Kidney CancerValidation of Gene Expression Signatures to Identify Low-risk Clear-cell Renal Cell Carcinoma Patients at Higher Risk for Disease-related Death
Introduction
Globally, the incidence of clear-cell renal cell carcinoma (ccRCC) varies widely in different regions, with the rates being higher in developed countries [1]. In the USA, approximately 62 000 new cases of ccRCC and an estimated 14 000 deaths occur annually [2]. Most patients have clinically localized disease at diagnosis, but a subset of these patients will ultimately have development of metastases and die of this disease.
Current prognostic models that use standard pathologic information perform reasonably well at predicting which patients with localized disease at presentation will ultimately have metastatic disease. However, one-third of ccRCC recurrences will be missed by following national ccRCC surveillance guidelines (PMID 25403213).
One of the more common prognostic models in ccRCC is the externally validated Mayo Clinic stage, size, grade, and necrosis (SSIGN) score [3]. At our institution, most patients (46%) have the lowest SSIGN score category of 0–3 at presentation. These patients also have the lowest rate of metastatic disease development; the estimated 5-yr and 10-yr cancer-specific survival rates for these patients are 87.8–99.4% and 77.9–97.1%, respectively. Given the many patients with a low SSIGN score at presentation, a test that can reliably identify those who ultimately die of ccRCC could improve surveillance recommendations.
Current prognostic algorithms in ccRCC do not incorporate recently identified recurrent molecular alterations [4]. We previously identified immunohistochemistry-based assays to improve patient stratification (PMID 26516698, 26300218). The incorporation of genomics-driven multimarker panels into current algorithms has the potential to: (1) identify key molecular drivers in patients who may have exhausted standard therapies, especially those with metastatic disease development, (2) predict disease recurrence, and (3) provide a molecular framework for individualized therapeutic intervention in an adjuvant setting.
The current study had two goals: (1) to improve on the prognostic algorithm of the Mayo SSIGN score, specifically in the largest group of patients with clinically localized ccRCC and those with a low Mayo SSIGN score, and (2) to incorporate molecular events into the prognostic model. We used a nested case-control method to identify patients with low-risk ccRCC who ultimately died after disease relapse. In this discovery cohort, we matched cases with controls based on Mayo SSIGN score. We then used quantitative transcriptome profiling of tissues using next-generation RNA sequencing (RNA-seq) to compare gene expression profiles in the cases versus controls. Finally, we identified a validation cohort of patients with low-risk ccRCC to test the top 50 genes that were different in the discovery cohort.
Section snippets
Patient selection
After approval from the Mayo Clinic Institutional Review Board, we queried the Mayo Clinic Renal Registry to identify patients older than 18 yr with low-risk ccRCC and available formalin-fixed paraffin-embedded (FFPE) tissue. We defined low-risk ccRCC as a Mayo SSIGN score of 0–3 [5], [6], [7]. From among the patients identified, we selected 24 patients who had relapse and died of the disease (cases) and 24 patients matched via Mayo SSIGN score (±1) and age (±10 yr) who did not have relapse
Clinical and pathologic characteristics
The discovery cohort comprised 24 patients with low-risk ccRCC with disease relapse and subsequent death and 24 matched low-risk ccRCC controls without relapse. These groups are summarized in Table 1. In this set, all controls had at least 1.9 more yr of follow-up than their respective cases. In aggregate, controls had an average of 9.2 yr of follow-up after nephrectomy (range, 3.3–20.0 yr), whereas cases had an average of 2.6 yr from nephrectomy until death (range, 0.5–10.5 yr; p < 0.001).
Discussion
Even if national ccRCC surveillance guidelines are followed, one-third of ccRCC recurrences will be missed (PMID 25403213). In this study, we identified genes that are differentially expressed in patients with low-risk ccRCC in both a discovery set and an independent validation set. To our knowledge, our study is the first to report quantitative transcriptome profiling of FFPE samples in a case-control study of low-risk ccRCC patients with disparate clinical outcomes.
Among the 10 genes we
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