Literature DB >> 30416077

Genomically annotated risk model for advanced renal-cell carcinoma: a retrospective cohort study.

Martin H Voss1, Albert Reising2, Yuan Cheng2, Parul Patel2, Mahtab Marker2, Fengshen Kuo3, Timothy A Chan3, Toni K Choueiri4, James J Hsieh5, A Ari Hakimi3, Robert J Motzer3.   

Abstract

BACKGROUND: The Memorial Sloan Kettering Cancer Center (MSKCC) risk model is an established prognostic tool for metastatic renal-cell carcinoma that integrates clinical and laboratory data, but is agnostic to tumour genomics. Several mutations, including BAP1 and PBRM1, have prognostic value in renal-cell carcinoma. Using two independent clinical trial datasets of patients with metastatic renal-cell carcinoma, we aimed to study whether the addition of the mutation status for several candidate prognostic genes to the MSKCC model could improve the model's prognostic performance.
METHODS: In this retrospective cohort study, we used available formalin-fixed paraffin-embedded tumour tissue and clinical outcome data from patients with metastatic renal-cell carcinoma assigned to treatment with tyrosine kinase inhibitors in the COMPARZ trial (training cohort; n=357) and RECORD-3 trial (validation cohort; n=258). Eligible patients in both trials were treatment-naive; had histologically confirmed, advanced, or metastatic renal-cell carcinoma; and a Karnofsky performance status score of at least 70. For each cohort, data from patients in all treatment groups (sunitinib and pazopanib in the training cohort, and everolimus and sunitinib in the validation cohort) were pooled for this analysis. In the training cohort, tumour tissue was used to evaluate somatic mutations by next-generation sequencing, and the association between cancer-specific outcomes (overall survival, progression-free survival, and overall response) and the mutation status of six genes of interest (BAP1, PBRM1, TP53, TERT, KDM5C, and SETD2) was tested. Only those genes with prognostic value in this setting were added to the MSKCC risk model to create a genomically annotated version. The validation cohort was used to independently test the prognostic value of the annotated model compared with the original MSKCC risk model.
FINDINGS: 357 (32%) of 1110 patients assigned to protocol treatment in the COMPARZ study between August, 2008, and September, 2011, were evaluable for mutation status and clinical outcomes in the training cohort. The independent validation cohort included 258 (55%) of 471 evaluable patients, enrolled between October, 2009, and June, 2011, on the RECORD-3 study. In the training cohort, the presence of any mutation in BAP1 or TP53, or both, and absence of any mutation in PBRM1 were prognostic in terms of overall survival (TP53wt/BAP1mut, TP53mut/BAP1wt o TP53mut/BAP1mut vs TP53wt/BAP1wt hazard ratio [HR] 1·57, 95% CI 1·21-2·04; p=0·0008; PBRM1wt vs PBRMmut, HR 1·58, 1·16-2·14; p=0·0035). The mutation status for these three prognostic genes were added to the original MSKCC risk model to create a genomically annotated version. Distribution of participants in the training cohort into the three risk groups of the original MSKCC model changed from 87 (24%) of 357 patients deemed at favourable risk, 217 (61%) at intermediate risk, and 53 (15%) at poor risk, to distribution across four risk groups in the genomically annotated risk model, with 36 (10%) of 357 deemed at favourable risk, 77 (22%) at good risk, 108 (30%) at intermediate risk, and 136 (38%) at poor risk. Addition of genomic information improved model performance for predicting overall survival (C-index: original model, 0·595 [95% CI 0·557-0·634] vs new model, 0·637 [0·595-0·679]) and progression-free survival (0·567 [95% CI 0·529-0·604] vs 0·602 [0·560-0·643]) with adequate discrimination of the proportion of patients who achieved an objective response (Cochran-Armitage one-sided p=0·0014). Analyses in the validation cohort confirmed the superiority of the genomically annotated risk model over the original version.
INTERPRETATION: The mutation status of BAP1, PBRM1, and TP53 has independent prognostic value in patients with advanced or metastatic renal-cell carcinoma treated with first-line tyrosine kinase inhibitors. Improved stratification of patients across risk groups by use of a genomically annotated model including the mutational status of these three genes warrants further investigation in prospective trials and could be of use as a model to stratify patients with metastatic renal-cell carcinoma in clinical trials. FUNDING: Novartis Pharmaceuticals Corporation, MSKCC Support Grant/Core Grant, and the J Randall & Kathleen L MacDonald Research Fund.
Copyright © 2018 Elsevier Ltd. All rights reserved.

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Year:  2018        PMID: 30416077      PMCID: PMC6701184          DOI: 10.1016/S1470-2045(18)30648-X

Source DB:  PubMed          Journal:  Lancet Oncol        ISSN: 1470-2045            Impact factor:   41.316


  27 in total

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2.  Adverse outcomes in clear cell renal cell carcinoma with mutations of 3p21 epigenetic regulators BAP1 and SETD2: a report by MSKCC and the KIRC TCGA research network.

Authors:  A Ari Hakimi; Irina Ostrovnaya; Boris Reva; Nikolaus Schultz; Ying-Bei Chen; Mithat Gonen; Han Liu; Shugaku Takeda; Martin H Voss; Satish K Tickoo; Victor E Reuter; Paul Russo; Emily H Cheng; Chris Sander; Robert J Motzer; James J Hsieh
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3.  Prognostic model for survival in patients with metastatic renal cell carcinoma: results from the international kidney cancer working group.

Authors:  Judith Manola; Patrick Royston; Paul Elson; Jennifer Bacik McCormack; Madhu Mazumdar; Sylvie Négrier; Bernard Escudier; Tim Eisen; Janice Dutcher; Michael Atkins; Daniel Y C Heng; Toni K Choueiri; Robert Motzer; Ronald Bukowski
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4.  Correlation of PD-L1 tumor expression and treatment outcomes in patients with renal cell carcinoma receiving sunitinib or pazopanib: results from COMPARZ, a randomized controlled trial.

Authors:  Toni K Choueiri; David J Figueroa; André P Fay; Sabina Signoretti; Yuan Liu; Robert Gagnon; Keith Deen; Christopher Carpenter; Peter Benson; Thai H Ho; Lini Pandite; Paul de Souza; Thomas Powles; Robert J Motzer
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5.  Genomic Biomarkers of a Randomized Trial Comparing First-line Everolimus and Sunitinib in Patients with Metastatic Renal Cell Carcinoma.

Authors:  James J Hsieh; David Chen; Patricia I Wang; Mahtab Marker; Almedina Redzematovic; Ying-Bei Chen; S Duygu Selcuklu; Nils Weinhold; Nancy Bouvier; Kety H Huberman; Umesh Bhanot; Michael S Chevinsky; Parul Patel; Patrizia Pinciroli; Helen H Won; Daoqi You; Agnes Viale; William Lee; A Ari Hakimi; Michael F Berger; Nicholas D Socci; Emily H Cheng; Jennifer Knox; Martin H Voss; Maurizio Voi; Robert J Motzer
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6.  Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: results from a large, multicenter study.

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7.  Clear Cell Renal Cell Carcinoma Subtypes Identified by BAP1 and PBRM1 Expression.

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8.  Circulating biomarkers and outcome from a randomised phase II trial of sunitinib vs everolimus for patients with metastatic renal cell carcinoma.

Authors:  Martin H Voss; David Chen; Mahtab Marker; A Ari Hakimi; Chung-Han Lee; James J Hsieh; Jennifer J Knox; Maurizio Voi; Robert J Motzer
Journal:  Br J Cancer       Date:  2016-02-23       Impact factor: 7.640

9.  Integrating cytokines and angiogenic factors and tumour bulk with selected clinical criteria improves determination of prognosis in advanced renal cell carcinoma.

Authors:  A J Zurita; R C Gagnon; Y Liu; H T Tran; R A Figlin; T E Hutson; A M D'Amelio; C N Sternberg; L N Pandite; J V Heymach
Journal:  Br J Cancer       Date:  2017-07-06       Impact factor: 7.640

10.  Final overall survival analysis for the phase II RECORD-3 study of first-line everolimus followed by sunitinib versus first-line sunitinib followed by everolimus in metastatic RCC.

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Journal:  Ann Oncol       Date:  2017-06-01       Impact factor: 32.976

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  41 in total

Review 1.  Epidemiology, Risk Assessment, and Biomarkers for Patients with Advanced Renal Cell Carcinoma.

Authors:  Kyrollis Attalla; Stanley Weng; Martin H Voss; A Ari Hakimi
Journal:  Urol Clin North Am       Date:  2020-06-10       Impact factor: 2.241

2.  Familial Kidney Cancer: Implications of New Syndromes and Molecular Insights.

Authors:  Maria I Carlo; A Ari Hakimi; Grant D Stewart; Gennady Bratslavsky; James Brugarolas; Ying-Bei Chen; W Marston Linehan; Eamonn R Maher; Maria J Merino; Kenneth Offit; Victor E Reuter; Brian Shuch; Jonathan A Coleman
Journal:  Eur Urol       Date:  2019-07-18       Impact factor: 20.096

3.  Update on the most promising biomarkers of response to immune checkpoint inhibitors in clear cell renal cell carcinoma.

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Journal:  World J Urol       Date:  2021-01-02       Impact factor: 4.226

Review 4.  Redefining the Role of Surgical Management of Metastatic Renal Cell Carcinoma.

Authors:  Walter R Hsiang; Patrick A Kenney; Michael S Leapman
Journal:  Curr Oncol Rep       Date:  2020-03-13       Impact factor: 5.075

5.  Systemic therapy for metastatic renal cell carcinoma-is timing everything?

Authors:  Ritesh R Kotecha; Martin H Voss
Journal:  Ann Transl Med       Date:  2019-09

Review 6.  Harnessing the Genomic Landscape of the Small Renal Mass to Guide Clinical Management.

Authors:  Andrew W Silagy; Alejandro Sanchez; Brandon J Manley; Karim Bensalah; Axel Bex; Jose A Karam; Börje Ljungberg; Brian Shuch; A Ari Hakimi
Journal:  Eur Urol Focus       Date:  2019-04-28

Review 7.  [Predictive biomarkers in oncologic uropathology].

Authors:  H Reis; T Szarvas; V Grünwald
Journal:  Pathologe       Date:  2019-05       Impact factor: 1.011

8.  Expression of PBRM1 as a prognostic predictor in metastatic renal cell carcinoma patients treated with tyrosine kinase inhibitor.

Authors:  Wen Cai; Zaoyu Wang; Biao Cai; Yichu Yuan; Wen Kong; Jin Zhang; Yonghui Chen; Qiang Liu; Yiran Huang; Jiwei Huang; Wei Xue
Journal:  Int J Clin Oncol       Date:  2019-11-13       Impact factor: 3.402

Review 9.  The evolving role of cytoreductive nephrectomy: incorporating genomics of metastatic renal cell carcinoma into treatment decisions.

Authors:  Roy Mano; Nikhil Gopal; A Ari Hakimi
Journal:  Curr Opin Urol       Date:  2019-09       Impact factor: 2.309

10.  Putative Drivers of Aggressiveness in TCEB1-mutant Renal Cell Carcinoma: An Emerging Entity with Variable Clinical Course.

Authors:  Renzo G DiNatale; Alexander N Gorelick; Vladimir Makarov; Kyle A Blum; Andrew W Silagy; Benjamin Freeman; Diego Chowell; Julian Marcon; Roy Mano; Alex Sanchez; Kyrollis Attalla; Stanley Weng; Martin Voss; Robert J Motzer; Paul Russo; Jonathan A Coleman; Victor E Reuter; Ying-Bei Chen; Timothy A Chan; Ed Reznik; Satish K Tickoo; A Ari Hakimi
Journal:  Eur Urol Focus       Date:  2019-12-06
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