Elsevier

European Urology Focus

Volume 2, Issue 6, 15 December 2016, Pages 608-615
European Urology Focus

Kidney Cancer
Validation of Gene Expression Signatures to Identify Low-risk Clear-cell Renal Cell Carcinoma Patients at Higher Risk for Disease-related Death

https://doi.org/10.1016/j.euf.2016.03.008Get rights and content

Abstract

Background

Approximately 5–10% of patients with “low-risk” clear cell renal cell carcinoma (ccRCC), as stratified by externally validated clinicopathologic prognostic algorithms, eventually have disease relapse and die. Improving prognostic algorithms for these low-risk patients could help to provide improved individualized surveillance recommendations.

Objective

To identify genes that are differentially expressed in patients with low-risk ccRCC who did and did not die of their disease.

Design, setting, and participants

Using the Mayo Clinic Renal Registry, we identified formalin-fixed paraffin-embedded samples from patients with low-risk ccRCC, as defined by Mayo Clinic stage, size, grade, and necrosis score of 0–3. We conducted a nested case-control study between patients who did (cases) and did not (controls) have ccRCC relapse and death, using two independent sets (discovery and validation). We performed RNA sequencing of all samples in the discovery set to identify differentially expressed genes. In the independent validation set, we assessed the top 50 expressed genes using the nCounter Analysis System (NanoString Technologies, Seattle, WA, USA).

Results and limitations

In the discovery set of 24 cases and 24 controls, 92 genes were differentially expressed with p < 0.001. The top 50 genes were validated in an independent set of 22 cases and 22 controls using linear mixed models. In the validation set, 10 genes remained differentially expressed between the groups.

Conclusions

RNA signatures from formalin-fixed paraffin-embedded blocks can identify patients with low-risk ccRCC who die of their disease. This finding provides an opportunity to help guide improved surveillance in patients with low-risk ccRCC.

Patient summary

In the current study we identified RNA signatures from low-risk clear cell renal cell carcinoma patients who died from this disease. Improving prognostic algorithms for these low-risk patients could help to provide improved individualized surveillance recommendations.

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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