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Updated: May 19, 2026
The Use of Reverse Phase Protein Arrays (RPPA) to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Deciphering the Genomic Landscape of Renal Cell Carcinoma Brain Metastases
Betul Gok Yavuz1,2,3, Peng Li1,2, Jose A Ovando-Ricardez1,2
1Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Abstract:
Brain metastases from renal cell carcinoma (RCC) remain a major cause of morbidity and mortality, yet the genomic features associated with metastatic dissemination remain poorly understood. Whole-exome sequencing was performed on 72 RCC brain metastasis samples with matched normal. To identify candidate genomic alterations associated with brain metastasis, the genomic alterations detected in the brain metastases were compared against alterations in extracranial metastases from the MSK-ECM cohort (n=137) and primary RCC tumors from TCGA (n=432) by case-control analyses. Candidate alterations were also identified through matched-pair analyses comparing brain metastases with matched primary tumors or extracranial metastases from the same patient (n=25). A random survival forest model incorporating the candidate CNA events was developed to predict overall survival. The candidate CNAs were further evaluated using functional experimental data from MetMap and DepMap. Survival analyses were conducted to assess the prognostic relevance of these alterations. We identified recurrent CNAs enriched in RCC brain metastases, including 4q loss, 7p gain, 7q gain, 8p loss, 8q gain, 9p21.3 deletion, 12q15 amplification, and 14q loss. These alterations were associated with significantly poorer patient survival among RCC patients. A random survival forest model based on these CNA events stratified TCGA-KIRC patients into prognostically distinct risk groups (C-index = 0.64). Among the recurrent CNAs, 8p loss, 8q gain, 9p21.3 deletion were associated with increased incidence of brain metastases across multiple primary cancer types in xenograft mouse models. These alterations were also strongly associated with metastatic progression and poor prognosis across RCC, lung adenocarcinoma, breast cancer, and melanoma. These findings indicate a shared genomic basis for brain tropism and highlight the potential utility of copy-number alterations as biomarkers for risk stratification and clinical decision-making.
Insights
Genomic alterations in copy number, specifically 8p loss and 8q gain, are linked to brain metastases in renal cell carcinoma (RCC). These copy-number alterations (CNAs) can predict patient survival and may indicate a shared genomic basis for brain tropism across cancers.
Area of Science:
- Genomics
- Oncology
- Cancer Metastasis
Background:
- Brain metastases from renal cell carcinoma (RCC) significantly increase morbidity and mortality.
- The genomic underpinnings of RCC brain metastasis remain largely uncharacterized.
Purpose of the Study:
- To identify genomic alterations associated with the development of brain metastases in RCC.
- To evaluate the prognostic significance and potential as biomarkers of identified copy-number alterations (CNAs).
Main Methods:
- Whole-exome sequencing of 72 RCC brain metastasis samples.
- Comparative genomic analyses against extracranial metastases and primary tumors.
- Matched-pair analyses and survival analyses.
- Random survival forest modeling for prognosis prediction.
Main Results:
- Recurrent CNAs enriched in brain metastases include 4q loss, 7p gain, 7q gain, 8p loss, 8q gain, 9p21.3 deletion, 12q15 amplification, and 14q loss.
- These CNAs were associated with significantly poorer patient survival in RCC.
- A CNA-based model stratified patients into distinct risk groups (C-index = 0.64).
- Specific CNAs (8p loss, 8q gain, 9p21.3 deletion) correlated with brain metastasis incidence and poor prognosis across multiple cancer types.
Conclusions:
- Identified CNAs are enriched in RCC brain metastases and are linked to poor outcomes.
- These CNAs may represent a shared genomic basis for brain tropism.
- CNAs show potential as biomarkers for risk stratification and clinical decision-making in metastatic cancers.
