Current Landscape of Genomic Biomarkers in Clear Cell Renal Cell Carcinoma - Beyond the Abstract
While the von-Hippel Lindau (VHL) gene mutation is the most commonly associated with ccRCC, other genes such as PBRM1, SETD2, BAP1, and KDM5C also play a role. These mutations vary in frequency and have been shown to affect patient outcomes differently. We discuss the value of these mutations in predicting RCC therapy response, with PBRM1 mutation found to be significantly enriched in the tumors of ccRCC patients with clinical benefit from nivolumab treatment.
Chromosomal copy number variations (CNVs) are also frequently observed in clear cell renal cell carcinoma (ccRCC), with 3p loss being the most common alteration and gain of 8q and loss of 9p being associated with adverse clinicopathologic features and worse outcomes, but their use as prognostic biomarkers is currently limited.
While PD-L1 expression may be useful as a predictor of responses to immunotherapy in other cancers, in RCC, results have been inconsistent across clinical trials. Tumor mutation burden and neoantigen burden have also been investigated as potential biomarkers, but low mutational burden in RCC may explain the lack of correlation with treatment response.
In addition, multigene signatures are a promising and well-studied group of biomarkers in clear cell renal cell carcinoma (ccRCC). Three well-developed signatures are ClearCode34, the Cell Cycle Progression (CCP) Score, and the 16-gene recurrence score (RS). ClearCode34 is a genomic classifier that can define two subtypes of ccRCC, good risk, and poor risk, and has been shown to be a strong predictor of recurrence and mortality. The CCP score assesses the expression of genes involved in cell cycle progression and has been shown to be associated with progression to metastatic disease, recurrence, and disease-specific mortality. The 16-gene RS is a tissue-based assay that can identify high-risk stage I and low-risk stage II-III patients, and it has been validated as a predictor of tumor recurrence, disease-free survival, and cancer-specific survival in both stage I-III and high-risk stage III patients. Although these biomarkers have been well validated in retrospective studies, they are not yet used in routine clinical practice.
Finally, renal cell carcinoma (RCC) has a rich immune landscape containing cells of the innate and adaptive immune systems that influence tumor growth and could be targeted for therapy or serve as prognostic biomarkers. Studies have identified T cell infiltration and major histocompatibility complex (MHC) class I antigen expression machinery as important factors in RCC outcomes, with T cell-enriched tumors having the worst cancer-specific survival (CSS). CD8+ T cells have been found to play a crucial role in the RCC tumor immune microenvironment (TIME) by influencing tumor progression and responsiveness to immunotherapy, while tumor-associated macrophages (TAMs) have been linked to tyrosine kinase inhibitor (TKI) outcomes and resistance to immunotherapy.
In summary, this review presents a narrative synthesis of genomic biomarkers in clear cell renal cell carcinoma, highlighting the limitations of existing biomarkers and the need for collaborative efforts to evaluate them. While there are several genomic biomarkers developed and studied for kidney cancer, none are currently used in clinical practice due to challenges in adoption and validation; however, with advances in molecular understanding and novel sequencing platforms, personalized medicine in kidney cancer may become a reality.
Written by: Brittney H. Cotta, MD, Department of Urology, Michigan Medicine, Ann Arbor, MI
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