Abstract
We have previously developed a multigene expression model of tumor radiosensitivity (RSI) with clinical validation in multiple cohorts and disease sites. We hypothesized RSI would identify glioblastoma patients who would respond to radiation and predict treatment outcomes. Clinical and array based gene expression (Affymetrix HT Human Genome U133 Array Plate Set) level 2 data was downloaded from the cancer genome atlas (TCGA). A total of 270 patients were identified for the analysis: 214 who underwent radiotherapy and temozolomide and 56 who did not undergo radiotherapy. Median follow-up for the entire cohort was 9.1 months (range: 0.04-92.2 months). Patients who did not receive radiotherapy were more likely to be older (p < 0.001) and of poorer performance status (p < 0.001). On multivariate analysis, RSI is an independent predictor of OS (HR = 1.64, 95% CI 1.08-2.5; p = 0.02). Furthermore, on subset analysis, radiosensitive patients had significantly improved OS in the patients with high MGMT expression (unmethylated MGMT), 1 year OS 84.1% vs. 53.7% (p = 0.005). This observation held on MVA (HR = 1.94, 95% CI 1.19-3.31; p = 0.008), suggesting that RT has a larger therapeutic impact in these patients. In conclusion, RSI predicts for OS in glioblastoma. These data further confirm the value of RSI as a disease-site independent biomarker.
Highlights
IntroductionDespite advances in surgical resection, chemotherapy, and radiation over the past several decades, glioblastoma continues to have a median survival of 14–15 months [1]
Glioblastoma is the most common central nervous system malignancy in adults
We found the RSI algorithm correlated to clinical endpoints in patients treated with RT
Summary
Despite advances in surgical resection, chemotherapy, and radiation over the past several decades, glioblastoma continues to have a median survival of 14–15 months [1]. Current standard of care for patients with glioblastoma is a maximal safe resection followed by radiotherapy with concurrent and adjuvant temozolomide [1]. There are several biomarkers to help predict prognosis in patients following surgical resection. O(6)-Methylguanine-DNA methyltransferase (MGMT) gene silencing has been found to be prognostic and predictive for outcomes following surgery and temozolomide [2]. As we move towards an era of personalized medicine, there is not yet a tool to help with the selection of patients most likely to benefit from radiotherapy and assist in dose selection in the management of glioblastoma
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