Using an innovative algorithm that analyzes gene regulatory and signaling networks, Columbia University Medical Center (CUMC) researchers have found that loss of a gene called KLHL9 is the driving force behind the most aggressive form of glioblastoma, the most common form of brain cancer. The CUMC team demonstrated in mice transplants that these tumors can be suppressed by reintroducing KLHL9 protein, offering a possible strategy for treating this lethal disease. The study was published in the online issue of Cell.
The team used the same approach to identify mutations and heritable variants that have been linked to breast cancer and Alzheimer’s disease, suggesting that the algorithm, combined with computer models of cellular regulation, is a powerful method for identifying genetic drivers of a wide range of diseases. Researchers combined existing computational tools with a new algorithm called DIGGIT (Driver-Gene Inference by Genetical-Genomic Information Theory), which “walks” backward from the master regulators to find the genetic events that drive cancer.
The new approach was tested on mesenchymal glioblastoma, the most aggressive subtype of the disease, by jointly analyzing the gene expression and mutational profile data of more than 250 patients collected by the Cancer Genome Atlas consortium. The CUMC team found two genes—C/EBPδ and KLHL9—that appear to activate glioblastoma’s master regulators. C/EBPδ had already been identified as a master regulator of the disease, so the researchers focused on KLHL9.
In subsequent laboratory studies, the researchers reactivated the defective KLHL9 gene in aggressive glioblastoma cells, which was sufficient to lose the mesenchymal phenotype. When KLHL9 protein was reintroduced into mice receiving direct transplants from patients with mesenchymal glioblastoma, their tumors regressed, providing further evidence that KLHL9 mutations (found in 50 percent of the mesenchymal glioblastoma patients) are directly responsible for driving this cancer subtype. Read the study abstract.Read more