Identification of novel biomarkers in Hunner's interstitial cystitis using the CIBERSORT, an algorithm based on machine learning.

Journal: BMC urology
PMID: 34399738

Abstract

BACKGROUND:  Hunner's interstitial cystitis (HIC) is a complex disorder characterized by pelvic pain, disrupted urine storage, and Hunner lesions seen on cystoscopy. There are few effective diagnostic biomarkers. In the present study, we used the novel machine learning tool CIBERSORT to measure immune cell subset infiltration and potential novel diagnostic biomarkers for HIC.

Authors

  • Kaining Lu
    Department of Urology, Ningbo First Hospital, 59, Liuting Street, Ningbo, 315010, Zhejiang, People's Republic of China.
  • Shan Wei
    Department of Respiratory and Critical Care Medicine, People's Hospital Affiliated to Ningbo University, Yinzhou People's Hospital, Ningbo, People's Republic of China.
  • Zhengyi Wang
    Department of Urology, Ningbo First Hospital, 59, Liuting Street, Ningbo, 315010, Zhejiang, People's Republic of China.
  • Kerong Wu
    Department of Urology, Ningbo First Hospital, 59, Liuting Street, Ningbo, 315010, Zhejiang, People's Republic of China.
  • Junhui Jiang
    Department of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, China.
  • Zejun Yan
    Department of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, China.
  • Yue Cheng

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