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Background <p>Mitochondrial-associated membranes (MAMs) participate in cellular metabolism, calcium signaling, and cancer reprogramming, but their role in kidney renal clear cell carcinoma (KIRC) remains unclear.</p> Methods <p>Clinical/transcriptomic data of KIRC and previously reported MAMs-related genes were obtained from TCGA, E-MTAB-1980, and GSE29609. After analyzing MAMs gene expression in KIRC, 101 models were generated via 10 machine learning algorithms to select the optimal MAMs-based scoring system. Survival (Kaplan-Meier) and Cox regression analyses evaluated its prognostic value; associations with immune cell infiltration, checkpoints, and drug sensitivity were explored, and key genes were validated in vitro and in vivo.</p> Results <p>Forty-two MAMs-related genes were identified, most highly expressed in KIRC tissues. A 9-gene MAMs scoring system was built using the Stepwise Cox model. High-score patients had worse prognosis, and the system was an independent prognostic factor for KIRC. High scores correlated with advanced TNM stage/grade, elevated CTLA4/PD1 (better immunotherapy response in CTLA4+/PD1+ subgroups), and sensitivity to temsirolimus/sunitinib (low scores sensitive to sorafenib). DNM1L was a key gene; its knockdown inhibited KIRC cell proliferation, invasion, and migration in vitro. In vivo experiments further confirmed that DNM1L knockdown suppressed tumor growth in BALB/c nude mice bearing KIRC xenografts.</p> Conclusion <p>This study identified high MAMs-related gene expression in KIRC, developed a 9-gene MAMs scoring system, and validated DNM1L as a key gene, providing new insights into KIRC prognostic biomarkers and therapeutic targets.</p>

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Characterizing prognostic and immunological traits of kidney renal clear cell carcinoma via mitochondria-associated membranes and identifying DNM1L as a potential therapeutic target using machine learning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月22日

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

摘要

Background

Mitochondrial-associated membranes (MAMs) participate in cellular metabolism, calcium signaling, and cancer reprogramming, but their role in kidney renal clear cell carcinoma (KIRC) remains unclear.

Methods

Clinical/transcriptomic data of KIRC and previously reported MAMs-related genes were obtained from TCGA, E-MTAB-1980, and GSE29609. After analyzing MAMs gene expression in KIRC, 101 models were generated via 10 machine learning algorithms to select the optimal MAMs-based scoring system. Survival (Kaplan-Meier) and Cox regression analyses evaluated its prognostic value; associations with immune cell infiltration, checkpoints, and drug sensitivity were explored, and key genes were validated in vitro and in vivo.

Results

Forty-two MAMs-related genes were identified, most highly expressed in KIRC tissues. A 9-gene MAMs scoring system was built using the Stepwise Cox model. High-score patients had worse prognosis, and the system was an independent prognostic factor for KIRC. High scores correlated with advanced TNM stage/grade, elevated CTLA4/PD1 (better immunotherapy response in CTLA4+/PD1+ subgroups), and sensitivity to temsirolimus/sunitinib (low scores sensitive to sorafenib). DNM1L was a key gene; its knockdown inhibited KIRC cell proliferation, invasion, and migration in vitro. In vivo experiments further confirmed that DNM1L knockdown suppressed tumor growth in BALB/c nude mice bearing KIRC xenografts.

Conclusion

This study identified high MAMs-related gene expression in KIRC, developed a 9-gene MAMs scoring system, and validated DNM1L as a key gene, providing new insights into KIRC prognostic biomarkers and therapeutic targets.