Ontology highlight
ABSTRACT: This is a whole genome metabolism model of a male patient diagnosed at the age of 32 years with Testicular Germ Cell Tumor affecting the patient's testis. This model was automatically generated by tINIT (Agren, R., et al. (2014). Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling. Mol Syst Biol; 10(3), 721.) using information coming from the sample TCGA-2G-AAEW-01A from GDC Portal (Initial release 1.0, accessed via GDC API) and, where relevant, augmented with metabolic pathway information extracted from Human Metabolic Atlas. This model has been produced by Human Pathology Atlas project ( Uhlen, M., et al.; A pathology atlas of the human cancer transcriptome. Science.) and is currently hosted on BioModels Database and identified by MODEL1707110445. To cite BioModels, please use: V Chelliah et al; BioModels: ten-year anniversary. Nucleic Acids Res 2015; 43 (D1): D542-D548. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.
ORGANISM(S): Homo sapiens
SUBMITTER: Adil Mardinoglu
PROVIDER: MODEL1707110445 | biostudies-other |
SECONDARY ACCESSION(S): 28818916
REPOSITORIES: biostudies-other

Science (New York, N.Y.) 20170801 6352
Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation o ...[more]