Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target.

Journal: Cancer immunology, immunotherapy : CII
PMID: 39998680

Abstract

BACKGROUND: The pathogenesis and progression of renal cell carcinoma (RCC) involve complex programmed cell death (PCD) processes. As the powerhouse of the cell, mitochondria can influence cell death mechanisms. However, the prognostic significance of the interplay between mitochondrial function (MF) and PCD remains unclear.

Authors

  • Guangyang Cheng
    Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
  • Zhaokai Zhou
    Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Shiqi Li
    Department of Neurosurgery, Shanghai Medical School, Huashan Hospital, Fudan University, 12 Wulumuqi Zhong Road, Shanghai, China.
  • Fu Peng
    Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu, China.
  • Shuai Yang
    School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei, Anhui, China.
  • Chuanchuan Ren
    Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China. cc_ren@zzu.edu.cn.

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