Reliable Biomarkers May Improve RCC Management
ORLANDO—Molecular features and information from gene and protein expression profiling of renal cell carcinoma (RCC) may increase the accuracy of current clinical prognostic models, a researcher said.
“In the metastatic setting, it will be possible to have predictive biomarkers that will help determine if you are going to give a patient a systemic therapy,” said Toni Choueiri, MD, Director of the Kidney Cancer Center at Dana Farber Cancer Institute in Boston. “These biomarkers could help determine if a specific targeted therapy or even a new experimental agent would be most appropriate.”
“In the localized setting, the goal is to build on what we have in terms of clinical prognostic factors,” Dr. Choueiri told Renal & Urology News. “In early stage renal cell carcinoma, we know that the stage of the tumor, the grade of the tumor, and how the patient presents with symptoms or without symptoms are very strong and independent predictors of outcome.”
Speaking at the Fourth Annual Genitourinary Cancers Symposium, Dr. Choueiri noted that with metastatic RCC, the classic anatomic and histologic tumor features of the primary tumor have limited prognostic value, he observed. Studies of the von Hippel-Lindau (VHL) gene, a crucial keystone in RCC pathogenesis, did not correlate with outcome to therapy targeting vascular endothelial growth factor. Other members of the same pathway are under investigation, including germline and tumor expression of the hypoxia inducible factors. In addition, specific molecular markers may be predictors of treatment-related toxicities, such as hypertension, he said.
RCC is a heterogeneous disease with widely varying clinical outcomes, said Dr. Choueiri, Assistant Professor of Medicine at Harvard Medical School in Boston. However, new molecular tools may help determine which patients may benefit the most from various therapeutic approaches.
New gene technology may be changing the way in how clinicians manage RCC patients, he said. Recently published studies have demonstrated a strong correlation of RCC recurrence with the expression of 16 genes in a multivariate model adjusted for clinical and pathologic variables. This discovery could pave the way for a multi-gene diagnostic that can estimate the risk of RCC recurrence following surgery.
Other investigators have identified two subtypes of RCC. Subset “A” showed expression of genes involved in angiogenesis, organic acid metabolism, fatty acid metabolism, and pyruvate metabolism. Subset “B” showed involvement of genes associated with cell differentiation, epithelial to mesenchymal transition. mitotic cell cycle, transformation growth factor beta and Wnt.
It may be possible to establish biomarkers for localized RCC as well as metastatic disease that can accurately predict the optimal systemic therapy, Dr. Choueiri said.