Machine-learning diagnostics of breast cancer using piRNA biomarkers.

Journal: Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
PMID: 39899375

Abstract

BACKGROUND AND OBJECTIVES: Prior studies have shown that small non-coding RNAs (sncRNAs) are associated with cancer occurrence or development. Recently, a newly discovered class of small ncRNAs known as PIWI-interacting RNAs (piRNAs) have been found to play a vital role in physiological processes and cancer initiation. This study aims to utilize piRNAs as innovative, noninvasive diagnostic biomarkers for breast cancer. Our objective is to develop computational methods that leverage piRNA attributes for breast cancer prediction and its application in diagnostics.

Authors

  • Amy R Zhao
    Scholars Program, CureScience Institute, San Diego, CA, USA.
  • Valentina L Kouznetsova
    San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA 92093, USA.
  • Santosh Kesari
    Pacific Neuroscience Institute, Santa Monica, CA 90404, USA.
  • Igor F Tsigelny
    San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA 92093, USA.

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