Molecular Subtypes Improve Prognostic Value of International Metastatic Renal Cell Carcinoma Database Consortium Prognostic Model

Abstract

Introduction: Gene-expression signatures for prognosis have been reported in localized renal cell carcinoma (RCC). The aim of this study was to test the predictive power of two different signatures, ClearCode34, a 34-gene signature model [Eur Urol 2014;66:77-84], and an 8-gene signature model [Eur Urol 2015;67:17-20], in the setting of systemic therapy for metastatic disease.

Materials and methods: Metastatic RCC (mRCC) patients from five institutions who were part of TCGA were identified and clinical data were retrieved. We trained and implemented each gene model as described by the original study. The latter was demonstrated by faithful regeneration of a figure and results from the original study. mRCC patients were dichotomized to good or poor prognostic risk groups using each gene model. Cox proportional hazard regression and concordance index (C-Index) analysis were used to investigate an association between each prognostic risk model and overall survival (OS) from first-line therapy.

Results: Overall, 54 patients were included in the final analysis. The primary endpoint was OS. Applying the ClearCode34 model, median survival for the low-risk-ccA (n = 17)-and the high-risk-ccB (n = 37)-subtypes were 27.6 and 22.3 months (hazard ratio (HR): 2.33; p = .039), respectively. ClearCode34 ccA/ccB and International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) classifications appear to represent distinct risk criteria in mRCC, and we observed no significant overlap in classification (p > .05, chi-square test). On multivariable analyses and adjusting for IMDC groups, ccB remained independently associated with a worse OS (p = .044); the joint model of ccA/ccB and IMDC was significantly more accurate in predicting OS than a model with IMDC alone (p = .045, F-test). This was also observed in C-Index analysis; a model with both ccA and ccB subtypes had higher accuracy (C-Index 0.63, 95% confidence interval [CI] = 0.51-0.75) and 95% CIs of the C-Index that did not include the null value of 0.5 in contrast to a model with IMDC alone (0.60, CI = 0.47-0.72). The 8-gene signature molecular subtype model was a weak but insignificant predictor of survival in this cohort (p = .13). A model that included both the 8-gene signature and IMDC (C-Index 0.62, CI = 0.49-0.76) was more prognostic than IMDC alone but did not reach significance, as the 95% CI included the null value of 0.5. These two genomic signatures share no genes in common and are enriched in different biological pathways. The ClearCode34 included genes ARNT and EPAS1 (also known as HIF2a), which are involved in regulation of gene expression by hypoxia-inducible factor.

Conclusion: The ClearCode34 but not the 8-gene molecular model improved the prognostic predictive power of the IMDC model in this cohort of 54 patients with metastatic clear cell RCC. The Oncologist 2017;22:286-292 IMPLICATIONS FOR PRACTICE: The clinical and laboratory factors included in the International Metastatic Renal Cell Carcinoma Database Consortium model provide prognostic information in metastatic renal cell carcinoma (mRCC). The present study shows that genomic signatures, originally validated in localized RCC, may add further complementary prognostic information in the metastatic setting. This study may provide new insights into the molecular basis of certain mRCC subgroups. The integration of clinical and molecular data has the potential to redefine mRCC classification, enhance the understanding of mRCC biology, and potentially predict response to treatment in the future.

Keywords: Genomics; Prognosis; Signature; TCGA; mRCC.

Figure 1.

Flow chart shows selection of signatures.

Figure 2.

Heat map showing hierarchical clustering analysis of the gene expression profiles of the ClearCode34 genes in metastatic renal cell carcinoma TCGA tumors (n = 54). Most tumors (n = 37) were classified as ccB. There was no significant overlap in the ccA/ccB subtype classification and the MSKCC or IDMC risk class. Abbreviations: IMDC, International Metastatic Renal Cell Carcinoma Database Consortium; MSKCC, Memorial Sloan Kettering Cancer Center; TCGA, The Cancer Genome Atlas.

Figure 3.

mRCC tumors stratified by the ClearCode34 signature were associated with overall survival. (A): Kaplan–Meier plot of overall survival of metastatic renal cell carcinoma Cancer Genome Atlas tumors, which were stratified into two molecular subtypes using ClearCode34 gene signature. (B): Forest plot shows the C‐Index of the ClearCode34 subtype, MSKCC or IMDC risk models, alone or joint model of ClearCode34 subtype and MSKCC or IMDCC. The C‐Index is conceptually similar to receiver operating characteristic curve analysis and ranges from 0 to1 where 0.5 is null (random, no discrimination). To be statistically significant, the C‐Index should have a 95% confidence interval not including 0.5. The C‐Index is indicated by a square, and the whiskers represent the 5% and 95% quartiles. Abbreviations: CI, confidence interval; C‐Index, concordance index; HR, hazard ratio; IMDC, International Metastatic Renal Cell Carcinoma Database Consortium; MSKCC, Memorial Sloan Kettering Cancer Center.

Figure 4.

Subtypes stratified by the 8‐gene signature were not significantly associated with overall survival. (A): Kaplan–Meier plot of overall survival of mRCC TCGA tumors, which were stratified into two molecular subtypes using 8‐gene model. (B): Forest plot shows the C‐Index of the 8‐gene, MSKCC or IMDC risk models, alone or joint model of ClearCode34 and MSKCC or IMDCC. The C‐Index is conceptually similar to receiver operating characteristic curve analysis and ranges from 0 to1 where 0.5 is null (random, no discrimination). To be statistically significant, the C‐Index should have a 95% confidence interval not including 0.5. The C‐Index is indicated by a square and the whiskers represent the 5% and 95% quartiles. Abbreviations: CI, confidence interval; C‐Index, concordance index; HR, hazard ratio; IMDC, International Metastatic Renal Cell Carcinoma Database Consortium; MSKCC, Memorial Sloan Kettering Cancer Center.