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.

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:Background: microRNAs (miRNAs) are approximately 21 nucleotide non-coding transcripts capable of regulating gene expression. The most widely studied mechanism of regulation involves binding of the miRNA to a target mRNA, usually in its 3â untranslated region (UTR). As a result, translation of the target mRNA is inhibited and sometimes the mRNA itself can be de-stabilized. The inhibitory effects of miRNAs have been linked to many diverse cellular processes including malignant proliferation and apoptosis, development and differentiation, metabolic processes and neural plasticity. We asked whether endogenous fluctuations in a set of mRNA and miRNA profiles contain correlated changes that are statistically distinguishable from the many other fluctuations in the data set. Methodology/Principal Findings: Biopsies from 12 human primary brain tumors were used to extract RNA. These samples were used to determine genome-wide mRNA expression levels by microarray analysis and a miRNA profile by real-time reverse transcription PCR (RT-PCR). Correlation coefficients were determined for all possible mRNA-miRNA pairs and the distribution of these correlations compared to the random distribution. An excess of high positive and negative correlation pairs were observed at the tails of these distributions. Most of these highest correlation pairs do not contain sufficiently complementary sequences to predict a target relationship; nor do they lie in physical proximity to each other. However, by examining pairs in which the significance of the correlation coefficients is modestly relaxed, negative correlations do tend to predict targets and positive correlations do tend to predict physically proximate pairs. A subset of high correlation pairs were experimentally validated by over-expressing or suppressing a miRNA and measuring the correlated mRNAs. Conclusions/Significance: Sufficient information exists within a set of tumor samples to detect endogenous correlations between miRNA and mRNA levels. Based on the validations of the correlations the causal arrow for these correlations is likely to be directed from the miRNAs to the mRNAs. From these data sets, we inferred and validated a tumor suppression pathway linked to miR-181c. Experiment Overall Design: Microarray data were obtained from the 12 tumors using Affymetrics HG-U133A array platforms. Tissue from glioma resections were obtained and collected at UCLA under approval from the Institutional Review Board. Categorization into high or low grade was based on the formal pathology report, with WHO grades III and IV being termed "high grade" and grades I and II termed "low grade". Histological diagnoses fell into the following categories: two low grade anaplastic mixed gliomas, one low grade oligodendroglioma, six high grade glioblastomas, two high grade gliosarcomas, and one high grade glioblastoma/gliosarcoma.

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

ITRAQ-based quantitative proteomic analysis of nuclear fractions of glioma (WHO grade II, III and IV) tissues to identify altered transcriptional regulatory proteins

Publications

Altered transcriptional regulatory proteins in glioblastoma and YBX1 as a potential regulator of tumor invasion.

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