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Dive into the research topics where Johanna Sápi is active.

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Featured researches published by Johanna Sápi.


Journal of Translational Medicine | 2012

Poorly differentiated synovial sarcoma is associated with high expression of enhancer of zeste homologue 2 (EZH2)

Yi-Che Changchien; Péter Tátrai; Gergő Papp; Johanna Sápi; László Fónyad; Miklós Szendrői; Zsuzsanna Pápai; Zoltán Sápi

BackgroundEnhancer of zeste homologue 2 (EZH2) is a polycomb group (PcG) family protein. Acting as a histone methyltransferase it plays crucial roles in maintaining epigenetic stem cell signature, while its deregulation leads to tumor development. EZH2 overexpression is commonly associated with poor prognosis in a variety of tumor types including carcinomas, lymphomas and soft tissue sarcomas. However, although the synovial sarcoma fusion proteins SYT-SSX1/2/4 are known to interact with PcG members, the diagnostic and prognostic significance of EZH2 expression in synovial sarcoma has not yet been investigated. Also, literature data are equivocal on the correlation between EZH2 expression and the abundance of trimethylated histone 3 lysine 27 (H3K27me3) motifs in tumors.MethodsImmunohistochemical stains of EZH2, H3K27me3, and Ki-67 were performed on tissue microarrays containing cores from 6 poorly differentiated, 39 monophasic and 10 biphasic synovial sarcomas, and evaluated by pre-established scoring criteria. Results of the three immunostainings were compared, and differences were sought between the histological subtypes as well as patient groups defined by gender, age, tumor location, the presence of distant metastasis, and the type of fusion gene. The relationship between EZH2 expression and survival was plotted on a Kaplan-Meier curve.ResultsHigh expression of EZH2 mRNA and protein was specifically detected in the poorly differentiated subtype. EZH2 scores were found to correlate with those of Ki-67 and H3K27me3. Cases with high EZH2 score were characterized by larger tumor size (≥ 5cm), distant metastasis, and poor prognosis. Even in the monophasic and biphasic subtypes, higher expression of EZH2 was associated with higher proliferation rate, larger tumor size, and the risk of developing distant metastasis. In these histological groups, EZH2 was superior to Ki-67 in predicting metastatic disease.ConclusionsHigh expression of EZH2 helps to distinguish poorly differentiated synovial sarcoma from the monophasic and biphasic subtypes, and it is associated with unfavorable clinical outcome. Importantly, high EZH2 expression is predictive of developing distant metastasis even in the better-differentiated subtypes. EZH2 overexpression in synovial sarcoma is correlated with high H3K27 trimethylation. Thus, along with other epigenetic regulators, EZH2 may be a future therapeutic target.


Computer Methods and Programs in Biomedicine | 2014

Model-based angiogenic inhibition of tumor growth using modern robust control method

Levente Kovács; Annamária Szeles; Johanna Sápi; Dániel András Drexler; Imre J. Rudas; István Harmati; Zoltán Sápi

Cancer is one of the most destructive and lethal illnesses of the modern civilization. In the last decades, clinical cancer research shifted toward molecular targeted therapies which have limited side effects in comparison to conventional chemotherapy and radiation therapy. Antiangiogenic therapy is one of the most promising cancer treatment methods. The dynamical model for tumor growth under angiogenic stimulator/inhibitor control was posed by Hahnfeldt et al. in 1999; it was investigated and partly modified many times. In this paper, a modified version of the originally published model is used to describe a continuous infusion therapy. In order to generalize individualized therapies a robust control method is proposed using H(∞) methodology. Uncertainty weighting functions are determined based on the real pathophysiological case and simulations are performed on different tumor volumes to demonstrate the robustness of the proposed method.


IFAC Proceedings Volumes | 2011

Model-Based Analysis and Synthesis of Tumor Growth under Angiogenic Inhibition: A Case Study

Dániel András Drexler; Levente Kovács; Johanna Sápi; István Harmati; Zoltán Benyó

Abstract Anti-angiogenic therapy is a promising method to fight cancer, however the special therapeutic drugs applied are quite expensive. The aim of this paper is to define simple therapeutical guidelines for sufficient treatment with the usage of the least amount of drugs possible with the help of control theory. We analyze a nonlinear tumor growth model, and use optimal control to design Linear Quadratic controller for offline simulations. The linear model is gained by working point linearization, after the examination of the possible operation points.


PLOS ONE | 2015

Tumor Volume Estimation and Quasi-Continuous Administration for Most Effective Bevacizumab Therapy

Johanna Sápi; Levente Kovács; Dániel András Drexler; Pál Kocsis; Dávid Gajári; Zoltán Sápi

Background Bevacizumab is an exogenous inhibitor which inhibits the biological activity of human VEGF. Several studies have investigated the effectiveness of bevacizumab therapy according to different cancer types but these days there is an intense debate on its utility. We have investigated different methods to find the best tumor volume estimation since it creates the possibility for precise and effective drug administration with a much lower dose than in the protocol. Materials and Methods We have examined C38 mouse colon adenocarcinoma and HT-29 human colorectal adenocarcinoma. In both cases, three groups were compared in the experiments. The first group did not receive therapy, the second group received one 200 μg bevacizumab dose for a treatment period (protocol-based therapy), and the third group received 1.1 μg bevacizumab every day (quasi-continuous therapy). Tumor volume measurement was performed by digital caliper and small animal MRI. The mathematical relationship between MRI-measured tumor volume and mass was investigated to estimate accurate tumor volume using caliper-measured data. A two-dimensional mathematical model was applied for tumor volume evaluation, and tumor- and therapy-specific constants were calculated for the three different groups. The effectiveness of bevacizumab administration was examined by statistical analysis. Results In the case of C38 adenocarcinoma, protocol-based treatment did not result in significantly smaller tumor volume compared to the no treatment group; however, there was a significant difference between untreated mice and mice who received quasi-continuous therapy (p = 0.002). In the case of HT-29 adenocarcinoma, the daily treatment with one-twelfth total dose resulted in significantly smaller tumors than the protocol-based treatment (p = 0.038). When the tumor has a symmetrical, solid closed shape (typically without treatment), volume can be evaluated accurately from caliper-measured data with the applied two-dimensional mathematical model. Conclusion Our results provide a theoretical background for a much more effective bevacizumab treatment using optimized administration.


symposium on applied computational intelligence and informatics | 2012

Flat control of tumor growth with angiogenic inhibition

Dániel András Drexler; Johanna Sápi; Annamária Szeles; István Harmati; Adalbert Kovács; Levente Kovács

Cancer represents nowadays one of the most destructive and lethal illnesses of our civilization. In the last decades, clinical cancer research shifted towards molecular targeted therapies which have limited side effects in comparison to conventional chemotherapy and radiation therapy. Antiangiogenic therapy is proved to be one of the most promising cancer treatment methods. This paper concerns on the model-based control of tumor growth under angiogenic inhibition. The tumor growth model is nonlinear, augmented with a linear model representing the pharmacokinetics of the applied inhibitor in tumor treatment. The control strategy is based on feedback linearization and path tracking. The result are compared with other, basically linear control strategies which were previously published by our group.


international conference on intelligent engineering systems | 2011

Modeling and optimal control strategies of diseases with high public health impact

Levente Kovács; Péter Szalay; Tamás Ferenci; Dániel András Drexler; Johanna Sápi; István Harmati; Zoltán Benyó

This paper summarizes the results of research tasks in the field of physiological modeling and control of diseases with high public health impact carried out by the Biomedical Engineering Laboratory of the Budapest University of Technology and Economics. The developed and presented optimal algorithms and strategies focus on three diseases with high public health impact diabetes (the question of artificial pancreas), obesity (predicting obesity-related risks) and cancer (antiangiogenic chemotherapy). The studies are done together with different Hungarian hospitals, from where measurement data were obtained.


IFAC Proceedings Volumes | 2012

Model-Based Angiogenic Inhibition of Tumor Growth Using Modern Robust Control Method

Annamária Szeles; Johanna Sápi; Dániel András Drexler; István Harmati; Zoltán Sápi; Levente Kovács

Abstract Cancer is one of the most destructive and lethal illnesses of the modern civilization. In the last decades, clinical cancer research shifted towards molecular targeted therapies which have limited side effects in comparison to conventional chemotherapy and radiation therapy. Anti-angiogenic therapy is one of the most promising cancer treatment methods. The dynamical model for tumor growth under angiogenic stimulator/inhibitor control was posed by Hahnfeldt et al. (1999), and it was investigated and partly modified many times. In this paper, a modified version of the originally published model is used in order to describe a continuous infusion therapy. To generalize individualized therapies a robust control method is proposed using ℋ ∞ methodology. Uncertainty weighting functions are determined based on the real pathophysiological case and simulations are performed on different tumor volumes to demonstrate the robustness of the proposed method.


symposium on applied computational intelligence and informatics | 2013

Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma

Johanna Sápi; Dániel András Drexler; István Harmati; Annamária Szeles; Bernadett Kiss; Zoltán Sápi; Levente Kovács

Cancer fighting treatments are expanding, and a promising type, targeted molecular therapies have a new approach. The aim of these therapies is not to eliminate the whole tumor, but to control the tumor into a given state and keep it there. Explicit knowledge of tumor growth dynamics and the effects of targeted molecular therapies is crucial in tumor treatment development. We show the results of mouse experiments where tumor growth was investigated in case of C38 colon adenocarcinoma and B16 melanoma. Several curves were fitted and tumor growth dynamics was examined. Three attributes of tumor were measured: tumor volume, tumor mass and vascularization; and tumor growth dynamics was examined. Tumor volume was measured with digital caliper, vascularization was investigated with CD31 antibody immunohistochemistry staining on frozen sections. The relationship between these tumor attributes were examined with linear regression analysis. The dynamics of tumor growth was identified as a second order linear system.


conference on decision and control | 2013

Model-based angiogenic inhibition of tumor growth using feedback linearization

Annamária Szeles; Dániel András Drexler; Johanna Sápi; István Harmati; Levente Kovács

In the last decades beside conventional cancer treatment methods, molecular targeted therapies show prosperous results. These therapies have limited side-effects, and in comparison to chemotherapy, tumorous cells show lower tendency of becoming resistant to the applied antiangiogenic drugs. In clinical research, antiangiogenic therapy is one of the most promising cancer treatment methods. Using a simplified model of the reference dynamical model for tumor growth under angiogenic inhibition from the literature, exact linearization is performed in the paper to handle the nonlinear behavior of the model. Two different control methods are applied on the linearized model: flat control and switching control. Simulations are performed on the nonlinear model to show the characteristics of the therapies carried out using the presented control methods.


international symposium on intelligent systems and informatics | 2013

Imaging method for model-based control of tumor diseases

Bernadett Kiss; Johanna Sápi; Levente Kovács

Modern approaches of cancer therapies have specific effect on the typical mechanisms of uncontrollably growing and multiplying tumor cells. These targeted therapies can be more efficient than commonly applied methods in clinical practice. Antiangiogenic therapy prevents tumors from forming new blood vessels to ensure sufficient oxygen and nutrients. Without appropriate vascularization, the development of the tumor is inhibited, thus metastasis formation is blocked. In this paper we briefly review the importance of antiangiogenic therapy. To improve mathematical models of tumor growth under angiogenic inhibitors, the process of tumor development must be analyzed. We have chosen Magnetic Resonance Imaging (MRI) to follow up the dynamics of tumor growth and monitor the effect of angiogenic inhibitors. T1-weighted images have been acquired using gradient-echo, spin echo and fast spin echo sequences to examine subcutaneous mouse tumors. We have found that fast spin echo results the best solution: short data acquisition time and good contrast without contrast agent.

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Dániel András Drexler

Budapest University of Technology and Economics

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István Harmati

Budapest University of Technology and Economics

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Annamária Szeles

Budapest University of Technology and Economics

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Péter Szalay

Budapest University of Technology and Economics

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Bernadett Kiss

Budapest University of Technology and Economics

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