Yuri Kogan

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

Scientific activity in 2009

  • Development and analysis of the model of cell fate decision, based on the intracellular signaling pathways (with Karin Halevi). We have developed a mathematical model describing the main intracellular regulatory pathways that are responsible for cell fate decision, in particular, proliferation and differentiation control in normal and malignant stem cells. At the first stage, we have concentrated on one the important signaling pathways, the Wnt pathway, which is responsible mainly for regulating proliferation by controlling intracellular levels of ?-Catenin. Our model represents several regulatory and feedback processes involved in this pathway. The aim of our research is to develop a mathematical and computational tool that will allow in silico prediction of the results of possible therapeutic interventions in this pathway, on both the cellular and tissue levels. We have achieved initial validation of the model, using independently published experimental data, which shows the influence of different external biochemical signals on the pathway function.
  • • Development and analysis of a data-driven model of immunotherapy of prostate cancer and development of the method of in-treatment model validation (with Nataly Kronik, Moran Elishmereni, Karin Halevi and Zvia Agur, and in collaboration with S. Vuk-Pavlovic at the Mayo clinic, Rochester, USA). We have developed a mathematical model for prostate cancer progression and its treatment by vaccine or cellular immunotherapy. The model was constructed and validated based on the analysis of the data collected during Phase IIa clinical trials of the cancer vaccine. The model was successful in representing individual results for most of the patients who have responded to the treatment. Further, we have developed an algorithm for constructing and validating the personalized model for each patient, during the initial stage of the clinical trial or treatment. This algorithm was retrospectively validated using the data from the aforementioned clinical trial. We have shown that for most of the patients, already in the middle of the trial we could construct a reliable personal model that would accurately predict the subsequent treatment outcome. This suggests that such methods can be applied prospectively and further used for suggesting protocol improvements during the trial or the treatment.

  • 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. Arakelyan L, Merbl Y, Daugulis P, Ginosar Y, Vainstain V, Kogan Y, Selitser V, Harpak H and Agur Z. 2002. Using multi-scale mathematical modeling in anti-angiogenic therapy, Chap. 7 in Cancer Modeling and Simulation Mathematical Biology and Medicine Series, Chapman & Hall/CRC
    2. Kheiffez Y, Kogan Y, Agur Z., (2004). Matrix and compact operator description of resonance and anti-resonance in cell populations subjected to phase-specific drugs. Journal of medical informatics and tecnologies. Vol. 8, MM11-MM29
    3. Forys U, Kheiffez Y, Kogan Y, (2005). Critical point analysis for three-dimensional cancer angiogenesis models, Mathematical Biosciences and Engineering, vol.2 no..3.
    4. Kheifetz Y, Kogan Y, Agur Z, (2006). Long-range predictability in models of cell populations subjected to phase-specific drugs: growth-rate approximation using properties of positive compact operators, M3AS, 16(7) Supp, July -11-15.
    5. Vainstein V., Ginosar Y., Shoham M., Ianovski A., Rabinovich A., Kogan Y., Selitser V., Agur Z. (2006). Improving cancer therapy by Doxorubicin and Granulocyte colony-stimulating factor: Insights from a Computerized Model of Human Granulopoiesis. Mathematical Modelling of Natural Phenomena 1(2), pp.70-80.
    6. Kogan Y, Ribba B, Marron K, Dahan N, Vainshtein V, Agur Z. (2007). Intensified Doxorubicin-Based Regimen Efficacy in Residual Non-Hodgkin’s Limphoma Disease: Towards a Computationally Supported Treatment Improvement. Mathematical Modelling of Natural Phenomena Vol. 2, No. 3, 47-68.
    7. Agur, Z., Elishmereni, M., Kogan, Y., Kheifetz, Y., Ziv, I., Shoham, M. & Vainstein, V. (2008). Mathematical modeling as a new approach for improving the efficacy/toxicity profile of drugs: the thrombocytopenia case study. In Preclinical development handbook. Ed. Gad, S.1229–1266. New York: John Wiley and Sons.
    8. Kronik N, Kogan Y, Vainstein V, Agur Z, (2008). Improving alloreactive CTL immunotherapy for malignant gliomas by a computerized model. Cancer Immunology, Immunotherapy, Vol. 57, pp.424-439.
    9. Kirnasovsky OU, Kogan Y, Agur Z. (2008). 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.
    10. Kirnasovsky O, Kogan Y, Agur Z. (2008). Analysis of a Mathematical Model for the Molecular Mechanism of Fate Decision in Mammary Stem Cells, MMNP. 3(7) pp. 78-89
    11. Agur Z, Elishmereni M, Kogan Y, Kheiffetz Y, Ziv I, Shoham M, Vainstein V. (2008). Mathematical modeling as a new approach for improving the efficacy/toxicity profile of drugs: the thrombocytopenia case study, Preclinical Development Handbook, Shayne Gad Ed., John Wiley and Sons, USA. pp 1229-1266.
    12. Kirnasovsky O, Kogan Y, Vainstein V, Agur Z, Investigation of tumour dynamics by mathematical modelling at the cellular level. Submitted.
    13. 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. Submitted.


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