Novel Biomarker May Be Predictive of Clear Cell Renal Cell Carcinoma Recurrence

Researchers have discovered a biomarker that could help identify which patients with clear cell renal cell carcinoma may be at greater risk of cancer recurrence, according to a recent study published by Mehra et al in JCO Precision Oncology.

Background

Approximately 3% to 5% of all cancer diagnoses are renal cancer. Clear cell renal cell carcinoma accounts for about 75% of renal cancer cases. Currently, treatment for clear cell renal cell carcinoma is determined by the size and grade of the tumor and stage of overall disease.

However a “one-size-fits-all” approach isn’t always effective. For instance, some patients with stage pT3 disease may never develop recurrence after initial treatment with surgery to remove the kidney. Rather than offer additional, often toxic, systemic therapy to all patients with pT3 disease, a biomarker test that can stratify patients based on low vs high risk for recurrence can guide physicians when deciding on the need for additional therapy. Nonetheless, there is no renal cancer biomarker in practice to help physicians gauge the likelihood of cancer recurrence and tailor either surveillance strategies or additional treatment.

“We need biomarkers to identify and better treat those who need to be treated and avoid treatment in those that do not need to be treated,” stressed senior study author Simpa S. Salami, MD, MPH, Associate Professor of Urology at Michigan Medicine.

Study Methods and Results

In the recent study, the researchers retrospectively identified 110 patients with clear cell renal cell carcinoma who had undergone nephrectomy and received follow-up treatment. They then performed capture transcriptome profiling using archival tissue specimens from these patients.

Through analyzing the RNA sequencing data, the researchers identified a 15-gene signature that was independently associated with cancer recurrence as well as poorer disease-free survival and disease-specific survival. In two large validation data sets—including data from the Cancer Genome Atlas—the 15-gene signature was independently associated with poorer disease-free survival and disease-specific survival.

Conclusions

“We’ve developed a 15-gene signature that can risk-stratify patients with clear cell renal [cell carcinoma] from low to high,” detailed Dr. Salami. “Even when we adjusted for other clinical variables, like age or grade of tumor, this signature was still independently associated with recurrence after treatment for this form of [renal] cancer,” he highlighted.

Despite the positive findings, the researchers noted that further studies may still be needed to define how these findings are implemented in the clinic.

“There’s potential for using this signature to identify patients who should receive low- vs high-intensity surveillance,” Dr. Salami underscored. “It could inform how frequently to do surveillance imaging after initial treatment and, if validated, may be used to guide the selection of patients for additional systemic treatment after surgery,” he concluded.

Disclosure: The research in this study was funded by the National Comprehensive Cancer Network, the University of Michigan Health System–Peking University Health Science Center Joint Institute, and the Robert Wood Johnson Foundation as part of the Harold Amos Medical Faculty Development Program. For full disclosures of the study authors, visit ascopubs.org.