Abstract 359: An age-related 99-gene signature from glioblastoma implicates differences in survival related to RAS activation

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Background: Glioblastoma (GBM) is the most common primary brain tumor with universally poor prognosis despite treatment with surgery, radiation and chemotherapy. One of the most significant prognostic factors is the patient's age at onset of disease, with younger patients demonstrating longer survival despite similar therapies. The aim of this work is to examine genomic differences that are tied to the age of onset that could explain the differences in outcomes. Methods: We used the gene expression profiles from 559 GBM patients (pts) included in the Cancer Genome Atlas (TCGA) to build a gene expression model of the expression of 12185 genes to predict patient age using elasticnet with 500 bootstraps. This model was used to predict the age of patients in a testing set of 419 pts with gliomas included in Repository for Brain Neoplasia Data (REMBRANDT) (99 grade II, 71 grade III and 125 grade IV and 124 with no grade). Receiver-operating characteristic (ROC) and survival analysis were performed to measure the performance of the model in predicting age, gene-set enrichment analysis (GSEA) was used to reveal network topology perturbations, Cox proportional hazards were used to predict survival of the different predicted classes. Results: Using a FDR cutoff of p=0.005, the bootstrapped elasticnet discovered 99 genes that were highly correlated with age in GBM patients that predicts age in the testing set of patients with gliomas with an area under the ROC curve of 0.97. GSEA motifs within these genes related to RAS activation in multiple cell lines, as well as genes related to immune modulation and increased CpG methylation. Survival analysis of the REMBRANDT pts showed that the cohort with an “older” gene signature had worse survival (median 27 months versus 15 months, log-rank p<0.00005). When applied to pts in REMBRANDT for whom age was not recorded (n=36), the model predicted classes also had significantly different survival (median 6 versus 10 months, log-rank p=0.001). Conclusions: We have developed a gene expression model related to age of onset of GBM, to investigate the differences inherent in the biology that may lead to better prognosis in younger patients. Of the 99 genes that are strongly predictive of age in an external validation set, many were related to RAS activation in cell lines, immune modulation and CpG methylation. RAS perturbations have been previously shown to induce gliomas in mice, and this study shows a relationship between RAS gene network activation and age that may play a role in the different survival outcomes between different ages. Future work will include the use of RAS targeted agents to elucidate their role in the management of gliomas for select pts. Citation Format: Andrew D. Trister, Robert Rostomily, Stephen H. Friend. An age-related 99-gene signature from glioblastoma implicates differences in survival related to RAS activation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 359. doi:10.1158/1538-7445.AM2014-359