IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0236097.html
   My bibliography  Save this article

A novel serum miRNA-pair classifier for diagnosis of sarcoma

Author

Listed:
  • Zheng Jin
  • Shanshan Liu
  • Pei Zhu
  • Mengyan Tang
  • Yuanxin Wang
  • Yuan Tian
  • Dong Li
  • Xun Zhu
  • Dongmei Yan
  • Zhenhua Zhu

Abstract

Soft tissue sarcomas (STS) is a set of rare malignant tumor originated from mesoderm. For the prognosis of sarcoma, early diagnosis is important, however, currently no mature and non-invasive method for diagnosis exists. MicroRNAs (miRNAs) are a class of noncoding RNAs and their expression varies greatly, especially during tumor activity. The purpose of this study was to construct a predictive model for the diagnosis of sarcomas based on the relative expression level of miRNA in serum. miRNA array expression data of 677 samples including 402 malignant sarcoma samples and 275 healthy samples was used to construct the prediction model. Based on 6 gene pairs, random generalized linear model (RGLM) was constructed, with an accuracy of 100% in the internal test dataset and of 74.3% in the merged external dataset in prediction whether a serum sample was obtained from a sarcoma patient, with a specificity of 100% in the internal test dataset and 90.5% in the external dataset. In conclusion, our serum miRNA-pair classifier has the potential to be used for the screening of sarcoma with high accuracy and specificity.

Suggested Citation

  • Zheng Jin & Shanshan Liu & Pei Zhu & Mengyan Tang & Yuanxin Wang & Yuan Tian & Dong Li & Xun Zhu & Dongmei Yan & Zhenhua Zhu, 2020. "A novel serum miRNA-pair classifier for diagnosis of sarcoma," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-9, July.
    • Handle: RePEc:plo:pone00:0236097
    DOI: 10.1371/journal.pone.0236097
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236097
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0236097&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0236097?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Naofumi Asano & Juntaro Matsuzaki & Makiko Ichikawa & Junpei Kawauchi & Satoko Takizawa & Yoshiaki Aoki & Hiromi Sakamoto & Akihiko Yoshida & Eisuke Kobayashi & Yoshikazu Tanzawa & Robert Nakayama & H, 2019. "A serum microRNA classifier for the diagnosis of sarcomas of various histological subtypes," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      More about this item

      Statistics

      Access and download statistics

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0236097. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.