Cargando…
Ovarian cancer detection by DNA methylation in cervical scrapings
BACKGROUND: Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screeni...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6881994/ https://www.ncbi.nlm.nih.gov/pubmed/31775891 http://dx.doi.org/10.1186/s13148-019-0773-3 |
_version_ | 1783474057995354112 |
---|---|
author | Wu, Tzu-I Huang, Rui-Lan Su, Po-Hsuan Mao, Shih-Peng Wu, Chen-Hsuan Lai, Hung-Cheng |
author_facet | Wu, Tzu-I Huang, Rui-Lan Su, Po-Hsuan Mao, Shih-Peng Wu, Chen-Hsuan Lai, Hung-Cheng |
author_sort | Wu, Tzu-I |
collection | PubMed |
description | BACKGROUND: Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screening, which remains a controversial and cost-prohibitive issue. Here, we demonstrate that Papanicolaou test (Pap test) cervical scrapings, instead of blood, can reveal genetic/epigenetic information for OC detection, using specific and sensitive DNA methylation biomarkers. RESULTS: We analyzed the methylomes of tissues (50 OC tissues versus 6 normal ovarian epithelia) and cervical scrapings (5 OC patients versus 10 normal controls), and integrated public methylomic datasets, including 79 OC tissues and 6 normal tubal epithelia. Differentially methylated genes were further classified by unsupervised hierarchical clustering, and each candidate biomarker gene was verified in both OC tissues and cervical scrapings by either quantitative methylation-specific polymerase chain reaction (qMSP) or bisulfite pyrosequencing. A risk-score by logistic regression was generated for clinical application. One hundred fifty-one genes were classified into four clusters, and nine candidate hypermethylated genes from these four clusters were selected. Among these, four genes fulfilled our selection criteria and were validated in training and testing set, respectively. The OC detection accuracy was demonstrated by area under the receiver operating characteristic curves (AUCs) in 0.80–0.83 of AMPD3, 0.79–0.85 of AOX1, 0.78–0.88 of NRN1, and 0.82–0.85 of TBX15. From this, we found OC-risk score, equation generated by logistic regression in training set and validated an OC-associated panel comprising AMPD3, NRN1, and TBX15, reaching a sensitivity of 81%, specificity of 84%, and OC detection accuracy of 0.91 (95% CI, 0.82–1) in testing set. CONCLUSIONS: Ovarian cancer detection from cervical scrapings is feasible, using particularly promising epigenetic biomarkers such as AMPD3/NRN1/TBX15. Further validation is warranted. |
format | Online Article Text |
id | pubmed-6881994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68819942019-12-03 Ovarian cancer detection by DNA methylation in cervical scrapings Wu, Tzu-I Huang, Rui-Lan Su, Po-Hsuan Mao, Shih-Peng Wu, Chen-Hsuan Lai, Hung-Cheng Clin Epigenetics Research BACKGROUND: Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screening, which remains a controversial and cost-prohibitive issue. Here, we demonstrate that Papanicolaou test (Pap test) cervical scrapings, instead of blood, can reveal genetic/epigenetic information for OC detection, using specific and sensitive DNA methylation biomarkers. RESULTS: We analyzed the methylomes of tissues (50 OC tissues versus 6 normal ovarian epithelia) and cervical scrapings (5 OC patients versus 10 normal controls), and integrated public methylomic datasets, including 79 OC tissues and 6 normal tubal epithelia. Differentially methylated genes were further classified by unsupervised hierarchical clustering, and each candidate biomarker gene was verified in both OC tissues and cervical scrapings by either quantitative methylation-specific polymerase chain reaction (qMSP) or bisulfite pyrosequencing. A risk-score by logistic regression was generated for clinical application. One hundred fifty-one genes were classified into four clusters, and nine candidate hypermethylated genes from these four clusters were selected. Among these, four genes fulfilled our selection criteria and were validated in training and testing set, respectively. The OC detection accuracy was demonstrated by area under the receiver operating characteristic curves (AUCs) in 0.80–0.83 of AMPD3, 0.79–0.85 of AOX1, 0.78–0.88 of NRN1, and 0.82–0.85 of TBX15. From this, we found OC-risk score, equation generated by logistic regression in training set and validated an OC-associated panel comprising AMPD3, NRN1, and TBX15, reaching a sensitivity of 81%, specificity of 84%, and OC detection accuracy of 0.91 (95% CI, 0.82–1) in testing set. CONCLUSIONS: Ovarian cancer detection from cervical scrapings is feasible, using particularly promising epigenetic biomarkers such as AMPD3/NRN1/TBX15. Further validation is warranted. BioMed Central 2019-11-27 /pmc/articles/PMC6881994/ /pubmed/31775891 http://dx.doi.org/10.1186/s13148-019-0773-3 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Wu, Tzu-I Huang, Rui-Lan Su, Po-Hsuan Mao, Shih-Peng Wu, Chen-Hsuan Lai, Hung-Cheng Ovarian cancer detection by DNA methylation in cervical scrapings |
title | Ovarian cancer detection by DNA methylation in cervical scrapings |
title_full | Ovarian cancer detection by DNA methylation in cervical scrapings |
title_fullStr | Ovarian cancer detection by DNA methylation in cervical scrapings |
title_full_unstemmed | Ovarian cancer detection by DNA methylation in cervical scrapings |
title_short | Ovarian cancer detection by DNA methylation in cervical scrapings |
title_sort | ovarian cancer detection by dna methylation in cervical scrapings |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6881994/ https://www.ncbi.nlm.nih.gov/pubmed/31775891 http://dx.doi.org/10.1186/s13148-019-0773-3 |
work_keys_str_mv | AT wutzui ovariancancerdetectionbydnamethylationincervicalscrapings AT huangruilan ovariancancerdetectionbydnamethylationincervicalscrapings AT supohsuan ovariancancerdetectionbydnamethylationincervicalscrapings AT maoshihpeng ovariancancerdetectionbydnamethylationincervicalscrapings AT wuchenhsuan ovariancancerdetectionbydnamethylationincervicalscrapings AT laihungcheng ovariancancerdetectionbydnamethylationincervicalscrapings |