Uhlén2017 - TCGA-2G-AAEW-01A - Testicular Germ Cell Tumor (male, 32 years)

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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.

Other models with the same disease include MODEL1707110446 MODEL1707110447 MODEL1707110448 MODEL1707110449 MODEL1707110450 MODEL1707110451 MODEL1707110452 MODEL1707110453 MODEL1707110454 MODEL1707110455 MODEL1707110456 MODEL1707110457 MODEL1707110458 MODEL1707110459 MODEL1707110460 MODEL1707110461 MODEL1707110462 MODEL1707110463 MODEL1707110464 MODEL1707110465 MODEL1707110466 MODEL1707110467 MODEL1707110468 MODEL1707110469 MODEL1707110470 MODEL1707110471 MODEL1707110472 MODEL1707110473 MODEL1707110474 MODEL1707110475 MODEL1707110476 MODEL1707110477 MODEL1707110478 MODEL1707110479 MODEL1707110480 MODEL1707110481 MODEL1707110482 MODEL1707110483 MODEL1707110484 MODEL1707110485 MODEL1707110486 MODEL1707110487 MODEL1707110488 MODEL1707110489 MODEL1707110490 MODEL1707110491 MODEL1707110492 MODEL1707110493 MODEL1707110494 MODEL1707110495 MODEL1707110496 MODEL1707110497 MODEL1707110498 MODEL1707110499 MODEL1707110500 MODEL1707110501 MODEL1707110523 MODEL1707110524 MODEL1707110786 MODEL1707110787 MODEL1707116246 MODEL1707116247 MODEL1707116248 MODEL1707116249 MODEL1707116250 MODEL1707116255 MODEL1707116256 MODEL1707116257 MODEL1707116258 MODEL1707116259 MODEL1707116382 MODEL1707116383 MODEL1707116384 MODEL1707116385 MODEL1707116386 MODEL1707116387 MODEL1707116388 MODEL1707116502 MODEL1707116503 MODEL1707116519 MODEL1707116520 MODEL1707116521 MODEL1707116522 MODEL1707116523 MODEL1707116531 MODEL1707116532 MODEL1707116533 MODEL1707116534 MODEL1707116535 MODEL1707116536 MODEL1707116537 MODEL1707116538 MODEL1707116539 MODEL1707116540 MODEL1707116541 MODEL1707116542 MODEL1707116543 MODEL1707116544 MODEL1707116545 MODEL1707116546 MODEL1707116619 MODEL1707116620 MODEL1707116621 MODEL1707116666 MODEL1707116667 MODEL1707116668 MODEL1707116669 MODEL1707116670 MODEL1707116671 MODEL1707116672 MODEL1707116673 MODEL1707116674 MODEL1707116733 MODEL1707116734 MODEL1707116735 MODEL1707116736 MODEL1707116737 MODEL1707116738 MODEL1707116739 MODEL1707116740 .

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.

Related Publication
  • A pathology atlas of the human cancer transcriptome.
  • Uhlen M, Zhang C, Lee S, Sjöstedt E, Fagerberg L, Bidkhori G, Benfeitas R, Arif M, Liu Z, Edfors F, Sanli K, von Feilitzen K, Oksvold P, Lundberg E, Hober S, Nilsson P, Mattsson J, Schwenk JM, Brunnström H, Glimelius B, Sjöblom T, Edqvist PH, Djureinovic D, Micke P, Lindskog C, Mardinoglu A, Ponten F
  • Science (New York, N.Y.) , 8/ 2017 , Volume 357 , Issue 6352 , PubMed ID: 28818916
  • School of Biotechnology, AlbaNova University Center, KTH-Royal Institute of Technology, Stockholm, Sweden.
  • 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 of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.
Adil Mardinoglu

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Model files

MODEL1707110445.xml Patient derived genome scale metabolic model for Testicular Germ Cell Tumor 12.47 MB Preview | Download

Additional files

Testicular Germ Cell Tumor.zip All 'Testicular Germ Cell Tumor' models 32.47 MB Preview | Download

  • Model originally submitted by : Adil Mardinoglu
  • Submitted: Aug 17, 2017 5:06:13 PM
  • Last Modified: Jan 7, 2020 5:55:18 PM
  • Version: 3 public model Download this version
    • Submitted on: Jan 7, 2020 5:55:18 PM
    • Submitted by: Adil Mardinoglu
    • With comment: Import of 'Uhlén2017 - TCGA-2G-AAEW-01A - Testicular Germ Cell Tumor (male, 32 years)'.
  • Version: 2 public model Download this version
    • Submitted on: Aug 17, 2017 5:05:58 PM
    • Submitted by: Adil Mardinoglu
    • With comment: Current version of Uhlén2017 - TCGA-2G-AAEW-01A - Testicular Germ Cell Tumor (male, 32 years)
  • Version: 1 public model Download this version
    • Submitted on: Aug 17, 2017 5:06:13 PM
    • Submitted by: Adil Mardinoglu
    • With comment: Original import of MODEL1707110445.xml.origin

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

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