Clinical utility of the S3-score for molecular prediction of outcome in non-metastatic and metastatic clear cell renal cell carcinoma

Background: Stratification of cancer patients to identify those with worse prognosis is increasingly important. Through in silico analyses, we recently developed a gene expression-based prognostic score (S3-score) for clear cell renal cell carcinoma (ccRCC), using the cell type-specific expression of 97 genes within the human nephron. Herein, we verified the score using whole-transcriptome data of independent cohorts and extend its application for patients with metastatic disease receiving tyrosine kinase inhibitor treatment. Finally, we sought to improve the signature for clinical application using qRT-PCR. Methods: A 97 gene-based S3-score (S3(97)) was evaluated in a set of 52 primary non-metastatic and metastatic ccRCC patients as well as in 53 primary metastatic tumors of sunitinib-treated patients. Gene expression data of The Cancer Genome Atlas (n = 463) was used for platform transfer and development of a simplified qRT-PCR-based 15-gene S3-score (S3(15)). This S3(15)-score was validated in 108 metastatic and non-metastatic ccRCC patients and ccRCC-derived metastases including in part several regions from one metastasis. Univariate and multivariate Cox regression stratified by T, N, M, and G were performed with cancer-specific and progression-free survival as primary endpoints. Results: The S3(97)-score was significantly associated with cancer-specific survival (CSS) in 52 ccRCC patients (HR 2.9, 95% Cl 1.0-8.0, PLog-rank = 3.3 x 10(-2)) as well as progression-free survival in sunitinib-treated patients (2.1, 1.1-4.2, PLog-rank = 2.2 x 10(-2)). The qRT-PCR based S3(15)-score performed similarly to the S3(97)-score, and was significantly associated with CSS in our extended cohort of 108 patients (5.0, 2.1-11.7, PLog-rank = 5.1 x 10(-5)) including metastatic (9.3, 1.8-50.0, PLog-rank = 2.3 x 10(-3)) and non-metastatic patients (4.4, 1.2-16.3, PLog-rank = 1.6 x 10(-2)), even in multivariate Cox regression, including clinicopathological parameters (7.3, 2.5-21.5, P-Wald = 3.3 x 10(-4)). Matched primary tumors and metastases revealed similar S3(15)-scores, thus allowing prediction of outcome from metastatic tissue. The molecular-based qRT-PCR S3(15)-score significantly improved prediction of CSS by the established clinicopathologicalbased SSIGN score (P = 1.6 x 10(-3)). Conclusion: The S3-score offers a new clinical avenue for ccRCC risk stratification in the non-metastatic, metastatic, and sunitinib-treated setting.