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Genomic variant predicts mortality, recurrence risks for clear cell renal cell carcinoma
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The single-nucleotide variant rs11762213 located in the MET oncogene independently predicted poor disease-specific survival and shorter time to recurrence among patients with clear cell renal cell carcinoma, according to study results.
The MET variant rs11762213 should be integrated into clinical practice as a prognostic stratification tool for these patients, according to the researchers.
“In the last few years, the oncogenome of renal cell carcinoma has been the focus of much research effort, and this has led to the discovery of recurrent alterations in clear cell renal cell carcinoma (ccRCC),” A. Ari Hakimi, MD, urologic oncologist at Memorial Sloan Kettering Cancer Center, and colleagues wrote. “Prediction models are important tools to use when one is counseling patients on their disease and tailoring case-specific treatment recommendations, yet clinical outcomes of renal cell carcinoma patients are highly variable and difficult to predict, even with the most comprehensive prognostic models.”
Researchers recently identified the novel single-nucleotide polymorphism (SNP) rs11762213, in the coding region of the MET oncogene, as a prognostic signifier for increased recurrence risk and poorer disease-specific survival (DSS) in patients with ccRCC, according to study background.
Thus, Hakimi and colleagues sought to validate the prognostic significance of rs11762213 among patients with high-risk ccRCC, as well as to explore the potential biological mechanisms of the variant.
Using data from The Cancer Genome Atlas and other public data sites, the researchers identified 272 patients for whom data on rs11762213 was available. They used available data sets to acquire paired tumor-normal data, genomic data and clinical information.
The influence of rs11762213 on DSS and time to recurrence served as the primary endpoint.
The researchers observed the risk allele in 10.3% (n = 28) of patients.
In analyses adjusted for Mayo Clinic Stage, Size, Grade and Necrosis score, the variant significantly predicted shorter DSS (HR = 3.88; 95% CI, 1.99-7.56) and time to recurrence (OR = 2.97; 95% CI, 1.43-6.2).
Further, the mapping of rs11762213 to regulatory regions within the genome suggested that it might affect DNA enhancer regions.
However, RNA and protein sequencing data from MET did not expose differences in steady-state expression when stratified by risk allele.
The researchers identified the differing median length of follow-up between the two risk allele groups (37.4 months vs. 19.8 months) as a potential study limitation.
“In conclusion, we have externally validated and proven the clinical utility of the MET variant rs11762213 for disease behavior in ccRCC and established its ability to improve prognostic models,” Hakimi and colleagues wrote. “We have demonstrated that this specific variant is the likely causal SNP and have provided computational evidence that it affects a regulatory domain within a well-known and well-characterized oncogene.” – by Cameron Kelsall
Disclosure: Hakimi reports no relevant financial disclosures. Other researchers report grants and personal fees from Bristol-Myers Squibb, CGI, Chugai, Eisai, Exelixis, Genentech, GlaxoSmithKline, Novartis and Pfizer outside of the submitted work.
Perspective
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Matthew Galsky, MD
As is the case with most solid tumors, patients undergoing potentially curative surgery for clinically localized renal cancer experience variable outcomes likely related to a range of tumor-specific and host-specific factors. Several prediction models based on clinical variables have been developed and externally validated to predict the likelihood of recurrence after nephrectomy in patients with renal cancer and to facilitate patient counseling. However, the operating characteristics of current predictions models based on clinical variables alone are suboptimal and do not fully explain the heterogeneity in outcomes.
Schutz and colleagues previously demonstrated that germline variants in the MET oncogene are associated with a higher likelihood of recurrence after nephrectomy in patients with renal cancer. Given that germline genetic variants can be tested in peripheral blood and are stable over time, this represents a highly feasible approach to integrate biologic information to risk prediction modeling.
The current analysis by Hakim and colleagues externally validates this prior observation using data from The Cancer Genome Atlas (TCGA). These investigators demonstrate that the variant allele rs11762213 located in the MET oncogene was found in approximately 10% of patients in TCGA and was associated with significantly worse cancer specific survival even adjusting for known clinical prognostic variables. These findings provide support for integration of rs11762213 into routine clinical testing.
However, like most prognostic — rather than predictive — biomarkers, the challenge for implementation lies in the clinical utility of testing. In the absence of adjuvant systemic therapies of demonstrated benefit in clinically localized renal cancer, how such information would enhance clinical care remains to be determined. Exploring rs11762213 in ongoing and planned adjuvant studies may be critical to the future development of risk adapted adjuvant therapy in this disease.
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