P. Steeg, T. Ouatas, D. Halverson, D. Palmieri, and M. Salerno, Metastasis Suppressor Genes: Basic Biology and Potential Clinical Use, Clinical Breast Cancer, vol.4, issue.1, pp.51-62, 2003.
DOI : 10.3816/CBC.2003.n.012

D. Hanahan and R. Weinberg, The Hallmarks of Cancer, Cell, vol.100, issue.1, pp.57-70, 2000.
DOI : 10.1016/S0092-8674(00)81683-9

D. Parkin, F. Bray, J. Ferlay, and P. Pisani, Global Cancer Statistics, 2002, Global cancer statistics, pp.74-108, 2002.
DOI : 10.3322/canjclin.55.2.74

L. Sobin, TNM classification of malignant timors Wiley-Liss, 2000.

A. Benson, . Iii, D. Schrag, M. Somerfield, A. Cohen et al., American Society of Clinical Oncology Recommendations on Adjuvant Chemotherapy for Stage II Colon Cancer, Journal of Clinical Oncology, vol.22, issue.16, pp.3408-3419, 2004.
DOI : 10.1200/JCO.2004.05.063

P. Dalerba, C. Maccalli, C. Casati, C. Castelli, and G. Parmiani, Immunology and immunotherapy of colorectal cancer, Critical Reviews in Oncology/Hematology, vol.46, issue.1, pp.33-57, 2003.
DOI : 10.1016/S1040-8428(02)00159-2

I. Atreya and M. Neurath, Immune cells in colorectal cancer: prognostic relevance and therapeutic strategies, Expert Review of Anticancer Therapy, vol.8, issue.4, pp.561-572, 2008.
DOI : 10.1586/14737140.8.4.561

J. Galon, A. Costes, F. Sanchez-cabo, A. Kirilovsky, B. Mlecnik et al., Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome, Science, vol.313, issue.5795, pp.1960-1964, 2006.
DOI : 10.1126/science.1129139

F. Pages, A. Berger, M. Camus, F. Sanchez-cabo, A. Costes et al., Effector Memory T Cells, Early Metastasis, and Survival in Colorectal Cancer, New England Journal of Medicine, vol.353, issue.25, pp.2654-2666, 2005.
DOI : 10.1056/NEJMoa051424

J. Galon, W. Fridman, and F. Pages, The Adaptive Immunologic Microenvironment in Colorectal Cancer: A Novel Perspective, Cancer Research, vol.67, issue.5, pp.1883-1886, 2007.
DOI : 10.1158/0008-5472.CAN-06-4806

A. Sturn, J. Quackenbush, and Z. Trajanoski, Genesis: cluster analysis of microarray data, Bioinformatics, vol.18, issue.1, pp.207-208, 2002.
DOI : 10.1093/bioinformatics/18.1.207

F. Harrel, Regression modeling strategies: with applications to Linear Models, Logistic Regression and Survival analysis Springer Series in Statistics, 2001.

J. Bland and D. Altman, The logrank test, BMJ, vol.328, issue.7447, 2004.
DOI : 10.1136/bmj.328.7447.1073

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC403858

D. Altman and P. Royston, The cost of dichotomising continuous variables, BMJ, vol.332, issue.7549, p.1080, 2006.
DOI : 10.1136/bmj.332.7549.1080

D. Altman, B. Lausen, W. Sauerbrei, and M. Schumacher, Dangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic Factors, JNCI Journal of the National Cancer Institute, vol.86, issue.11, pp.829-835, 1994.
DOI : 10.1093/jnci/86.11.829

H. Heinzl, A cautionary note on segmenting a cyclical covariate by minimum P-value search, Computational Statistics & Data Analysis, vol.35, issue.4, pp.451-461, 2009.
DOI : 10.1016/S0167-9473(00)00023-2

D. Faraggi and R. Simon, A simulation study of cross-validation for selecting an optimal cutpoint in univariate survival analysis, pp.2203-2213, 1996.

N. Hollander, W. Sauerbrei, and M. Schumacher, Confidence intervals for the effect of a prognostic factor after selection of an ???optimal??? cutpoint, Statistics in Medicine, vol.48, issue.11, pp.1701-1713, 2004.
DOI : 10.1002/sim.1611

J. Pittman, E. Huang, J. Nevins, Q. Wang, and M. West, Bayesian analysis of binary prediction tree models for retrospectively sampled outcomes, Biostatistics, vol.5, issue.4, pp.587-601, 2004.
DOI : 10.1093/biostatistics/kxh011

P. Shannon, A. Markiel, O. Ozier, N. Baliga, J. Wang et al., Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks, Genome Research, vol.13, issue.11, pp.2498-2504, 2003.
DOI : 10.1101/gr.1239303

M. Cline, M. Smoot, E. Cerami, A. Kuchinsky, N. Landys et al., Integration of biological networks and gene expression data using Cytoscape, Nature Protocols, vol.31, issue.10, pp.2366-2382, 2007.
DOI : 10.1038/nprot.2007.324

G. Bindea, B. Mlecnik, H. Hackl, P. Charoentong, M. Tosolini et al., ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks, Bioinformatics, vol.25, issue.8, pp.1091-1093, 2009.
DOI : 10.1093/bioinformatics/btp101

O. Garcia, C. Saveanu, M. Cline, M. Fromont-racine, A. Jacquier et al., GOlorize: a Cytoscape plug-in for network visualization with Gene Ontology-based layout and coloring, Bioinformatics, vol.23, issue.3, pp.394-396, 2007.
DOI : 10.1093/bioinformatics/btl605

URL : https://hal.archives-ouvertes.fr/pasteur-01404708

M. Ashburner, C. Ball, J. Blake, D. Botstein, H. Butler et al., Gene Ontology: tool for the unification of biology, Nature Genetics, vol.9, issue.1, pp.25-29, 2000.
DOI : 10.1038/75556

D. Hwang, A. Rust, S. Ramsey, J. Smith, D. Leslie et al., A data integration methodology for systems biology, Proceedings of the National Academy of Sciences, vol.102, issue.48, pp.17296-17301, 2005.
DOI : 10.1073/pnas.0508647102

S. Liang, S. Fuhrman, and R. Somogyi, Reveal, a general reverse engineering algorithm for inference of genetic network architectures, Pac Symp Biocomput, pp.18-29, 1998.

A. Margolin, I. Nemenman, K. Basso, C. Wiggins, G. Stolovitzky et al., ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context, BMC Bioinformatics, vol.7, issue.Suppl 1, p.7, 2006.
DOI : 10.1186/1471-2105-7-S1-S7

C. Von-mering, L. Jensen, B. Snel, S. Hooper, M. Krupp et al., STRING: known and predicted protein-protein associations, integrated and transferred across organisms, Nucleic Acids Research, vol.33, issue.Database issue, pp.433-437, 2005.
DOI : 10.1093/nar/gki005

A. Anderson and V. Quaranta, Integrative mathematical oncology, Nature Reviews Cancer, vol.247, issue.3, pp.227-234, 2008.
DOI : 10.1038/nrc2329

R. Araujo and D. Mcelwain, A history of the study of solid tumour growth: the contribution of mathematical modelling, Bulletin of Mathematical Biology, vol.66, issue.5, pp.1039-1091, 2004.
DOI : 10.1016/j.bulm.2003.11.002

F. Kozusko and M. Bourdeau, A unified model of sigmoid tumour growth based on cell proliferation and quiescence, Cell Proliferation, vol.238, issue.6, pp.824-834, 2007.
DOI : 10.1038/35098076

P. Macklin, S. Mcdougall, A. Anderson, M. Chaplain, V. Cristini et al., Multiscale modelling and nonlinear simulation of vascular tumour growth, Journal of Mathematical Biology, vol.67, issue.2, pp.765-798, 2009.
DOI : 10.1007/s00285-008-0216-9

T. Roose, S. Chapman, and P. Maini, Mathematical Models of Avascular Tumor Growth, SIAM Review, vol.49, issue.2, pp.179-208, 2007.
DOI : 10.1137/S0036144504446291

A. Anderson, Single-Cell-Based Models in, Biology and Medicine (Mathematics and Biosciences in Interaction) Birkhauser, vol.12001

P. Beverley, Primer: making sense of T-cell memory, Nature Clinical Practice Rheumatology, vol.10, issue.1, pp.43-49, 2008.
DOI : 10.1038/ncprheum0671

D. Boer, R. Oprea, M. Antia, R. Murali-krishna, K. Ahmed et al., Recruitment Times, Proliferation, and Apoptosis Rates during the CD8+ T-Cell Response to Lymphocytic Choriomeningitis Virus, Journal of Virology, vol.75, issue.22, pp.10663-10669, 2001.
DOI : 10.1128/JVI.75.22.10663-10669.2001

D. Boer, R. Homann, D. Perelson, and A. , Different Dynamics of CD4+ and CD8+ T Cell Responses During and After Acute Lymphocytic Choriomeningitis Virus Infection, The Journal of Immunology, vol.171, issue.8, pp.3928-3935, 2003.
DOI : 10.4049/jimmunol.171.8.3928

R. Antia, V. Ganusov, and R. Ahmed, The role of models in understanding CD8+ T-cell memory, Nature Reviews Immunology, vol.4, issue.2, pp.101-111, 2005.
DOI : 10.1038/nri1550

P. Kim, P. Lee, and D. Levy, Dynamics and Potential Impact of the Immune Response to Chronic Myelogenous Leukemia, PLoS Computational Biology, vol.17, issue.6, p.1000095, 2008.
DOI : 10.1371/journal.pcbi.1000095.t018

H. Moore and N. Li, A mathematical model for chronic myelogenous leukemia (CML) and T cell interaction, Journal of Theoretical Biology, vol.227, issue.4, pp.513-523, 2004.
DOI : 10.1016/j.jtbi.2003.11.024

S. Eikenberry, C. Thalhauser, and Y. Kuang, Tumor-Immune Interaction, Surgical Treatment, and Cancer Recurrence in a Mathematical Model of Melanoma, PLoS Computational Biology, vol.52, issue.4, p.1000362, 2009.
DOI : 10.1371/journal.pcbi.1000362.t002