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Science. 2017 Aug 18;357(6352). pii: eaan2507. doi: 10.1126/science.aan2507.

A pathology atlas of the human cancer transcriptome.

Author information

1
Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, Sweden. mathias.uhlen@scilifelab.se.
2
Center for Biosustainability, Danish Technical University, Copenhagen, Denmark.
3
School of Biotechnology, AlbaNova University Center, KTH-Royal Institute of Technology, Stockholm, Sweden.
4
Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, Sweden.
5
Department of Immunology Genetics and Pathology, Uppsala University, Uppsala, Sweden.
6
Division of Pathology, Lund University, Skåne University Hospital, Lund, Sweden.
7
Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.

Abstract

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.

PMID:
28818916
DOI:
10.1126/science.aan2507
[Indexed for MEDLINE]

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