Search results for: tumor antigens

Authors: Miceska Simona, Škof Erik, Frković Grazio Snježana, Jeričević Anja, Smrkolj Špela, Cvjetićanin Branko, Novaković Srdjan, Grčar Kuzmanov Biljana, Kloboves-Prevodnik Veronika

Abstract:

Objectives: High-grade serous ovarian cancer (HGSOC) is characterized by the dissemination of the tumor cells (TC) in the peritoneal cavity forming malignant ascites at the time of diagnosis or recurrence. Still, cytology itself has been underutilized as a modality for the diagnosis of HGSOC from ascites, and histological examination from the tumor tissue is yet the only validated method used. The objective of this study was to evaluate the reliability of cytology in the diagnosis of HGSOC in relation to the histopathological examination. Methods: The study included 42 patients with histologically confirmed HGSOC, accompanied by malignant ascites. To confirm the malignancy of the TC in the ascites and to define their immunophenotype, immunohistochemical reaction (IHC) of the following antigens: Calretinin, MOC, WT1, PAX8, p53, p16 & Ki-67 was evaluated on ascites cytospins and tissue blocks. For complete cytological determination of HGSOC, BRCA 1/2 gene mutation was determined from ascites, tissue block, and blood. BRCA1/2 mutation from blood was performed to define the type of mutation, somatic vs germline. Results: Among 42 patients, the immunophenotype of HGSOC from ascites was confirmed in 36 cases (86%). For more profound analysis, the patients were divided in 3 groups regarding the number of TC present in the ascites: patients with less than 10% TC, 10% TC, and more than 10% TC. From all included patients, in the group with less than 10% TC, there were 10 cases, and only 5 of them(50%) showed HGSOC phenotype; 12 cases had equally 10% of TC, and 11 cases (92%) showed HGSOC phenotype; 20 cases had more than 10% TC and all of them (100%) confirmed the HGSOC immunophenotype from ascites. Only 33 patients were eligible for further BRCA1/2 analysis. Eleven BRCA1/2 mutations were detected from thetissue block: 6 germline and 5 somatic. In 2 cases with less than 10% TC, BRCA1/2 mutation was not detected; 4 cases had 10% TC, and 2 of them (50%) confirmed the mutation; 4 cases had more than 10% TC, and all showed 100% reliability with the tumor tissue. Conclusions: Cytology is a highly reliable method for determining the immunophenotype of HGSOC and BRCA1/2 mutation if more than 10% of tumor cells are present in the ascites. This may present an additional non-invasive clinical approach for fast and effective diagnose in the future, especially in inoperable conditions or relapses.

Keywords: cytology, ascites, high-grade serous ovarian cancer, immunophenotype, BRCA1/2

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Authors: Iulianna Taritsa, Kuldeep Neote, Eric Fossel

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Lysosome-induced immunogenic cell death (LIICD) is a powerful mechanism of targeting cancer cells that kills circulating malignant cells and primes the host’s immune cells against future remission. Current immunotherapies for cancer are limited in preventing recurrence – a gap that can be bridged by training the immune system to recognize cancer neoantigens. Lysosomal leakage can be induced therapeutically to traffic antigens from dying cells to dendritic cells, which can later present those tumorigenic antigens to T cells. Previous research has shown that oxidative agents administered in the tumor microenvironment can initiate LIICD. We generated a fusion protein between an oxidative agent known as xanthine oxidase (XO) and a mini-antibody specific for EGFR/HER2-sensitive breast tumor cells. The anti-EGFR single domain antibody fragment is uniquely sourced from llama, which is functional without the presence of a light chain. These llama micro-antibodies have been shown to be better able to penetrate tissues and have improved physicochemical stability as compared to traditional monoclonal antibodies. We demonstrate that the fusion protein created is stable and can induce early markers of immunogenic cell death in an in vitro human breast cancer cell line (SkBr3). Specifically, we measured overall cell death, as well as surface-expressed calreticulin, extracellular ATP release, and HMGB1 production. These markers are consensus indicators of ICD. Flow cytometry, luminescence assays, and ELISA were used respectively to quantify biomarker levels between treated versus untreated cells. We also included a positive control group of SkBr3 cells dosed with doxorubicin (a known inducer of LIICD) and a negative control dosed with cisplatin (a known inducer of cell death, but not of the immunogenic variety). We looked at each marker at various time points after cancer cells were treated with the XO/antibody fusion protein, doxorubicin, and cisplatin. Upregulated biomarkers after treatment with the fusion protein indicate an immunogenic response. We thus show the potential for this fusion protein to induce an anticancer effect paired with an adaptive immune response against EGFR/HER2+ cells. Our research in human cell lines here provides evidence for the success of the same therapeutic method for patients and serves as the gateway to developing a new treatment approach against breast cancer.

Keywords: apoptosis, breast cancer, immunogenic cell death, lysosome

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Authors: Madhu Gupta, Vikas Sharma, Suresh P. Vyas

Abstract:

CD13 receptors are abundantly overexpressed in tumor cells as well as in neovasculature. The CD13 receptors were selected as a targeted site and polymeric nanoparticles (NPs) as a targeted delivery system. By combining these, a cyclic NGR (cNGR) peptide ligand was coupled on the terminal end of polyethylene glycol-b-poly(lactic-co-glycolic acid) (PEG-b-PLGA) and prepared the dual targeted-NPs (cNGR-PEG-PTX-NPs) to enhance the intracellular delivery of anticancer drug to tumor cells and tumor endothelial cells via ligand-receptor interaction. In-vitro cytotoxicity studies confirmed that the presence of cNGR enhanced the cytotoxic efficiency by 2.8 folds in Human Umbilical Vein Endothelial (HUVEC) cells, while cytotoxicity was improved by 2.6 folds in human fibrosarcoma (HT-1080) cells as compared to non-specific stealth NPs. Compared with other tested NPs, cNGR-PEG-PTX-NPs revealed more cytotoxicity by inducing more apoptosis and higher intracellular uptake. The tumor volume inhibition rate was 59.7% in case of cNGR-PEG-PTX-NPs that was comparatively more with other formulations, indicating that cNGR-PEG-PTX-NPs could more effectively inhibit tumor growth. As a consequence, the cNGR-PEG-PTX-NPs play a key role in enhancing tumor therapeutic efficiency for treatment of CD13 receptor specific solid tumor.

Keywords: cyclic NGR, CD13 receptor, targeted polymeric NPs, solid tumor, intracellular delivery

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Authors: Nadine Wiesmann, Melanie Viel, Christoph Buhr, Rachel Tanner, Wolfgang Tremel, Juergen Brieger

Abstract:

Recidivation of tumors and the development of resistances against the classical anti-tumor approaches represent a major challenge we face when treating cancer. In order to master this challenge, we are in desperate need of new treatment options beyond the beaten tracks. Zinc oxide nanoparticles (ZnO NPs) represent such an innovative approach. Zinc oxide is characterized by a high level of biocompatibility, concurrently ZnO NPs are able to exert anti-tumor effects. By concentration of the nanoparticles at the tumor site, tumor cells can specifically be exposed to the nanoparticles while low zinc concentrations at off-target sites are tolerated well and can be excreted easily. We evaluated the toxicity of ZnO NPs in vitro with the help of immortalized tumor cell lines and primary cells stemming from healthy tissue. Additionally, the Chorioallantoic Membrane Assay (CAM Assay) was employed to gain insights into the in vivo behavior of the nanoparticles. We could show that ZnO NPs interact with tumor cells as nanoparticulate matter. Furthermore, the extensive release of zinc ions from the nanoparticles nearby and within the tumor cells results in overload with zinc. Beyond that, ZnO NPs were found to further the generation of reactive oxygen species (ROS). We were able to show that tumor cells were more prone to the toxic effects of ZnO NPs at intermediate concentrations compared to fibroblasts. With the help of ZnO NPs covered by a silica shell in which FITC dye was incorporated, we were able to track ZnO NPs within tumor cells as well as within a whole organism in the CAM assay after injection into the bloodstream. Depending on the applied concentrations, selective tumor cell killing seems feasible. Furthermore, the combinational treatment of tumor cells with radiotherapy and ZnO NPs shows promising results. Still, further investigations are needed to gain a better understanding of the interaction between ZnO NPs and the human body to be able to pave the way for their application as an innovative anti-tumor agent in the clinics.

Keywords: metal oxide nanoparticles, nanomedicine, overcome resistances against classical treatment options, zinc oxide nanoparticles

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Authors: Sarah K. Hagi, Majdi Alnowaimi

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In the last decade, there were immense advancements in the medical imaging modalities. These advancements can scan a whole volume of the lung organ in high resolution images within a short time. According to this performance, the physicians can clearly identify the complicated anatomical and pathological structures of lung. Therefore, these advancements give large opportunities for more advance of all types of lung cancer treatment available and will increase the survival rate. However, lung cancer is still one of the major causes of death with around 19% of all the cancer patients. Several factors may affect survival rate. One of the serious effects is the breathing process, which can affect the accuracy of diagnosis and lung tumor treatment plan. We have therefore developed a semi automated algorithm to localize the 3D lung tumor positions across all respiratory data during respiratory motion. The algorithm can be divided into two stages. First, a lung tumor segmentation for the first phase of the 4D computed tomography (CT). Lung tumor segmentation is performed using an active contours method. Then, localize the tumor 3D position across all next phases using a 12 degrees of freedom of an affine transformation. Two data set where used in this study, a compute simulate for 4D CT using extended cardiac-torso (XCAT) phantom and 4D CT clinical data sets. The result and error calculation is presented as root mean square error (RMSE). The average error in data sets is 0.94 mm ± 0.36. Finally, evaluation and quantitative comparison of the results with a state-of-the-art registration algorithm was introduced. The results obtained from the proposed localization algorithm show a promising result to localize alung tumor in 4D CT data.

Keywords: automated algorithm , computed tomography, lung tumor, tumor localization

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Authors: Bo-Huei Huang, Chih-Hsun Yang, Meng-Tsan Tsai

Abstract:

Optical coherence tomography (OCT) enables to provide advantages of noninvasive imaging, high resolution, and high imaging speed. In this study, we integrated OCT and a CW laser for tumor diagnosis and treatment. The axial and transverse resolutions of the developed OCT system are 3 μm and 1 μm, respectively. The frame rate of OCT system is 30 frames/s. In this study, the tumor cells were implanted into the mice skin and scanned by OCT to observe the morphological and angiographic changes. With OCT imaging, 3D microstructures and skin angiography of mice skin can be simultaneously acquired, which can be utilized for identification of the tumor distribution. Then, the CW laser beam can be accurately controlled to expose on the center of the tumor, according to the OCT results. Moreover, OCT was used to monitor the induced photothermolysis and to evaluate the treatment outcome. The results showed that OCT-guided laser therapy could efficiently improve the treatment outcome and the extra damage induced by CW can be greatly reduced. Such OCT-guided laser therapy system could be a potential tool for dermatological applications.

Keywords: optical coherence tomography, laser therapy, skin tumor, position guide

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

Abstract:

Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Sandabad Sara, Sayd Tahri Yassine, Hammouch Ahmed

Abstract:

The development of science has allowed computer scientists to touch the medicine and bring aid to radiologists as we are presenting it in our article. Our work focuses on the detection and localization of tumors areas in the human brain; this will be a completely automatic without any human intervention. In front of the huge volume of MRI to be treated per day, the radiologist can spend hours and hours providing a tremendous effort. This burden has become less heavy with the automation of this step. In this article we present an automatic and effective tumor detection, this work consists of two steps: the first is the image filtering using the filter Nl-means, then applying the expectation maximization algorithm (EM) for retrieving the tumor mask from the brain MRI and extracting the tumor area using the mask obtained from the second step. To prove the effectiveness of this method multiple evaluation criteria will be used, so that we can compare our method to frequently extraction methods used in the literature.

Keywords: MRI, Em algorithm, brain, tumor, Nl-means

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

Abstract:

The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: H. Feza Carlak, N. G. Gencer

Abstract:

To increase the temperature contrast in thermal images, the characteristics of the electrical conductivity and thermal imaging modalities can be combined. In this experimental study, it is objected to observe whether the temperature contrast created by the tumor tissue can be improved just due to the current application within medical safety limits. Various thermal breast phantoms are developed to simulate the female breast tissue. In vitro experiments are implemented using a thermal infrared camera in a controlled manner. Since experiments are implemented in vitro, there is no metabolic heat generation and blood perfusion. Only the effects and results of the electrical stimulation are investigated. Experimental study is implemented with two-dimensional models. Temperature contrasts due to the tumor tissues are obtained. Cancerous tissue is determined using the difference and ratio of healthy and tumor images. 1 cm diameter single tumor tissue causes almost 40 °mC temperature contrast on the thermal-breast phantom. Electrode artifacts are reduced by taking the difference and ratio of background (healthy) and tumor images. Ratio of healthy and tumor images show that temperature contrast is increased by the current application.

Keywords: medical diagnostic imaging, breast phantom, active thermography, breast cancer detection

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Authors: Ella Tyuryumina, Alexey Neznanov

Abstract:

This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

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Authors: Javad Khoshnegah, Hossein Nourani, Ali Mirshahi

Abstract:

A 12-year-old female Terrier presented with lethargy, decreased appetite, melena, polyuria and polydipsia. On physical examination skin lesions including crusting, erythema and pupolopustular lesions, were observed mainly on the abdomen. Based on blood examinations, ultrasonography, necropsy and histopathological findings, the condition was diagnosed as superficial necrolytic dermatitis. Gross necropsy revealed hepatomegaly (severe vacuolar change of the hepatocytes) and a 5×5 mass adjusent to mesenteric lymph nodes which is finally diagnosed as tumor. Immunohistochemical analysis of the neoplastic cells revealed that the tumor was a glucagonoma.

Keywords: dog, glucagonoma, immunohistochemistry, tumor

Procedia PDF Downloads 235

Authors: Mostafa Sefidgar, Sohrab Zendehboudi, Hossein Bazmara, Madjid Soltani

Abstract:

Based on findings from clinical applications, most drug treatments fail to eliminate malignant tumors completely even though drug delivery through systemic administration may inhibit their growth. Therefore, better understanding of tumor formation is crucial in developing more effective therapeutics. For this purpose, nowadays, solid tumor modeling and simulation results are used to predict how therapeutic drugs are transported to tumor cells by blood flow through capillaries and tissues. A solid tumor is investigated as a porous media for fluid flow simulation. Most of the studies use Darcy model for porous media. In Darcy model, the fluid friction is neglected and a few simplified assumptions are implemented. In this study, the effect of these assumptions is studied by considering Brinkman model. A multi scale mathematical method which calculates fluid flow to a solid tumor is used in this study to investigate how neglecting fluid friction affects the solid tumor simulation. In this work, the mathematical model in our previous studies is developed by considering two model of momentum equation for porous media: Darcy and Brinkman. The mathematical method involves processes such as fluid flow through solid tumor as porous media, extravasation of blood flow from vessels, blood flow through vessels and solute diffusion, convective transport in extracellular matrix. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network. Finally, the two models of porous media are used for modeling fluid flow in normal and tumor tissues in three different shapes of tumors. Simulations of interstitial fluid transport in a solid tumor demonstrate that the simplifications used in Darcy model affect the interstitial velocity and Brinkman model predicts a lower value for interstitial velocity than the values that Darcy model does.

Keywords: solid tumor, porous media, Darcy model, Brinkman model, drug delivery

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Authors: E. Solfaroli Camillocci, C. Mancini-Terracciano, V. Bocci, A. Carollo, M. Colandrea, F. Collamati, M. Cremonesi, M. E. Ferrari, P. Ferroli, F. Ghielmetti, C. M. Grana, M. Marafini, S. Morganti, M. Patane, G. Pedroli, B. Pollo, L. Recchia, A. Russomando, M. Schiariti, M. Toppi, G. Traini, R. Faccini

Abstract:

A Radio-Guided Surgery technique exploiting β− emitting radio-tracers has been suggested to overcome the impact of the large penetration of γ radiation. The detection of electrons in low radiation background provides a clearer delineation of the margins of lesioned tissues. As a start, the clinical cases were selected between the tumors known to express receptors to a β− emitting radio-tracer: 90Y-labelled DOTATOC. The results of tests on ex-vivo specimens of meningioma brain tumor and abdominal neuroendocrine tumors are presented. Voluntary patients were enrolled according to the standard uptake value (SUV > 2 g/ml) and the expected tumor-to-non-tumor ratios (TNR∼10) estimated from PET images after administration of 68Ga-DOTATOC. All these tests validated this technique yielding a significant signal on the bulk tumor and a negligible background from the nearby healthy tissue. Even injecting as low as 1.4 MBq/kg of radiotracer, tumor remnants of 0.1 ml would be detectable. The negligible medical staff exposure was confirmed and among the biological wastes only urine had a significant activity.

Keywords: ex-vivo test, meningioma, neuroendocrine tumor, radio-guided surgery

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Authors: Dimitrios Binas, Marianna Konidari, Charis Bourgioti, Lia Angela Moulopoulou, Theodore Economopoulos, George Matsopoulos

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High grade ovarian epithelial cancer (OEC) is fatal gynecological cancer and the poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study proposes a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: image segmentation, ovarian epithelial cancer, quantitative characteristics, image registration, tumor visualization

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Authors: Ibtihal D. Mustafa, Mawia A. Hassan

Abstract:

Tumor segmentation from MRI image is important part of medical images experts. This is particularly a challenging task because of the high assorting appearance of tumor tissue among different patients. MRI images are advance of medical imaging because it is give richer information about human soft tissue. There are different segmentation techniques to detect MRI brain tumor. In this paper, different procedure segmentation methods are used to segment brain tumors and compare the result of segmentations by using correlation and structural similarity index (SSIM) to analysis and see the best technique that could be applied to MRI image.

Keywords: MRI, segmentation, correlation, structural similarity

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Authors: Ella Tyuryumina, Alexey Neznanov

Abstract:

Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: Ella Tyuryumina, Alexey Neznanov

Abstract:

This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

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Authors: Wan-Ting Kuo, Yi-Wen Liu, Hsiao-Sheng Liu

Abstract:

Annual incidence of bladder cancer increases in the world and occurs frequently in the male. Most common type is transitional cell carcinoma (TCC) which is treated by transurethral resection followed by intravesical administration of agents. In clinical treatment of bladder cancer, chemotherapeutic drugs-induced apoptosis is always used in patients. However, cancers usually develop resistance to chemotherapeutic drugs and often lead to aggressive tumors with worse clinical outcomes. Approximate 70% TCC recurs and 30% recurrent tumors progress to high-grade invasive tumors, indicating that new therapeutic agents are urgently needed to improve the successful rate of overall treatment. Nonapoptotic program cell death may assist to overcome worse clinical outcomes. Autophagy which is one of the nonapoptotic pathways provides another option for bladder cancer patients. Autophagy is reported as a potent anticancer therapy in some cancers. First of all, we established a mouse orthotopic bladder tumor formation model in order to create a similar tumor microenvironment. IVIS system and micro-ultrasound were utilized to noninvasively monitor tumor formation. In addition, we carried out intravesical treatment in our animal model to be consistent with human clinical treatment. In our study, we carried out intravesical instillation of the autophagy inducer in mouse orthotopic bladder tumor to observe tumor formation by noninvasive IVIS system and micro-ultrasound. Our results showed that bladder tumor formation is suppressed by the autophagy inducer, and there are no significant side effects in the physiology of mice. Furthermore, the autophagy inducer upregulated autophagy in bladder tissues of the treated mice was confirmed by Western blot, immunohistochemistry, and immunofluorescence. In conclusion, we reveal that a novel autophagy inducer with low side effects suppresses bladder tumor formation in our mouse orthotopic bladder tumor model, and it provides another therapeutic approach in bladder cancer patients.

Keywords: bladder cancer, transitional cell carcinoma, orthotopic bladder tumor formation model, autophagy

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Authors: Feixiong Chen, Naoufel Haddour, Marie Frenea-Robin, Yves MéRieux, Yann Chevolot, Virginie Monnier

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Neonatal thrombopenia occurs when the mother generates antibodies against her baby’s platelet antigens. It is particularly critical for newborns because it can cause coagulation troubles leading to intracranial hemorrhage. In this case, diagnosis must be done quickly to make platelets transfusion immediately after birth. Before transfusion, platelet antigens must be tested carefully to avoid rejection. The majority of thrombopenia (95 %) are caused by antibodies directed against Human Platelet Antigen 1a (HPA-1a) or 5b (HPA-5b). The common method for antigen platelets detection is polymerase chain reaction allowing for identification of gene sequence. However, it is expensive, time-consuming and requires significant blood volume which is not suitable for newborns. We propose to develop a point-of-care device based on double functionalized magnetic colloids with 1) antibodies specific to antigen platelets and 2) highly sensitive electroactive molecules in order to be detected by an electrochemical microsensor. These magnetic colloids will be used first to isolate platelets from other blood components, then to capture specifically platelets bearing HPA-1a and HPA-5b antigens and finally to attract them close to sensor working electrode for improved electrochemical signal. The expected advantages are an assay time lower than 20 min starting from blood volume smaller than 100 µL. Our functionalization procedure based on amine dendrimers and NHS-ester modification of initial carboxyl colloids will be presented. Functionalization efficiency was evaluated by colorimetric titration of surface chemical groups, zeta potential measurements, infrared spectroscopy, fluorescence scanning and cyclic voltammetry. Our results showed that electroactive molecules and antibodies can be immobilized successfully onto magnetic colloids. Application of a magnetic field onto working electrode increased the detected electrochemical signal. Magnetic colloids were able to capture specific purified antigens extracted from platelets.

Keywords: Magnetic Nanoparticles , Electroactive Molecules, Antibody, Platelet

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Authors: Naim Izet Kajtazi

Abstract:

Context: Although rare, glomus tumor (i.e., nonchromaffin chemodectomas and paragan¬gliomas) is the most common middle ear tumor, with female predominance. Pre-operative embolization is often required to devascularize the hypervascular tumor for better surgical outcomes. Process: A 35-year-old female presented with episodes of frequent dizziness, ear fullness, and right ear tinnitus for 12 months. Head imaging revealed a right glomus tympanicum tumor. She underwent pre-operative endovascular embolization of the glomus tympanicum tumor with surgical, cyanoacrylate-based glue. Immediately after the procedure, she developed drowsiness and severe pain in the right temporal region. Further investigations revealed a right cerebellar stroke in the posterior inferior cerebellar artery territory. She was treated with intravenous heparin, followed by one year of oral anticoagulation. With rehabilitation, she significantly recovered from her post embolization stroke. However, the tumor was resected at another institution. Ten years later, follow-up imaging indicated a gradual increase in the size of the glomus jugulare tumor, compressing the nearby critical vascular structures. She subsequently received radiation therapy to treat the residual tumor. Outcome: Currently, she has no neurological deficit, but her mild dizziness, right ear tinnitus, and hearing impairment persist. Relevance: This case highlights the complex nature of these tumors, which often bring challenges to the patients as well as treatment teams. The multi-disciplinary team approach is necessary to tailor the management plan for individual tumors. Although embolization is a safe procedure, careful attention and thoughtful anatomic knowledge regarding dangerous anastomosis are essential to avoid devastating complications. Complications occur due to encountered vessel anomalies and new anastomoses formed during the gluing and changes in hemodynamics.

Keywords: stroke, embolization, MRI brain, cerebral angiogram

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Authors: Sahar Essa, Hussain A. Safar, Raj Raghupathy

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Human cytomegalovirus (CMV) continues to be a source of severe complications in immunologically immature and immunocompromised hosts. Effective CMV vaccines that help diminish CMV disease in transplant patients and avoid congenital infection are of great importance. Though the exact roles of defense mechanisms are unidentified, viral-specific antibodies and cytokine responses are known to be involved in controlling CMV infections. CMV envelope glycoprotein B (UL55/gB), matrix proteins (UL83/pp65, UL99/pp28, UL32/pp150), and assembly protein UL80a/pp38 are known to be targets of antiviral immune responses. We immunized mice intraperitoneally with these five CMV-related proteins (commercial) for their ability to induce specific antibody responses (in-house immunoassay) and cytokine production (commercial assay) in a mouse model. We observed a significant CMV-antigen-specific antibody response to pp38 and pp65 (E/C ˃2.0, p˂0.001). Mice immunized with pp38 had significantly higher concentrations of GM-CSF, IFN-α, IL-2 IL-4, IL-5, and IL-17A (p˂0.05). Mice immunized with pp65 showed significantly higher concentrations of GM-CSF, IFN-γ, IL-2 IL-4, IL-10, IL-12, IL-17A, and TNF-α. Th1 to Th2 cytokines ratios revealed a Th1 cytokine bias in mice immunized with pp38, pp65, pp150, and gB. We suggest that stimulation with multiple CMV-related proteins, which include pp38, pp65, and gB antigens, will allow both humoral and cellular immune responses to be efficiently activated, thus serving as appropriate CMV antigens for future vaccines.

Keywords: cytomegalovirus, UL99/pp28, UL80a/pp38, UL83/pp65, UL32/pp150, UL55/gB, CMV-antigen-specific antibody, CMV antigen-specific cytokine responses

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Salvador Garcia Bernal, Chi Zheng, Keqi Zhang, Lei Mao

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Circulating Tumor Cells (CTC) is used to detect tumoral cell metastases using blood samples of patients with cancer (lung, breast, etc.). Using an immunofluorescent method a three channel image (Red, Green, and Blue) are obtained. These set of images usually overpass the 11 x 30 M pixels in size. An aided tool is designed for imaging cell analysis to segmented and identify the tumorous cell based on the three markers signals. Our Method, it is cell-based (area and cell shape) considering each channel information and extracting and making decisions if it is a valid CTC. The system also gives information about number and size of tumor cells found in the sample. We present results in real-life samples achieving acceptable performance in identifying CTCs in short time.

Keywords: Circulating Tumor Cells (CTC), cell analysis, immunofluorescent, medical image analysis

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Authors: Maria Valeria De Bonis, Gianpaolo Ruocco

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Nowadays, computational modeling is paving new design and verification ways in a number of industrial sectors. The technology is ripe to challenge some case in the Bioengineering and Medicine frameworks: for example, looking at the strategical and ethical importance of oncology research, efforts should be made to yield new and powerful resources to tumor knowledge and understanding. With these driving motivations, we approach this gigantic problem by using some standard engineering tools such as the mathematics behind the biomass transfer. We present here some bacterial colonization studies in complex structures. As strong analogies hold with some tumor proliferation, we extend our study to a benchmark case of solid tumor. By means of a commercial software, we model biomass and energy evolution in arbitrary media. The approach will be useful to cast virtualization cases of cancer growth in human organs, while augmented reality tools will be used to yield for a realistic aid to informed decision in treatment and surgery.

Keywords: bacteria, simulation, tumor, precision medicine

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Authors: Roberto Coppo, Francesca Orso, Daniela Dettori, Elena Quaglino, Lei Nie, Mehran M. Sadeghi, Daniela Taverna

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Malignant melanoma is currently the fifth most common cancer in the white population and it is fatal in its metastatic stage. Several research studies in recent years have provided evidence that cancer initiation and progression are driven by genetic alterations of the tumor and paracrine interactions between tumor and microenvironment. Scattered data show that the Endothelial and Smooth muscle cell-Derived Neuropilin-like molecule (ESDN) controls cell proliferation and movement of stroma and tumor cells. To investigate the role of ESDN in the tumor microenvironment during melanoma progression, murine melanoma cells (B16 or B16-F10) were injected in ESDN knockout mice in order to evaluate how the absence of ESDN in stromal cells could influence melanoma progression. While no effect was found on primary tumor growth, increased cell extravasation and lung metastasis formation was observed in ESDN knockout mice compared to wild type controls. In order to understand how cancer cells cross the endothelial barrier during metastatic dissemination in an ESDN-null microenvironment, structure, and permeability of lung blood vessels were analyzed. Interestingly, ESDN knockout mice showed structurally altered and more permeable vessels compared to wild type animals. Since cell surface molecules mediate the process of tumor cell extravasation, the expression of a panel of extravasation-related ligands and receptors was analyzed. Importantly, modulations of N-cadherin, E-selectin, ICAM-1 and VAP-1 were observed in ESDN knockout endothelial cells, suggesting the presence of a favorable tumor microenvironment which facilitates melanoma cell extravasation and metastasis formation in the absence of ESDN. Furthermore, a potential contribution of immune cells in tumor dissemination was investigated. An increased recruitment of macrophages in the lungs of ESDN knockout mice carrying subcutaneous B16-F10 tumors was found. In conclusion, our data suggest a functional role of ESDN in the tumor microenvironment during melanoma progression and the identification of the mechanisms that regulate tumor cell extravasation could lead to the development of new therapies to reduce metastasis formation.

Keywords: melanoma, tumor microenvironment, extravasation, cell surface molecules

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Authors: Mahmoodreza Tahamtan

Abstract:

Background: Malignant surface epithelial ovarian tumors (SEOT) account for approximately 90% of primary ovarian cancer. Wilms tumor gene (WT1) product was defined as a tumor suppressor gene, but today it is considered capable of performing oncogenic functions. There seems to be differences in WT1 expression patterns among SEOT subtypes. We evaluate the immunohistochemical expression of WT1 protein among different histologic subtypes of SEOT. Materials and Methods: Immunohistochemistry for WT1 was done on 35 serous cystadenocarcinomas, 9 borderline serous tumors, 3 mucinous cystadenocarcinomas, 10 borderline mucinous tumors, 7 endometrioid ovarian carcinomas, 3 clear cell carcinomas, 1 malignant Brenner tumor, 2 metastatic adenocarcinomas, and 6 endometrial adenocarcinomas. A tumor was considered negative if < 1% of tumor cells were stained.Positive reactions were graded as follows:1+,1%-24%; 2+,25%-49%; 3+,50%-74%; 4+,75%-100%. Results: Of the 35 cases of ovarian serous cystadenocarcinoma, 30(85.7%) were diffusely positive (3+,4+),4 showed reactivity of < 50% of the tumor cells (1+,2+), and one were negative. All 9 borderline serous tumors showed immunoreactivity with WT1. All the mucinous tumors(n:13), endometrioid carcinomas (n: 7), clear cell carcinomas (n: 3), metastatic adenocarcinomas (n: 2) and primary endometrial carcinomas (n:6) were negative. The single malignant Brenner tumor showed a positive reaction for WT1(4+) Conclusion: WT1 is a good marker to distinguish primary ovarian serous carcinomas from other surface epithelial tumors (especially endometrioid subtype) and metastatic carcinomas (especially endometrial serous carcinoma), other than malignant mesothelioma. We cannot rely to the degree of expression inorder to separate high grade borderline serous tumors from low grade ones.

Keywords: WT1, ovary, epithelial tumors, malignant

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Authors: Rasime Kalkan, Emine Ikbal Atli, Ali Arslantaş, Muhsin Özdemir, Sevilhan Artan

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Glioblastoma (WHO grade IV), is the malignant form of brain tumor, the genetic background of the GBM is highly variable. The tumor mass of a GBM is multilayered and every tumor layer shows distinct characteristics with a different cell population. The treatment planning of GBM should be focused on the tumor genetic characteristics. We screened primary glioblastoma multiforme (GBM) in a population-based study for MGMT and RARβ methylation and IDH1 mutation correlated them with clinical data and treatment. There was no correlation between MGMT-promoter methylation and overall survival. The overall survival time of the patients with methylated RARβ was statically (OS;p<0,05) significance between the patients who were treated with chemotherapy and radiotherapy. Here we showed the status of IDH1 gene associatied with younger age. We demonstrated that the together with MGMT gene the RARβ gene should be used as a potantial treatment decision marker for GBMs.

Keywords: RARβ, primary glioblastoma multiforme, methylation, MGMT

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Authors: Hatem A. El-Mezayen, Ahmed Abdelmajeed, Fatehya Metwally, Usama Elsaly, Salwa Atef

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Tumor metastasis involves the dissemination of malignant cells into the basement membrane and vascular system contributes to the circulating pool of these markers. In this context our aim has been focused on development of a non-invasive. Circulating tumor cells (CTCs) represent a unique liquid biopsy carrying comprehensive biological information of the primary tumor. Herein, we sought to develop a novel score based on the combination of the most significant CTCs biomarkers with and routine laboratory tests for accurate detection of metastatic breast cancer. Methods: Cytokeratin 18 (CK18), Cytokeratin 19 (CK19), and CA15.3 were assayed in metastatic breast cancer (MBC) patients (75), non-MBC patients (50) and healthy control (20). Results: Areas under receiving operating curve (AUCs) were calculated and used for construction on novel score. A novel score named MBC-CTCs = CA15.3 (U/L) × 0.08 + CK 18 % × 2.9 + CK19 × 3.1– 510. That function correctly classified 87% of metastatic breast cancer at cut-off value = 0.55. (i.e great than 0.55 indicates patients with metastatic breast cancer and less than 0.55 indicates patients with non-metastatic breast cancer). Conclusion: MBC-CTCs is a novel, non-invasive and simple can applied to discriminate patients with metastatic breast cancer.

Keywords: metastatic breast cancer, circulating tumor cells, cytokeratin, EpiCam

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Authors: Sudson Sirivaidyapong, Ratthanan Sathienbumrungkit, Nongnapas Ruangpet, Nattanun Uaprayoon, Chawisa Wejjakul

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Many factors initiate mammary gland tumor in female dogs such as age, breed, sex, estrous cycle, birth control and pseudopregnancy. Those factors are mostly associated with canine sex hormone. In this study, questionnaires and direct interviews were used to collect information from owners of female dogs that had been diagnosed as mammary tumors at our veterinary teaching hospital, during January 2015 to October 2016 to compare the prevalence of mammary tumor between nulliparous and multiparous female dogs. 200 dogs (from all 212 mammary tumor patients, some were excluded because of inadequate information) were included in the study, 72.5% were nulliparous and 27.5% were multiparous. The results revealed that breed, age, birth control age and birth control methods were not different in both groups; most dogs in both groups were various purebreds, geriatric age, and low incidence of hormonal contraception while 100% of multiparous dogs and 83.7% of nulliparous dogs had been neutered at over two years old. The significant differences between two groups were the frequency of pseudopregnancy and estrus which were much higher in nulliparous female dogs. It can be concluded from our study that nulliparous dogs may be more likely at higher risk of mammary tumor compared to multiparous dogs from various factors especially, the frequency of estrus and the occurrence of pseudopregnancy which related to more times of sex hormonal contact. This study was a preliminary data for further studies to determine the other risk factors of mammary gland tumors in dogs, and to our knowledge, it is the first report on a significantly higher prevalence of mammary tumor in nulliparous female dogs than that in multiparous dogs. This finding corresponds with the study of breast cancer in women but may be from different causes and factors due to the differences in estrous physiology.

Keywords: canine, female dogs, nulliparous, multiparous, mammary tumor, prevalence

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