Prognostic and predictive biomarkers for metastatic renal cell carcinoma

Abstract

Several prognostic models incorporating serum biomarkers to estimate patient survival have been established for metastatic renal cell carcinoma. Interim advancements in biomarker research have highlighted much additional serum, gene mutation, genetic expression signatures, and histologic biomarkers that predict clinical outcomes and response to treatments. We, therefore, reviewed biomarkers associated with overall, cancer-specific, progression-free, and disease-free survival, overall response, and time to treatment failure rate in adult populations with metastatic renal cell carcinoma. We reviewed human studies reporting associations between biomarkers and clinical outcomes. Data were abstracted via standardized form, then reported with hazard ratios and confidence intervals where appropriate, subdivided by biomarker type (serum, gene mutation, genetic expression, and histologic). We identified a range of newer biomarkers that have clinical associations with prognostic and predictive outcomes. Beyond biomarkers used in modern risk models, those consistently associated with prognosis included serum levels of CAIX, COP-NLR, CRP, s-TATI, and VEGF, gene mutations in BAP1, CDKN2A, CIMP/FH, and TERT, gene expression of ERV and NQO1, and histologic macrophage infiltration and expression of CAIX and PDL1. Biomarkers consistently associated with the response to targeted antiangiogenic therapy included serum CRP, mutations in MET, PBRM-1, BAP1, and the mTOR pathway, TERT promoter mutations, and expression of PTEN and angiogenic gene signatures. Gene expression of hERV, T-effector, and immunogenic signatures have been associated with improved response to immune checkpoint inhibition. Future models should incorporate well-studied biomarkers to help clinicians predict outcomes and treatment responses for patients with metastatic renal cell carcinoma.

Keywords

Carcinoma / renal cell / biomarkers / precision medicine / patient-specific modeling / neoplasms

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