Assistant Professor of Urology University of Michigan
Introduction: There is a critical need to develop prognostic biomarkers to improve the management of patients with clear cell renal cell carcinoma (ccRCC). This study aims to develop and validate gene expression-based biomarkers associated with recurrent disease to facilitate risk-stratification of ccRCC.
Methods: We retrospectively identified 110 patients who underwent radical nephrectomy for localized ccRCC. Patients who recurred were matched based on grade/stage to patients without recurrence. RNA next-generation sequencing (NGS) was performed on formalin-fixed paraffin-embedded (FFPE) tissue using whole-transcriptome sequencing on the illumina platform. We developed a gene signature to predict recurrence/progression-free survival (PFS) using a 15-fold lasso and elastic-net regularized linear Cox model. We derived Myriad Prolaris™ commercially available 31-gene cell cycle proliferation (mxCCP) score using RNA-seq data for each patient. Validation datasets were assembled: dataset #1 - The Cancer Genome Atlas ccRCC (TCGA, n= 382) and dataset #2 [Seishi Ogawa Japanese (n=87), International Cancer Genome Consortium (ICGC; n=81), GSE22541 (n=20) and Clinical Proteomics Tumor Analysis Consortium (CPTAC; n=91)]. Kaplan-Meier (KM) curves and multivariate Cox proportional hazard testing were then used to validate the independent prognostic impact of the gene signature on PFS and disease specific survival (DSS).
Results: After quality control, the training cohort comprised 50 patients with recurrence and 41 patients without, with a median follow-up 26 and 36 months, respectively. There were no significant differences between age, sex, grade, and stage between groups (all p > 0.05). We developed a 15-gene signature which was the only variable independently associated with worse PFS and DSS (PFS: HR=11.08, CI=4.9-25.1; DSS: HR=9.67, CI=3.4-27.7), adjusting for clinical-pathologic variables and mxCCP score. The 15-gene signature was also independently associated with worse PFS and DSS in both validation datasets [Validation #1 (n=382), PFS: HR=2.6, CI=1.6-4.3; DSS: HR=3; CI=1.4-6.1 and Validation #2 (n=279), PFS: HR=1.6, CI=0.7-3.6; DSS: HR=3.1; CI=1.5-6.4] adjusting for clinical-pathologic variables and mxCCP score.
Conclusions: We developed and validated a novel 15-gene prognostic signature to improve risk stratification of patients with ccRCC. This signature has the potential to facilitate optimal treatment allocation and may lead to the development of novel therapeutic targets.
Source of Funding: National Comprehensive Cancer Network
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