IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0299138.html
   My bibliography  Save this article

Cuproptosis-associated ncRNAs predict breast cancer subtypes

Author

Listed:
  • Qing Xia
  • Jinze Shen
  • Qurui Wang
  • Ruixiu Chen
  • Xinying Zheng
  • Qibin Yan
  • Lihua Du
  • Hanbing Li
  • Shiwei Duan

Abstract

Background: Cuproptosis is a novel copper-dependent mode of cell death that has recently been discovered. The relationship between Cuproptosis-related ncRNAs and breast cancer subtypes, however, remains to be studied. Methods: The aim of this study was to construct a breast cancer subtype prediction model associated with Cuproptosis. This model could be used to determine the subtype of breast cancer patients. To achieve this aim, 21 Cuproptosis-related genes were obtained from published articles and correlation analysis was performed with ncRNAs differentially expressed in breast cancer. Random forest algorithms were subsequently utilized to select important ncRNAs and build breast cancer subtype prediction models. Results: A total of 94 ncRNAs significantly associated with Cuproptosis were obtained and the top five essential features were chosen to build a predictive model. These five biomarkers were differentially expressed in the five breast cancer subtypes and were closely associated with immune infiltration, RNA modification, and angiogenesis. Conclusion: The random forest model constructed based on Cuproptosis-related ncRNAs was able to accurately predict breast cancer subtypes, providing a new direction for the study of clinical therapeutic targets.

Suggested Citation

  • Qing Xia & Jinze Shen & Qurui Wang & Ruixiu Chen & Xinying Zheng & Qibin Yan & Lihua Du & Hanbing Li & Shiwei Duan, 2024. "Cuproptosis-associated ncRNAs predict breast cancer subtypes," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-21, February.
    • Handle: RePEc:plo:pone00:0299138
    DOI: 10.1371/journal.pone.0299138
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0299138
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0299138&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0299138?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:pone00:0299138. 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.