Uhlén2017 - TCGA-AF-2687-01A - Rectum Adenocarcinoma (male, 58 years)

Model Identifier
MODEL1707111946
Short description

This is a whole genome metabolism model of a male patient diagnosed at the age of 58 years with Rectum Adenocarcinoma affecting the patient's colon and rectum.

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-AF-2687-01A 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 MODEL1707111946.

Other models with the same disease include MODEL1707111947 MODEL1707111948 MODEL1707111949 MODEL1707111950 MODEL1707111951 MODEL1707111952 MODEL1707111953 MODEL1707111954 MODEL1707111955 MODEL1707111956 MODEL1707111957 MODEL1707111958 MODEL1707111959 MODEL1707111960 MODEL1707111961 MODEL1707111962 MODEL1707111963 MODEL1707111964 MODEL1707111965 MODEL1707111966 MODEL1707111967 MODEL1707111968 MODEL1707111969 MODEL1707111970 MODEL1707111971 MODEL1707111972 MODEL1707111973 MODEL1707111974 MODEL1707111975 MODEL1707111976 MODEL1707111977 MODEL1707111978 MODEL1707111979 MODEL1707111980 MODEL1707111981 MODEL1707111982 MODEL1707111983 MODEL1707111984 MODEL1707111985 MODEL1707111986 MODEL1707111987 MODEL1707111988 MODEL1707111989 MODEL1707111990 MODEL1707111991 MODEL1707111992 MODEL1707111993 MODEL1707111994 MODEL1707111995 MODEL1707111996 MODEL1707111997 MODEL1707111998 MODEL1707111999 MODEL1707112000 MODEL1707112001 MODEL1707112002 MODEL1707112003 MODEL1707112004 MODEL1707112005 MODEL1707112006 MODEL1707112007 MODEL1707112008 MODEL1707112009 MODEL1707112010 MODEL1707112011 MODEL1707112012 MODEL1707112013 MODEL1707112014 MODEL1707112015 MODEL1707112016 MODEL1707112017 MODEL1707112018 MODEL1707112019 MODEL1707112020 MODEL1707112021 MODEL1707112022 MODEL1707112023 MODEL1707112024 MODEL1707112025 MODEL1707112026 MODEL1707112027 MODEL1707112028 MODEL1707112029 MODEL1707112030 MODEL1707112031 MODEL1707112032 MODEL1707112922 MODEL1707113458 MODEL1707113459 MODEL1707113460 MODEL1707113461 MODEL1707113462 MODEL1707113463 MODEL1707113539 MODEL1707113540 MODEL1707113541 MODEL1707114028 MODEL1707114029 MODEL1707114030 MODEL1707114031 MODEL1707114032 MODEL1707114033 MODEL1707114034 MODEL1707114035 MODEL1707114036 MODEL1707114037 MODEL1707114038 MODEL1707114039 MODEL1707114040 MODEL1707114364 MODEL1707114386 MODEL1707114387 MODEL1707114388 MODEL1707114389 MODEL1707114390 MODEL1707114391 MODEL1707114392 MODEL1707114651 MODEL1707114652 MODEL1707114653 MODEL1707114654 MODEL1707114655 MODEL1707114656 MODEL1707114657 MODEL1707114658 MODEL1707114659 MODEL1707114660 MODEL1707114661 MODEL1707114662 MODEL1707114663 MODEL1707114664 MODEL1707114665 MODEL1707114666 MODEL1707114667 MODEL1707114668 MODEL1707115095 MODEL1707115096 MODEL1707115097 MODEL1707115098 MODEL1707115099 MODEL1707115100 MODEL1707115101 MODEL1707115102 MODEL1707115329 MODEL1707115330 MODEL1707115331 .

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.

Format
SBML (L2V3)
Related Publication
  • A pathology atlas of the human cancer transcriptome. Click here to expand
  • Mathias Uhlen, Cheng Zhang, Sunjae Lee, Evelina Sjöstedt, Linn Fagerberg, Gholamreza Bidkhori, Rui Benfeitas, Muhammad Arif, Zhengtao Liu, Fredrik Edfors, Kemal Sanli, Kalle von Feilitzen, Per Oksvold, Emma Lundberg, Sophia Hober, Peter Nilsson, Johanna Mattsson, Jochen M Schwenk, Hans Brunnström, Bengt Glimelius, Tobias Sjöblom, Per-Henrik Edqvist, Dijana Djureinovic, Patrick Micke, Cecilia Lindskog, Adil Mardinoglu, Fredrik Ponten
  • Science (New York, N.Y.) , 8/ 2017 , Volume 357 , Issue 6352 , pages: eaan2507 , PubMed ID: 28818916
  • Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, Sweden. mathias.uhlen@scilifelab.se.
  • 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.
Contributors
Submitter of the first revision: Adil Mardinoglu
Submitter of this revision: Adil Mardinoglu
Curator: Adil Mardinoglu

Metadata information

is (1 statement)
BioModels Database MODEL1707111946

hasTaxon (1 statement)
Taxonomy Homo sapiens

hasProperty (3 statements)
Human Disease Ontology rectum adenocarcinoma
Mathematical Modelling Ontology Constraint-based model
PATO male

isDerivedFrom (2 statements)
BioModels Database MODEL1402200003
Genomic Data Commons Data Portal f9204a59-6877-4d06-a20e-fd7ab0859ed5


Curation status
Non-curated

Connected external resources