TY - JOUR
T1 - Integrated extracellular microRNA profiling for ovarian cancer screening
AU - Yokoi, Akira
AU - Matsuzaki, Juntaro
AU - Yamamoto, Yusuke
AU - Yoneoka, Yutaka
AU - Takahashi, Kenta
AU - Shimizu, Hanako
AU - Uehara, Takashi
AU - Ishikawa, Mitsuya
AU - Ikeda, Shun ichi
AU - Sonoda, Takumi
AU - Kawauchi, Junpei
AU - Takizawa, Satoko
AU - Aoki, Yoshiaki
AU - Niida, Shumpei
AU - Sakamoto, Hiromi
AU - Kato, Ken
AU - Kato, Tomoyasu
AU - Ochiya, Takahiro
N1 - Funding Information:
The authors thank Tomomi Fukuda, Hiroko Tadokoro, Tatsuya Suzuki, Makiko Ichikawa, Junpei Kawauchi, Satoshi Kondou, and Kamakura Techno-Science Inc. for performing the microarray assays. The authors thank Noriko Abe and Michiko Ohori for collecting samples from the freezing room and Kazuki Sudo for independent confirmation of participant eligibility. Some of the samples and clinical information used in this study was obtained from the National Cancer Center Biobank, which is supported by National Cancer Center Research and Development Fund (29-A-1). The authors also thank the Biobank at the National Center for Geriatrics and Gerontology for providing biological resources. This study was financially supported through a Development of Diagnostic Technology for Detection of miRNA in Body Fluids grant from the Japan Agency for Medical Research and Development (to TO).
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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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U2 - 10.1038/s41467-018-06434-4
DO - 10.1038/s41467-018-06434-4
M3 - Article
C2 - 30333487
AN - SCOPUS:85055075300
SN - 2041-1723
VL - 9
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 4319
ER -
