CT-Based Radiogenomic Prediction of ICAM1 and RAET1E as Biomarkers of NK Cytotoxicity in Clear Cell Renal Cell Carcinoma - Report - MDSpire

CT-Based Radiogenomic Prediction of ICAM1 and RAET1E as Biomarkers of NK Cytotoxicity in Clear Cell Renal Cell Carcinoma

  • By

  • Ma, Xinwei

  • Yang, Jiao

  • Qian, Xusheng

  • Dou, Xin

  • Ji, Shiliang

  • Dai, Yakang

  • Yang, Yi

  • Wang, Yi

  • Zhu, Jianbing

  • May 20, 2026

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Clinical Report: Radiogenomic Assessment of NK Cell Cytotoxicity in ccRCC

Overview

This study presents a noninvasive CT-based radiogenomic framework for identifying biomarkers associated with NK cell cytotoxicity in clear cell renal cell carcinoma (ccRCC). Key findings include the identification of ICAM1 and RAET1E as significant indicators of tumor stage and survival outcomes.

Background

Clear cell renal cell carcinoma (ccRCC) is characterized by tumor heterogeneity and a complex immune microenvironment. Traditional tissue sampling methods can be invasive and may not accurately reflect the tumor's molecular landscape. This study explores the potential of CT imaging to noninvasively assess biomarkers related to NK cell activity, which could enhance patient stratification and treatment planning.

Data Highlights

BiomarkerAUCExpression Association
ICAM175.7%Higher in advanced tumor stage
RAET1E67.3%Lower in advanced tumor stage

Key Findings

  • Identification of 835 imaging-associated genes enriched in immune-related pathways.
  • ICAM1 and RAET1E showed strong radiogenomic associations with AUCs of 75.7% and 67.3%, respectively.
  • Immunohistochemistry confirmed increased ICAM1 and decreased RAET1E expression in ccRCC tissues.
  • Higher ICAM1 and lower RAET1E expression correlated with advanced tumor stage and poorer survival outcomes.
  • External validation of the L1-SVM model achieved predictive accuracies of 76.92% for ICAM1 and 73.08% for RAET1E.

Clinical Implications

The findings suggest that CT-derived radiomic features can serve as noninvasive indicators of immune activity in ccRCC. Clinicians may consider integrating these imaging biomarkers into routine assessments to better inform treatment decisions and patient management.

Conclusion

This study highlights the potential of radiogenomic analysis in ccRCC, particularly in identifying biomarkers related to NK cell cytotoxicity. Further research is warranted to validate these findings and explore their clinical applications.

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  9. Atezolizumab plus cabozantinib versus cabozantinib for patients with renal cell carcinoma after progression with prior immune checkpoint inhibitor treatment (CONTACT-03): a multicentre, randomized, open-label, phase 3 trial - PMC
  10. Cabozantinib plus nivolumab and ipilimumab in previously untreated, advanced renal cell carcinoma: final results and biomarker analyses from the phase III COSMIC-313 study - ScienceDirect
  11. Accuracy of CT-Based Radiomics Models for Preoperative Grading of Clear Cell Renal Cell Carcinoma: A Systematic Review and Meta-analysis - PubMed
  12. Clinical application of radiomics for the prediction of treatment outcome and survival in patients with renal cell carcinoma: a systematic review - PubMed
  13. Progressive natural killer cell dysfunction in advanced-stage clear-cell renal cell carcinoma and association with clinical outcomes - ScienceDirect
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