Integrated extracellular microRNA profiling for ovarian cancer screening

Akira Yokoi, Juntaro Matsuzaki, Yusuke Yamamoto, Yutaka Yoneoka, Kenta Takahashi, Hanako Shimizu, Takashi Uehara, Mitsuya Ishikawa, Shun-ichi Ikeda, Takumi Sonoda, Junpei Kawauchi, Satoko Takizawa, Yoshiaki Aoki, Shumpei Niida, Hiromi Sakamoto, Ken Kato, Tomoyasu Kato and Takahiro Ochiya ()
Additional contact information
Akira Yokoi: National Cancer Center Research Institute
Juntaro Matsuzaki: National Cancer Center Research Institute
Yusuke Yamamoto: National Cancer Center Research Institute
Yutaka Yoneoka: National Cancer Center Hospital
Kenta Takahashi: National Cancer Center Hospital
Hanako Shimizu: National Cancer Center Hospital
Takashi Uehara: National Cancer Center Hospital
Mitsuya Ishikawa: National Cancer Center Hospital
Shun-ichi Ikeda: National Cancer Center Hospital
Takumi Sonoda: National Cancer Center Research Institute
Junpei Kawauchi: New Frontiers Research Institute, Toray Industries
Satoko Takizawa: New Frontiers Research Institute, Toray Industries
Yoshiaki Aoki: Dynacom Co., Ltd.
Shumpei Niida: National Center for Geriatrics and Gerontology
Hiromi Sakamoto: National Cancer Center Research Institute
Ken Kato: National Cancer Center Hospital
Tomoyasu Kato: National Cancer Center Hospital
Takahiro Ochiya: National Cancer Center Research Institute

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract 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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06434-4

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DOI: 10.1038/s41467-018-06434-4

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