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This article is part of the supplement: São Paulo Advanced School of Comparative Oncology: Abstracts

Open Access Keynote lecture presentation

Integrative cancer informatics for the identification of prognostic and predictive biomarkers

Igor Jurisica

Author affiliations

Ontario Cancer Institute and University Health Network, University of Toronto, Canada

Citation and License

BMC Proceedings 2013, 7(Suppl 2):K7  doi:10.1186/1753-6561-7-S2-K7

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1753-6561/7/S2/K7


Published:4 April 2013

© 2013 Jurisica; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Keynote lecture presentation

Cancer development is a multi-step process that leads to uncontrolled tumor cell growth. Multiple pathways are involved; typically some signalling and regulatory pathways are activated, while others are suppressed. Systematically exploring these networks of proteins will lead to better understanding of disease initiation and progression. Integrating these data with microRNA regulatory networks may identify control mechanism that these master regulators use to affect oncogenesis. Including data on drug targets, modes of actions predicted from drug profiles and compound similarity will in turn lead to more effective patient treatment. To address these challenges, we developed a system for an integrative analysis, prediction and characterization of molecular signatures and relevant protein-protein interactions, microRNA: gene interactions, and resources for rationally identifying drug combinations for cancer treatment.

Competing interests

There are no competing interests in this presentation.