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Updated: Mar 8, 2026

A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
Functional PTGS2 polymorphism-based models as novel predictive markers in metastatic renal cell carcinoma patients
Arancha Cebrián1, Teresa Gómez Del Pulgar1, María José Méndez-Vidal2
1Fundación Jiménez Díaz University Hospital, Madrid, Spain.
Abstract:
Sunitinib is the currently standard treatment for metastatic renal cell carcinoma (mRCC). Multiple candidate predictive biomarkers for sunitinib response have been evaluated but none of them has been implemented in the clinic yet. The aim of this study was to analyze single nucleotide polymorphisms (SNPs) in genes linked to mode of action of sunitinib and immune response as biomarkers for mRCC. This is a multicenter, prospective and observational study involving 20 hospitals. Seventy-five mRCC patients treated with sunitinib as first line were used to assess the impact of 63 SNPs in 31 candidate genes on clinical outcome. rs2243250 (IL4) and rs5275 (PTGS2) were found to be significantly associated with shorter cancer-specific survival (CSS). Moreover, allele C (rs5275) was associated with higher PTGS2 expression level confirming its functional role. Combination of rs5275 and rs7651265 or rs2243250 for progression free survival (PFS) or CSS, respectively, was a more valuable predictive biomarker remaining significant after correction for multiple testing. It is the first time that association of rs5275 with survival in mRCC patients is described. Two-SNP models containing this functional variant may serve as more predictive biomarkers for sunitinib and could suppose a clinically relevant tool to improve the mRCC patient management.
Insights
This study identifies specific genetic markers (SNPs) that predict treatment response in metastatic renal cell carcinoma (mRCC) patients receiving sunitinib. These findings may lead to improved patient management and personalized cancer therapy.
Area of Science:
- Oncology
- Pharmacogenomics
- Genetics
Background:
- Sunitinib is a standard treatment for metastatic renal cell carcinoma (mRCC).
- Predictive biomarkers for sunitinib response are needed for clinical application.
- Current biomarkers for sunitinib efficacy in mRCC are lacking.
Purpose of the Study:
- To investigate single nucleotide polymorphisms (SNPs) in genes related to sunitinib's mechanism of action and immune response.
- To evaluate these SNPs as predictive biomarkers for clinical outcomes in mRCC patients treated with sunitinib.
Main Methods:
- A multicenter, prospective, observational study involving 75 mRCC patients treated with first-line sunitinib.
- Analysis of 63 SNPs in 31 candidate genes.
- Assessment of the impact of SNPs on cancer-specific survival (CSS) and progression-free survival (PFS).
Main Results:
- rs2243250 (IL4) and rs5275 (PTGS2) SNPs were significantly associated with shorter CSS.
- Allele C of rs5275 correlated with higher PTGS2 expression, indicating functional relevance.
- Combined SNP models (e.g., rs5275 with rs7651265 or rs2243250) showed improved predictive value for PFS and CSS.
Conclusions:
- The study identified novel SNP biomarkers (rs5275, rs2243250) associated with sunitinib treatment outcomes in mRCC.
- The functional variant rs5275 and two-SNP models show potential as clinically relevant predictive biomarkers.
- These findings could enhance personalized management strategies for mRCC patients undergoing sunitinib therapy.
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