Project description:BackgroundGlioma is the most common of all primary brain tumors with poor prognosis and high mortality. The 2016 World Health Organization classification of the tumors of central nervous system uses molecular parameters in addition to histology to redefine many tumor entities. The new classification scheme divides diffuse gliomas into low-grade glioma (LGG) and glioblastoma (GBM) as per histology. LGGs are further divided into isocitrate dehydrogenase (IDH) wild type or mutant, which is further classified into either oligodendroglioma that harbors 1p/19q codeletion or diffuse astrocytoma that has an intact 1p/19q loci but enriched for ATRX loss and TP53 mutation. GBMs are divided into IDH wild type that corresponds to primary or de novo GBMs and IDH mutant that corresponds to secondary or progressive GBMs. To make the 2016 WHO subtypes of diffuse gliomas more robust, we carried out Prediction Analysis of Microarrays (PAM) to develop DNA methylation signatures for these subtypes.ResultsIn this study, we applied PAM on a training set of diffuse gliomas derived from The Cancer Genome Atlas (TCGA) and identified DNA methylation signatures to classify LGG IDH wild type from LGG IDH mutant, LGG IDH mutant with 1p/19q codeletion from LGG IDH mutant with intact 1p/19q loci and GBM IDH wild type from GBM IDH mutant with an accuracy of 99-100%. The signatures were validated using the test set of diffuse glioma samples derived from TCGA with an accuracy of 96 to 99%. In addition, we also carried out additional validation of all three signatures using independent LGG and GBM cohorts. Further, the methylation signatures identified a fraction of samples as discordant, which were found to have molecular and clinical features typical of the subtype as identified by methylation signatures.ConclusionsThus, we identified methylation signatures that classified different subtypes of diffuse glioma accurately and propose that these signatures could complement 2016 WHO classification scheme of diffuse glioma.

Project description:Background: Molecular profiling of diffuse gliomas has provided significant insights into the pathogenesis, classification and prognostication of these malignancies. However, previous molecular studies of glioma have largely focused on genomic readouts and targeted proteomic profiling technologies. Consequently, proteomic and downstream functional landscape of gliomas in general, and molecular subgroups in particular, remains largely unexplored. Here, we utilize liquid chromatography tandem mass spectrometry to profile genomically-defined cohorts of gliomas spanning the full range of World Health Organization (WHO) grades. Methods: Bulk frozen tissue and purified micro-dissected regions from formalin-fixed paraffin-embedded (FFPE) tissues were assembled and utilized to define robust proteomic signatures of both low grade, infiltrative and high-grade tumors. As a final analysis, primary tumor tissue was compared with both IDH-mutated and IDH-wildtype glioblastoma stem cell (GSC) lines to further overcome tissue heterogeneity and pinpoint proteins differences likely arising in the relevant glial cellular drivers of tumor development. Results: In aggregate, 5,496 unique proteins over 3 glioma cohorts were identified, and span common molecular subclasses based on IDH and 1p19q co-deletion status and all four WHO grades. Supervised clustering highlights substantial proteome and systems-level pathway differences between different genetically defined glioma subtypes and WHO grades. By using bulk tumor statistical analysis, 833 proteins distinguish different WHO grade tumors, while FFPE tumor dissection reveals 287 proteins in GBMs with abundance changes according to IDH mutation status. Using our integrative approach, calcium signaling, proteins of the endoplasmic reticulum and extracellular integrin proteins are most conserved proteomic markers that distinguish aggressive, IDH-wt, from IDH-mut GBM tumors in primary and tissue culture models gliomagenesis. Conclusions: This proteomic survey provides the largest and most diverse unbiased protein-based brain tumor resource to date. Current treatments for glial tumors are largely non-specific and overlap between genomic subtypes and WHO grades. Our analysis provides early insight into the vast downstream and epigenetic protein-level differences within this molecular framework. Given the central position proteins occupy in driving biology and phenotype, further characterization of the substantial proteomic diversity that exist between the molecular subtypes and grades of gliomas, proteomics may help define more personalized prognostic and predictive biomarkers for precision care.

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Multidimensional scaling of diffuse gliomas: application to the 2016 World Health Organization classification system with prognostically relevant molecular subtype discovery.

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