A new test may help identify which patients with newly diagnosed glioblastoma are more likely to benefit from bevacizumab. This research was presented at the 2013 annual meeting of the American Society of Clinical Oncology in early June in Chicago, Illinois.

Glioblastoma is the most frequent and aggressive type of brain tumor. Despite slight gains, tumors pose a high risk of recurrence and are commonly fatal.

“In general, glioblastomas are heterogeneous and no drug has been found that benefits every patient,” said lead author Erik Sulman, MD, PhD, of University of Texas MD Anderson Cancer Center in Houston. “We wanted to determine which patients are most likely to benefit from bevacizumab and use that information to develop a diagnostic tool that can predict which patients may be good candidates for the drug.”

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This study is associated with RTOG 0825, which is a large, multi-center phase III trial. It evaluated the addition of bevacizumab to standard chemoradiation and maintenance temozolomide in treating newly diagnosed glioblastoma. Half of the enrolled patients received bevacizumab and the other half received a placebo.

Bevacizumab is a monoclonal antibody that binds to the protein vascular endothelial growth factor. It is an antiangiogenesis agent, so it prevents the growth of new blood vessels that tumors need to develop. In previous studies, some patients with recurring glioblastoma had longer progression-free survival and reduced symptoms with bevacizumab. This study sought to understand the ability of a particular gene expression signature to predict response to bevacizumab.

As part of RTOG 0825, 637 randomized patients submitted specimens for molecular analysis. The umbrella study data also included molecular stratification that measured the degree of gene enrichment. These genes are known to function in cancer cell invasion and in establishing new blood supply, which is a function that bevacizumab is designed to prevent.

Researchers observed a significant association between a lower mesenchymal signature and better survival in patients taking bevacizumab. Based on this association and following the examination of 43 genes in total, researchers modeled a novel gene expression predictor of outcome specific to those in the bevacizumab group.

“One of the key things about this predictor is that it’s designed to be used on standard, archival tumors found in most clinical pathology labs,” Sulman said. “It doesn’t require fresh tissue.”

The group plans ongoing studies to determine the extent to which this gene signature represents a predictive marker for bevacizumab use in newly diagnosed glioblastoma.

“We will use data from the remaining patients on the trial to validate these findings,” Sulman said. “We hope the test will be validated and used as a diagnostic tool to select patients for initial treatment with bevacizumab. Then, we plan to look beyond glioblastoma to see if it could benefit other tumor types currently treated or in clinical trials with bevacizumab.”