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Purpose <p>Clear cell renal cell carcinoma (ccRCC) is a heterogeneous malignancy with limited prognostic biomarkers. This study aimed to explore the prognostic value of mitophagy-related long non-coding RNAs (MRlncRNAs) and construct a risk model to assist survival prediction and clinical decision-making.</p> Methods <p>Transcriptomic, clinical, and somatic mutation data of ccRCC patients were obtained from The Cancer Genome Atlas (TCGA). MRlncRNAs were identified through co-expression with mitophagy-related genes. A prognostic risk model was constructed using Cox and LASSO regression analyses and validated in independent cohorts. Functional analyses explored associations with the immune microenvironment, tumor mutation burden (TMB), and drug sensitivity.</p> Results <p>Five MRlncRNAs (AC002070.1, AC092953.2, AC103706.1, LINC01943, and LINC02027) were identified as independent prognostic biomarkers. The risk model effectively stratified patients into high- and low-risk groups with significant differences in overall survival (OS) and progression-free survival. Low-risk patients exhibited enhanced anti-tumor immune activity and greater sensitivity to drugs such as bortezomib, while high-risk patients showed immune suppression, higher TMB, and increased responsiveness to agents targeting EGFR and TGF-β pathways.</p> Conclusion <p>This study developed and validated a robust MRlncRNA-based prognostic model for ccRCC that integrates mitophagy-related molecular features with immune and therapeutic profiles. This model provides novel insights for prognostic evaluation and offers a promising tool for guiding individualized treatment strategies.</p>

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Integrating mitophagy-associated lncRNAs to predict prognosis and therapeutic response in clear cell renal cell carcinoma

  • 期刊论文

  • 发表日期：

    2025年6月27日

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  • Guofan Hu,
  • Shuangze Zhong,
  • Hansheng Lin,
  • Jingwei He

摘要

Purpose

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous malignancy with limited prognostic biomarkers. This study aimed to explore the prognostic value of mitophagy-related long non-coding RNAs (MRlncRNAs) and construct a risk model to assist survival prediction and clinical decision-making.

Methods

Transcriptomic, clinical, and somatic mutation data of ccRCC patients were obtained from The Cancer Genome Atlas (TCGA). MRlncRNAs were identified through co-expression with mitophagy-related genes. A prognostic risk model was constructed using Cox and LASSO regression analyses and validated in independent cohorts. Functional analyses explored associations with the immune microenvironment, tumor mutation burden (TMB), and drug sensitivity.

Results

Five MRlncRNAs (AC002070.1, AC092953.2, AC103706.1, LINC01943, and LINC02027) were identified as independent prognostic biomarkers. The risk model effectively stratified patients into high- and low-risk groups with significant differences in overall survival (OS) and progression-free survival. Low-risk patients exhibited enhanced anti-tumor immune activity and greater sensitivity to drugs such as bortezomib, while high-risk patients showed immune suppression, higher TMB, and increased responsiveness to agents targeting EGFR and TGF-β pathways.

Conclusion

This study developed and validated a robust MRlncRNA-based prognostic model for ccRCC that integrates mitophagy-related molecular features with immune and therapeutic profiles. This model provides novel insights for prognostic evaluation and offers a promising tool for guiding individualized treatment strategies.