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MODEL1604260000 - Santos2016 - Gene signatures of immune sensitivity and resistance in melanoma micrometastatis


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Reference Publication
Publication ID: 10.1038/srep24967...
Guido Santos, Svetoslav Nikolov, Xin Lai, Martin Eberhardt, Florian S. Dreyer, Sushmita Paul, Gerold Schuler & Julio Vera
Model-based genotype-phenotype mapping used to investigate gene signatures of immune sensitivity and resistance in melanoma micrometastasis
Scientific Reports
Systems Biology and Mathematical Modelling Group, University of La Laguna, Spain  [more]
Original Model: MODEL1604260000.origin
Submitter: Vijayalakshmi Chelliah
Submission Date: 26 Apr 2016 15:05:35 UTC
Last Modification Date: 26 Apr 2016 17:10:21 UTC
Creation Date: 26 Apr 2016 17:10:21 UTC
Encoders:  Guido Santos
Santos2016 - Gene signatures of immune sensitivity and resistance in melanoma micrometastatis

This is a non-SBML model

This model is not available in SBML yet (the SBML file that is provided here is a dummy SBML model). However, the original matlab code and the associated data file of the model, provided by the authors can be downloaded from the link below: [vacSim.m, data.mat].

This model is described in the article:

Santos, G., Nikolov, S., Lai, X., Eberhardt, M., Dreyer, Florian S., Paul, S., Schuler, G., Vera, J.,
Scientific Reports 6, Article number: 24967 (2016)


In this paper, we combine kinetic modelling and patient gene expression data analysis to elucidate biological mechanisms by which melanoma becomes resistant to the immune system and to immunotherapy. To this end, we systematically perturbed the parameters in a kinetic model and performed a mathematical analysis of their impact, thereby obtaining signatures associated with the emergence of phenotypes of melanoma immune sensitivity and resistance. Our phenotypic signatures were compared with published clinical data on pretreatment tumor gene expression in patients subjected to immunotherapy against metastatic melanoma. To this end, the differentially expressed genes were annotated with standard gene ontology terms and aggregated into metagenes. Our method sheds light on putative mechanisms by which melanoma may develop immunoresistance. Precisely, our results and the clinical data point to the existence of a signature of intermediate expression levels for genes related to antigen presentation that constitutes an intriguing resistance mechanism, whereby micrometastases are able to minimize the combined anti-tumor activity of complementary responses mediated by cytotoxic T cells and natural killer cells, respectively. Finally, we computationally explored the efficacy of cytokines used as low-dose co-adjuvants for the therapeutic anticancer vaccine to overcome tumor immunoresistance.

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