Screening and validation of long non-coding RNAs associated with colorectal cancer based on random forest and LASSO regression algorithm.

Journal: Discover oncology
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: Colorectal cancer (CRC) ranks as the third most prevalent contributor to global disease burden and represents the second highest mortality rate among all malignancies worldwide. Long non-coding RNAs (lncRNAs) are a new class of regulatory RNAs, which play a crucial role in the occurrence and development of colorectal cancer. Therefore, it is potentially important to use bioinformatics and machine learning methods to study novel biomarkers for CRC.

Authors

  • Yujia Zhao
  • Qian Li
    Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Xintong Cui
    Department of Health Statistics, School of Public Health, Shenyang Medical College, 146 Huanghe North Street, Shenyang, 110034, China.
  • Zhiyu Zhang
    Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
  • Yong You
    The Fourth People's Hospital of Shenyang, Shenyang, 110034, China.
  • Xiaowen Hou
    Minfound Medical Systems Co. Ltd., 8 Dongze Road, Yuecheng District, Shaoxing, Zhejiang, 312099, China.
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Xu Feng
    State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.

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