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Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications.

ABSTRACT: Diagnosis and classification of gliomas mostly relies on histopathology and a few genetic markers. Here we interrogated microarray gene expression profiles (GEP) of 268 diffuse astrocytic gliomas-33 diffuse astrocytomas (DA), 52 anaplastic astrocytomas (AA) and 183 primary glioblastoma (GBM)-based on multivariate analysis, to identify discriminatory GEP that might support precise histopathological tumor stratification, particularly among inconclusive cases with II-III grade diagnosed, which have different prognosis and treatment strategies. Microarrays based GEP was analyzed on 155 diffuse astrocytic gliomas (discovery cohort) and validated in another 113 tumors (validation set) via sequential univariate analysis (pairwise comparison) for discriminatory gene selection, followed by nonnegative matrix factorization and canonical biplot for identification of discriminatory GEP among the distinct histological tumor subtypes. GEP data analysis identified a set of 27 genes capable of differentiating among distinct subtypes of gliomas that might support current histological classification. DA?+?AA showed similar molecular profiles with only a few discriminatory genes overexpressed (FSTL5 and SFRP2) and underexpressed (XIST, TOP2A and SHOX2) in DA vs AA and GBM. Compared to DA?+?AA, GBM displayed underexpression of ETNPPL, SH3GL2, GABRG2, SPX, DPP10, GABRB2 and CNTN3 and overexpression of CHI3L1, IGFBP3, COL1A1 and VEGFA, among other differentially expressed genes.

SUBMITTER: Gonzalez-Garcia N

PROVIDER: S-EPMC7347847 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications.

González-García Nerea N Nieto-Librero Ana Belén AB Vital Ana Luisa AL Tao Herminio José HJ González-Tablas María M Otero Álvaro Á Galindo-Villardón Purificación P Orfao Alberto A Tabernero María Dolores MD

Scientific reports 20200709 1

Diagnosis and classification of gliomas mostly relies on histopathology and a few genetic markers. Here we interrogated microarray gene expression profiles (GEP) of 268 diffuse astrocytic gliomas-33 diffuse astrocytomas (DA), 52 anaplastic astrocytomas (AA) and 183 primary glioblastoma (GBM)-based on multivariate analysis, to identify discriminatory GEP that might support precise histopathological tumor stratification, particularly among inconclusive cases with II-III grade diagnosed, which have ...[more]

PMID: 32647207

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Project description:Recent studies have demonstrated that tumor-driving alterations are often different among gliomas that originated from different brain regions and have underscored the importance of analyzing molecular characteristics of gliomas stratified by brain region. Therefore, to elucidate molecular characteristics of diffuse cerebellar gliomas (DCGs), 27 adult, mostly glioblastoma cases were analyzed. Comprehensive analysis using whole-exome sequencing, RNA sequencing, and Infinium methylation array (n = 17) demonstrated their distinct molecular profile compared to gliomas in other brain regions. Frequent mutations in chromatin-modifier genes were identified including, noticeably, a truncating mutation in SETD2 (n = 4), which resulted in loss of H3K36 trimethylation and was mutually exclusive with H3F3A K27M mutation (n = 3), suggesting that epigenetic dysregulation may lead to DCG tumorigenesis. Alterations that cause loss of p53 function including TP53 mutation (n = 9), PPM1D mutation (n = 2), and a novel type of PPM1D fusion (n = 1), were also frequent. On the other hand, mutations and copy number changes commonly observed in cerebral gliomas were infrequent. DNA methylation profile analysis demonstrated that all DCGs except for those with H3F3A mutations were categorized in the "RTK I (PDGFRA)" group, and those DCGs had a gene expression signature that was highly associated with PDGFRA. Furthermore, compared with the data of 315 gliomas derived from different brain regions, promoter methylation of transcription factors genes associated with glial development showed a characteristic pattern presumably reflecting their tumor origin. Notably, SOX10, a key transcription factor associated with oligodendroglial differentiation and PDGFRA regulation, was up-regulated in both DCG and H3 K27M-mutant diffuse midline glioma, suggesting their developmental and biological commonality. In contrast, SOX10 was silenced by promoter methylation in most cerebral gliomas. These findings may suggest potential tailored targeted therapy for gliomas according to their brain region, in addition to providing molecular clues to identify the region-related cellular origin of DCGs.

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.

Dataset Information

Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications.

Publications

Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications.

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