title: The radiosensitivity index predicts for overall survival in glioblastoma.
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.
authors.affiliation: Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
authors.forename: Kamran A
authors.initials: KA
authors.lastname: Ahmed
authors.affiliation: Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, MI 48073, USA.
authors.forename: Prakash
authors.initials: P
authors.lastname: Chinnaiyan
authors.affiliation: Department of Biostatistics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
authors.forename: William J
authors.initials: WJ
authors.lastname: Fulp
authors.affiliation: Department of Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
authors.forename: Steven
authors.initials: S
authors.lastname: Eschrich
authors.affiliation: Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
authors.forename: Javier F
authors.initials: JF
authors.lastname: Torres-Roca
authors.affiliation: Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
authors.forename: Jimmy J
authors.initials: JJ
authors.lastname: Caudell
mesh_terms: D000328:Adult; D000368:Aged; D018906:Antineoplastic Agents, Alkylating / Q000627:therapeutic use; D001932:Brain Neoplasms / Q000235:genetics* / Q000401:mortality / Q000532:radiotherapy; D059248:Chemoradiotherapy / Q000379:methods; D003606:Dacarbazine / Q000031:analogs & derivatives / Q000627:therapeutic use; D005260:Female; D005909:Glioblastoma / Q000235:genetics* / Q000401:mortality / Q000532:radiotherapy; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011836:Radiation Tolerance / Q000235:genetics*; D000077204:Temozolomide; D059467:Transcriptome; D016896:Treatment Outcome
chemical_list: D018906:Antineoplastic Agents, Alkylating; D003606:Dacarbazine; D000077204:Temozolomide
keywords: glioblastoma; radiosensitivity; signature