Analyzing Prognostic and Immune Characteristics of Kidney Renal Clear Cell Carcinoma through Mitochondria-Associated Membranes and Identifying DNM1L as a Potential Target for Therapy Using Machine Learning Techniques - Takeaways - MDSpire

Analyzing Prognostic and Immune Characteristics of Kidney Renal Clear Cell Carcinoma through Mitochondria-Associated Membranes and Identifying DNM1L as a Potential Target for Therapy Using Machine Learning Techniques

  • By

  • Sheng Li

  • Jinkang Lin

  • Fucun Zheng

  • Xiaoqiang Liu

  • Situ Xiong

  • Bin Fu

  • Jin Zeng

  • January 22, 2026

  • 0 min

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  • 1

    Kidney renal clear cell carcinoma (KIRC) accounts for over 70% of renal cell carcinoma cases and poses significant therapeutic challenges.

  • 2

    Mitochondria-associated membranes (MAMs) play crucial roles in cancer cell metabolism and may influence treatment resistance in KIRC.

  • 3

    This study developed a MAMs-based scoring model using 10 machine learning algorithms to assess prognostic outcomes in KIRC patients.

  • 4

    The MAMs model was validated across multiple datasets, demonstrating its potential as a reliable prognostic tool for KIRC.

  • 5

    DNM1L was identified as a key therapeutic target, with its knockdown shown to suppress tumor growth in KIRC both in vitro and in vivo.

Original Source(s)

Analyzing Prognostic and Immune Characteristics of Kidney Renal Clear Cell Carcinoma through Mitochondria-Associated Membranes and Identifying DNM1L as a Potential Target for Therapy Using Machine Learning Techniques

  • by Sheng Li, Jinkang Lin, Fucun Zheng, Xiaoqiang Liu, Situ Xiong, Bin Fu, Jin Zeng

  • January 22, 2026

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