Adding Genomic Factors to MSKCC Risk Model in Metastatic Renal Cell Carcinoma


Key Points

  • Mutation in BAP1 or TP53 or both and absence of any mutation in PBRM1 were prognostic for overall survival.
  • The addition of genomic information improved the predictive ability of the MSKCC risk model for overall and progression-free survival.

In a study reported in The Lancet Oncology, Voss et al found that adding the mutation status of prognostic genes to the Memorial Sloan Kettering Cancer Center (MSKCC) risk model improved the prognostic performance of the model in patients with advanced renal cell carcinoma.

The study involved previously untreated patients with advanced or metastatic renal cell carcinoma who received tyrosine kinase inhibitor therapy and who were evaluable for mutation status and clinical outcome from the CMPARZ trial (training cohort; n = 357) and the RECORD-3 trial (validation cohort; n = 258). In the training cohort, tumor tissue was used to evaluate somatic mutations by next-generation sequencing, with the association of clinical outcomes and mutation status for six genes of interest (BAP1, PBRM1, TP53, TERT, KDM5C, and SETD2) being evaluated. Genes with prognostic value were added to the MSKCC risk model to create a genomically annotated model.

Performance of Genomically Annotated Model

In the training cohort, any mutation in BAP1 or TP53 or both and the absence of any mutation in PBRM1 were prognostic for overall survival. The hazard ratio for TP53 wild-type/BAP1 mutant, TP53 mutant/BAP1 wild-type, or TP53 mutant/BAP1 mutant vs TP53 wild-type/BAP1 wild-type was 1.57 (P = .0008); the hazard ratio for PBRM1 wild-type vs PBRM1 mutant was 1.58 (P = .0035).

When the mutation status of each of the 3 genes was added to the MSKCC risk model, risk distribution in the training cohort changed from 87 (24%) of 357 patients at favorable risk, 217 (61%) at intermediate risk, and 53 (15%) at poor risk in the MSKCC risk model alone to a 4-risk group model consisting of 36 (10%) of 357 at favorable risk, 77 (22%) at good risk, 108 (30%) at intermediate risk, and 136 (38%) at poor risk. The addition of the genomic information improved prediction for overall survival (C-index = 0.595 for original model vs 0.637 for new model) and progression-free survival (C-index = 0.567 vs 0.602), with adequate discrimination of patients having objective response (P = .03 for original model, P = .0014 for new model).

In the validation cohort, C-index values for overall survival with the original vs new model were 0.658 vs 0.670. Median overall survival was 34.9 months among patients redistributed from the intermediate-risk group to the good-risk group, 27.7 months in those remaining in the intermediate-risk group, and 16.9 months for those redistributed from the intermediate- to poor-risk group.

The investigators concluded, “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.”

The study was funded by Novartis Pharmaceuticals Corporation, MSKCC Support Grant/Core Grant, and J. Randall & Kathleen L. MacDonald Research Fund.

Martin H. Voss, MD, of Memorial Sloan Kettering Cancer Center, is the corresponding author for The Lancet Oncology article.

Disclosure: See the study authors’ full disclosures at

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