Project description:Diffuse infiltrating gliomas are the most common primary brain malignancy found in adults, and Glioblastoma multiforme, the highest grade glioma, is associated with a median survival of 7 months. Transcriptional profiling has been applied to 85 gliomas from 74 patients to elucidate glioma biology, prognosticate survival, and define tumor sub-classes. These studies reveal that transcriptional profiling of gliomas is more accurate at predicting survival than traditional pathologic grading, and that gliomas characteristically express coordinately regulated genes of one of four molecular signatures: neurogenesis, synaptic transmission, mitotic, or extra-cellular matrix. Elucidation of these survival associated molecular signatures will aid in tumor prognostication and define targets for future directed therapy. Evaluate a large number of diffuse infiltrating gliomas through transcriptional profiling. Glioma tumor sub-classes may be identified through large scale gene expression studies. All patients undergoing surgical treatment at the University of California, Los Angeles for primary brain cancers between 1996 and 2003 were invited to participate in this Institutional Review Board approved study. 74 of the patients participating in this broad protocol were analyzed as part of this study if their initial tumor was diagnosed as a grade III (n=24) or IV (n=50) glioma of any histologic type on initial surgical treatment and fresh frozen material was obtained. Only grade III and IV gliomas were included in this study as the distinction between these grades is subtle and prone to misclassification. The time in days elapsed from resection to the day of death, or if the patient has remained alive, to the current day was recorded for all samples studied. Patient ages at diagnosis varied from 18 to 82 years. There were 46 females and 28 males. Probes were prepared using standard Affymetrix protocols, and hybridized to Affymetrix HG-U133A and HG-U133B arrays.

Project description:Diffuse infiltrating gliomas are the most common primary brain malignancy found in adults, and Glioblastoma multiforme, the highest grade glioma, is associated with a median survival of 7 months. Transcriptional profiling has been applied to 85 gliomas from 74 patients to elucidate glioma biology, prognosticate survival, and define tumor sub-classes. These studies reveal that transcriptional profiling of gliomas is more accurate at predicting survival than traditional pathologic grading, and that gliomas characteristically express coordinately regulated genes of one of four molecular signatures: neurogenesis, synaptic transmission, mitotic, or extra-cellular matrix. Elucidation of these survival associated molecular signatures will aid in tumor prognostication and define targets for future directed therapy. Evaluate a large number of diffuse infiltrating gliomas through transcriptional profiling. Glioma tumor sub-classes may be identified through large scale gene expression studies. All patients undergoing surgical treatment at the University of California, Los Angeles for primary brain cancers between 1996 and 2003 were invited to participate in this Institutional Review Board approved study. 74 of the patients participating in this broad protocol were analyzed as part of this study if their initial tumor was diagnosed as a grade III (n=24) or IV (n=50) glioma of any histologic type on initial surgical treatment and fresh frozen material was obtained. Only grade III and IV gliomas were included in this study as the distinction between these grades is subtle and prone to misclassification. The time in days elapsed from resection to the day of death, or if the patient has remained alive, to the current day was recorded for all samples studied. Patient ages at diagnosis varied from 18 to 82 years. There were 46 females and 28 males. Probes were prepared using standard Affymetrix protocols, and hybridized to Affymetrix HG-U133A and HG-U133B arrays. Keywords: disease state analysis

Dataset Information

A model of molecular characteristics to classify WHO Grade III glioma patients

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets