Comment
Although most patients with renal cell carcinoma have localised tumours that can be cured with surgery, many patients experience disease relapse caused by local recurrence or distant metastases. The occurrence of metastatic disease is the single most important surrogate event predictive of death from this disease. Currently, no consensus has been established for standardised follow-up protocols to detect early asymptomatic metastatic relapse, therefore, an obvious rationale exists for the identification of clinical, genetic, or molecular biomarkers that enable the identification of patients at risk for relapse. A plethora of potential clinical, genetic, and molecular biomarkers for recurrence prognostication have been published in recent years.1,2 Classic prognostication models like those from Frank and colleagues3 or Sorbellini and colleagues4 used only standard clinicopathological factors as prognostic factors to predict recurrence. Klatte and colleagues5 developed a model that combined clinicopathological features with several molecular markers and showed a concordance index of 0·904%. The same group also created a prognostic model based on clinicopathological parameters and the loss of chromosome 9p,6 which had a concordance index of 0·89. However, both studies were based on a modest sample size and the results were not validated. In The Lancet Oncology, Brian Rini and colleagues7 describe the identification and validation of a 16-gene signature (recurrence score) that showed improved recurrence prognostication in patients with localised clear-cell renal cell carcinoma when compared with a model based on clinicopathological features alone. The authors showed that the concordance index increased from 0·74 when the Leibovich score alone was used to 0·81 with the inclusion of their 16-gene signature. The authors used extensive genetic tests and straightforward methods to analyse both a large development cohort and an external multicentric validation cohort. These clear strengths, combined with the fact that the authors re-reviewed pathologies before patients were included in the study, distinguish this investigation from previous studies. Rini and colleagues’ findings also provide insight into the biology of renal cell carcinoma. Genes that were found to be prognostically relevant are members of
vascular, immune response, inflammation, cell cycle progression, and proliferation pathways. These results concur with previous findings suggesting that hypoxic renal cell carcinomas display more aggressive features than vascularised tumours.8,9 As existing targeted treatment strategies mainly tackle angiogenesis pathways, these treatments might preferentially target vascularised tumours and be ineffective in the treatment of the highly aggressive hypoxic renal cell carcinomas. Although Rini and colleagues’ study is extensive, it has some limitations that need further assessment. Due to reclassification of pathology or insufficient tissue, a total of 1371 (59%) of 2313 patients were excluded from model development for clinical or pathological reasons. Furthermore, the retrospective analysis included patients who were treated between 1985 and 2003 in the development cohort, and between 1995 and 2007 in the validation cohort. Follow-up was not standardised across all institutions, and no centralised review and confirmation of recurrence sites could be done during these long periods. Additionally, other prognostic models that use only classical clinicopathological features have shown concordance indices of 0·80–0·82, which were similar to that reported in this study (whereas surely we would hope for a clear improvement with the use of new biomarkers).3,4 Finally, during a median of follow-up of 6·2 years, only 221 (23%) of 942 patients in the development cohort had disease recurrence. However, this finding is not unexpected because many patients with renal cell carcinoma have late relapse (>5 years after their initial diagnosis).10 The 2013 ARISER trial11 investigated the adjuvant use of the monoclonal chimeric antibody girentuximab that targets carbonic anhydrase IX in patients with renal cell carcinoma with a high risk of recurrence. Although the study did not meet its primary endpoint to improve recurrence-free survival, it was the largest randomised trial to monitor disease recurrence in this disease, since all prognostic models that had been developed previously were created based on retrospective data. The ARISER trial showed that the median time to recurrence was 71·4 months, which is much longer than expected based on retrospective data. Similar data were recently presented in the adjuvant ASSURE trial.12 In Rini and colleagues’ study, the potential median disease-free
www.thelancet.com/oncology Published online May 13, 2015 http://dx.doi.org/10.1016/S1470-2045(15)70227-5
Steve Gschmeissner/Science Photo Library
Prognostication in localised renal cell carcinoma
Lancet Oncol 2015 Published Online May 13, 2015 http://dx.doi.org/10.1016/ S1470-2045(15)70227-5 See Online/Articles http://dx.doi.org/10.1016/ S1470-2045(15)70167-1
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Comment
survival boundary has not yet been reached, and therefore the performance of the 16-gene signature needs to be assessed with longer term follow-up. Finally, the clinical relevance of the recurrence score remains to be confirmed in a randomised trial, as has been done for other prognostic scores like the International Metastatic Renal Cell Carcinoma Database Consortium risk model. Collectively, the elegant study by Rini and colleagues provides an impressive level of evidence for a 16 gene signature as a prognostic instrument in recurrence prognostication. The test could be offered provisionally to patients as information complimentary to standard clincopathologic variable. Going forward, it will be important for basic scientists to use the very valuable genetic data to undertake mechanistic studies to obtain new potential targets for adjuvant therapies. These therapies are urgently needed because all adjuvant trials for patients with high risk renal cell carcinoma have been negative thus far.
We declare no competing interests.
*Nils Kroeger, Uwe Zimmermann, Martin Burchardt, Allan J Pantuck
11
Department of Urology, University Medicine at the Ernst-Moritz Arndt University, 17489 Greifswald, Germany (NK, UZ, MB); and Institute of Urologic Oncology, Department of Urology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA (AJP) [email protected]
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Kroeger N, Heng DY, Kattan M. Independent predictors of clinical outcomes and prediction models. In: Magi-Galluzzi C, Przybycin CG, eds. Genitourinary pathology. New York: Springer Science+Business Media, 2015: 355–72. Sun M, Shariat SF, Cheng C, et al. Prognostic factors and predictive models in renal cell carcinoma: a contemporary review. Eur Urol 2011; 60: 644–61. Frank I, Blute ML, Cheville JC, et al. A multifactorial postoperative surveillance model for patients with surgically treated clear cell renal cell carcinoma. J Urol 2003; 170: 2225–32. Sorbellini M, Kattan MW, Snyder ME, et al. A postoperative prognostic nomogram predicting recurrence for patients with conventional clear cell renal cell carcinoma. J Urol 2005; 173: 48–51. Klatte T, Seligson DB, LaRochelle J, et al. Molecular signatures of localized clear cell renal cell carcinoma to predict disease-free survival after nephrectomy. Cancer Epidemiol Biomarkers Prev 2009; 18: 894–900. Klatte T, Rao PN, de Martino M, et al. Cytogenetic profile predicts prognosis of patients with clear cell renal cell carcinoma. J Clin Oncol 2009; 27: 746–53. Rini B, Godddard A, Knezevic D, et al. A 16-gene assay to predict recurrence after surgery in localised renal cell carcinoma: an observational cohort study. Lancet Oncol 2015; published online May 13. http://dx.doi. org/10.1016/S1470-2045(15)70167-1. Brannon AR, Reddy A, Seiler M, et al. Molecular stratification of clear cell renal cell carcinoma by consensus clustering reveals distinct subtypes and survival patterns. Genes Cancer 2010; 1: 152–63. Kroeger N, Seligson DB, Klatte T, et al. Clinical, molecular, and genetic correlates of lymphatic spread in clear cell renal cell carcinoma. Eur Urol 2012; 61: 888–95. Kroeger N, Choueiri TK, Lee JL, et al. Survival outcome and treatment response of patients with late relapse from renal cell carcinoma in the era of targeted therapy. Eur Urol 2014; 65: 1086–92. Belldegrun AS, Chamie K, Kloepfer P, et al. ARISER: a randomized double blind phase III study to evaluate adjuvant cG250 treatment versus placebo in patients with high-risk ccRCC—results and implications for adjuvant clinical trials. Proc Am Soc Clin Oncol 2013; 31 (suppl): abstr 4507. Haas NB, Manola J, Uzzo RG, et al. Initial results from ASSURE (E2805): adjuvant sorafenib or sunitinib for unfavorable renal carcinoma, an ECOGACRIN-led, NCTN phase III trial. Proc Am Soc Clin Oncol 2015; 33 (suppl 7): abstr 403.
www.thelancet.com/oncology Published online May 13, 2015 http://dx.doi.org/10.1016/S1470-2045(15)70227-5
Although most patients with renal cell carcinoma have localised tumours that can be cured with surgery, many patients experience disease relapse caused by local recurrence or distant metastases. The occurrence of metastatic disease is the single most important surrogate event predictive of death from this disease. Currently, no consensus has been established for standardised follow-up protocols to detect early asymptomatic metastatic relapse, therefore, an obvious rationale exists for the identification of clinical, genetic, or molecular biomarkers that enable the identification of patients at risk for relapse. A plethora of potential clinical, genetic, and molecular biomarkers for recurrence prognostication have been published in recent years.1,2 Classic prognostication models like those from Frank and colleagues3 or Sorbellini and colleagues4 used only standard clinicopathological factors as prognostic factors to predict recurrence. Klatte and colleagues5 developed a model that combined clinicopathological features with several molecular markers and showed a concordance index of 0·904%. The same group also created a prognostic model based on clinicopathological parameters and the loss of chromosome 9p,6 which had a concordance index of 0·89. However, both studies were based on a modest sample size and the results were not validated. In The Lancet Oncology, Brian Rini and colleagues7 describe the identification and validation of a 16-gene signature (recurrence score) that showed improved recurrence prognostication in patients with localised clear-cell renal cell carcinoma when compared with a model based on clinicopathological features alone. The authors showed that the concordance index increased from 0·74 when the Leibovich score alone was used to 0·81 with the inclusion of their 16-gene signature. The authors used extensive genetic tests and straightforward methods to analyse both a large development cohort and an external multicentric validation cohort. These clear strengths, combined with the fact that the authors re-reviewed pathologies before patients were included in the study, distinguish this investigation from previous studies. Rini and colleagues’ findings also provide insight into the biology of renal cell carcinoma. Genes that were found to be prognostically relevant are members of
vascular, immune response, inflammation, cell cycle progression, and proliferation pathways. These results concur with previous findings suggesting that hypoxic renal cell carcinomas display more aggressive features than vascularised tumours.8,9 As existing targeted treatment strategies mainly tackle angiogenesis pathways, these treatments might preferentially target vascularised tumours and be ineffective in the treatment of the highly aggressive hypoxic renal cell carcinomas. Although Rini and colleagues’ study is extensive, it has some limitations that need further assessment. Due to reclassification of pathology or insufficient tissue, a total of 1371 (59%) of 2313 patients were excluded from model development for clinical or pathological reasons. Furthermore, the retrospective analysis included patients who were treated between 1985 and 2003 in the development cohort, and between 1995 and 2007 in the validation cohort. Follow-up was not standardised across all institutions, and no centralised review and confirmation of recurrence sites could be done during these long periods. Additionally, other prognostic models that use only classical clinicopathological features have shown concordance indices of 0·80–0·82, which were similar to that reported in this study (whereas surely we would hope for a clear improvement with the use of new biomarkers).3,4 Finally, during a median of follow-up of 6·2 years, only 221 (23%) of 942 patients in the development cohort had disease recurrence. However, this finding is not unexpected because many patients with renal cell carcinoma have late relapse (>5 years after their initial diagnosis).10 The 2013 ARISER trial11 investigated the adjuvant use of the monoclonal chimeric antibody girentuximab that targets carbonic anhydrase IX in patients with renal cell carcinoma with a high risk of recurrence. Although the study did not meet its primary endpoint to improve recurrence-free survival, it was the largest randomised trial to monitor disease recurrence in this disease, since all prognostic models that had been developed previously were created based on retrospective data. The ARISER trial showed that the median time to recurrence was 71·4 months, which is much longer than expected based on retrospective data. Similar data were recently presented in the adjuvant ASSURE trial.12 In Rini and colleagues’ study, the potential median disease-free
www.thelancet.com/oncology Published online May 13, 2015 http://dx.doi.org/10.1016/S1470-2045(15)70227-5
Steve Gschmeissner/Science Photo Library
Prognostication in localised renal cell carcinoma
Lancet Oncol 2015 Published Online May 13, 2015 http://dx.doi.org/10.1016/ S1470-2045(15)70227-5 See Online/Articles http://dx.doi.org/10.1016/ S1470-2045(15)70167-1
1
Comment
survival boundary has not yet been reached, and therefore the performance of the 16-gene signature needs to be assessed with longer term follow-up. Finally, the clinical relevance of the recurrence score remains to be confirmed in a randomised trial, as has been done for other prognostic scores like the International Metastatic Renal Cell Carcinoma Database Consortium risk model. Collectively, the elegant study by Rini and colleagues provides an impressive level of evidence for a 16 gene signature as a prognostic instrument in recurrence prognostication. The test could be offered provisionally to patients as information complimentary to standard clincopathologic variable. Going forward, it will be important for basic scientists to use the very valuable genetic data to undertake mechanistic studies to obtain new potential targets for adjuvant therapies. These therapies are urgently needed because all adjuvant trials for patients with high risk renal cell carcinoma have been negative thus far.
We declare no competing interests.
*Nils Kroeger, Uwe Zimmermann, Martin Burchardt, Allan J Pantuck
11
Department of Urology, University Medicine at the Ernst-Moritz Arndt University, 17489 Greifswald, Germany (NK, UZ, MB); and Institute of Urologic Oncology, Department of Urology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA (AJP) [email protected]
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Kroeger N, Heng DY, Kattan M. Independent predictors of clinical outcomes and prediction models. In: Magi-Galluzzi C, Przybycin CG, eds. Genitourinary pathology. New York: Springer Science+Business Media, 2015: 355–72. Sun M, Shariat SF, Cheng C, et al. Prognostic factors and predictive models in renal cell carcinoma: a contemporary review. Eur Urol 2011; 60: 644–61. Frank I, Blute ML, Cheville JC, et al. A multifactorial postoperative surveillance model for patients with surgically treated clear cell renal cell carcinoma. J Urol 2003; 170: 2225–32. Sorbellini M, Kattan MW, Snyder ME, et al. A postoperative prognostic nomogram predicting recurrence for patients with conventional clear cell renal cell carcinoma. J Urol 2005; 173: 48–51. Klatte T, Seligson DB, LaRochelle J, et al. Molecular signatures of localized clear cell renal cell carcinoma to predict disease-free survival after nephrectomy. Cancer Epidemiol Biomarkers Prev 2009; 18: 894–900. Klatte T, Rao PN, de Martino M, et al. Cytogenetic profile predicts prognosis of patients with clear cell renal cell carcinoma. J Clin Oncol 2009; 27: 746–53. Rini B, Godddard A, Knezevic D, et al. A 16-gene assay to predict recurrence after surgery in localised renal cell carcinoma: an observational cohort study. Lancet Oncol 2015; published online May 13. http://dx.doi. org/10.1016/S1470-2045(15)70167-1. Brannon AR, Reddy A, Seiler M, et al. Molecular stratification of clear cell renal cell carcinoma by consensus clustering reveals distinct subtypes and survival patterns. Genes Cancer 2010; 1: 152–63. Kroeger N, Seligson DB, Klatte T, et al. Clinical, molecular, and genetic correlates of lymphatic spread in clear cell renal cell carcinoma. Eur Urol 2012; 61: 888–95. Kroeger N, Choueiri TK, Lee JL, et al. Survival outcome and treatment response of patients with late relapse from renal cell carcinoma in the era of targeted therapy. Eur Urol 2014; 65: 1086–92. Belldegrun AS, Chamie K, Kloepfer P, et al. ARISER: a randomized double blind phase III study to evaluate adjuvant cG250 treatment versus placebo in patients with high-risk ccRCC—results and implications for adjuvant clinical trials. Proc Am Soc Clin Oncol 2013; 31 (suppl): abstr 4507. Haas NB, Manola J, Uzzo RG, et al. Initial results from ASSURE (E2805): adjuvant sorafenib or sunitinib for unfavorable renal carcinoma, an ECOGACRIN-led, NCTN phase III trial. Proc Am Soc Clin Oncol 2015; 33 (suppl 7): abstr 403.
www.thelancet.com/oncology Published online May 13, 2015 http://dx.doi.org/10.1016/S1470-2045(15)70227-5
