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Open Access Highly Accessed Research article

The functional cancer map: A systems-level synopsis of genetic deregulation in cancer

Markus Krupp1*, Thorsten Maass1, Jens U Marquardt1, Frank Staib1, Tobias Bauer2, Rainer König2, Stefan Biesterfeld3, Peter R Galle1, Achim Tresch4 and Andreas Teufel1

Author Affiliations

1 Department of Medicine I, Johannes Gutenberg University, Mainz, Germany

2 Institut of Pharmacy and Molecular Biotechnology, Bioquant, University of Heidelberg, INF 267, 69120 Heidelberg, Germany

3 Institute for Pathology, Johannes Gutenberg University, Mainz, Germany, and Department of Cytopathology, Heinrich Heine University, Düsseldorf, Germany

4 Gene Center Munich, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University, Munich, Germany

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BMC Medical Genomics 2011, 4:53  doi:10.1186/1755-8794-4-53

Published: 30 June 2011

Abstract

Background

Cancer cells are characterized by massive dysegulation of physiological cell functions with considerable disruption of transcriptional regulation. Genome-wide transcriptome profiling can be utilized for early detection and molecular classification of cancers. Accurate discrimination of functionally different tumor types may help to guide selection of targeted therapy in translational research. Concise grouping of tumor types in cancer maps according to their molecular profile may further be helpful for the development of new therapeutic modalities or open new avenues for already established therapies.

Methods

Complete available human tumor data of the Stanford Microarray Database was downloaded and filtered for relevance, adequacy and reliability. A total of 649 tumor samples from more than 1400 experiments and 58 different tissues were analyzed. Next, a method to score deregulation of KEGG pathway maps in different tumor entities was established, which was then used to convert hundreds of gene expression profiles into corresponding tumor-specific pathway activity profiles. Based on the latter, we defined a measure for functional similarity between tumor entities, which yielded to phylogeny of tumors.

Results

We provide a comprehensive, easy-to-interpret functional cancer map that characterizes tumor types with respect to their biological and functional behavior. Consistently, multiple pathways commonly associated with tumor progression were revealed as common features in the majority of the tumors. However, several pathways previously not linked to carcinogenesis were identified in multiple cancers suggesting an essential role of these pathways in cancer biology. Among these pathways were 'ECM-receptor interaction', 'Complement and Coagulation cascades', and 'PPAR signaling pathway'.

Conclusion

The functional cancer map provides a systematic view on molecular similarities across different cancers by comparing tumors on the level of pathway activity. This work resulted in identification of novel superimposed functional pathways potentially linked to cancer biology. Therefore, our work may serve as a starting point for rationalizing combination of tumor therapeutics as well as for expanding the application of well-established targeted tumor therapies.

Keywords:
cancer; systems biology; prognostic marker; microarray; bioinformatics