Yuri Kogan

Yuri Yuri Kogan holds a BA degree in Theoretical Mathematics from the Tel-Aviv University (TAU). Over many years of scientific research at IMBM, he has been involved in biomathematical modelling of several cancer diseases, as well as in researching cancer stem cells, intracellular signal transduction and clinical immunotherapy. His current research continues to focus on modelling cancer growth and treatment, in particular, immunotherapy of prostate cancer and glioblastomas, modelling of cancer stem cells, and modelling of intracellular signal transduction.

Scientific activity in 2011

  • Further development of intracellular signaling model.We use the validated Wnt pathway model to explore the possible role of mutations in APC gene, which is one of the most influential components of the pathway. This will be done along with validation of our model predictions of the pathway target proteins concentrations by appropriate experimental data. Other cancer-related mutations in the pathway will be similarly explored. Our aim is to suggest possible therapeutic intervention for suppressing the oncogenic effects of such mutations. We will also extend our model to include other major signaling pathways, such as Shh and Notch. At a later stage, we will integrate our model into a multi-scale modelling framework , which will include cellular and tissue dynamics and cancer progression and treatment.
  • Application and development of immunotherapy treatment model and in-trial model personalization algorithm. Our immunotherapy model will be further developed to include important biological processes and components, which are ignored now. We will develop and further explore the applicability of our algorithm to different treatment modalities.

Work program for 2010

  • Further development of the intracellular signaling model, extending the model to include other major signaling pathways. The model will eventually be integrated into a multi-scale framework that will describe tissue dynamics of cancer progression and treatment.
  • Application and development of an immunotherapy treatment model. The modelbe applied to the new human clinical data in order to validate the proposed algorithm and will be further developed to include important biological processes, such as immune memory, which are currently neglected.

Publications

  1. Vainstein V, Kirnasovsky OU, Kogan Y, Agur Z, Strategies for cancer stem cell elimination: Insights from mathematical modelling, 2011 In preparation
  2. Kogan Y., Halevi-Tobias K., Hochman G., Baczmanska A.K., Leyns L., Agur Z. Synergistic effect of sFRP1 and Dkk1 on ßCatenin accumulation: results from a new mathematical model of the Wnt signaling pathway. 2011 In preparation
  3. Kogan Y., Halevi-Tobias K., Elishmereni M., Vuk Pavlović S., Agur Z. In–Treatment Personalization of Immunotherapy by a New Algorithm Applied to Clinical Data. 2011 In preparation.
  4. Kogan Y., Forys U., Shukron O., Kronik N., Agur Z. Cellular immunotherapy for high grade Gliomas: mathematical analysis deriving efficacious infusion rates based on patient requirements. SIAM J. Appl. Math. 2010 70(6) pp. 1953-1976
  5. Agur Z., Kogan Y., Levi L., Harrison H., Lamb R., Kirnasovsky O.U., Clarke R.B. Disruption of a Quorum Sensing Mechanism Triggers Tumorigenesis: a Simple Discrete Model Corroborated by Experiments in Mammary Cancer Stem Cells. Biol Direct, 2010 5(1) pp.20-41
  6. Kronik N., Kogan Y., Elishmereni M., Halevi-Tobias K., Vuk Pavlović S., Agur Z. Predicting Effect of Prostate Cancer Immunotherapy by Personalized Mathematical Models, PLoS one, 2010 5(12) e15482
  7. Kirnasovsky O, Kogan Y, Agur Z. Analysis of a Mathematical Model for the Molecular Mechanism of Fate Decision in Mammary Stem Cells, MMNP. 2008 3(7) pp. 78-89
  8. Kirnasovsky OU, Kogan Y, Agur Z. Resilience in stem cell renewal: development of the Agur--Daniel--Ginosar model. Discrete and Continuous Dynamical Systems - Series B (DCDS-B), Volume: 10, Number: 1, July 2008
  9. Kronik N, Kogan Y, Vainstein V, Agur Z, Improving alloreactive CTL immunotherapy for malignant gliomas by a computerized model. Cancer Immunology, Immunotherapy, 2008 vol. 57, pp.424-439,.
  10. Agur Z, Elishmereni M, Kogan Y, Kheifetz Y, Ziv I, Shoham M, Vainstein V, Mathematical modeling as a new approach for improving the efficacy/toxicity profile of drugs: the thrombocytopenia case study. In: Preclinical Development Handbook, John Wiley and Sons. 2008, pp 1229-1266
  11. Kogan Y, Ribba B, Marron K, Dahan N, Vainshtein V, Agur Z. 2004. Intensified Doxorubicin-Based Regimen Efficacy in Residual Non-Hodgkin’s Limphoma Disease: Towards a Computationally Supported Treatment Improvement. Mathematical Modelling of Natural Phenomena 2007 Vol. 2, No. 3, , pp. 47-68.
  12. Vainstein V., Ginosar Y., Shoham M., Ianovski A., Rabinovich A., Kogan Y., Selitser V., Agur Z. Improving cancer therapy by Doxorubicin and Granulocyte colony-stimulating factor: Insights from a Computerized Model of Human Granulopoiesis. Mathematical Modelling of Natural Phenomena 2006 1(2), pp.70-80.
  13. Arakelyan L, Merbl Y, Daugulis P, Ginosar Y, Vainstain V, Kogan Y, Selitser V, Harpak H and Agur Z. Using multi-scale mathematical modeling in anti-angiogenic therapy, Chap. 7 in Cancer Modeling and Simulation Mathematical Biology and Medicine Series, Chapman & Hall/CRC 2002
  14. Kheifetz Y, Kogan Y, Agur Z, Long-range predictability in models of cell populations subjected to phase-specific drugs: growth-rate approximation using properties of positive compact operators, M3AS, 2006 16(7) Supp, July -11-15.
  15. Forys U, Kheiffez Y, Kogan Y, Critical point analysis for three-dimensional cancer angiogenesis models, Mathematical Biosciences and Engineering, 2005 vol.2 num.3, August.
  16. Kheiffez Y, Kogan Y, Agur Z., Matrix and compact operator description of resonance and anti-resonance in cell populations subjected to phase-specific drugs. Journal of medical informatics and tecnologies. 2004 vol. 8, , MM11-MM29

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