A study found the gene mutations key in patients treated with first-line TKIs, and useful additions to a risk model that stratifies patients with mRCC.
The mutation status of three genes – BAP1, PBRM1, and TP53 – had independent prognostic value for patients with advanced or metastatic renal cell carcinoma (RCC) treated with first-line tyrosine kinase inhibitors, and was a useful additional to a risk model that stratifies patients with the disease, a new study indicated.
When mutation status of these three genes was added to the Memorial Sloan Kettering Cancer Center (MSKCC) risk model, there was improved risk stratification of patients with RCC about to initiate first-line therapy.
“Compared with the original MSKCC risk model, our genomically annotated tool altered risk grouping for about half of participants analyzed from two independent cohorts, with dedicated analyses suggesting improved correlation with overall survival, progression-free survival, and the proportion of patients who achieved an objective response,” Martin H. Voss, MD, of Memorial Sloan Kettering Cancer Center, and colleagues wrote in Lancet Oncology.
Currently, the MSKCC risk model integrates clinical and laboratory data as a prognostic tool for patients with RCC. In this analysis, Voss and colleagues tested if several mutations had any prognostic value in RCC.
The researchers conducted a retrospective study using tissue and outcome data from patients with metastatic disease assigned to TKIs in the COMPARZ trial (357 patients) and RECORD-3 trial (258 patients). In the training cohort, they used next-generation sequencing to evaluate associations between cancer-specific outcomes and the mutation status of six genes (BAP1, PBRM1, TP53, TERT, KDM5C, and SETD2). Using the original MSKCC risk model, 24% of patients were favorable risk, 61% were intermediate risk, and 15% were poor risk.
Samples with any mutation in BAP1 or TP53, or both (odds ratio [OR], 1.57; 95% CI, 1.21–2.04; P = .0008), and the absence of a mutation in PBRM1 (OR, 1.58; 95% CI, 1.16–2.14; P = .0035) were prognostic for overall survival. For progression-free survival, PBRM1 status had prognostic effect.
In the validation model, BAP1, TP53, and PBRM1, were added to the MSKCC model and the model was tested for prognostic value against the original MSKCC risk model. One point was added for the presence of one or more mutations in BAP1, TP53, or both. In addition, one point was added if BAP1, TP53, and PBRM1 had concurrent mutations or if PBRM1 was wild type.
Overall, patients could score between zero and seven points and the number of risk groups increased from three to four. Favorable risk was zero points, good risk, one point, intermediate risk, two points, and poor risk, three or more points.
Using the updated model, 10% of patients were favorable risk; 22%, good risk; 30%, intermediate risk; and 38%, poor risk. The addition of the genomic information improved the performance of the model for predicting overall survival and progression-free survival, according to the study.
“Future work could include extending our investigations to include the IMDC model, the second of the two most commonly applied tools for prognostication and stratification in the metastatic space,” the researchers wrote.
Commenting in an accompanying editorial Neeraj Agarwal, MD, and Roberto Nussenzveig, of Huntsman Cancer Institute, and Sumanta K. Pal, MD, of City of Hope Comprehensive Cancer Center, noted that although this study shows the value of genomic information on prognostic models, it comes at a time “when the MSKCC stratification tool is being phased out.”
“Allocation to novel regimens such as cabozantinib or nivolumab plus ipilimumab is predicated on intermediate-risk or poor-risk classification on the basis of IMDC criteria, not MSKCC criteria,” they wrote. “With this development in mind, the genomic markers assessed by Voss and colleagues could warrant reassessment in the context of the studies that are leading to approval of these regimens. Until this happens, clinical implement of the IMDC criteria (without genomic markers) will most likely prevail.”
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