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Increasing the Generalization Capability of Biomarkers Through Systems Biology Malaria Vaccines Case Study
EP22697
Poster Title: Increasing the Generalization Capability of Biomarkers Through Systems Biology Malaria Vaccines Case Study
Submitted on 04 Feb 2015
Author(s): Simón Perera del Rosario 1, Raquel Valls 1, Gemma Moncunill 2, Teresa Sardón 1, Carlota Dobaño 2, José Manuel Mas 1
Affiliations: 1. Anaxomics Biotech, Barcelona, Spain 2. Malaria Immunology Group, CRESIB, Barcelona, Spain
This poster was presented at Diagnostics & Biomarkers Online
Poster Views: 2,032
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Poster Information
Abstract: Finding biomarker combinations is a difficult task. As a problem with a large number of solutions, they usually lack generalization power. One example is the fact that a surrogate biomarker of immunity has been difficult to achieve for malaria and other complex diseases through classical immunological assays. Within the context of SysMalVac, a project partially funded by the European Seventh Framework Programme (FP7) [1], Anaxomics proposed to use Systems Biology in order to analyse two malaria vaccination models (the RTS,S vaccine and the CPS immunization strategy) in order to identify combinatorial biomarkers of protection. The aim of the project is to design a tool able to predict whether a person will be protected from malaria after vaccination. The prediction is achieved through the development of mathematical models including newly generated cellular transcriptome profiles, immunological read-outs and transcriptomic results from both trials, and experimental data obtained from non-human primates. This analytical tool will not also predict each individual’s protection, but will also allow identifying a biomarker signature indicative of protection to malaria.

[1] The SysMalVac Consortium. SysMalVac. 2013 [cited 2014 11 July 2014]; Available from: http://www.sysmalvac.eu/
Summary: The results underline the utility of Systems Biology (and specially Anaxomics’s TPMS) for the interpretation of high-throughput data in BM identification, with a better generalization capability than conventional methods.References: 1. Ransohoff, D.F. (2004). Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer.
4(4): p. 309-314.
2. Mas JM, Pujol A, Aloy P, Farrés J. Methods and systems for identifying molecules or processes of biological interest by using knowledge discovery in biological data. 2010. US Patent Application Nº. 12/912,535.
3. The SysMalVac Consortium (2013). SysMalVac [cited 11 July 2014]; Available from: http://www.sysmalvac.eu/.
4. Casares, S., T.D. Brumeanu, and T.L. Richie (2010). The RTS,S malaria vaccine. Vaccine 28(31): p. 4880-94.
5. Roestenberg, M., et al. (2011). Long-term protection against malaria after experimental sporozoite inoculation: an open-label follow-up study. Lancet. 377(9779): p. 1770-6.
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