This article is part of the supplement: International Workshop on Computational Systems Biology: Approaches to Analysis of Genome Complexity and Regulatory Gene Networks

Open Access Open Badges Research

Data integration and exploration for the identification of molecular mechanisms in tumor-immune cells interaction

Bernhard Mlecnik12, Fatima Sanchez-Cabo13, Pornpimol Charoentong1, Gabriela Bindea12, Franck Pagès24, Anne Berger4, Jerome Galon24* and Zlatko Trajanoski1*

Author affiliations

1 Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria

2 INSERM, U872, Integrative Cancer Immunology, Paris, France

3 Genomics Unit, Spanish National Centre for Cardiovascular Research, Madrid, Spain

4 AP-HP, Georges Pompidou European Hospital, Paris, France

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Citation and License

BMC Genomics 2010, 11(Suppl 1):S7  doi:10.1186/1471-2164-11-S1-S7

Published: 10 February 2010


Cancer progression is a complex process involving host-tumor interactions by multiple molecular and cellular factors of the tumor microenvironment. Tumor cells that challenge immune activity may be vulnerable to immune destruction. To address this question we have directed major efforts towards data integration and developed and installed a database for cancer immunology with more than 1700 patients and associated clinical data and biomolecular data. Mining of the database revealed novel insights into the molecular mechanisms of tumor-immune cell interaction. In this paper we present the computational tools used to analyze integrated clinical and biomolecular data. Specifically, we describe a database for heterogenous data types, the interfacing bioinformatics and statistical tools including clustering methods, survival analysis, as well as visualization methods. Additionally, we discuss generic issues relevant to the integration of clinical and biomolecular data, as well as recent developments in integrative data analyses including biomolecular network reconstruction and mathematical modeling.