1. Mathematical modeling of differential effects of neo-adjuvant Sunitinib on primary tumor and metastatic growth
   C. Nicolò, M. Mastri, J. ML Ebos and S. Benzekry
   in preparation, 2019


2. Impact of treatment breaks and burst in the neo-adjuvant setting for anti-angiogenic therapy of kidney cancer
   M. Mastri, C. Nicolò S. Benzekry and J. ML Ebos
   in preparation, 2019


3. Machine learning and mechanistic modeling for prediction of metastatic relapse in breast cancer
   C. Nicolo, C. Perier, M. Prague, G. MacGrogan, O. Saut, S. Benzekry
   under revision at the Journal of Clinical Oncology: Cancer Clin Informatics
   bioRxiv, doi:10.1101/634428, 2019


4. A reduced Gompertz model for predicting tumor age using a population approach
   C. Vaghi, A. Rodallec, R. Fanciullino, J. Ciccolini, J. Mochel, M. Mastri, C. Poignard, J. ML Ebos, S. Benzekry
   under revision at PLoS Computational Biology
   bioRxiv, doi:10.1101/670869, 2019


5. Population Modeling of Tumor Growth Curves, the Reduced Gompertz Model and Prediction of the Age of a Tumor.
   C. Vaghi, A. Rodallec, R. Fanciullino, J. Ciccolini, J. Mochel, M. Mastri, J. ML Ebos, C. Poignard and S. Benzekry
   In G. Bebis, T. Benos, K. Chen, K. Jahn, & E. Lima (Eds.), (pp. 87–97). Presented at the Mathematical and Computational Oncology, Cham: Springer International Publishing, 2019


6. Quantitative mathematical modeling of clinical brain metastasis dynamics in non-small cell lung cancer
   M. Bilous, C. Serdjebi, A. Boyer, P. Tomasini, C. Pouypoudat, D. Barbolosi, F. Barlesi, F. Chomy and S. Benzekry
   Scientific Reports, Volume 9, Issue 1, 13018, bioRxiv, hal, 2019


7. CAR T-Cell Immunotherapy in Human and Veterinary Oncology: Changing the Odds Against Hematological Malignancies
   J. P Mochel, S. C Ekker, C. M Johannes, A. E Jergens, K. Allenspach, A. Bourgois-Mochel, M. Knouse, S. Benzekry, W. Wierson, A. K LeBlanc, S. S Kenderian
   AAPS J, Volume 21, Issue 3, p.50, hal, 2019


8. A transient senescence-associated secretome promotes tumor growth following antiangiogenic therapy withdrawal
   Mastri M, Tracz A, Lee CR, Attwood K, Christensen JG, Ebos JML
   Cell Reports, Volume 25, Issue 13, p. 3706-3720, 2018


9. Tumor-independent host secretomes induced by angiogenesis and immune-checkpoint inhibitors
   Mastri M, Tracz A, Lee CR, Attwood K, Kerbel RS, Dolan M, Shi Y, Ebos JML
   Molecular Cancer Therapeutics, Volume 17, Issue 7, pp.1602-1612, 2018


10. Turning cold tumors into hot tumors: harnessing the potential of tumor immunity using nanoparticles
    A. Rodallec, G. Sicard, R. Fanciullino, S. Benzekry, B. Lacarelle, G. Milano, J. Ciccolini
    Expert Opin Drug Met, DOI:10.1080/17425255.2018.1540588, 2018


11. Revisiting bevacizumab + cytotoxics scheduling using mathematical modeling: proof of concept study in experimental non-small cell lung carcinoma
    D.C. Imbs^*, R. El Cheikh^*, A. Boyer, J. Ciccolini, C. Mascaux, B. Lacarelle, F. Barlesi, D. Barbolosi and S. Benzekry, ^* = equal contribution
    CPT Pharmacometrics Syst Pharmacol, Volume 3, Issue 14 suppl, pp. 2335, hal, 2017


12. Dose- and time-dependence of the host-mediated response to paclitaxel therapy: a mathematical modeling approach
    M. Benguigui, D. Alishekevitz, M. Timaner, D. Shechter, Z. Raviv, S. Benzekry^*, Y. Shaked^*, ^* = joint supervising authors
    Oncotarget, hal, 2018


13. Pharmacokinetics of nanoparticles in oncology: clues for anticipating interpatient variability
    R. Fanciullino, S. Benzekry, B. Lacarelle, J. Ciccolini, A. Rodallec
    Critical Reviews in Oncology/Hematology, Volume 129, pp. 1-12, hal, 2018


14. Mathematical modeling of tumor-tumor distant interactions supports a systemic control of tumor growth
    S. Benzekry, C. Lamont, D. Barbolosi, L. Hlatky, P. Hahnfeldt
    Cancer Research, Volume 77, Issue 18, pp.5183-5193, 10.1158/0008-5472.CAN-17-0564, 2017


15. Model Driven Optimization of Antiangiogenics + Cytotoxics Combination: Application to Breast Cancer Mice Treated with Bevacizumab + Paclitaxel Doublet Leads to Reduced Tumor Growth and Fewer Metastasis
    S. Mollard, J. Ciccolini, D.C. Imbs, R. El Cheikh, D. Barbolosi, S. Benzekry
    Oncotarget, Volume 5, 10.18632/oncotarget.15484, 2017


16. Androgens modulate male-derived endothelial cell homeostasis using androgen receptor-dependent and receptor-independent mechanisms
    Torres-Estay V, Carreño DV, Fuenzalida P, Watts A, San Francisco IF, Montecinos VP, Sotomayor PC, Ebos J, Smith GJ, Godoy AS.
    Angiogenesis, 2017


17. Sunitinib Stimulates Expression of VEGFC by Tumor Cells and Promotes Lymphangiogenesis in Clear Cell Renal Cell Carcinomas
    Dufies M, Giuliano S, Ambrosetti D, Claren A, Ndiaye PD, Mastri M, Moghrabi W, Cooley LS, Ettaiche M, Chamorey E, Parola J, Vial V, Lupu-Plesu M, Bernhard JC, Ravaud A, Borchiellini D, Ferrero JM, Bikfalvi A, Ebos JM, Khabar KS, Grépin R, Pagès G.
    Cancer Res, Volume 77, Issue 5, pp.1212-1226, 2017


18. Non-Standard Radiotherapy Fractionations Delay the Time to Malignant Transformation of Low-Grade Gliomas
    A. Henares-Molina, S. Benzekry, P.C. Lara, M. Garcia-Rojo, V.M. Perez-Garcia and A. Martinez-Gonzalez
    PloS One, Volume 12, Issue 6, e0178552, hal, 2017


19. Modeling spontaneous metastasis following surgery: an in vivo-in silico approach
    S. Benzekry, A. Tracz, M. Mastri, R. Corbelli, D. Barbolosi, J.M.L. Ebos
    Cancer Research, Volume 76, Issue 3, pp. 535-547, 10.1158/0008-5472.CAN-15-1389, 2016.


20. On the growth and dissemination laws in a mathematical model of metastatic growth
    S. Benzekry, J. ML Ebos
    ITM Web of Conferences, Volume 5, 10.1051/itmconf/20150500007, 2015


21. Classical Mathematical Models for Description and Forecast of Preclinical Tumor Growth
    S. Benzekry, C. Lamont, A. Beheshti, A. Tracz, J.M.L. Ebos, L. Hlatky, P. Hahnfeldt
    PloS Computational Biology, Volume 10, Issue 8, e1003800, 2014

1. June 2019, Population Approach Group meeting in Europe (PAGE), Stockholm, Sweden. Machine learning versus mechanistic modeling for prediction of metastatic relapse in breast cancer. Oral
   C. Nicolò, C. Perier, M. Prague, C. Bellera, G. MacGrogan, O. Saut, S. Benzekry
   
   
2. June 2019, Population Approach Group meeting in Europe (PAGE), Stockholm, Sweden. Machine learning combined to mechanistic modeling of differential effects of neo-adjuvant Sunitinib on primary tumor and metastatic growth. Oral
   C. Nicolò, M. Mastri, J. ML Ebos, S. Benzekry
   
   
3. May 2019, NCI Mathematical Oncology Meeting, Portland, USA. Machine learning versus mechanistic modeling for prediction of metastatic relapse in breast cancer. Oral
   S. Benzekry
   
   
4. August 2018, 17th Biennial Congress of the Metastasis Research Society, Princeton, NJ, USA. Poster.
   M. Mastri, C. Périer, G. MacGrogan, J ML Ebos, S. Benzekry
   
   
5. July 2018, Mathematical perspectives in the biology and therapeutics of cancer, Marseille, France. Oral. Improving intra-tumor drug distribution of anti-cancer nanoparticles by data-informed mathematical modeling.
   C. Vaghi, A. Rodallec, R. Fanciullino, J. Ciccolini, J. ML Ebos, C. Poignard, S. Benzekry
   
   
6. June 2018, Data science summer school, Polytechnique, Palaiseau, France. Poster (best poster award)
   C. Vaghi, A. Rodallec, R. Fanciullino, J. Ciccolini, J. ML Ebos, C. Poignard, S. Benzekry
   
   
7. April 2018, Annual meeting of the AACR, Chicago, USA. Poster. Mathematical modeling of differential effects of Sunitinib on primary tumor and metastatic growth.
   C. Nicolò, M. Mastri, A. Tracz, J ML Ebos, S. Benzekry
   
   
8. May 2017, ISoP local Event, Paris, France. Poster. Population modeling of differential effects of Sunitinib on primary tumor and metastatic growth
   
   
9. October 2015, Journées du cancéropôle Grand Sud-Ouest, Bordeaux, France. Poster. Modeling spontaneous metastasis following surgery: an in vivo-in silico approach