Scientists at the Translational Genomics Research Institute (TGen) have just published evidence suggesting that survival from glioblastoma (GBM), an aggressive and deadly form of brain cancer, could be determined by the complexity of their tumor. The findings from this new study, which were published recently in Neuro-Oncology through an article entitled “Integrated Genomic Analysis of Survival Outliers in Glioblastoma,” suggest that the survival of those patients whose cancer cells exhibit a complex genomic landscape, on average, exceeded those patients with a less complex tumor structure.
The current standard-of-care treatment for GBM typically involves the surgical removal of as much tumor as possible without destroying healthy brain tissue. Surgery is usually coupled with radiation and oral chemotherapy using temozolomide (TMZ). This regimen often extends median survival to 14.7 months.
The TGen investigators found that the standard-of-care worked best for patients with complex, albeit fragile, tumor genomes that are defined as those with more abnormal genomic events, such as mutations, rearrangements, or amplifications. The researchers discovered that the more abnormal the tumor genome, the more likely the therapy was to improve patient survival.
By studying those patients at the extreme ends of the survival timeline—the "outliers"—the TGen team hoped to identify the role tumor complexity plays in treatment outcomes.
"It's kind of like the game Jenga,” remarked senior study investigator Michael Berens, Ph.D., professor, and director of TGen's Cancer and Cell Biology Division. “What are the key blocks that, if you take them out, the tower of cancer comes tumbling down."
In contrast, those patients with simple, but robust, cancer genomes had shorter survival. The current standard-of-care therapies found few ways to thwart the cancer. This surprised the researchers because the most complex cancers with multiple mutations often evade targeted therapies while the simple tumors either shrink or disappear.
"The typical approach to discovering the genomic drivers of human cancers is to find and understand a pivotal mechanism," explained lead study author Sen Peng, Ph.D., a bioinformatician and staff scientist at TGen. "In our 'outliers' study, we discovered instead that the broader genomic landscape was far more telling of which patients may best respond to standard care, information that one day may determine if patients would be best served by conventional or experimental therapy."
This was the first genomic study that comprehensively examined GBM outliers in the survival spectrum. The researchers used deep genomic sequencing to examine 18 GBM tumor samples from deceased patients who were part of the Ohio Brain Tumor Study (OBTS), including ten short-term survivors (average survival of 7 months), and eight long-term survivors (average survival 33 months). Each group of "outliers" represented the shortest and longest quartile of the study's overall patient survival distribution.
"This study categorizes those patients who should receive standard-of-care therapies, and those who should be prioritized to receive potential benefit from a new, more innovative regimen," Dr. Berens noted. "In particular, those with likely short-term-survival may benefit from molecular profiling of targetable mutations and gene pathways."
The new data also highlighted several genetic features that indicate targetable mutations that could hold promise for better clinical outcomes, thereby enabling a more precise treatment plan.
"The result would be more effective therapy directed to identified features in profiled patient cancer specimens, as opposed to subjecting all patients to chemotherapy in hopes of a positive response," said Dr. Berens.