A CpG-methylation-based assay to predict survival in clear cell renal cell carcinoma

Abstract

Clear cell renal cell carcinomas (ccRCCs) display divergent clinical behaviours. Molecular markers might improve risk stratification of ccRCC. Here we use, based on genome-wide CpG methylation profiling, a LASSO model to develop a five-CpG-based assay for ccRCC prognosis that can be used with formalin-fixed paraffin-embedded specimens. The five-CpG-based classifier was validated in three independent sets from China, United States and the Cancer Genome Atlas data set. The classifier predicts the overall survival of ccRCC patients (hazard ratio=2.96−4.82; P=3.9 × 10−6−2.2 × 10−9), independent of standard clinical prognostic factors. The five-CpG-based classifier successfully categorizes patients into high-risk and low-risk groups, with significant differences of clinical outcome in respective clinical stages and individual ‘stage, size, grade and necrosis' scores. Moreover, methylation at the five CpGs correlates with expression of five genes: PITX1, FOXE3, TWF2, EHBP1L1 and RIN1. Our five-CpG-based classifier is a practical and reliable prognostic tool for ccRCC that can add prognostic value to the staging system.

The epigenetic landscape of renal cancer

“…Analysis of genome-wide epigenetic profiles of different renal tumour types has identified methylation signatures (epi-signatures) that can identify specific subtypes of RCC 233 .…”

Prognostic DNA Methylation Markers for Renal Cell Carcinoma: A Systematic Review

“…Furthermore, combination of methylation of GREM1, LAD1, NEFH and NEURL in a four-marker panel showed superior prognostic value as compared to the markers alone (Supplementary Table 4), indicating that the combination of several markers can improve predictive capacity. This was also shown by Wei et al [11] who developed a prognostic risk score based on a five-CpG-based-classifier encompassing methylation of PITX1, FOXE3, TWF2, RIN1 and EHBP1L1. Patients in the high-risk group had poorer OS as compared with patients in the low-risk group (HR: 4.27, 95% CI: 2.18-8.37), also when corrected for age, TNM stage, tumor grade and tumor necrosis (HR: 4.10; 95% CI: 2.05-8.19).…”

“…The currently used models for predicting patient outcome, such as the University of California Los Angeles (UCLA) Integrated Staging System (UISS) and the Stage Size Grade Necrosis (SSIGN) Risk Score [5][6][7][8], are based on clinicopathological features (Tumor, Node, Metastasis [TNM] stage, tumor size, tumor grade, presence of necrosis and Eastern Cooperative Oncology Group [ECOG] performance status). Despite high predictive capacity of these models (C-statistics of 0.809 [9] and 0.823 [10], respectively), patients with similar clinicopathological features or risk scores can still have divergent outcomes [11]. Therefore, addition of molecular markers to the current prognostic models could improve their prognostic value, which was demonstrated for ClearCode34 [12].…”

Genome-wide DNA methylation analysis reveals a prognostic classifier for non-metastatic colorectal cancer (ProMCol classifier)

“…Differentially methylated CpG sites between the tumour and normal mucosa tissue were identified and used as starting point for the survival analysis, as was done before by Wei et al 17. After investigation of the prognostic information of single CpG sites, a prognostic classifier for patients with non-metastatic CRC, the ProMCol classifier, was constructed.…”