IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0348414.html

Development of predictive models for the prognosis of triple-negative breast cancer using multiple transcriptomic analyses

Author

Listed:
  • Suhyun Hwangbo
  • Yoojin Choi
  • Jae Yong Ryu

Abstract

Triple-negative breast cancer (TNBC) is a subtype of breast cancer (BC) and constitutes approximately 15–20% of all BC cases. This subtype has the most aggressive behavior and the worst prognosis. Numerous studies have been conducted over the past several decades to address the lack of clinically available treatment options. In particular, potential markers targeting effective treatment options have been actively studied. However, these efforts were hindered by the complex mechanisms of TNBC, and no study has demonstrated a model with a predictive performance exceeding 0.85. This study developed TNBC prognosis predictive models with a predictive performance exceeding 0.94. Applying the nine selected markers to five independent datasets demonstrated their potential as TNBC-specific prognostic markers. Most of these genes (including GPR61, PZP, IGFL1, and AHCTF1) are associated with overall survival (OS) in patients with TNBC. Based on these results, these nine selected genes may serve as prognostic markers for OS in patients with TNBC.

Suggested Citation

  • Suhyun Hwangbo & Yoojin Choi & Jae Yong Ryu, 2026. "Development of predictive models for the prognosis of triple-negative breast cancer using multiple transcriptomic analyses," PLOS ONE, Public Library of Science, vol. 21(5), pages 1-14, May.
    • Handle: RePEc:plo:pone00:0348414
    DOI: 10.1371/journal.pone.0348414
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0348414
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0348414&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0348414?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
    ---><---

    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:pone00:0348414. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.