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Integrated extracellular microRNA profiling for ovarian cancer screening

A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microar...

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Autores principales: Yokoi, Akira, Matsuzaki, Juntaro, Yamamoto, Yusuke, Yoneoka, Yutaka, Takahashi, Kenta, Shimizu, Hanako, Uehara, Takashi, Ishikawa, Mitsuya, Ikeda, Shun-ichi, Sonoda, Takumi, Kawauchi, Junpei, Takizawa, Satoko, Aoki, Yoshiaki, Niida, Shumpei, Sakamoto, Hiromi, Kato, Ken, Kato, Tomoyasu, Ochiya, Takahiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192980/
https://www.ncbi.nlm.nih.gov/pubmed/30333487
http://dx.doi.org/10.1038/s41467-018-06434-4
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author Yokoi, Akira
Matsuzaki, Juntaro
Yamamoto, Yusuke
Yoneoka, Yutaka
Takahashi, Kenta
Shimizu, Hanako
Uehara, Takashi
Ishikawa, Mitsuya
Ikeda, Shun-ichi
Sonoda, Takumi
Kawauchi, Junpei
Takizawa, Satoko
Aoki, Yoshiaki
Niida, Shumpei
Sakamoto, Hiromi
Kato, Ken
Kato, Tomoyasu
Ochiya, Takahiro
author_facet Yokoi, Akira
Matsuzaki, Juntaro
Yamamoto, Yusuke
Yoneoka, Yutaka
Takahashi, Kenta
Shimizu, Hanako
Uehara, Takashi
Ishikawa, Mitsuya
Ikeda, Shun-ichi
Sonoda, Takumi
Kawauchi, Junpei
Takizawa, Satoko
Aoki, Yoshiaki
Niida, Shumpei
Sakamoto, Hiromi
Kato, Ken
Kato, Tomoyasu
Ochiya, Takahiro
author_sort Yokoi, Akira
collection PubMed
description A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9–10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer.
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spelling pubmed-61929802018-10-19 Integrated extracellular microRNA profiling for ovarian cancer screening Yokoi, Akira Matsuzaki, Juntaro Yamamoto, Yusuke Yoneoka, Yutaka Takahashi, Kenta Shimizu, Hanako Uehara, Takashi Ishikawa, Mitsuya Ikeda, Shun-ichi Sonoda, Takumi Kawauchi, Junpei Takizawa, Satoko Aoki, Yoshiaki Niida, Shumpei Sakamoto, Hiromi Kato, Ken Kato, Tomoyasu Ochiya, Takahiro Nat Commun Article A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9–10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer. Nature Publishing Group UK 2018-10-17 /pmc/articles/PMC6192980/ /pubmed/30333487 http://dx.doi.org/10.1038/s41467-018-06434-4 Text en © The Author(s) 2018 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
Yokoi, Akira
Matsuzaki, Juntaro
Yamamoto, Yusuke
Yoneoka, Yutaka
Takahashi, Kenta
Shimizu, Hanako
Uehara, Takashi
Ishikawa, Mitsuya
Ikeda, Shun-ichi
Sonoda, Takumi
Kawauchi, Junpei
Takizawa, Satoko
Aoki, Yoshiaki
Niida, Shumpei
Sakamoto, Hiromi
Kato, Ken
Kato, Tomoyasu
Ochiya, Takahiro
Integrated extracellular microRNA profiling for ovarian cancer screening
title Integrated extracellular microRNA profiling for ovarian cancer screening
title_full Integrated extracellular microRNA profiling for ovarian cancer screening
title_fullStr Integrated extracellular microRNA profiling for ovarian cancer screening
title_full_unstemmed Integrated extracellular microRNA profiling for ovarian cancer screening
title_short Integrated extracellular microRNA profiling for ovarian cancer screening
title_sort integrated extracellular microrna profiling for ovarian cancer screening
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192980/
https://www.ncbi.nlm.nih.gov/pubmed/30333487
http://dx.doi.org/10.1038/s41467-018-06434-4
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