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Updated: Jan 25, 2026

Modeling Spontaneous Metastatic Renal Cell Carcinoma mRCC in Mice Following Nephrectomy
Published on: April 29, 2014
Identification of Predictive Genomic Biomarkers in Metastatic Clear Cell Renal Cell Carcinoma: A Comprehensive
Mimma Rizzo1, Gaetano Pezzicoli1, Camilla Porta2
1Division of Medical Oncology, AOU Consorziale Policlinico di Bari, Bari, Italy.
Purpose:
Limited validated prognostic biomarkers are available to guide treatment decisions for patients with metastatic clear cell renal cell carcinoma (mccRCC).
Methods:
This study used a US-based renal cell cancer clinicogenomic database to analyze the predictive value of genomic alterations in patients treated with immune checkpoint inhibitors (ICI) and antiangiogenic (AA) therapies. Three co-occurring gene clusters (C) were considered: (C1) VHL, SETD2, PBRM1, KDM5C, and NFE2L2; (C2) TP53, TSC1, TERT, and DNMT3A; and (C3) CDKN2A, CDKN2B, BAP1, NF2, and MTAP.
Results:
In first line, among 493 patients who underwent systemic therapy, 201 (40.8%) and 172 (34.9%) received AA monotherapy (AAm) and ICI combinations (ICI-C), respectively. TERT, TSC1, and TET2 and C2 were identified as positive predictors of response to ICI-C versus AAm. Conversely, C1 was a predictive marker for enhanced AAm efficacy. Among ICI-C, ICI + AA was more effective than ICI + ICI in patients with SETD2 alterations, and less effective in mutant TSC1.
Conclusion:
These findings require prospective validation to confirm their clinical utility.
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