</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-3405-7817</orcidid></search><sort><creationdate>20220501</creationdate><title>DNA methylation marker to estimate ovarian cancer cell fraction</title><author>Ebata, Takahiro ; Yamashita, Satoshi ; Takeshima, Hideyuki ; Yoshida, Hiroshi ; Kawata, Yoshiko ; Kino, Nao ; Yasugi, Toshiharu ; Terao, Yasuhisa ; Yonemori, Kan ; Kato, Tomoyasu ; Ushijima, Toshikazu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c485t-56de16fe360b51fea6b78b2cbb9f74d352eb327bfcaa70dbde0bbf2bec5c54c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Biomarkers, Tumor - genetics</topic><topic>Cell Line, Tumor</topic><topic>DNA Methylation</topic><topic>DNA, Neoplasm - genetics</topic><topic>Female</topic><topic>Genetic Markers</topic><topic>Hematology</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Kruppel-Like Transcription Factors - genetics</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Oncology</topic><topic>Original Paper</topic><topic>Ovarian cancer</topic><topic>Ovarian Neoplasms - genetics</topic><topic>Ovarian Neoplasms - pathology</topic><topic>Pathology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ebata, Takahiro</creatorcontrib><creatorcontrib>Yamashita, Satoshi</creatorcontrib><creatorcontrib>Takeshima, Hideyuki</creatorcontrib><creatorcontrib>Yoshida, Hiroshi</creatorcontrib><creatorcontrib>Kawata, Yoshiko</creatorcontrib><creatorcontrib>Kino, Nao</creatorcontrib><creatorcontrib>Yasugi, Toshiharu</creatorcontrib><creatorcontrib>Terao, Yasuhisa</creatorcontrib><creatorcontrib>Yonemori, Kan</creatorcontrib><creatorcontrib>Kato, Tomoyasu</creatorcontrib><creatorcontrib>Ushijima, Toshikazu</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Medical oncology (Northwood, London, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ebata, Takahiro</au><au>Yamashita, Satoshi</au><au>Takeshima, Hideyuki</au><au>Yoshida, Hiroshi</au><au>Kawata, Yoshiko</au><au>Kino, Nao</au><au>Yasugi, Toshiharu</au><au>Terao, Yasuhisa</au><au>Yonemori, Kan</au><au>Kato, Tomoyasu</au><au>Ushijima, Toshikazu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>DNA methylation marker to estimate ovarian cancer cell fraction</atitle><jtitle>Medical oncology (Northwood, London, England)</jtitle><stitle>Med Oncol</stitle><addtitle>Med Oncol</addtitle><date>2022-05-01</date><risdate>2022</risdate><volume>39</volume><issue>5</issue><spage>78</spage><epage>78</epage><pages>78-78</pages><artnum>78</artnum><issn>1357-0560</issn><eissn>1559-131X</eissn><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.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>35195779</pmid><doi>10.1007/s12032-022-01679-y</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-3405-7817</orcidid><oa>free_for_read</oa></addata></record> |
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| issn | 1357-0560 1559-131X |
| language | eng |
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| source | Springer Nature:Jisc Collections:Springer Nature Read and Publish 2023-2025: Springer Reading List |
| subjects | Biomarkers, Tumor - genetics Cell Line, Tumor DNA Methylation DNA, Neoplasm - genetics Female Genetic Markers Hematology Humans Internal Medicine Kruppel-Like Transcription Factors - genetics Medicine Medicine & Public Health Oncology Original Paper Ovarian cancer Ovarian Neoplasms - genetics Ovarian Neoplasms - pathology Pathology |
| title | DNA methylation marker to estimate ovarian cancer cell fraction |
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