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伴有静脉瘤栓的肾细胞癌新辅助阿昔替尼治疗反应的血管生成和免疫预测指标

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

作者信息

Wray Rebecca, Paverd Hania, Machado Ines, Barbieri Johanna, Easita Farhana, Edwards Abigail R, Gallagher Ferdia A, Mendichovszky Iosif A, Mitchell Thomas J, de la Roche Maike, Shields Jacqueline D, Ursprung Stephan, Wallis Lauren, Warren Anne Y, Welsh Sarah J, Crispin-Ortuzar Mireia, Stewart Grant D, Jones James O

机构信息

Early Cancer Institute, University of Cambridge, Cambridge, UK.

Department of Oncology, University of Cambridge, Cambridge, UK.

出版信息

Nat Commun. 2025 Apr 28;16(1):3870. doi: 10.1038/s41467-025-58436-8.

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.

摘要

静脉肿瘤血栓(VTT)是指原发性肿瘤侵犯肾静脉和下腔静脉,影响10%至15%的肾细胞癌(RCC)患者。VTT的根治性手术风险很高,但新辅助治疗可能会改善治疗结果。NAXIVA试验表明,在接受新辅助阿昔替尼(一种VEGFR靶向治疗)8周后,VTT的缓解率为35%。然而,了解无反应情况对于更好的治疗至关重要。在这里,我们表明在这种情况下对阿昔替尼的反应具有一组独特且可预测的特征。我们使用数字病理学、流式细胞术、血浆细胞因子分析和RNA测序对NAXIVA期间收集的样本进行了多参数研究。有反应者在治疗期间具有更高的基线微血管密度以及VEGF-A和PlGF的诱导增加。一个整合特征的多模态机器学习模型预测反应的曲线下面积(AUC)为0.868,使用第3周的特征时提高到0.945。关键预测特征包括血浆CCL17和IL-12。这些发现可能会指导VTT未来的治疗策略,改善这种具有挑战性情况的临床管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24e1/12037771/b78f6e96a7f2/41467_2025_58436_Fig1_HTML.jpg

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