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Angiogenic and immune predictors of neoadjuvant axitinib response in renal cell carcinoma with venous tumour thrombus

Author

Listed:
  • Rebecca Wray

    (University of Cambridge
    University of Cambridge
    University of Cambridge)

  • Hania Paverd

    (University of Cambridge
    University of Cambridge
    University of Cambridge
    Cambridge University Hospitals NHS Foundation Trust)

  • Ines Machado

    (University of Cambridge
    University of Cambridge)

  • Johanna Barbieri

    (University of Cambridge)

  • Farhana Easita

    (University of Cambridge)

  • Abigail R. Edwards

    (University of Cambridge)

  • Ferdia A. Gallagher

    (Cambridge University Hospitals NHS Foundation Trust
    University of Cambridge)

  • Iosif A. Mendichovszky

    (Cambridge University Hospitals NHS Foundation Trust
    University of Cambridge)

  • Thomas J. Mitchell

    (University of Cambridge
    Cambridge University Hospitals NHS Foundation Trust
    University of Cambridge)

  • Maike Roche

    (University of Cambridge)

  • Jacqueline D. Shields

    (University of Nottingham Biodiscovery Institute)

  • Stephan Ursprung

    (Cambridge University Hospitals NHS Foundation Trust
    University of Cambridge)

  • Lauren Wallis

    (University of Warwick)

  • Anne Y. Warren

    (Cambridge University Hospitals NHS Foundation Trust)

  • Sarah J. Welsh

    (Royal Devon University Healthcare NHS Foundation Trust)

  • Mireia Crispin-Ortuzar

    (University of Cambridge
    University of Cambridge
    University of Cambridge)

  • Grant D. Stewart

    (University of Cambridge
    Cambridge University Hospitals NHS Foundation Trust
    University of Cambridge)

  • James O. Jones

    (University of Cambridge
    University of Cambridge
    Cambridge University Hospitals NHS Foundation Trust
    University of Cambridge)

Abstract

Venous tumour thrombus (VTT), where the primary tumour invades the renal vein and inferior vena cava, affects 10–15% of renal cell carcinoma (RCC) patients. Curative surgery for VTT is high-risk, but neoadjuvant therapy may improve outcomes. The NAXIVA trial demonstrated a 35% VTT response rate after 8 weeks of neoadjuvant axitinib, a VEGFR-directed therapy. However, understanding non-response is critical for better treatment. Here we show that response to axitinib in this setting is characterised by a distinct and predictable set of features. We conduct a multiparametric investigation of samples collected during NAXIVA using digital pathology, flow cytometry, plasma cytokine profiling and RNA sequencing. Responders have higher baseline microvessel density and increased induction of VEGF-A and PlGF during treatment. A multi-modal machine learning model integrating features predict response with an AUC of 0.868, improving to 0.945 when using features from week 3. Key predictive features include plasma CCL17 and IL-12. These findings may guide future treatment strategies for VTT, improving the clinical management of this challenging scenario.

Suggested Citation

  • Rebecca Wray & Hania Paverd & Ines Machado & Johanna Barbieri & Farhana Easita & Abigail R. Edwards & Ferdia A. Gallagher & Iosif A. Mendichovszky & Thomas J. Mitchell & Maike Roche & Jacqueline D. Sh, 2025. "Angiogenic and immune predictors of neoadjuvant axitinib response in renal cell carcinoma with venous tumour thrombus," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58436-8
    DOI: 10.1038/s41467-025-58436-8
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    References listed on IDEAS

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    1. Stephen-John Sammut & Mireia Crispin-Ortuzar & Suet-Feung Chin & Elena Provenzano & Helen A. Bardwell & Wenxin Ma & Wei Cope & Ali Dariush & Sarah-Jane Dawson & Jean E. Abraham & Janet Dunn & Louise H, 2022. "Multi-omic machine learning predictor of breast cancer therapy response," Nature, Nature, vol. 601(7894), pages 623-629, January.
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