Esteban Emilio, Exposito Francisco, Crespo Guillermo, Lambea Julio, Pinto Alvaro, Puente Javier, Arranz Jose A, Redrado Miriam, Rodriguez-Antona Cristina, de Andrea Carlos, Lopez-Brea Marta, Redin Esther, Rodriguez Angel, Serrano Diego, Garcia Jorge, Grande Enrique, Castellano Daniel, Calvo Alfonso
Medical Oncology Department, Hospital Central de Asturias, 33011 Oviedo, Spain.
IDISNA and Program in Solid Tumors, Center for Applied Medical Research (CIMA), University of Navarra, 31008 Pamplona, Spain.
Cancers (Basel). 2021 Jun 7;13(11):2849. doi: 10.3390/cancers13112849.
Sunitinib and pazopanib are standard first-line treatments for patients with metastatic renal cell carcinoma (mRCC). Nonetheless, as the number of treatment options increases, there is a need to identify biomarkers that can predict drug efficacy and toxicity. In this prospective study we evaluated a set of biomarkers that had been previously identified within a secretory signature in mRCC patients. This set includes tumor expression of c-Met and serum levels of HGF, IL-6, IL-8, CXCL9, CXCL10 and CXCL11. Our cohort included 60 patients with mRCC from 10 different Spanish hospitals who received sunitinib ( = 51), pazopanib ( = 4) or both ( = 5). Levels of biomarkers were studied in relation to response rate, progression-free survival (PFS) and overall survival (OS). High tumor expression of c-Met and high basal serum levels of HGF, IL-6, CXCL11 and CXCL10 were significantly associated with reduced PFS and/or OS. In multivariable Cox regression analysis, CXCL11 was identified as an independent biomarker predictive of shorter PFS and OS, and HGF was an independent predictor of reduced PFS. Correlation analyses using our cohort of patients and patients from TCGA showed that HGF levels were significantly correlated with those of IL-6, CXCL11 and CXCL10. Bioinformatic protein-protein network analysis revealed a significant interaction between these proteins, all this suggesting a coordinated expression and secretion. We also developed a prognostic index that considers this group of biomarkers, where high values in mRCC patients can predict higher risk of relapse (HR 5.28 [2.32-12.0], < 0.0001). In conclusion, high plasma HGF, CXCL11, CXCL10 and IL-6 levels are associated with worse outcome in mRCC patients treated with sunitinib or pazopanib. Our findings also suggest that these factors may constitute a secretory cluster that acts coordinately to promote tumor growth and resistance to antiangiogenic therapy.
舒尼替尼和帕唑帕尼是转移性肾细胞癌（mRCC）患者的标准一线治疗药物。然而，随着治疗选择的增加，有必要识别能够预测药物疗效和毒性的生物标志物。在这项前瞻性研究中，我们评估了一组先前在mRCC患者的分泌特征中鉴定出的生物标志物。这组标志物包括c-Met的肿瘤表达以及血清中HGF、IL-6、IL-8、CXCL9、CXCL10和CXCL11的水平。我们的队列包括来自10家不同西班牙医院的60例mRCC患者，他们接受了舒尼替尼（n = 51）、帕唑帕尼（n = 4）或两者（n = 5）治疗。研究了生物标志物水平与缓解率、无进展生存期（PFS）和总生存期（OS）的关系。c-Met的高肿瘤表达以及HGF、IL-6、CXCL11和CXCL10的高基础血清水平与PFS和/或OS缩短显著相关。在多变量Cox回归分析中，CXCL11被确定为预测PFS和OS缩短的独立生物标志物，而HGF是PFS缩短的独立预测因子。使用我们的患者队列和来自TCGA的患者进行的相关性分析表明，HGF水平与IL-6、CXCL11和CXCL10的水平显著相关。生物信息学蛋白质-蛋白质网络分析揭示了这些蛋白质之间的显著相互作用，所有这些表明它们存在协同表达和分泌。我们还开发了一个考虑这组生物标志物的预后指数，mRCC患者中该指数的高值可预测更高的复发风险（HR 5.28 [2.32 - 12.0]，P < 0.0001）。总之，血浆中HGF、CXCL11、CXCL10和IL-6的高水平与接受舒尼替尼或帕唑帕尼治疗的mRCC患者的不良预后相关。我们的研究结果还表明，这些因素可能构成一个分泌簇，协同作用以促进肿瘤生长和对抗血管生成治疗的耐药性。
