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Integrated extracellular microRNA profiling for ovarian cancer screening

Author

Listed:
  • Akira Yokoi

    (National Cancer Center Research Institute
    Nagoya University Graduate School of Medicine)

  • 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)

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.

Suggested Citation

  • Akira Yokoi & Juntaro Matsuzaki & Yusuke Yamamoto & Yutaka Yoneoka & Kenta Takahashi & Hanako Shimizu & Takashi Uehara & Mitsuya Ishikawa & Shun-ichi Ikeda & Takumi Sonoda & Junpei Kawauchi & Satoko T, 2018. "Integrated extracellular microRNA profiling for ovarian cancer screening," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06434-4
    DOI: 10.1038/s41467-018-06434-4
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    Cited by:

    1. Muhammad Irfan, 2018. "A Mini Review on Some Latest Break Throughs on Molecular Intervention for Human Diseases," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 11(1), pages 8307-8309, November.
    2. Natsuko Satomi-Tsushita & Akihiko Shimomura & Juntaro Matsuzaki & Yusuke Yamamoto & Junpei Kawauchi & Satoko Takizawa & Yoshiaki Aoki & Hiromi Sakamoto & Ken Kato & Chikako Shimizu & Takahiro Ochiya &, 2019. "Serum microRNA-based prediction of responsiveness to eribulin in metastatic breast cancer," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-12, September.

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