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Serum microRNA-based prediction of responsiveness to eribulin in metastatic breast cancer

Author

Listed:
  • Natsuko Satomi-Tsushita
  • Akihiko Shimomura
  • Juntaro Matsuzaki
  • Yusuke Yamamoto
  • Junpei Kawauchi
  • Satoko Takizawa
  • Yoshiaki Aoki
  • Hiromi Sakamoto
  • Ken Kato
  • Chikako Shimizu
  • Takahiro Ochiya
  • Kenji Tamura

Abstract

The identification of biomarkers for predicting the responsiveness to eribulin in patients with metastatic breast cancer pretreated with an anthracycline and a taxane remains an unmet need. Here, we established a serum microRNA (miRNA)-based prediction model for the emergence of new distant metastases after eribulin treatment. Serum samples were collected from metastatic breast cancer patients prior to eribulin treatment and comprehensively evaluated by miRNA microarray. The prediction model for estimating eribulin efficacy was established using the logistic LASSO regression model. Serum samples were collected from 147 patients, of which 52 developed at least one new distant metastasis after eribulin monotherapy and 95 did not develop new distant metastases. A combination of eight serum miRNAs (miR-4483, miR-8089, miR-4755-3p, miR-296-3p, miR-575, miR-4710, miR-5698 and miR-3160-5p) predicted the appearance of new distant metastases with an area under the curve of 0.79, sensitivity of 0.69 and specificity of 0.82. The serum levels of miR-8089 and miR-5698 were significantly associated with overall survival after the initiation of eribulin treatment. The present study provides evidence that serum miRNA profiling may serve as a biomarker for the responsiveness to eribulin and for predicting the development of new distant metastases in metastatic breast cancer.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0222024
    DOI: 10.1371/journal.pone.0222024
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    1. 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.
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