Dataset Information


Individual Assignment of Adult Diffuse Gliomas into the EM/PM Molecular Subtypes Using a TaqMan Low-Density Array [Taqman Low Density Array]

ABSTRACT: Diagnosis of glioma into the hierarchy of human brain development would greatly facilitate mechanistic studies and clinical services in combating glioma. By analysing the multi-dimension big data of glioma genome and clinical manifestations, we have recently developed an EM/PM classification scheme anchored in the brain development and glioma pathogenesis (Sun et al., PNAS 111:3538-3543, 2014). To translate the EM/PM classification into a clinical diagnostic tool, we here designed and validated a TaqMan low-density RT-PCR array (TLDA) and a support vector machine (SVM) based prediction model that enables individual diagnosis of gliomas into the EM/PM subtype with high accuracy and precision. Results of 153 individually diagnosed adult diffuse gliomas of WHO grades II-IV derived from Chinese or Swedish patients confirmed our previous data base investigations: EM and PM gliomas show distinct prognosis, occur at different ages, and harbor mutually exclusive patterns of genomic alterations detected by Sanger sequencing and shallow-coverage whole genome sequencing (WGS). Further, we show that shallow-coverage WGS enabled a systematic identification of clonal and subclonal copy number variations (CNV) in glioma genomes, and the extent and the pattern of CNV can serve as an objective marker of tumor progression in the PM gliomas harboring IDH mutations. Overall design: Over 200 glioma samples were divided into training, validation and test cohort and were then tested by a custom Taqman Low Density Array which contains 44 classifiers and 4 reference genes. The result data were used to train and validate an individual EM/PM GEP subtype predictor using SVM algorithm for glioma.

INSTRUMENT(S): Taqman Low Density Array For Glioma Subtyping

ORGANISM(S): Homo sapiens  

SUBMITTER: Fan Xiaolong  

PROVIDER: GSE131464 | GEO | 2019-05-21


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