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The prolonged storage of glucose as glycogen can promote the quiescence of tumor cells, whereas the accumulation of an aberrant form of glycogen without the primer protein glycogenin can induce the metabolic switch towards a glycolytic phenotype. Here, we analyzed the expression of n = 67 genes involved in glycogen metabolism on the uveal melanoma (UM) cohort of the Cancer Genome Atlas (TCGA) study and validated the differentially expressed genes in an independent cohort. We also evaluated the glycogen levels with regard to the prognostic factors via a differential periodic acid-Schiff (PAS) staining. UMs with monosomy-3 exhibited a less glycogenetic and more insulin-resistant gene expression profile, together with the reduction of glycogen levels, which were associated with the metastases. Expression of glycogenin-1 (Locus: 3q24) was lower in the monosomy-3 tumors, whereas the complementary isoform glycogenin-2 (Locus: Xp22.33) was upregulated in females. Remarkably, glycogen was more abundant in the monosomy-3 tumors of male versus female patients. We therefore provide the first evidence to the dysregulation of glycogen metabolism as a novel factor that may be aggravating the course of UM particularly in males.
Pubmed ID: 32751097
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Software package as distribution of ImageJ and ImageJ2 together with Java, Java3D and plugins organized into coherent menu structure. Used to assist research in life sciences.
View all literature mentionsA high performance search engine for gene expression that integrates thousands of manually curated public microarray and RNAseq experiments and nicely visualizes gene expression across different biological contexts (diseases, drugs, tissues, cancers, genotypes, etc.). There are two basic analysis approaches: # for a gene of interest, identify which conditions affect its expression. # for condition(s) of interest, identify which genes are specifically expressed in this/these conditions. Genevestigator builds on the deep integration of data, both at the level of data normalization and on the level of sample annotations. This deep integration allows scientists to ask new types of questions that cannot be addressed using conventional tools.
View all literature mentionsComputable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19, 2022.
View all literature mentionsAmerican chemical, life science and biotechnology company owned by Merck KGaA. Merger of Sigma Chemical Company and Aldrich Chemical Company. Provides organic and inorganic chemicals, building blocks, reagents, advanced materials and stable isotopes for chemical synthesis, medicinal chemistry and materials science, antibiotics, buffers, carbohydrates, enzymes, forensic tools, hematology and histology, nucleotides, proteins, peptides, amino acids and their derivatives.
View all literature mentionsA commercial antibody supplier which supplies primary and secondary antibodies, biochemicals, proteins, peptides, lysates, immunoassays and other kits.
View all literature mentionsA portal that provides visualization, analysis and download of large-scale cancer genomics data sets.
View all literature mentionsWeb tool where one component is front end Xena Browser and another component is back end Xena Hubs. Web based Xena Browser empowers biologists to explore data across multiple Xena Hubs with variety of visualizations and analyses. Xena Hubs host genomics data from laptops, public servers, behind firewall, or in cloud, and can be public or private. Xena Browser receives data simultaneously from multiple Xena Hubs and integrates them into single coherent visualization within browser. Allows users to explore functional genomic data sets for correlations between genomic and/or phenotypic variables.
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