Genomic Signatures May Predict Metastasis in Patients With Clear Cell RCC

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Identifying gene signatures in patients with clear cell renal cell carcinoma (ccRCC) that can predict the likelihood of their disease metastasizing, as well as the site of metastasis, may help to better stratify risk assessment for the disease and plan appropriate treatment strategies.

Identifying gene signatures in patients with clear cell renal cell carcinoma (ccRCC) that can predict the likelihood of their disease metastasizing, as well as the site of metastasis, may help to better stratify risk assessment for the disease and plan appropriate treatment strategies.

In a collaborative study from Cancer Genetics, Inc. and Memorial Sloan Kettering Cancer Center that analyzed specimens from 144 ccRCC patients with primary and metastatic lesions, researchers used genome-wide copy number profiling to identify genomic copy number alterations (CNAs) associated with ccRCC metastasis. The results of this study were presented at the 2015 Genitourinary Cancers Symposium in Orlando, Fla.

Of the approximately 43,000 new cases of ccRCC diagnosed in the United States each year, about one-third of patients have metastatic disease at the time of diagnosis, and therefore have a poor prognosis. In addition, 20% to 30% of patients with ccRCC relapse within 3 years after nephrectomy. Therefore, for patients with early-stage ccRCC, predicting the metastatic activity of their disease is crucial in improving outcomes.

Differential CNAs between primary and metastatic lesions and between different metastatic sites were identified using Fisher’s exact test in two data sets, with 25 CNAs found to be significantly different (P < .05); 11 were more frequent in metastatic lesions, which had three CNAs that were associated with inferior survival. Across the metastatic lesions, nine CNAs were discovered to be enriched in lung lesions and three CNAs with bone.

The identification of these potential biomarkers for metastasis in ccRCC opens a new path for personalized treatment of this disease. As a result of the findings of this study, Cancer Genetics, Inc. will integrate the identified gene signatures into a next generation sequencing-based panel for kidney cancer, which the company hopes will be available for use for both clinical trials and clinical diagnosis, and management of patients in the near future.

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