E-GEOD-13041 - Transcription profiling by array of human glioblastoma samples from patients of different ages

Status
Released on 26 October 2008, last updated on 6 March 2012
Organism
Homo sapiens
Samples (267)
Arrays (3)
Protocols (6)
Description
Background: Glioblastomas are the most common primary brain tumour in adults. While the prognosis for patients is poor, gene expression profiling has detected signatures that can sub-classify GBMs relative to histopathology and clinical variables. One category of GBM defined by a gene expression signature is termed ProNeural (PN), and has substantially longer patient survival relative to other gene expression-based subtypes of GBMs. Age of onset is a major predictor of the length of patient survival where younger patients survive longer than older patients. The reason for this survival advantage has not been clear. We collected 267 GBM CEL files and normalized them relative to other microarrays of the same Affymetrix platform. 377 probesets on U133A and U133 Plus 2.0 arrays were used in a gene voting strategy with 177 probesets of matching genes on older U95Av2 arrays. Kaplan-Meier curves and Cox proportional hazard analyses were applied in distinguishing survival differences between expression subtypes and age. Results: Here we collected 267 glioblastomas and explore the relationship between gene expression subtype, age at diagnosis, and survival. This meta-analysis of published data in addition to new data confirms the existence of four distinct GBM expression-signatures. Further, patients with PN subtype GBMs had longer survival, as expected. However, the age of the patient at diagnosis is not predictive of survival time when controlled for the PN subtype. Conclusions: The survival benefit of younger age is nullified when patients are stratified by gene expression group. Thus, the main cause of the age effect in GBMs is the more frequent occurrence of PN GBMs in younger patients relative to older patients. Experiment Overall Design: Clinical data including histopathology, age, sex, and survival time from diagnosis were retrieved from 181 glioblastomas which have been reported within previous studies between 2003 and 2006 and for which CEL files (Affymetrix, Santa Clara, CA) were available from the authors. In addition, we collected 86 new patient-unique tumour biopsies from the UCLA Neuro-oncology Program (n = 55) and the Barrow Neurological Institute (n = 31) for a grand total of 267 glioblastomas. Newly acquired tumours were collected through institutional review board approved protocols and assigned WHO grades at UCLA Neuropathology or Barrow Neuropathology by PSM. Time of survival (days), sex, and, age were collected where available. Patient age at the time of diagnosis was available for 239 patients and ranged from 18 to 86 years. Sex of the individual was available for those 239 patients (151 males and 88 females). There were no technical replicates. There were no control or reference samples. No dye swap due to single channel array platforms.
Experiment types
transcription profiling by array, unknown experiment type
Contact
Citation
Gene expression analysis of glioblastomas identifies the major molecular basis for the prognostic benefit of younger age. Lee Y, Scheck AC, Cloughesy TF, Lai A, Dong J, Farooqi HK, Liau LM, Horvath S, Mischel PS, Nelson SF. , Europe PMC 18940004
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