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Glioma growth is often accompanied by a hypoxic microenvironment favorable for the induction and maintenance of the glioma stem cell (GSC) phenotype. Due to the paucity of cell models of Isocitrate Dehydrogenase 1 mutant (IDH1mut) GSCs, biology under hypoxic conditions has not been sufficiently studied as compared to IDH1 wildtype (IDH1wt) GSCs. We therefore grew well-characterized IDH1mut (n = 4) and IDH1wt (n = 4) GSC lines under normoxic (20%) and hypoxic (1.5%) culture conditions and harvested mRNA after 72 h. Transcriptome analyses were performed and hypoxia regulated genes were further analyzed using the expression and clinical data of the lower grade glioma cohort of The Cancer Genome Atlas (LGG TCGA) in a confirmatory approach and to test for possible survival associations. Results show that global expression changes were more pronounced in IDH1wt than in IDH1mut GSCs. However, when focusing on known hypoxia-regulated gene sets, enrichment analyses showed a comparable regulation in both IDH1mut and IDH1wt GSCs. Of 272 significantly up-regulated genes under hypoxic conditions in IDH1mut GSCs a hypoxia-related survival score (HRS-score) of five genes (LYVE1, FAM162A, WNT6, OTP, PLOD1) was identified by the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm which was able to predict survival independent of age, 1p19q co-deletion status and WHO grade (II vs. III) in the LGG TCGA cohort and in the Rembrandt dataset. Altogether, we were able to identify and validate a novel hypoxia-related survival score in IDH1mut GSCs consisting of five hypoxia-regulated genes which was significantly associated with patient survival independent of known prognostic confounders.
Pubmed ID: 30257451 RIS Download
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International functional genomics data collection generated from microarray or next-generation sequencing (NGS) platforms. Repository of functional genomics data supporting publications. Provides genes expression data for reuse to the research community where they can be queried and downloaded. Integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Contains a subset of curated and re-annotated Archive data which can be queried for individual gene expression under different biological conditions across experiments. Data collected to MIAME and MINSEQE standards. Data are submitted by users or are imported directly from the NCBI Gene Expression Omnibus.
View all literature mentionsProject exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
View all literature mentionsSoftware package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.
View all literature mentionsSoftware R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. Used to process probe level data and for exploratory oligonucleotide array analysis.
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