Concurrent Tumor Segmentation and Registration with Uncertainty-based Sparse non-Uniform Graphs

PubMed Central

Parisot, Sarah; Wells, William; Chemouny, Stéphane; Duffau, Hugues; Paragios, Nikos

2014-01-01

In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model. PMID:24717540

Minimizing metastatic risk in radiotherapy fractionation schedules

NASA Astrophysics Data System (ADS)

Badri, Hamidreza; Ramakrishnan, Jagdish; Leder, Kevin

2015-11-01

Metastasis is the process by which cells from a primary tumor disperse and form new tumors at distant anatomical locations. The treatment and prevention of metastatic cancer remains an extremely challenging problem. This work introduces a novel biologically motivated objective function to the radiation optimization community that takes into account metastatic risk instead of the status of the primary tumor. In this work, we consider the problem of developing fractionated irradiation schedules that minimize production of metastatic cancer cells while keeping normal tissue damage below an acceptable level. A dynamic programming framework is utilized to determine the optimal fractionation scheme. We evaluated our approach on a breast cancer case using the heart and the lung as organs-at-risk (OAR). For small tumor α /β values, hypo-fractionated schedules were optimal, which is consistent with standard models. However, for relatively larger α /β values, we found the type of schedule depended on various parameters such as the time when metastatic risk was evaluated, the α /β values of the OARs, and the normal tissue sparing factors. Interestingly, in contrast to standard models, hypo-fractionated and semi-hypo-fractionated schedules (large initial doses with doses tapering off with time) were suggested even with large tumor α/β values. Numerical results indicate the potential for significant reduction in metastatic risk.

PERSPECTIVE: Physical aspects of cancer invasion

NASA Astrophysics Data System (ADS)

Guiot, Caterina; Pugno, Nicola; Delsanto, Pier Paolo; Deisboeck, Thomas S.

2007-12-01

Invasiveness, one of the hallmarks of tumor progression, represents the tumor's ability to expand into the host tissue by means of several complex biochemical and biomechanical processes. Since certain aspects of the problem present a striking resemblance with well-known physical mechanisms, such as the mechanical insertion of a solid inclusion in an elastic material specimen (G Eaves 1973 The invasive growth of malignant tumours as a purely mechanical process J. Pathol. 109 233; C Guiot, N Pugno and P P Delsanto 2006 Elastomechanical model of tumor invasion Appl. Phys. Lett. 89 233901) or a water drop impinging on a surface (C Guiot, P P Delsanto and T S Deisboeck 2007 Morphological instability and cancer invasion: a 'splashing water drop' analogy Theor. Biol. Med. Model 4 4), we propose here an analogy between these physical processes and a cancer system's invasive branching into the surrounding tissue. Accounting for its solid and viscous properties, we then arrive, as a unifying model, to an analogy with a granular solid. While our model has been explicitly formulated for multicellular tumor spheroids in vitro, it should also contribute to a better understanding of tumor invasion in vivo.

A partial differential equation model and its reduction to an ordinary differential equation model for prostate tumor growth under intermittent hormone therapy.

PubMed

Tao, Youshan; Guo, Qian; Aihara, Kazuyuki

2014-10-01

Hormonal therapy with androgen suppression is a common treatment for advanced prostate tumors. The emergence of androgen-independent cells, however, leads to a tumor relapse under a condition of long-term androgen deprivation. Clinical trials suggest that intermittent androgen suppression (IAS) with alternating on- and off-treatment periods can delay the relapse when compared with continuous androgen suppression (CAS). In this paper, we propose a mathematical model for prostate tumor growth under IAS therapy. The model elucidates initial hormone sensitivity, an eventual relapse of a tumor under CAS therapy, and a delay of a relapse under IAS therapy, which are due to the coexistence of androgen-dependent cells, androgen-independent cells resulting from reversible changes by adaptation, and androgen-independent cells resulting from irreversible changes by genetic mutations. The model is formulated as a free boundary problem of partial differential equations that describe the evolution of populations of the abovementioned three types of cells during on-treatment periods and off-treatment periods. Moreover, the model can be transformed into a piecewise linear ordinary differential equation model by introducing three new volume variables, and the study of the resulting model may help to devise optimal IAS schedules.

Tumor propagation model using generalized hidden Markov model

NASA Astrophysics Data System (ADS)

Park, Sun Young; Sargent, Dustin

2017-02-01

Tumor tracking and progression analysis using medical images is a crucial task for physicians to provide accurate and efficient treatment plans, and monitor treatment response. Tumor progression is tracked by manual measurement of tumor growth performed by radiologists. Several methods have been proposed to automate these measurements with segmentation, but many current algorithms are confounded by attached organs and vessels. To address this problem, we present a new generalized tumor propagation model considering time-series prior images and local anatomical features using a Hierarchical Hidden Markov model (HMM) for tumor tracking. First, we apply the multi-atlas segmentation technique to identify organs/sub-organs using pre-labeled atlases. Second, we apply a semi-automatic direct 3D segmentation method to label the initial boundary between the lesion and neighboring structures. Third, we detect vessels in the ROI surrounding the lesion. Finally, we apply the propagation model with the labeled organs and vessels to accurately segment and measure the target lesion. The algorithm has been designed in a general way to be applicable to various body parts and modalities. In this paper, we evaluate the proposed algorithm on lung and lung nodule segmentation and tracking. We report the algorithm's performance by comparing the longest diameter and nodule volumes using the FDA lung Phantom data and a clinical dataset.

Cell-ECM Interactions During Cancer Invasion

NASA Astrophysics Data System (ADS)

Jiang, Yi

The extracellular matrix (ECM), a fibrous material that forms a network in a tissue, significantly affects many aspects of cellular behavior, including cell movement and proliferation. Transgenic mouse tumor studies indicate that excess collagen, a major component of ECM, enhances tumor formation and invasiveness. Clinically, tumor associated collagen signatures are strong markers for breast cancer survival. However, the underlying mechanisms are unclear since the properties of ECM are complex, with diverse structural and mechanical properties depending on various biophysical parameters. We have developed a three-dimensional elastic fiber network model, and parameterized it with in vitro collagen mechanics. Using this model, we study ECM remodeling as a result of local deformation and cell migration through the ECM as a network percolation problem. We have also developed a three-dimensional, multiscale model of cell migration and interaction with ECM. Our model reproduces quantitative single cell migration experiments. This model is a first step toward a fully biomechanical cell-matrix interaction model and may shed light on tumor associated collagen signatures in breast cancer. This work was partially supported by NIH-U01CA143069.

TH-E-BRF-01: Exploiting Tumor Shrinkage in Split-Course Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Unkelbach, J; Craft, D; Hong, T

2014-06-15

Purpose: In split-course radiotherapy, a patient is treated in several stages separated by weeks or months. This regimen has been motivated by radiobiological considerations. However, using modern image-guidance, it also provides an approach to reduce normal tissue dose by exploiting tumor shrinkage. In this work, we consider the optimal design of split-course treatments, motivated by the clinical management of large liver tumors for which normal liver dose constraints prohibit the administration of an ablative radiation dose in a single treatment. Methods: We introduce a dynamic tumor model that incorporates three factors: radiation induced cell kill, tumor shrinkage, and tumor cellmore » repopulation. The design of splitcourse radiotherapy is formulated as a mathematical optimization problem in which the total dose to the liver is minimized, subject to delivering the prescribed dose to the tumor. Based on the model, we gain insight into the optimal administration of radiation over time, i.e. the optimal treatment gaps and dose levels. Results: We analyze treatments consisting of two stages in detail. The analysis confirms the intuition that the second stage should be delivered just before the tumor size reaches a minimum and repopulation overcompensates shrinking. Furthermore, it was found that, for a large range of model parameters, approximately one third of the dose should be delivered in the first stage. The projected benefit of split-course treatments in terms of liver sparing depends on model assumptions. However, the model predicts large liver dose reductions by more than a factor of two for plausible model parameters. Conclusion: The analysis of the tumor model suggests that substantial reduction in normal tissue dose can be achieved by exploiting tumor shrinkage via an optimal design of multi-stage treatments. This suggests taking a fresh look at split-course radiotherapy for selected disease sites where substantial tumor regression translates into reduced target volumes.« less

Hedgehog Pathway Inhibition Radiosensitizes Non-Small Cell Lung Cancers

PubMed Central

Zeng, Jing; Aziz, Khaled; Chettiar, Sivarajan T.; Aftab, Blake T.; Armour, Michael; Gajula, Rajendra; Gandhi, Nishant; Salih, Tarek; Herman, Joseph M.; Wong, John; Rudin, Charles M.; Tran, Phuoc T.; Hales, Russell K.

2012-01-01

Purpose Despite improvements in chemoradiation, local control remains a major clinical problem in locally advanced non-small cell lung cancer. The Hedgehog pathway has been implicated in tumor recurrence by promoting survival of tumorigenic precursors and through effects on tumor-associated stroma. Whether Hedgehog inhibition can affect radiation efficacy in vivo has not been reported. Methods and Materials We evaluated the effects of a targeted Hedgehog inhibitor (HhAntag) and radiation on clonogenic survival of human non-small cell lung cancer lines in vitro. Using an A549 cell line xenograft model, we examined tumor growth, proliferation, apoptosis, and gene expression changes after concomitant HhAntag and radiation. In a transgenic mouse model of KrasG12D-induced and Twist1-induced lung adenocarcinoma, we assessed tumor response to radiation and HhAntag by serial micro-computed tomography (CT) scanning. Results In 4 human lung cancer lines in vitro, HhAntag showed little or no effect on radio-sensitivity. By contrast, in both the human tumor xenograft and murine inducible transgenic models, HhAntag enhanced radiation efficacy and delayed tumor growth. By use of the human xenograft model to differentiate tumor and stromal effects, mouse stromal cells, but not human tumor cells, showed significant and consistent downregulation of Hedgehog pathway gene expression. This was associated with increased tumor cell apoptosis. Conclusions Targeted Hedgehog pathway inhibition can increase in vivo radiation efficacy in lung cancer preclinical models. This effect is associated with pathway suppression in tumor-associated stroma. These data support clinical testing of Hedgehog inhibitors as a component of multimodality therapy for locally advanced non-small cell lung cancer. PMID:23182391

Hedgehog pathway inhibition radiosensitizes non-small cell lung cancers.

PubMed

Zeng, Jing; Aziz, Khaled; Chettiar, Sivarajan T; Aftab, Blake T; Armour, Michael; Gajula, Rajendra; Gandhi, Nishant; Salih, Tarek; Herman, Joseph M; Wong, John; Rudin, Charles M; Tran, Phuoc T; Hales, Russell K

2013-05-01

Despite improvements in chemoradiation, local control remains a major clinical problem in locally advanced non-small cell lung cancer. The Hedgehog pathway has been implicated in tumor recurrence by promoting survival of tumorigenic precursors and through effects on tumor-associated stroma. Whether Hedgehog inhibition can affect radiation efficacy in vivo has not been reported. We evaluated the effects of a targeted Hedgehog inhibitor (HhAntag) and radiation on clonogenic survival of human non-small cell lung cancer lines in vitro. Using an A549 cell line xenograft model, we examined tumor growth, proliferation, apoptosis, and gene expression changes after concomitant HhAntag and radiation. In a transgenic mouse model of Kras(G12D)-induced and Twist1-induced lung adenocarcinoma, we assessed tumor response to radiation and HhAntag by serial micro-computed tomography (CT) scanning. In 4 human lung cancer lines in vitro, HhAntag showed little or no effect on radiosensitivity. By contrast, in both the human tumor xenograft and murine inducible transgenic models, HhAntag enhanced radiation efficacy and delayed tumor growth. By use of the human xenograft model to differentiate tumor and stromal effects, mouse stromal cells, but not human tumor cells, showed significant and consistent downregulation of Hedgehog pathway gene expression. This was associated with increased tumor cell apoptosis. Targeted Hedgehog pathway inhibition can increase in vivo radiation efficacy in lung cancer preclinical models. This effect is associated with pathway suppression in tumor-associated stroma. These data support clinical testing of Hedgehog inhibitors as a component of multimodality therapy for locally advanced non-small cell lung cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

Hedgehog Pathway Inhibition Radiosensitizes Non-Small Cell Lung Cancers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Jing; Aziz, Khaled; Chettiar, Sivarajan T.

2013-05-01

Purpose: Despite improvements in chemoradiation, local control remains a major clinical problem in locally advanced non-small cell lung cancer. The Hedgehog pathway has been implicated in tumor recurrence by promoting survival of tumorigenic precursors and through effects on tumor-associated stroma. Whether Hedgehog inhibition can affect radiation efficacy in vivo has not been reported. Methods and Materials: We evaluated the effects of a targeted Hedgehog inhibitor (HhAntag) and radiation on clonogenic survival of human non-small cell lung cancer lines in vitro. Using an A549 cell line xenograft model, we examined tumor growth, proliferation, apoptosis, and gene expression changes after concomitant HhAntagmore » and radiation. In a transgenic mouse model of Kras{sup G12D}-induced and Twist1-induced lung adenocarcinoma, we assessed tumor response to radiation and HhAntag by serial micro-computed tomography (CT) scanning. Results: In 4 human lung cancer lines in vitro, HhAntag showed little or no effect on radiosensitivity. By contrast, in both the human tumor xenograft and murine inducible transgenic models, HhAntag enhanced radiation efficacy and delayed tumor growth. By use of the human xenograft model to differentiate tumor and stromal effects, mouse stromal cells, but not human tumor cells, showed significant and consistent downregulation of Hedgehog pathway gene expression. This was associated with increased tumor cell apoptosis. Conclusions: Targeted Hedgehog pathway inhibition can increase in vivo radiation efficacy in lung cancer preclinical models. This effect is associated with pathway suppression in tumor-associated stroma. These data support clinical testing of Hedgehog inhibitors as a component of multimodality therapy for locally advanced non-small cell lung cancer.« less

Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs.

PubMed

Parisot, Sarah; Wells, William; Chemouny, Stéphane; Duffau, Hugues; Paragios, Nikos

2014-05-01

In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model. Copyright © 2014 Elsevier B.V. All rights reserved.

Novel rodent model of breast cancer survival with persistent anxiety-like behavior and inflammation.

PubMed

Pyter, Leah M; Suarez-Kelly, Lorena P; Carson, William E; Kaur, Jasskiran; Bellisario, Joshua; Bever, Savannah R

2017-07-14

Breast cancer survivors are an expanding population that is troubled by lasting mental health problems, including depression and anxiety. These issues reduce quality-of-life throughout survivorhood. Research indicates that tumor biology, cancer treatments, and stress contribute to these mood disturbances. Although the mechanisms underlying these various causes remain under investigation, neuroinflammation is a leading hypothesis. To date, rodent models of recurrence-free tumor survival for understanding mechanisms by which these behavioral issues persist after cancer are lacking. Here, we test the extent to which potential behavioral symptoms persist after mammary tumor removal in mice (i.e., establishment of a cancer survivor model), while also empirically testing the causal role of tumors in the development of neuroinflammatory-mediated affective-like behaviors. Complete surgical resection of a non-metastatic orthotopic, syngeneic mammary tumor reversed tumor-induced increases of circulating cytokines (IL-6, CXCL1, IL-10) and myeloid-derived cells and modulated neuroinflammatory gene expression (Cd11b, Cxcl1). Multiple anxiety-like behaviors and some central and peripheral immune markers persisted or progressed three weeks after tumor resection. Together, these data indicate that persistent behavioral changes into cancer survivorhood may be due, in part, to changes in immunity that remain even after successful tumor removal. This novel survivor paradigm represents an improvement in modeling prevalent cancer survivorship issues and studying the basic mechanisms by which cancer/cancer treatments influence the brain and behavior. Copyright © 2017 Elsevier B.V. All rights reserved.

3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained

PubMed Central

Zanoni, Michele; Piccinini, Filippo; Arienti, Chiara; Zamagni, Alice; Santi, Spartaco; Polico, Rolando; Bevilacqua, Alessandro; Tesei, Anna

2016-01-01

The potential of a spheroid tumor model composed of cells in different proliferative and metabolic states for the development of new anticancer strategies has been amply demonstrated. However, there is little or no information in the literature on the problems of reproducibility of data originating from experiments using 3D models. Our analyses, carried out using a novel open source software capable of performing an automatic image analysis of 3D tumor colonies, showed that a number of morphology parameters affect the response of large spheroids to treatment. In particular, we found that both spheroid volume and shape may be a source of variability. We also compared some commercially available viability assays specifically designed for 3D models. In conclusion, our data indicate the need for a pre-selection of tumor spheroids of homogeneous volume and shape to reduce data variability to a minimum before use in a cytotoxicity test. In addition, we identified and validated a cytotoxicity test capable of providing meaningful data on the damage induced in large tumor spheroids of up to diameter in 650 μm by different kinds of treatments. PMID:26752500

Fibroblasts Influence Survival and Therapeutic Response in a 3D Co-Culture Model

PubMed Central

Majety, Meher; Pradel, Leon P.; Gies, Manuela; Ries, Carola H.

2015-01-01

In recent years, evidence has indicated that the tumor microenvironment (TME) plays a significant role in tumor progression. Fibroblasts represent an abundant cell population in the TME and produce several growth factors and cytokines. Fibroblasts generate a suitable niche for tumor cell survival and metastasis under the influence of interactions between fibroblasts and tumor cells. Investigating these interactions requires suitable experimental systems to understand the cross-talk involved. Most in vitro experimental systems use 2D cell culture and trans-well assays to study these interactions even though these paradigms poorly represent the tumor, in which direct cell-cell contacts in 3D spaces naturally occur. Investigating these interactions in vivo is of limited value due to problems regarding the challenges caused by the species-specificity of many molecules. Thus, it is essential to use in vitro models in which human fibroblasts are co-cultured with tumor cells to understand their interactions. Here, we developed a 3D co-culture model that enables direct cell-cell contacts between pancreatic, breast and or lung tumor cells and human fibroblasts/ or tumor-associated fibroblasts (TAFs). We found that co-culturing with fibroblasts/TAFs increases the proliferation in of several types of cancer cells. We also observed that co-culture induces differential expression of soluble factors in a cancer type-specific manner. Treatment with blocking antibodies against selected factors or their receptors resulted in the inhibition of cancer cell proliferation in the co-cultures. Using our co-culture model, we further revealed that TAFs can influence the response to therapeutic agents in vitro. We suggest that this model can be reliably used as a tool to investigate the interactions between a tumor and the TME. PMID:26053043

An iterative hyperelastic parameters reconstruction for breast cancer assessment

NASA Astrophysics Data System (ADS)

Mehrabian, Hatef; Samani, Abbas

2008-03-01

In breast elastography, breast tissues usually undergo large compressions resulting in significant geometric and structural changes, and consequently nonlinear mechanical behavior. In this study, an elastography technique is presented where parameters characterizing tissue nonlinear behavior is reconstructed. Such parameters can be used for tumor tissue classification. To model the nonlinear behavior, tissues are treated as hyperelastic materials. The proposed technique uses a constrained iterative inversion method to reconstruct the tissue hyperelastic parameters. The reconstruction technique uses a nonlinear finite element (FE) model for solving the forward problem. In this research, we applied Yeoh and Polynomial models to model the tissue hyperelasticity. To mimic the breast geometry, we used a computational phantom, which comprises of a hemisphere connected to a cylinder. This phantom consists of two types of soft tissue to mimic adipose and fibroglandular tissues and a tumor. Simulation results show the feasibility of the proposed method in reconstructing the hyperelastic parameters of the tumor tissue.

Cell intrinsic abrogation of TGFβ signaling delays but does not prevent dysfunction of self/tumor specific CD8 T cells in a murine model of autochthonous prostate cancer

PubMed Central

Chou, Cassie K.; Schietinger, Andrea; Liggitt, H. Denny; Tan, Xiaoxia; Funk, Sarah; Freeman, Gordon J.; Ratliff, Timothy L.; Greenberg, Norman M.; Greenberg, Philip D.

2012-01-01

Adoptive T cell therapy (ACT) for the treatment of established cancers is actively being pursued in clinical trials. However, poor in vivo persistence and maintenance of anti-tumor activity of transferred T cells remain major problems. Transforming growth factor beta (TGFβ) is a potent immunosuppressive cytokine that is often expressed at high levels within the tumor microenvironment, potentially limiting T cell mediated anti-tumor activity. Here, we used a model of autochthonous murine prostate cancer to evaluate the effect of cell intrinsic abrogation of TGFβ signaling in self/tumor specific CD8 T cells used in ACT to target the tumor in situ. We found that persistence and anti-tumor activity of adoptively transferred effector T cells deficient in TGFβ signaling was significantly improved in the cancerous prostate. However, over time, despite persistence in peripheral lymphoid organs, the numbers of transferred cells in the prostate decreased and the residual prostate infiltrating T cells were no longer functional. These findings reveal that TGFβ negatively regulates the accumulation and effector function of transferred self/tumor specific CD8 T cells and highlight that, when targeting a tumor antigen that is also expressed as a self-protein, additional substantive obstacles are operative within the tumor microenvironment, potentially hampering the success of ACT for solid tumors. PMID:22984076

Social Competence in Pediatric Brain Tumor Survivors: Application of a Model from Social Neuroscience and Developmental Psychology

PubMed Central

Hocking, Matthew C.; McCurdy, Mark; Turner, Elise; Kazak, Anne E.; Noll, Robert B.; Phillips, Peter; Barakat, Lamia P.

2014-01-01

Pediatric brain tumor (BT) survivors are at risk for psychosocial late effects across many domains of functioning, including neurocognitive and social. The literature on the social competence of pediatric BT survivors is still developing and future research is needed that integrates developmental and cognitive neuroscience research methodologies to identify predictors of survivor social adjustment and interventions to ameliorate problems. This review discusses the current literature on survivor social functioning through a model of social competence in childhood brain disorder and suggests future directions based on this model. Interventions pursuing change in survivor social adjustment should consider targeting social ecological factors. PMID:25382825

Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs.

PubMed

Saunders, Christopher T; Wong, Wendy S W; Swamy, Sajani; Becq, Jennifer; Murray, Lisa J; Cheetham, R Keira

2012-07-15

Whole genome and exome sequencing of matched tumor-normal sample pairs is becoming routine in cancer research. The consequent increased demand for somatic variant analysis of paired samples requires methods specialized to model this problem so as to sensitively call variants at any practical level of tumor impurity. We describe Strelka, a method for somatic SNV and small indel detection from sequencing data of matched tumor-normal samples. The method uses a novel Bayesian approach which represents continuous allele frequencies for both tumor and normal samples, while leveraging the expected genotype structure of the normal. This is achieved by representing the normal sample as a mixture of germline variation with noise, and representing the tumor sample as a mixture of the normal sample with somatic variation. A natural consequence of the model structure is that sensitivity can be maintained at high tumor impurity without requiring purity estimates. We demonstrate that the method has superior accuracy and sensitivity on impure samples compared with approaches based on either diploid genotype likelihoods or general allele-frequency tests. The Strelka workflow source code is available at ftp://strelka@ftp.illumina.com/. csaunders@illumina.com

Stochastic modelling of slow-progressing tumors: Analysis and applications to the cell interplay and control of low grade gliomas

NASA Astrophysics Data System (ADS)

Rodríguez, Clara Rojas; Fernández Calvo, Gabriel; Ramis-Conde, Ignacio; Belmonte-Beitia, Juan

2017-08-01

Tumor-normal cell interplay defines the course of a neoplastic malignancy. The outcome of this dual relation is the ultimate prevailing of one of the cells and the death or retreat of the other. In this paper we study the mathematical principles that underlay one important scenario: that of slow-progressing cancers. For this, we develop, within a stochastic framework, a mathematical model to account for tumor-normal cell interaction in such a clinically relevant situation and derive a number of deterministic approximations from the stochastic model. We consider in detail the existence and uniqueness of the solutions of the deterministic model and study the stability analysis. We then focus our model to the specific case of low grade gliomas, where we introduce an optimal control problem for different objective functionals under the administration of chemotherapy. We derive the conditions for which singular and bang-bang control exist and calculate the optimal control and states.

Osteosarcoma Models: From Cell Lines to Zebrafish

PubMed Central

Mohseny, Alexander B.; Hogendoorn, Pancras C. W.; Cleton-Jansen, Anne-Marie

2012-01-01

High-grade osteosarcoma is an aggressive tumor most commonly affecting adolescents. The early age of onset might suggest genetic predisposition; however, the vast majority of the tumors are sporadic. Early onset, most often lack of a predisposing condition or lesion, only infrequent (<2%) prevalence of inheritance, extensive genomic instability, and a wide histological heterogeneity are just few factors to mention that make osteosarcoma difficult to study. Therefore, it is sensible to design and use models representative of the human disease. Here we summarize multiple osteosarcoma models established in vitro and in vivo, comment on their utilities, and highlight newest achievements, such as the use of zebrafish embryos. We conclude that to gain a better understanding of osteosarcoma, simplification of this extremely complex tumor is needed. Therefore, we parse the osteosarcoma problem into parts and propose adequate models to study them each separately. A better understanding of osteosarcoma provides opportunities for discovering and assaying novel effective treatment strategies. “Sometimes the model is more interesting than the original disease” PJ Hoedemaeker (1937–2007). PMID:22566751

3D discrete angiogenesis dynamic model and stochastic simulation for the assessment of blood perfusion coefficient and impact on heat transfer between nanoparticles and malignant tumors.

PubMed

Yifat, Jonathan; Gannot, Israel

2015-03-01

Early detection of malignant tumors plays a crucial role in the survivability chances of the patient. Therefore, new and innovative tumor detection methods are constantly searched for. Tumor-specific magnetic-core nano-particles can be used with an alternating magnetic field to detect and treat tumors by hyperthermia. For the analysis of the method effectiveness, the bio-heat transfer between the nanoparticles and the tissue must be carefully studied. Heat diffusion in biological tissue is usually analyzed using the Pennes Bio-Heat Equation, where blood perfusion plays an important role. Malignant tumors are known to initiate an angiogenesis process, where endothelial cell migration from neighboring vasculature eventually leads to the formation of a thick blood capillary network around them. This process allows the tumor to receive its extensive nutrition demands and evolve into a more progressive and potentially fatal tumor. In order to assess the effect of angiogenesis on the bio-heat transfer problem, we have developed a discrete stochastic 3D model & simulation of tumor-induced angiogenesis. The model elaborates other angiogenesis models by providing high resolution 3D stochastic simulation, capturing of fine angiogenesis morphological features, effects of dynamic sprout thickness functions, and stochastic parent vessel generator. We show that the angiogenesis realizations produced are well suited for numerical bio-heat transfer analysis. Statistical study on the angiogenesis characteristics was derived using Monte Carlo simulations. According to the statistical analysis, we provide analytical expression for the blood perfusion coefficient in the Pennes equation, as a function of several parameters. This updated form of the Pennes equation could be used for numerical and analytical analyses of the proposed detection and treatment method. Copyright © 2014 Elsevier Inc. All rights reserved.

HAMLET kills tumor cells by apoptosis: structure, cellular mechanisms, and therapy.

PubMed

Gustafsson, Lotta; Hallgren, Oskar; Mossberg, Ann-Kristin; Pettersson, Jenny; Fischer, Walter; Aronsson, Annika; Svanborg, Catharina

2005-05-01

New cancer treatments should aim to destroy tumor cells without disturbing normal tissue. HAMLET (human alpha-lactalbumin made lethal to tumor cells) offers a new molecular approach to solving this problem, because it induces apoptosis in tumor cells but leaves normal differentiated cells unaffected. After partial unfolding and binding to oleic acid, alpha-lactalbumin forms the HAMLET complex, which enters tumor cells and freezes their metabolic machinery. The cells proceed to fragment their DNA, and they disintegrate with apoptosis-like characteristics. HAMLET kills a wide range of malignant cells in vitro and maintains this activity in vivo in patients with skin papillomas. In addition, HAMLET has striking effects on human glioblastomas in a rat xenograft model. After convection-enhanced delivery, HAMLET diffuses throughout the brain, selectively killing tumor cells and controlling tumor progression without apparent tissue toxicity. HAMLET thus shows great promise as a new therapeutic with the advantage of selectivity for tumor cells and lack of toxicity.

Radiotherapy Dose Fractionation under Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Davison, Matt; Kim, Daero; Keller, Harald

2011-11-01

In radiotherapy, radiation is directed to damage a tumor while avoiding surrounding healthy tissue. Tradeoffs ensue because dose cannot be exactly shaped to the tumor. It is particularly important to ensure that sensitive biological structures near the tumor are not damaged more than a certain amount. Biological tissue is known to have a nonlinear response to incident radiation. The linear quadratic dose response model, which requires the specification of two clinically and experimentally observed response coefficients, is commonly used to model this effect. This model yields an optimization problem giving two different types of optimal dose sequences (fractionation schedules). Which fractionation schedule is preferred depends on the response coefficients. These coefficients are uncertainly known and may differ from patient to patient. Because of this not only the expected outcomes but also the uncertainty around these outcomes are important, and it might not be prudent to select the strategy with the best expected outcome.

Pituitary Tumors

MedlinePlus

... hormones in your body. This can cause endocrine diseases such as Cushing's syndrome and hyperthyroidism. Symptoms of pituitary tumors include Headaches Vision problems Nausea and vomiting Problems caused ... the tumor. Other options include medicines, radiation therapy, and chemotherapy.

Surface-region context in optimal multi-object graph-based segmentation: robust delineation of pulmonary tumors.

PubMed

Song, Qi; Chen, Mingqing; Bai, Junjie; Sonka, Milan; Wu, Xiaodong

2011-01-01

Multi-object segmentation with mutual interaction is a challenging task in medical image analysis. We report a novel solution to a segmentation problem, in which target objects of arbitrary shape mutually interact with terrain-like surfaces, which widely exists in the medical imaging field. The approach incorporates context information used during simultaneous segmentation of multiple objects. The object-surface interaction information is encoded by adding weighted inter-graph arcs to our graph model. A globally optimal solution is achieved by solving a single maximum flow problem in a low-order polynomial time. The performance of the method was evaluated in robust delineation of lung tumors in megavoltage cone-beam CT images in comparison with an expert-defined independent standard. The evaluation showed that our method generated highly accurate tumor segmentations. Compared with the conventional graph-cut method, our new approach provided significantly better results (p < 0.001). The Dice coefficient obtained by the conventional graph-cut approach (0.76 +/- 0.10) was improved to 0.84 +/- 0.05 when employing our new method for pulmonary tumor segmentation.

Modeling NF2 Tumors for Drug Screening Using Induced Pluripotent Stem Cells

DTIC Science & Technology

2016-10-01

Laryngoscope, 124(August), pp.340–346. 11. Searchfield, G.D., Muñoz, D.J.B. & Thorne, P.R., 2004. Ensemble spontaneous activity in the guinea - pig ...Keywords 3 3. Accomplishments 3 4. Impact 10 5. Changes/Problems 10 6. Products 10 7. Participants & Other Collaborating Organizations 11 8...and differences in activity may alter cytokine production in the NF2 microenvironment, contributing to angiogenesis and tumor growth (Koppes et al

Cancer: A Problem of Developmental Biology; Scientific Evidence for Reprogramming and Differentiation Therapy.

PubMed

Sell, Stewart; Nicolini, Andrea; Ferrari, Paola; Biava, Pier M

2016-01-01

Current medical literature acknowledges that embryonic micro-environment is able to suppress tumor development. Administering carcinogenic substances during organogenesis in fact leads to embryonic malformations, but not to offspring tumor growth. Once organogenesis has ended, administration of carcinogenic substances causes a rise in offspring tumor development. These data indicate that cancer can be considered a deviation in normal development, which can be regulated by factors of the embryonic microenvironment. Furthermore, it has been demonstrated that teratoma differentiates into normal tissues once it is implanted in the embryo. Recently, it has been shown that implanting a melanoma in Zebrafish embryo did not result in a tumor development; however, it did in the adult specimen. This demonstrates that cancer cells can differentiate into normal tissues when implanted in the embryo. In addition, it was demonstrated that other tumors can revert into a normal phenotype and/or differentiate into normal tissue when implanted in the embryo. These studies led some authors to define cancer as a problem of developmental biology and to predict the present concept of "cancer stem cells theory". In this review, we record the most important researches about the reprogramming and differentiation treatments of cancer cells to better clarify how the substances taken from developing embryo or other biological substances can induce differentiation of malignant cells. Lastly, a model of cancer has been proposed here, conceived by one of us, which is consistent with the reality, as demonstrated by a great number of researches. This model integrates the theory of the "maturation arrest" of cancer cells as conceived by B. Pierce with the theory which describes cancer as a process of deterministic chaos determined by genetic and/or epigenetic alterations in differentiated cells, which leads a normal cell to become cancerous. All the researches here described demonstrated that cancer can be considered a problem of developmental biology and that one of the most important hallmarks of cancer is the loss of differentiation as already described by us in other articles.

Designing effective anticancer-radiopeptides. A Molecular Dynamics study of their interaction with model tumor and healthy cell membranes.

PubMed

Capozzi, E; Aureli, S; Minicozzi, V; Rossi, G C; Stellato, F; Morante, S

2018-06-06

One of the greatest merit of the use of radiopeptides in oncology is their selectivity which, however, brings about the drawback that each radiopeptide is specific for a given tumor type. To overcome this problem the direction currently taken in drug design is that of radiolabelling peptide hormones (or their analogues), relying on their intrinsic ability to bind to specific receptors in precise areas of the human body, at the cost, however, of a poor selectivity against healthy cells. We present here an extensive Molecular Dynamics study of a promising alternative inspired by the mechanism through which antimicrobial peptides interact with the negatively charged bacterial membranes. Appropriately modifying the human antimicrobial peptide, LL-37, we designed a functionalized radionuclide carrier capable of binding more strongly to the negatively charged (model) tumor membranes than to the neutral healthy ones. The mechanism behind this behaviour relies on the fact that at the slight acidic pH surrounding tumor tissues the histidines belonging to the peptide get protonated thus making it positively charged. We have investigated by an extended numerical study the way in which this artificial peptide interacts with models of tumor and healthy cell membranes, proving by Potential Mean Force calculations that the affinity of the peptide to model tumor membranes is significantly larger than to healthy ones. These features (high affinity and generic tumor selectivity) recommend antimicrobial derived customized carriers as promising theranostic constructs in cancer diagnostic and therapy. Copyright © 2018 Elsevier B.V. All rights reserved.

A technology platform to assess multiple cancer agents simultaneously within a patient's tumor

PubMed Central

Klinghoffer, Richard A.; Frazier, Jason P.; Moreno-Gonzalez, Alicia; Strand, Andrew D.; Kerwin, William S.; Casalini, Joseph R.; Thirstrup, Derek J.; You, Sheng; Morris, Shelli M.; Watts, Korashon L.; Veiseh, Mandana; Grenley, Marc O.; Tretyak, Ilona; Dey, Joyoti; Carleton, Michael; Beirne, Emily; Pedro, Kyle D.; Ditzler, Sally H.; Girard, Emily J.; Deckwerth, Thomas L.; Bertout, Jessica A.; Meleo, Karri A.; Filvaroff, Ellen H.; Chopra, Rajesh; Press, Oliver W.; Olson, James M.

2016-01-01

A fundamental problem in cancer drug development is that antitumor efficacy in preclinical cancer models does not translate faithfully to patient outcomes. Much of early cancer drug discovery is performed under in vitro conditions in cell-based models that poorly represent actual malignancies. To address this inconsistency, we have developed a technology platform called CIVO, which enables simultaneous assessment of up to eight drugs or drug combinations within a single solid tumor in vivo. The platform is currently designed for use in animal models of cancer and patients with superficial tumors but can be modified for investigation of deeper-seated malignancies. In xenograft lymphoma models, CIVO microinjection of well-characterized anticancer agents (vincristine, doxorubicin, mafosfamide, and prednisolone) induced spatially defined cellular changes around sites of drug exposure, specific to the known mechanisms of action of each drug. The observed localized responses predicted responses to systemically delivered drugs in animals. In pair-matched lymphoma models, CIVO correctly demonstrated tumor resistance to doxorubicin and vincristine and an unexpected enhanced sensitivity to mafosfamide in multidrug-resistant lymphomas compared with chemotherapy-naïve lymphomas. A CIVO-enabled in vivo screen of 97 approved oncology agents revealed a novel mTOR (mammalian target of rapamycin) pathway inhibitor that exhibits significantly increased tumor-killing activity in the drug-resistant setting compared with chemotherapy-naïve tumors. Finally, feasibility studies to assess the use of CIVO in human and canine patients demonstrated that microinjection of drugs is toxicity-sparing while inducing robust, easily tracked, drug-specific responses in autochthonous tumors, setting the stage for further application of this technology in clinical trials. PMID:25904742

Tissue-scale, personalized modeling and simulation of prostate cancer growth

NASA Astrophysics Data System (ADS)

Lorenzo, Guillermo; Scott, Michael A.; Tew, Kevin; Hughes, Thomas J. R.; Zhang, Yongjie Jessica; Liu, Lei; Vilanova, Guillermo; Gomez, Hector

2016-11-01

Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed “predictive medicine.” Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.

Genetic therapy in gliomas: historical analysis and future perspectives.

PubMed

Mattei, Tobias Alécio; Ramina, Ricardo; Miura, Flavio Key; Aguiar, Paulo Henrique; Valiengo, Leandro da Costa

2005-03-01

High-grade gliomas are relatively frequent in adults, and consist of the most malignant kind of primary brain tumor. Being resistant to standard treatment modalities such as surgery, radiation, and chemotherapy, it is fatal within 1 to 2 years of onset of symptoms. Although several gene therapy systems proved to be efficient in controlling or eradicating these tumors in animal models, the clinical studies performed so far were not equally successful. Most clinical studies showed that methodologies that increase tumor infection/transduction and, consequently confer more permanent activity against the tumor, will lead to enhanced therapeutic results. Due to the promising practical clinical benefits that can be expected for the near future, an exposition to the practicing neurosurgeon about the basic issues in genetic therapy of gliomas seems convenient. Among the main topics, we shall discuss anti-tumoral mechanisms of various genes that can be transfected, the advantages and drawbacks of the different vectors utilized, the possibilities of tumor targeting by modifications in the native tropism of virus vectors, as well as the different physical methods for vector delivery to the tumors. Along with the exposition we will also review of the history of the genetic therapy for gliomas, with special focus on the main problems found during the advancement of scientific discoveries in this area. A general analysis is also made of the present state of this promising therapeutic modality, with reference to the problems that still must be solved and the new paradigms for future research in this area.

The perivascular niche regulates breast tumor dormancy

PubMed Central

Peinado, Héctor; Mori, Hidetoshi; Matei, Irina R.; Evason, Kimberley J.; Brazier, Hélène; Almeida, Dena; Koller, Antonius; Hajjar, Katherine A.; Stainier, Didier Y.R.; Chen, Emily I.; Lyden, David

2013-01-01

In a significant fraction of breast cancer patients, distant metastases emerge after years or even decades of latency. How disseminated tumor cells (DTCs) are kept dormant, and what ‘wakes them up’, are fundamental problems in tumor biology. To address these questions, we utilized metastasis assays in mice to show that dormant DTCs reside upon microvasculature of lung, bone marrow and brain. We then engineered organotypic microvascular niches to determine whether endothelial cells directly influence breast cancer cell (BCC) growth. These models demonstrated that endothelial-derived thrombospondin-1 induces sustained BCC quiescence. This suppressive cue was lost in sprouting neovasculature; time-lapse analysis showed that sprouting vessels not only permit, but accelerate BCC outgrowth. We confirmed this surprising result in dormancy models and in zebrafish, and identified active TGF-β1 and periostin as tumor-promoting, endothelial tip cell-derived factors. Our work reveals that stable microvasculature constitutes a ‘dormant niche,’ whereas sprouting neovasculature sparks micrometastatic outgrowth. PMID:23728425

A model for cancer tissue heterogeneity.

PubMed

Mohanty, Anwoy Kumar; Datta, Aniruddha; Venkatraj, Vijayanagaram

2014-03-01

An important problem in the study of cancer is the understanding of the heterogeneous nature of the cell population. The clonal evolution of the tumor cells results in the tumors being composed of multiple subpopulations. Each subpopulation reacts differently to any given therapy. This calls for the development of novel (regulatory network) models, which can accommodate heterogeneity in cancerous tissues. In this paper, we present a new approach to model heterogeneity in cancer. We model heterogeneity as an ensemble of deterministic Boolean networks based on prior pathway knowledge. We develop the model considering the use of qPCR data. By observing gene expressions when the tissue is subjected to various stimuli, the compositional breakup of the tissue under study can be determined. We demonstrate the viability of this approach by using our model on synthetic data, and real-world data collected from fibroblasts.

Optimal Co-segmentation of Tumor in PET-CT Images with Context Information

PubMed Central

Song, Qi; Bai, Junjie; Han, Dongfeng; Bhatia, Sudershan; Sun, Wenqing; Rockey, William; Bayouth, John E.; Buatti, John M.

2014-01-01

PET-CT images have been widely used in clinical practice for radiotherapy treatment planning of the radiotherapy. Many existing segmentation approaches only work for a single imaging modality, which suffer from the low spatial resolution in PET or low contrast in CT. In this work we propose a novel method for the co-segmentation of the tumor in both PET and CT images, which makes use of advantages from each modality: the functionality information from PET and the anatomical structure information from CT. The approach formulates the segmentation problem as a minimization problem of a Markov Random Field (MRF) model, which encodes the information from both modalities. The optimization is solved using a graph-cut based method. Two sub-graphs are constructed for the segmentation of the PET and the CT images, respectively. To achieve consistent results in two modalities, an adaptive context cost is enforced by adding context arcs between the two subgraphs. An optimal solution can be obtained by solving a single maximum flow problem, which leads to simultaneous segmentation of the tumor volumes in both modalities. The proposed algorithm was validated in robust delineation of lung tumors on 23 PET-CT datasets and two head-and-neck cancer subjects. Both qualitative and quantitative results show significant improvement compared to the graph cut methods solely using PET or CT. PMID:23693127

An Emerging Allee Effect Is Critical for Tumor Initiation and Persistence

PubMed Central

Böttger, Katrin; Hatzikirou, Haralambos; Voss-Böhme, Anja; Cavalcanti-Adam, Elisabetta Ada; Herrero, Miguel A.; Deutsch, Andreas

2015-01-01

Tumor cells develop different strategies to cope with changing microenvironmental conditions. A prominent example is the adaptive phenotypic switching between cell migration and proliferation. While it has been shown that the migration-proliferation plasticity influences tumor spread, it remains unclear how this particular phenotypic plasticity affects overall tumor growth, in particular initiation and persistence. To address this problem, we formulate and study a mathematical model of spatio-temporal tumor dynamics which incorporates the microenvironmental influence through a local cell density dependence. Our analysis reveals that two dynamic regimes can be distinguished. If cell motility is allowed to increase with local cell density, any tumor cell population will persist in time, irrespective of its initial size. On the contrary, if cell motility is assumed to decrease with respect to local cell density, any tumor population below a certain size threshold will eventually extinguish, a fact usually termed as Allee effect in ecology. These results suggest that strategies aimed at modulating migration are worth to be explored as alternatives to those mainly focused at keeping tumor proliferation under control. PMID:26335202

Actively targeted gold nanoparticles as novel radiosensitizer agents: an in vivo head and neck cancer model

NASA Astrophysics Data System (ADS)

Popovtzer, Aron; Mizrachi, Aviram; Motiei, Menachem; Bragilovski, Dimitri; Lubimov, Leon; Levi, Mattan; Hilly, Ohad; Ben-Aharon, Irit; Popovtzer, Rachela

2016-01-01

A major problem in the treatment of head and neck cancer today is the resistance of tumors to traditional radiation therapy, which results in 40% local failure, despite aggressive treatment. The main objective of this study was to develop a technique which will overcome tumor radioresistance by increasing the radiation absorbed in the tumor using cetuximab targeted gold nanoparticles (GNPs), in clinically relevant energies and radiation dosage. In addition, we have investigated the biological mechanisms underlying tumor shrinkage and the in vivo toxicity of GNP. The results showed that targeted GNP enhanced the radiation effect and had a significant impact on tumor growth (P < 0.001). The mechanism of radiation enhancement was found to be related to earlier and greater apoptosis (TUNEL assay), angiogenesis inhibition (by CD34 level) and diminished repair mechanism (PCNA staining). Additionally, GNPs have been proven to be safe as no evidence of toxicity has been observed.

Longitudinal measurement of extracellular matrix rigidity in 3D tumor models using particle-tracking microrheology.

PubMed

Jones, Dustin P; Hanna, William; El-Hamidi, Hamid; Celli, Jonathan P

2014-06-10

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(ω). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.

FISHtrees 3.0: Tumor Phylogenetics Using a Ploidy Probe.

PubMed

Gertz, E Michael; Chowdhury, Salim Akhter; Lee, Woei-Jyh; Wangsa, Darawalee; Heselmeyer-Haddad, Kerstin; Ried, Thomas; Schwartz, Russell; Schäffer, Alejandro A

2016-01-01

Advances in fluorescence in situ hybridization (FISH) make it feasible to detect multiple copy-number changes in hundreds of cells of solid tumors. Studies using FISH, sequencing, and other technologies have revealed substantial intra-tumor heterogeneity. The evolution of subclones in tumors may be modeled by phylogenies. Tumors often harbor aneuploid or polyploid cell populations. Using a FISH probe to estimate changes in ploidy can guide the creation of trees that model changes in ploidy and individual gene copy-number variations. We present FISHtrees 3.0, which implements a ploidy-based tree building method based on mixed integer linear programming (MILP). The ploidy-based modeling in FISHtrees includes a new formulation of the problem of merging trees for changes of a single gene into trees modeling changes in multiple genes and the ploidy. When multiple samples are collected from each patient, varying over time or tumor regions, it is useful to evaluate similarities in tumor progression among the samples. Therefore, we further implemented in FISHtrees 3.0 a new method to build consensus graphs for multiple samples. We validate FISHtrees 3.0 on a simulated data and on FISH data from paired cases of cervical primary and metastatic tumors and on paired breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). Tests on simulated data show improved accuracy of the ploidy-based approach relative to prior ploidyless methods. Tests on real data further demonstrate novel insights these methods offer into tumor progression processes. Trees for DCIS samples are significantly less complex than trees for paired IDC samples. Consensus graphs show substantial divergence among most paired samples from both sets. Low consensus between DCIS and IDC trees may help explain the difficulty in finding biomarkers that predict which DCIS cases are at most risk to progress to IDC. The FISHtrees software is available at ftp://ftp.ncbi.nih.gov/pub/FISHtrees.

FISHtrees 3.0: Tumor Phylogenetics Using a Ploidy Probe

PubMed Central

Chowdhury, Salim Akhter; Lee, Woei-Jyh; Wangsa, Darawalee; Heselmeyer-Haddad, Kerstin; Ried, Thomas; Schwartz, Russell; Schäffer, Alejandro A.

2016-01-01

Advances in fluorescence in situ hybridization (FISH) make it feasible to detect multiple copy-number changes in hundreds of cells of solid tumors. Studies using FISH, sequencing, and other technologies have revealed substantial intra-tumor heterogeneity. The evolution of subclones in tumors may be modeled by phylogenies. Tumors often harbor aneuploid or polyploid cell populations. Using a FISH probe to estimate changes in ploidy can guide the creation of trees that model changes in ploidy and individual gene copy-number variations. We present FISHtrees 3.0, which implements a ploidy-based tree building method based on mixed integer linear programming (MILP). The ploidy-based modeling in FISHtrees includes a new formulation of the problem of merging trees for changes of a single gene into trees modeling changes in multiple genes and the ploidy. When multiple samples are collected from each patient, varying over time or tumor regions, it is useful to evaluate similarities in tumor progression among the samples. Therefore, we further implemented in FISHtrees 3.0 a new method to build consensus graphs for multiple samples. We validate FISHtrees 3.0 on a simulated data and on FISH data from paired cases of cervical primary and metastatic tumors and on paired breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). Tests on simulated data show improved accuracy of the ploidy-based approach relative to prior ploidyless methods. Tests on real data further demonstrate novel insights these methods offer into tumor progression processes. Trees for DCIS samples are significantly less complex than trees for paired IDC samples. Consensus graphs show substantial divergence among most paired samples from both sets. Low consensus between DCIS and IDC trees may help explain the difficulty in finding biomarkers that predict which DCIS cases are at most risk to progress to IDC. The FISHtrees software is available at ftp://ftp.ncbi.nih.gov/pub/FISHtrees. PMID:27362268

Determining tumor blood flow parameters from dynamic image measurements

NASA Astrophysics Data System (ADS)

Libertini, Jessica M.

2008-11-01

Many recent cancer treatments focus on preventing angiogenesis, the process by which a tumor promotes the growth of large and efficient capillary beds for the increased nourishment required to support the tumor's rapid growth[l]. To measure the efficacy of these treatments in a timely fashion, there is an interest in using data from dynamic sequences of contrast-enhanced medical imaging, such as MRI and CT, to measure blood flow parameters such as perfusion, permeability-surface-area product, and the relative volumes of the plasma and extracellular-extravascular space. Starting with a two compartment model presented by the radiology community[2], this work challenges the application of a simplification to this problem, which was originally developed to model capillary reuptake[3]. While the primary result of this work is the demonstration of the inaccuracy of this simplification, the remainder of the paper is dedicated to presenting alternative methods for calculating the perfusion and plasma volume coefficients. These methods are applied to model data sets based on real patient data, and preliminary results are presented.

Combining radiation with autophagy inhibition enhances suppression of tumor growth and angiogenesis in esophageal cancer.

PubMed

Chen, Yongshun; Li, Xiaohong; Guo, Leiming; Wu, Xiaoyuan; He, Chunyu; Zhang, Song; Xiao, Yanjing; Yang, Yuanyuan; Hao, Daxuan

2015-08-01

Radiotherapy is an effective treatment for esophageal cancer; however, tumor resistance to radiation remains a major biological problem. The present study aimed to investigate whether inhibition of autophagy may decrease overall tumor resistance to radiation. The effects of the autophagy inhibitor 3-methyladenine (3-MA) on radiosensitivity were tested in the EC9706 human esophageal squamous cell carcinoma cell line by colony formation assay. Furthermore, the synergistic cytotoxic effects of 3-MA and radiation were assessed in a tumor xenograft model in nude mice. Mechanistic studies were performed using flow cytometry, immunohistochemistry and western blot analysis. The results of the present study demonstrated that radiation induced an accumulation of autophagosomes and 3-MA effectively inhibited radiation-induced autophagy. Inhibition of autophagy was shown to significantly increase the radiosensitivity of the tumors in vitro and in vivo. The enhancement ratio of sensitization in EC9706 cells was 1.76 when the cells were treated with 10 mM 3-MA, alongside ionizing radiation. In addition, autophagy inhibition increased apoptosis and reduced tumor cell proliferation. The combination of radiation and autophagy inhibition resulted in a significant reduction in tumor volume and vasculature in the murine model. The present study demonstrated in vitro and in vivo that radiation-induced autophagy has a protective effect against cell death, and inhibition of autophagy is able to enhance the radiosensitivity of esophageal squamous cell carcinoma.

Combining radiation with autophagy inhibition enhances suppression of tumor growth and angiogenesis in esophageal cancer

PubMed Central

CHEN, YONGSHUN; LI, XIAOHONG; GUO, LEIMING; WU, XIAOYUAN; HE, CHUNYU; ZHANG, SONG; XIAO, YANJING; YANG, YUANYUAN; HAO, DAXUAN

2015-01-01

Radiotherapy is an effective treatment for esophageal cancer; however, tumor resistance to radiation remains a major biological problem. The present study aimed to investigate whether inhibition of autophagy may decrease overall tumor resistance to radiation. The effects of the autophagy inhibitor 3-methyladenine (3-MA) on radiosensitivity were tested in the EC9706 human esophageal squamous cell carcinoma cell line by colony formation assay. Furthermore, the synergistic cytotoxic effects of 3-MA and radiation were assessed in a tumor xenograft model in nude mice. Mechanistic studies were performed using flow cytometry, immunohistochemistry and western blot analysis. The results of the present study demonstrated that radiation induced an accumulation of autophagosomes and 3-MA effectively inhibited radiation-induced autophagy. Inhibition of autophagy was shown to significantly increase the radiosensitivity of the tumors in vitro and in vivo. The enhancement ratio of sensitization in EC9706 cells was 1.76 when the cells were treated with 10 mM 3-MA, alongside ionizing radiation. In addition, autophagy inhibition increased apoptosis and reduced tumor cell proliferation. The combination of radiation and autophagy inhibition resulted in a significant reduction in tumor volume and vasculature in the murine model. The present study demonstrated in vitro and in vivo that radiation-induced autophagy has a protective effect against cell death, and inhibition of autophagy is able to enhance the radiosensitivity of esophageal squamous cell carcinoma. PMID:25891159

Brain tumor segmentation with Vander Lugt correlator based active contour.

PubMed

Essadike, Abdelaziz; Ouabida, Elhoussaine; Bouzid, Abdenbi

2018-07-01

The manual segmentation of brain tumors from medical images is an error-prone, sensitive, and time-absorbing process. This paper presents an automatic and fast method of brain tumor segmentation. In the proposed method, a numerical simulation of the optical Vander Lugt correlator is used for automatically detecting the abnormal tissue region. The tumor filter, used in the simulated optical correlation, is tailored to all the brain tumor types and especially to the Glioblastoma, which considered to be the most aggressive cancer. The simulated optical correlation, computed between Magnetic Resonance Images (MRI) and this filter, estimates precisely and automatically the initial contour inside the tumorous tissue. Further, in the segmentation part, the detected initial contour is used to define an active contour model and presenting the problematic as an energy minimization problem. As a result, this initial contour assists the algorithm to evolve an active contour model towards the exact tumor boundaries. Equally important, for a comparison purposes, we considered different active contour models and investigated their impact on the performance of the segmentation task. Several images from BRATS database with tumors anywhere in images and having different sizes, contrast, and shape, are used to test the proposed system. Furthermore, several performance metrics are computed to present an aggregate overview of the proposed method advantages. The proposed method achieves a high accuracy in detecting the tumorous tissue by a parameter returned by the simulated optical correlation. In addition, the proposed method yields better performance compared to the active contour based methods with the averages of Sensitivity=0.9733, Dice coefficient = 0.9663, Hausdroff distance = 2.6540, Specificity = 0.9994, and faster with a computational time average of 0.4119 s per image. Results reported on BRATS database reveal that our proposed system improves over the recently published state-of-the-art methods in brain tumor detection and segmentation. Copyright © 2018 Elsevier B.V. All rights reserved.

Experimental and theoretical investigation of intratumoral nanoparticle distribution to enhance magnetic nanoparticle hyperthermia

NASA Astrophysics Data System (ADS)

Attaluri, Anilchandra

Magnetic nanoparticles have gained prominence in recent years for use in clinical applications such as imaging, drug delivery, and hyperthermia. Magnetic nanoparticle hyperthermia is a minimally invasive and effective approach for confined heating in tumors with little collateral damage. One of the major problems in the field of magnetic nanoparticle hyperthermia is irregular heat distribution in tumors which caused repeatable heat distribution quite impossible. This causes under dosage in tumor area and overheating in normal tissue. In this study, we develop a unified approach to understand magnetic nanoparticle distribution and temperature elevations in gel and tumors. A microCT imaging system is first used to visualize and quantify nanoparticle distribution in both tumors and tissue equivalent phantom gels. The microCT based nanoparticle concentration is related to specific absorption rate (SAR) of the nanoparticles and is confirmed by heat distribution experiments in tissue equivalent phantom gels. An optimal infusion protocol is identified to generate controllable and repeatable nanoparticle distribution in tumors. In vivo animal experiments are performed to measure intratumoral temperature elevations in PC3 xenograft tumors implanted in mice during magnetic nanoparticle hyperthermia. The effect of nanofluid injection parameters on the resulted temperature distribution is studied. It shows that the tumor temperatures can be elevated above 50°C using very small amounts of ferrofluid with a relatively low magnetic field. Slower ferrofluid infusion rates result in smaller nanoparticle distribution volumes in the tumors, however, it gives the much required controllability and repeatability when compared to the higher infusion rates. More nanoparticles occupy a smaller volume in the vicinity of the injection site with slower infusion rates, causing higher temperature elevations in the tumors. Based on the microCT imaging analyses of nanoparticles in tumors, a mass transport model is developed to simulate nanoparticle convection and diffusion in tumors, heat-induced tumor structural changes, as well as nanoparticle re-distribution during nanoparticle hyperthermia procedures. The modeled thermal damage induced nanoparticle redistribution predicts a 20% increase in the radius of the spherical tissue region containing nanoparticles. The developed model has demonstrated the feasibility of enhancing nanoparticle dispersion from injection sites using targeted thermal damage.

Specific tumor labeling enhanced by polyethylene glycol linkage of near infrared dyes conjugated to a chimeric anti-carcinoembryonic antigen antibody in a nude mouse model of human pancreatic cancer

NASA Astrophysics Data System (ADS)

Maawy, Ali A.; Hiroshima, Yukihiko; Zhang, Yong; Luiken, George A.; Hoffman, Robert M.; Bouvet, Michael

2014-10-01

Labeling of metastatic tumors can aid in their staging and resection of cancer. Near infrared (NIR) dyes have been used in the clinic for tumor labeling. However, there can be a nonspecific uptake of dye by the liver, lungs, and lymph nodes, which hinders detection of metastasis. In order to overcome these problems, we have used two NIR dyes (DyLight 650 and 750) conjugated to a chimeric anti-carcinoembryonic antigen antibody to evaluate how polyethylene glycol linkage (PEGylation) can improve specific tumor labeling in a nude mouse model of human pancreatic cancer. The conjugated PEGylated and non-PEGylated DyLight 650 and 750 dyes were injected intravenously into non-tumor-bearing nude mice. Serum samples were collected at various time points in order to determine serum concentrations and elimination kinetics. Conjugated PEGylated dyes had significantly higher serum dye concentrations than non-PEGylated dyes (p=0.005 for the 650 dyes and p<0.001 for the 750 dyes). Human pancreatic tumors subcutaneously implanted into nude mice were labeled with antibody-dye conjugates and serially imaged. Labeling with conjugated PEGylated dyes resulted in significantly brighter tumors compared to the non-PEGylated dyes (p<0.001 for the 650 dyes; p=0.01 for 750 dyes). PEGylation of the NIR dyes also decreased their accumulation in lymph nodes, liver, and lung. These results demonstrate enhanced selective tumor labeling by PEGylation of dyes conjugated to a tumor-specific antibody, suggesting their future clinical use in fluorescence-guided surgery.

Social problem solving and social performance after a group social skills intervention for childhood brain tumor survivors.

PubMed

Schulte, Fiona; Vannatta, Kathryn; Barrera, Maru

2014-02-01

The aim of this study was to explore the ability of a group social skills intervention program for childhood brain tumor survivors to effect two steps of the social information processing model: social problem solving and social performance. Participants were 15 survivors (eight men and seven women) aged 7-15 years. The intervention consisted of eight 2-h weekly sessions focused on social skills including friendship making. Social problem solving, using hypothetical scenarios, was assessed during sessions 1 and 8. Social performance was observed during intervention sessions 1, 4, and 8. Compared with session 1, significant increases were found in social performance: frequency of maintaining eye contact and social conversations with peers over the course of the intervention. No significant changes in social problem solving were noted. This pilot study is the first to report improvements related to group social skills intervention at the level of observed social performance over the course of intervention. The lack of change in social problem solving suggests that survivors may possess the social knowledge required for social situations but have difficulty enacting social behaviors. Copyright © 2013 John Wiley & Sons, Ltd.

Toward an Ising Model of Cancer and Beyond

PubMed Central

Torquato, Salvatore

2011-01-01

The holy grail of tumor modeling is to formulate theoretical and computational tools that can be utilized in the clinic to predict neoplastic progression and propose individualized optimal treatment strategies to control cancer growth. In order to develop such a predictive model, one must account for the numerous complex mechanisms involved in tumor growth. Here we review resarch work that we have done toward the development of an “Ising model” of cancer. The Ising model is an idealized statistical-mechanical model of ferromagnetism that is based on simple local-interaction rules, but nonetheless leads to basic insights and features of real magnets, such as phase transitions with a critical point. The review begins with a description of a minimalist four-dimensional (three dimensions in space and one in time) cellular automaton (CA) model of cancer in which healthy cells transition between states (proliferative, hypoxic, and necrotic) according to simple local rules and their present states, which can viewed as a stripped-down Ising model of cancer. This model is applied to model the growth of glioblastoma multiforme, the most malignant of brain cancers. This is followed by a discussion of the extension of the model to study the effect on the tumor dynamics and geometry of a mutated subpopulation. A discussion of how tumor growth is affected by chemotherapeutic treatment, including induced resistance, is then described. How angiogenesis as well as the heterogeneous and confined environment in which a tumor grows is incorporated in the CA model is discussed. The characterization of the level of organization of the invasive network around a solid tumor using spanning trees is subsequently described. Then, we describe open problems and future promising avenues for future research, including the need to develop better molecular-based models that incorporate the true heterogeneous environment over wide range of length and time scales (via imaging data), cell motility, oncogenes, tumor suppressor genes and cell-cell communication. A discussion about the need to bring to bear the powerful machinery of the theory of heterogeneous media to better understand the behavior of cancer in its microenvironment is presented. Finally, we propose the possibility of using optimization techniques, which have been used profitably to understand physical phenomena, in order to devise therapeutic (chemotherapy/radiation) strategies and to understand tumorigenesis itself. PMID:21301063

Modeling of FMISO [F18] nanoparticle PET tracer in normal-cancerous tissue based on real clinical image.

PubMed

Asgari, Hanie; Soltani, M; Sefidgar, Mostafa

2018-07-01

Hypoxia as one of the principal properties of tumor cells is a reaction to the deprivation of oxygen. The location of tumor cells could be identified by assessment of oxygen and nutrient level in human body. Positron emission tomography (PET) is a well-known non-invasive method that is able to measure hypoxia based on the FMISO (Fluoromisonidazole) tracer dynamic. This paper aims to study the PET tracer concentration through convection-diffusion-reaction equations in a real human capillary-like network. A non-uniform oxygen pressure along the capillary path and convection mechanism for FMISO transport are taken into account to accurately model the characteristics of the tracer. To this end, a multi-scale model consists of laminar blood flow through the capillary network, interstitial pressure, oxygen pressure, FMISO diffusion and FMISO convection transport in the extravascular region is developed. The present model considers both normal and tumor tissue regions in computational domain. The accuracy of numerical model is verified with the experimental results available in the literature. The convection and diffusion types of transport mechanism are employed in order to calculate the concentration of FMISO in the normal and tumor sub-domain. The influences of intravascular oxygen pressure, FMISO transport mechanisms, capillary density and different types of tissue on the FMISO concentration have been investigated. According to result (Table 4) the convection mechanism of FMISO molecules transportation is negligible, but it causes more accuracy of the proposed model. The approach of present study can be employed in order to investigate the effects of various parameters, such as tumor shape, on the dynamic behavior of different PET tracers, such as FDG, can be extended to different case study problems, such as drug delivery. Copyright © 2018 Elsevier Inc. All rights reserved.

[Augmented reality for image guided therapy (ARIGT) of kidney tumor during nephron sparing surgery (NSS): animal model and clinical approach].

PubMed

Drewniak, Tomasz; Rzepecki, Maciej; Juszczak, Kajetan; Kwiatek, Wojciech; Bielecki, Jakub; Zieliński, Krzysztof; Ruta, Andrzej; Czekierda, Łukasz; Moczulskis, Zbigniew

2011-01-01

The main problem in nephron sparing surgery (NSS) is to preserve renal tumors oncological purity during the removal of the tumor with a margin of macroscopically unchanged kidney tissue while keeping the largest possible amount of normal parenchyma of the operated kidney. The development of imaging techniques, in particular IGT (Image Guided Therapy) allows precise imaging of the surgical field and, therefore, is essential in improving the effectiveness of NSS (increase of nephron sparing with the optimal radicality). The aim of this study was to develop a method of the three-dimensional (3D) imaging of the kidney tumor and its lodge in the operated kidney using 3D laser scanner during NSS procedure. Additionally, the animal model of visualization was developed. The porcine kidney model was used to test the set built up with HD cameras and linear laser scanner connected to a laptop with graphic software (David Laser Scanner, Germany) showing the surface of the kidney and the lodge after removal the chunk of renal parenchyma. Additionally, the visualization and reconstruction was performed on animal porcine model. Moreover, 5 patients (3 women, 2 men) aged from 37 to 68 years (mean 56), diagnosed with kidney tumors in CT scans with a diameter of 3.7-6.9 cm (mean 4.9) were operated in our Department this year, scanning the surface during the treatment with the kidney tumor and kidney tumor after it is removed with a margin of renal tissue. In one case, the lodge of removed tumor was scanned. Dimensions in 3D reconstruction images of laser scans in the study of animal model and the images obtained intraoperatively were compared with the dimensions evaluated during preoperative CT scans, intraoperative measurements. Three-dimensional imaging laser scanner operating field loge resected tumor and the tumor on the kidney of animal models and during NSS treatments for patients with kidney tumors is possible in real time with an accuracy of -2 mm do +9 mm (+/- 3 mm). The duration of data acquisition by laser scanner and obtain three-dimensional image of the operating field takes an average of 13 seconds +/- 2 seconds. Movements associated with breathing and heart rate did not affect on the quality of the reconstruction. The imposition of the scanned surface texture occurs in real time, allowing you to identify renal parenchymal structures such as renal cortex, pyramids, pyelo-calices complex. Imaging control of NSS procedures is possible in animal models and in real time intraoperatively. The comparison of tumor size and the tumor lodge obtained in preoperative CT scans with the measurements during NSS procedure provide the surgeon to assess the extent of macroscopic estimation of the resection. This procedure helps the surgeon in obtaining oncological radicality with saving as much normal tissue kidney as possible. Performance of the imaging methods should be evaluated on a larger group of patients with kidney tumors eligible for NSS treatment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Bo, E-mail: luboufl@gmail.com; Park, Justin C.; Fan, Qiyong

Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparsemore » optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.« less

Partition-based acquisition model for speed up navigated beta-probe surface imaging

NASA Astrophysics Data System (ADS)

Monge, Frédéric; Shakir, Dzhoshkun I.; Navab, Nassir; Jannin, Pierre

2016-03-01

Although gross total resection in low-grade glioma surgery leads to a better patient outcome, the in-vivo control of resection borders remains challenging. For this purpose, navigated beta-probe systems combined with 18F-based radiotracer, relying on activity distribution surface estimation, have been proposed to generate reconstructed images. The clinical relevancy has been outlined by early studies where intraoperative functional information is leveraged although inducing low spatial resolution in reconstruction. To improve reconstruction quality, multiple acquisition models have been proposed. They involve the definition of attenuation matrix for designing radiation detection physics. Yet, they require high computational power for efficient intraoperative use. To address the problem, we propose a new acquisition model called Partition Model (PM) considering an existing model where coefficients of the matrix are taken from a look-up table (LUT). Our model is based upon the division of the LUT into averaged homogeneous values for assigning attenuation coefficients. We validated our model using in vitro datasets, where tumors and peri-tumoral tissues have been simulated. We compared our acquisition model with the o_-the-shelf LUT and the raw method. Acquisition models outperformed the raw method in term of tumor contrast (7.97:1 mean T:B) but with a difficulty of real-time use. Both acquisition models reached the same detection performance with references (0.8 mean AUC and 0.77 mean NCC), where PM slightly improves the mean tumor contrast up to 10.1:1 vs 9.9:1 with the LUT model and more importantly, it reduces the mean computation time by 7.5%. Our model gives a faster solution for an intraoperative use of navigated beta-probe surface imaging system, with improved image quality.

A New Ghost Cell/Level Set Method for Moving Boundary Problems: Application to Tumor Growth

PubMed Central

Macklin, Paul

2011-01-01

In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics—an effect observed in real tumor growth. PMID:21331304

A feasibility study of treatment verification using EPID cine images for hypofractionated lung radiotherapy

NASA Astrophysics Data System (ADS)

Tang, Xiaoli; Lin, Tong; Jiang, Steve

2009-09-01

We propose a novel approach for potential online treatment verification using cine EPID (electronic portal imaging device) images for hypofractionated lung radiotherapy based on a machine learning algorithm. Hypofractionated radiotherapy requires high precision. It is essential to effectively monitor the target to ensure that the tumor is within the beam aperture. We modeled the treatment verification problem as a two-class classification problem and applied an artificial neural network (ANN) to classify the cine EPID images acquired during the treatment into corresponding classes—with the tumor inside or outside of the beam aperture. Training samples were generated for the ANN using digitally reconstructed radiographs (DRRs) with artificially added shifts in the tumor location—to simulate cine EPID images with different tumor locations. Principal component analysis (PCA) was used to reduce the dimensionality of the training samples and cine EPID images acquired during the treatment. The proposed treatment verification algorithm was tested on five hypofractionated lung patients in a retrospective fashion. On average, our proposed algorithm achieved a 98.0% classification accuracy, a 97.6% recall rate and a 99.7% precision rate. This work was first presented at the Seventh International Conference on Machine Learning and Applications, San Diego, CA, USA, 11-13 December 2008.

Alternative therapies for metastatic breast cancer: multimodal approach targeting tumor cell heterogeneity.

PubMed

Sambi, Manpreet; Haq, Sabah; Samuel, Vanessa; Qorri, Bessi; Haxho, Fiona; Hill, Kelli; Harless, William; Szewczuk, Myron R

2017-01-01

One of the primary challenges in developing effective therapies for malignant tumors is the specific targeting of a heterogeneous cancer cell population within the tumor. The cancerous tumor is made up of a variety of distinct cells with specialized receptors and proteins that could potentially be viable targets for drugs. In addition, the diverse signals from the local microenvironment may also contribute to the induction of tumor growth and metastasis. Collectively, these factors must be strategically studied and targeted in order to develop an effective treatment protocol. Targeted multimodal approaches need to be strategically studied in order to develop a treatment protocol that is successful in controlling tumor growth and preventing metastatic burden. Breast cancer, in particular, presents a unique problem because of the variety of subtypes of cancer that can arise and the multiple drug targets that could be exploited. For example, the tumor stage and subtypes often dictate the appropriate treatment regimen. Alternate multimodal therapies should consider the importance of time-dependent drug administration, as well as targeting the local and systemic tumor environment. Many reviews and papers have briefly touched on the clinical implications of this cellular heterogeneity; however, there has been very little discussion on the development of study models that reflect this diversity and on multimodal therapies that could target these subpopulations. Here, we summarize the current understanding of the origins of intratumoral heterogeneity in breast cancer subtypes, and its implications for tumor progression, metastatic potential, and treatment regimens. We also discuss the advantages and disadvantages of utilizing specific breast cancer models for research, including in vitro monolayer systems and three-dimensional mammospheres, as well as in vivo murine models that may have the capacity to encompass this heterogeneity. Lastly, we summarize some of the current advancements in the development of multitarget therapeutics that have shown promising results in clinical and preclinical studies when used alone or in combination with traditional regimens of surgery, chemotherapy, and/or radiation.

Immunotherapy in new pre-clinical models of HPV-associated oral cancers.

PubMed

Paolini, Francesca; Massa, Silvia; Manni, Isabella; Franconi, Rosella; Venuti, Aldo

2013-03-01

Cervical, anal, penile and a sub-set of head and neck (HN) tumors are critical health problems caused by high risk Human Papilloma Viruses (HPVs), like HPV type 16. No specific/effective pharmacological treatments exist. A valid preventive vaccination as well as the immunotherapy of persistent infections, pre-cancerous lesions or early-stage cancers could drive the HPV disease burden down. These treatments might be featured through low-cost platforms like those based on DNA and plant biotechnologies to produce tailored and enhanced formulations taking profit from the use of plants as bio-factories and as a source of immune-stimulators. Finally, and regardless of the formulation type, pre-clinical tests and models are crucial to foresee efficacy of immunotherapy before clinical trials.   In this study, we created an orthotopic mouse model for HPV-related oral tumors, a subset of HN tumors for which no models have been generated before. The model was obtained by inducing the stable expression of the HPV16 E7 protein into the mouse oral squamous cell carcinoma (OSCC) AT-84 (AT-84 E7). The AT-84 E7 cells were injected into the mouth pavement of C3H mice via an extra-oral route to obtain orthotopic tumors. The model turned out to mimic the natural history of the human HPV oral cancer. From AT-84 E7, through engineering to express luciferase, the bioluminescent AT-84 E7-Luc cells were obtained for a fast and easy monitoring by imaging. The AT-84 E7 and the AT-84 E7-Luc tumors were used to test the efficacy of E7-based therapeutic vaccines that we had previously generated and that had been already proven to be active in mice against non-orthotopic E7-expressing tumors (TC-1 cells). In particular, we used genetic and plant-derived formulations based on attenuated HPV16 E7 variants either fused to plant virus genes with immunological activity or produced by tobacco plants. Mice were monitored by imaging allowing to test the size reduction of the mouth implanted experimental tumors in function of the different regimens used. The proposed tumor model is easy to handle and to reproduce and it is efficacious in monitoring immunotherapy. Furthermore, it is expected to be more predictive of clinical outcome of therapeutic vaccines than non-orthotopic models that are currently used. Finally, imaging offers unique opportunities to predict formulation efficacy through measuring tumor growth in vivo.

3D brain tumor localization and parameter estimation using thermographic approach on GPU.

PubMed

Bousselham, Abdelmajid; Bouattane, Omar; Youssfi, Mohamed; Raihani, Abdelhadi

2018-01-01

The aim of this paper is to present a GPU parallel algorithm for brain tumor detection to estimate its size and location from surface temperature distribution obtained by thermography. The normal brain tissue is modeled as a rectangular cube including spherical tumor. The temperature distribution is calculated using forward three dimensional Pennes bioheat transfer equation, it's solved using massively parallel Finite Difference Method (FDM) and implemented on Graphics Processing Unit (GPU). Genetic Algorithm (GA) was used to solve the inverse problem and estimate the tumor size and location by minimizing an objective function involving measured temperature on the surface to those obtained by numerical simulation. The parallel implementation of Finite Difference Method reduces significantly the time of bioheat transfer and greatly accelerates the inverse identification of brain tumor thermophysical and geometrical properties. Experimental results show significant gains in the computational speed on GPU and achieve a speedup of around 41 compared to the CPU. The analysis performance of the estimation based on tumor size inside brain tissue also presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genetic predispositions and childhood cancer.

PubMed Central

Shannon, K

1998-01-01

This article provides an overview of the problem of genetic susceptibility to childhood cancer with a particular emphasis on problems with ascertaining inherited cancer risk and the role of tumor-suppressor gene mutations in cancer predispositions. The association between neurofibromatosis type 1 and childhood leukemia is used to illustrate some of the issues faced by molecular biologists and genetic epidemiologists in identifying and analyzing at-risk individuals. The problem of incomplete penetrance in cancer susceptibility is presented and potential models are discussed. The article concludes with a number of tentative conclusions from existing data and speculations for future studies. Images Figure 1 PMID:9646040

Fast and robust brain tumor segmentation using level set method with multiple image information.

PubMed

Lok, Ka Hei; Shi, Lin; Zhu, Xianlun; Wang, Defeng

2017-01-01

Brain tumor segmentation is a challenging task for its variation in intensity. The phenomenon is caused by the inhomogeneous content of tumor tissue and the choice of imaging modality. In 2010 Zhang developed the Selective Binary Gaussian Filtering Regularizing Level Set (SBGFRLS) model that combined the merits of edge-based and region-based segmentation. To improve the SBGFRLS method by modifying the singed pressure force (SPF) term with multiple image information and demonstrate effectiveness of proposed method on clinical images. In original SBGFRLS model, the contour evolution direction mainly depends on the SPF. By introducing a directional term in SPF, the metric could control the evolution direction. The SPF is altered by statistic values enclosed by the contour. This concept can be extended to jointly incorporate multiple image information. The new SPF term is expected to bring a solution for blur edge problem in brain tumor segmentation. The proposed method is validated with clinical images including pre- and post-contrast magnetic resonance images. The accuracy and robustness is compared with sensitivity, specificity, DICE similarity coefficient and Jaccard similarity index. Experimental results show improvement, in particular the increase of sensitivity at the same specificity, in segmenting all types of tumors except for the diffused tumor. The novel brain tumor segmentation method is clinical-oriented with fast, robust and accurate implementation and a minimal user interaction. The method effectively segmented homogeneously enhanced, non-enhanced, heterogeneously-enhanced, and ring-enhanced tumor under MR imaging. Though the method is limited by identifying edema and diffuse tumor, several possible solutions are suggested to turn the curve evolution into a fully functional clinical diagnosis tool.

Porphyrin lipid nanoparticles for enhanced photothermal therapy in a patient-derived orthotopic pancreas xenograft cancer model

NASA Astrophysics Data System (ADS)

MacLaughlin, Christina M.; Ding, Lili; Jin, Cheng; Cao, Pingjiang; Siddiqui, Iram; Hwang, David M.; Chen, Juan; Wilson, Brian C.; Zheng, Gang; Hedley, David W.

2016-03-01

Local disease control is a major problem in the treatment of pancreatic cancer, because curative-intent surgery is only possible in a minority of patients, and radiotherapy cannot be delivered in curative doses. Despite the promise of photothermal therapy (PTT) for ablation of pancreatic tumors, this approach remains under investigated. Using photothermal sensitizers in combination with laser light for PTT can result in more efficient conversion of light energy to heat, and confinement of thermal destruction to the tumor, thus sparing adjacent organs and vasculature. Porphyrins have been previously employed as photosensitizers for PDT and PTT, however their incorporation in to "porphysomes", lipid-based nanoparticles each containing ~80,000 porphyrins through conjugation of pyropheophorbide to phospholipids, carries two distinct advantages: 1) high-density porphyrin packing imparts the nanoparticles with enhanced photonic properties for imaging and phototherapy; 2) the enhanced permeability and retention effect may be exploited for optimal delivery of porphysomes to the tumor region thus high payload porphyrin delivery. The feasibility of porphysome-enhanced PTT for pancreatic cancer treatment was investigated using a patient-derived orthotopic pancreas xenograft tumor model. Uptake of porphysomes at the orthotopic tumor site was validated using ex vivo fluorescence imaging of intact organs of interest. The accumulation of porphysomes in orthotopic tumor microstructure was also confirmed by fluorescence imaging of excised tissue slices. PTT progress was monitored as changes in tumor surface temperature using IR optical imaging. Histological analyses were conducted to examine microstructure changes in tissue morphology, and the viability of remaining tumor tissues following exposure to heat. These studies may also provide insight as to the contribution of heat sink in application of thermal therapies to highly vascularized pancreatic tumors.

The sweet spot: FDG and other 2-carbon glucose analogs for multi-modal metabolic imaging of tumor metabolism

PubMed Central

Cox, Benjamin L; Mackie, Thomas R; Eliceiri, Kevin W

2015-01-01

Multi-modal imaging approaches of tumor metabolism that provide improved specificity, physiological relevance and spatial resolution would improve diagnosing of tumors and evaluation of tumor progression. Currently, the molecular probe FDG, glucose fluorinated with 18F at the 2-carbon, is the primary metabolic approach for clinical diagnostics with PET imaging. However, PET lacks the resolution necessary to yield intratumoral distributions of deoxyglucose, on the cellular level. Multi-modal imaging could elucidate this problem, but requires the development of new glucose analogs that are better suited for other imaging modalities. Several such analogs have been created and are reviewed here. Also reviewed are several multi-modal imaging studies that have been performed that attempt to shed light on the cellular distribution of glucose analogs within tumors. Some of these studies are performed in vitro, while others are performed in vivo, in an animal model. The results from these studies introduce a visualization gap between the in vitro and in vivo studies that, if solved, could enable the early detection of tumors, the high resolution monitoring of tumors during treatment, and the greater accuracy in assessment of different imaging agents. PMID:25625022

A Reconstruction Algorithm for Breast Cancer Imaging With Electrical Impedance Tomography in Mammography Geometry

PubMed Central

Kao, Tzu-Jen; Isaacson, David; Saulnier, Gary J.; Newell, Jonathan C.

2009-01-01

The conductivity and permittivity of breast tumors are known to differ significantly from those of normal breast tissues, and electrical impedance tomography (EIT) is being studied as a modality for breast cancer imaging to exploit these differences. At present, X-ray mammography is the primary standard imaging modality used for breast cancer screening in clinical practice, so it is desirable to study EIT in the geometry of mammography. This paper presents a forward model of a simplified mammography geometry and a reconstruction algorithm for breast tumor imaging using EIT techniques. The mammography geometry is modeled as a rectangular box with electrode arrays on the top and bottom planes. A forward model for the electrical impedance imaging problem is derived for a homogeneous conductivity distribution and is validated by experiment using a phantom tank. A reconstruction algorithm for breast tumor imaging based on a linearization approach and the proposed forward model is presented. It is found that the proposed reconstruction algorithm performs well in the phantom experiment, and that the locations of a 5-mm-cube metal target and a 6-mm-cube agar target could be recovered at a target depth of 15 mm using a 32 electrode system. PMID:17405377

Drug scheduling of cancer chemotherapy based on natural actor-critic approach.

PubMed

Ahn, Inkyung; Park, Jooyoung

2011-11-01

Recently, reinforcement learning methods have drawn significant interests in the area of artificial intelligence, and have been successfully applied to various decision-making problems. In this paper, we study the applicability of the NAC (natural actor-critic) approach, a state-of-the-art reinforcement learning method, to the drug scheduling of cancer chemotherapy for an ODE (ordinary differential equation)-based tumor growth model. ODE-based cancer dynamics modeling is an active research area, and many different mathematical models have been proposed. Among these, we use the model proposed by de Pillis and Radunskaya (2003), which considers the growth of tumor cells and their interaction with normal cells and immune cells. The NAC approach is applied to this ODE model with the goal of minimizing the tumor cell population and the drug amount while maintaining the adequate population levels of normal cells and immune cells. In the framework of the NAC approach, the drug dose is regarded as the control input, and the reward signal is defined as a function of the control input and the cell populations of tumor cells, normal cells, and immune cells. According to the control policy found by the NAC approach, effective drug scheduling in cancer chemotherapy for the considered scenarios has turned out to be close to the strategy of continuing drug injection from the beginning until an appropriate time. Also, simulation results showed that the NAC approach can yield better performance than conventional pulsed chemotherapy. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

On the Significance of Fuzzification of the N and M in Cancer Staging

PubMed Central

Yones, Sara A; Moussa, Ahmed S; Hassan, Hesham; Alieldin, Nelly H

2014-01-01

The tumor, node, metastasis (TNM) staging system has been regarded as one of the most widely used staging systems for solid cancer. The “T” is assigned a value according to the primary tumor size, whereas the “N” and “M” are dependent on the number of regional lymph nodes and the presence of distant metastasis, respectively. The current TNM model classifies stages into five crisp classes. This is unrealistic since the drastic modification in treatment that is based on a change in one class may be based on a slight shift around the class boundary. Moreover, the system considers any tumor that has distant metastasis as stage 4, disregarding the metastatic lesion concentration and size. We had handled the problem of T staging in previous studies using fuzzy logic. In this study, we focus on the fuzzification of N and M staging for more accurate and realistic modeling which may, in turn, lead to better treatment and medical decisions. PMID:25089089

Optimization of spatiotemporally fractionated radiotherapy treatments with bounds on the achievable benefit

NASA Astrophysics Data System (ADS)

Gaddy, Melissa R.; Yıldız, Sercan; Unkelbach, Jan; Papp, Dávid

2018-01-01

Spatiotemporal fractionation schemes, that is, treatments delivering different dose distributions in different fractions, can potentially lower treatment side effects without compromising tumor control. This can be achieved by hypofractionating parts of the tumor while delivering approximately uniformly fractionated doses to the surrounding tissue. Plan optimization for such treatments is based on biologically effective dose (BED); however, this leads to computationally challenging nonconvex optimization problems. Optimization methods that are in current use yield only locally optimal solutions, and it has hitherto been unclear whether these plans are close to the global optimum. We present an optimization framework to compute rigorous bounds on the maximum achievable normal tissue BED reduction for spatiotemporal plans. The approach is demonstrated on liver tumors, where the primary goal is to reduce mean liver BED without compromising any other treatment objective. The BED-based treatment plan optimization problems are formulated as quadratically constrained quadratic programming (QCQP) problems. First, a conventional, uniformly fractionated reference plan is computed using convex optimization. Then, a second, nonconvex, QCQP model is solved to local optimality to compute a spatiotemporally fractionated plan that minimizes mean liver BED, subject to the constraints that the plan is no worse than the reference plan with respect to all other planning goals. Finally, we derive a convex relaxation of the second model in the form of a semidefinite programming problem, which provides a rigorous lower bound on the lowest achievable mean liver BED. The method is presented on five cases with distinct geometries. The computed spatiotemporal plans achieve 12-35% mean liver BED reduction over the optimal uniformly fractionated plans. This reduction corresponds to 79-97% of the gap between the mean liver BED of the uniform reference plans and our lower bounds on the lowest achievable mean liver BED. The results indicate that spatiotemporal treatments can achieve substantial reductions in normal tissue dose and BED, and that local optimization techniques provide high-quality plans that are close to realizing the maximum potential normal tissue dose reduction.

Combined Parameter and State Estimation Problem in a Complex Domain: RF Hyperthermia Treatment Using Nanoparticles

NASA Astrophysics Data System (ADS)

Bermeo Varon, L. A.; Orlande, H. R. B.; Eliçabe, G. E.

2016-09-01

The particle filter methods have been widely used to solve inverse problems with sequential Bayesian inference in dynamic models, simultaneously estimating sequential state variables and fixed model parameters. This methods are an approximation of sequences of probability distributions of interest, that using a large set of random samples, with presence uncertainties in the model, measurements and parameters. In this paper the main focus is the solution combined parameters and state estimation in the radiofrequency hyperthermia with nanoparticles in a complex domain. This domain contains different tissues like muscle, pancreas, lungs, small intestine and a tumor which is loaded iron oxide nanoparticles. The results indicated that excellent agreements between estimated and exact value are obtained.

[Contrast-enhanced ultrasound in animal models].

PubMed

Paprottka, P M; Zengel, P; Ingrisch, M; Cyran, C C; Eichhorn, M; Reiser, M F; Nikolaou, K; Clevert, D-A

2011-06-01

In the past the detection of tumor perfusion was achieved solely via invasive procedures, such as intravital microscopy or with the help of costly modalities, such as multidetector computed tomography (MDCT), magnetic resonance tomography (MRT) or the combined use of positron emission tomography and computed tomography (PET/CT). Ultrasound offers the non-invasive display of organs without usage of ionizing radiation and it is widely available. However, colour-coded ultrasound and power Doppler do not allow the detection of tumor microcirculation. The introduction of contrast-enhanced ultrasound (CEUS) as well as new high-frequency ultrasound probes made it possible to detect and quantify tumor microcirculation with high resolution. CEUS has been used clinically on human beings for more than 10 years. During the last years different tumor models in experimental animals were used for the establishment of this new technique, e.g. in rats, hamsters and mice. CEUS allows the detection of functional parameters, such as the angiogenetic metabolic status of tissue pretreatment and posttreatment. Further research is required to solve the problems of absolute quantification of these perfusion parameters to allow the comparison of CEUS with other modalities (e.g. MRT and CT).

Mammalian models of chemically induced primary malignancies exploitable for imaging-based preclinical theragnostic research

PubMed Central

Liu, Yewei; Yin, Ting; Feng, Yuanbo; Cona, Marlein Miranda; Huang, Gang; Liu, Jianjun; Song, Shaoli; Jiang, Yansheng; Xia, Qian; Swinnen, Johannes V.; Bormans, Guy; Himmelreich, Uwe; Oyen, Raymond

2015-01-01

Compared with transplanted tumor models or genetically engineered cancer models, chemically induced primary malignancies in experimental animals can mimic the clinical cancer progress from the early stage on. Cancer caused by chemical carcinogens generally develops through three phases namely initiation, promotion and progression. Based on different mechanisms, chemical carcinogens can be divided into genotoxic and non-genotoxic ones, or complete and incomplete ones, usually with an organ-specific property. Chemical carcinogens can be classified upon their origins such as environmental pollutants, cooked meat derived carcinogens, N-nitroso compounds, food additives, antineoplastic agents, naturally occurring substances and synthetic carcinogens, etc. Carcinogen-induced models of primary cancers can be used to evaluate the diagnostic/therapeutic effects of candidate drugs, investigate the biological influential factors, explore preventive measures for carcinogenicity, and better understand molecular mechanisms involved in tumor initiation, promotion and progression. Among commonly adopted cancer models, chemically induced primary malignancies in mammals have several advantages including the easy procedures, fruitful tumor generation and high analogy to clinical human primary cancers. However, in addition to the time-consuming process, the major drawback of chemical carcinogenesis for translational research is the difficulty in noninvasive tumor burden assessment in small animals. Like human cancers, tumors occur unpredictably also among animals in terms of timing, location and the number of lesions. Thanks to the availability of magnetic resonance imaging (MRI) with various advantages such as ionizing-free scanning, superb soft tissue contrast, multi-parametric information, and utility of diverse contrast agents, now a workable solution to this bottleneck problem is to apply MRI for noninvasive detection, diagnosis and therapeutic monitoring on those otherwise uncontrollable animal models with primary cancers. Moreover, it is foreseeable that the combined use of chemically induced primary cancer models and molecular imaging techniques may help to develop new anticancer diagnostics and therapeutics. PMID:26682141

Sorting cancer karyotypes using double-cut-and-joins, duplications and deletions.

PubMed

Zeira, Ron; Shamir, Ron

2018-05-03

Problems of genome rearrangement are central in both evolution and cancer research. Most genome rearrangement models assume that the genome contains a single copy of each gene and the only changes in the genome are structural, i.e., reordering of segments. In contrast, tumor genomes also undergo numerical changes such as deletions and duplications, and thus the number of copies of genes varies. Dealing with unequal gene content is a very challenging task, addressed by few algorithms to date. More realistic models are needed to help trace genome evolution during tumorigenesis. Here we present a model for the evolution of genomes with multiple gene copies using the operation types double-cut-and-joins, duplications and deletions. The events supported by the model are reversals, translocations, tandem duplications, segmental deletions, and chromosomal amplifications and deletions, covering most types of structural and numerical changes observed in tumor samples. Our goal is to find a series of operations of minimum length that transform one karyotype into the other. We show that the problem is NP-hard and give an integer linear programming formulation that solves the problem exactly under some mild assumptions. We test our method on simulated genomes and on ovarian cancer genomes. Our study advances the state of the art in two ways: It allows a broader set of operations than extant models, thus being more realistic, and it is the first study attempting to reconstruct the full sequence of structural and numerical events during cancer evolution. Code and data are available in https://github.com/Shamir-Lab/Sorting-Cancer-Karyotypes. ronzeira@post.tau.ac.il, rshamir@tau.ac.il. Supplementary data are available at Bioinformatics online.

Co-registration of multi-modality imaging allows for comprehensive analysis of tumor-induced bone disease

PubMed Central

Seeley, Erin H.; Wilson, Kevin J.; Yankeelov, Thomas E.; Johnson, Rachelle W.; Gore, John C.; Caprioli, Richard M.; Matrisian, Lynn M.; Sterling, Julie A.

2014-01-01

Bone metastases are a clinically significant problem that arises in approximately 70% of metastatic breast cancer patients. Once established in bone, tumor cells induce changes in the bone microenvironment that lead to bone destruction, pain, and significant morbidity. While much is known about the later stages of bone disease, less is known about the earlier stages or the changes in protein expression in the tumor micro-environment. Due to promising results of combining magnetic resonance imaging (MRI) and Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry (MALDI IMS) ion images in the brain, we developed methods for applying these modalities to models of tumor-induced bone disease in order to better understand the changes in protein expression that occur within the tumor-bone microenvironment. Specifically, we integrated three dimensional-volume reconstructions of spatially resolved MALDI IMS with high-resolution anatomical and diffusion weighted MRI data and histology in an intratibial model of breast tumor-induced bone disease. This approach enables us to analyze proteomic profiles from MALDI IMS data with corresponding in vivo imaging and ex vivo histology data. To the best of our knowledge, this is the first time these three modalities have been rigorously registered in the bone. The MALDI mass-to-charge ratio peaks indicate differential expression of calcyclin, ubiquitin, and other proteins within the tumor cells, while peaks corresponding to hemoglobin A and calgranulin A provided molecular information that aided in the identification of areas rich in red and white blood cells, respectively. This multimodality approach will allow us to comprehensively understand the bone-tumor microenvironment and thus may allow us to better develop and test approaches for inhibiting bone metastases. PMID:24487126

Tumor Blood Vessel Dynamics

NASA Astrophysics Data System (ADS)

Munn, Lance

2009-11-01

``Normalization'' of tumor blood vessels has shown promise to improve the efficacy of chemotherapeutics. In theory, anti-angiogenic drugs targeting endothelial VEGF signaling can improve vessel network structure and function, enhancing the transport of subsequent cytotoxic drugs to cancer cells. In practice, the effects are unpredictable, with varying levels of success. The predominant effects of anti-VEGF therapies are decreased vessel leakiness (hydraulic conductivity), decreased vessel diameters and pruning of the immature vessel network. It is thought that each of these can influence perfusion of the vessel network, inducing flow in regions that were previously sluggish or stagnant. Unfortunately, when anti-VEGF therapies affect vessel structure and function, the changes are dynamic and overlapping in time, and it has been difficult to identify a consistent and predictable normalization ``window'' during which perfusion and subsequent drug delivery is optimal. This is largely due to the non-linearity in the system, and the inability to distinguish the effects of decreased vessel leakiness from those due to network structural changes in clinical trials or animal studies. We have developed a mathematical model to calculate blood flow in complex tumor networks imaged by two-photon microscopy. The model incorporates the necessary and sufficient components for addressing the problem of normalization of tumor vasculature: i) lattice-Boltzmann calculations of the full flow field within the vasculature and within the tissue, ii) diffusion and convection of soluble species such as oxygen or drugs within vessels and the tissue domain, iii) distinct and spatially-resolved vessel hydraulic conductivities and permeabilities for each species, iv) erythrocyte particles advecting in the flow and delivering oxygen with real oxygen release kinetics, v) shear stress-mediated vascular remodeling. This model, guided by multi-parameter intravital imaging of tumor vessel structure and function, provides a tool for identifying the structural and functional determinants of tumor vessel normalization.

Respiratory-gated CT as a tool for the simulation of breathing artifacts in PET and PET/CT.

PubMed

Hamill, J J; Bosmans, G; Dekker, A

2008-02-01

Respiratory motion in PET and PET/CT blurs the images and can cause attenuation-related errors in quantitative parameters such as standard uptake values. In rare instances, this problem even causes localization errors and the disappearance of tumors that should be detectable. Attenuation errors are severe near the diaphragm and can be enhanced when the attenuation correction is based on a CT series acquired during a breath-hold. To quantify the errors and identify the parameters associated with them, the authors performed a simulated PET scan based on respiratory-gated CT studies of five lung cancer patients. Diaphragmatic motion ranged from 8 to 25 mm in the five patients. The CT series were converted to 511-keV attenuation maps which were forward-projected and exponentiated to form sinograms of PET attenuation factors at each phase of respiration. The CT images were also segmented to form a PET object, moving with the same motion as the CT series. In the moving PET object, spherical 20 mm mobile tumors were created in the vicinity of the dome of the liver and immobile 20 mm tumors in the midchest region. The moving PET objects were forward-projected and attenuated, then reconstructed in several ways: phase-matched PET and CT, gated PET with ungated CT, ungated PET with gated CT, and conventional PET. Spatial resolution and statistical noise were not modeled. In each case, tumor uptake recovery factor was defined by comparing the maximum reconstructed pixel value with the known correct value. Mobile 10 and 30 mm tumors were also simulated in the case of a patient with 11 mm of breathing motion. Phase-matched gated PET and CT gave essentially perfect PET reconstructions in the simulation. Gated PET with ungated CT gave tumors of the correct shape, but recovery was too large by an amount that depended on the extent of the motion, as much as 90% for mobile tumors and 60% for immobile tumors. Gated CT with ungated PET resulted in blurred tumors and caused recovery errors between -50% and +75%. Recovery in clinical scans would be 0%-20% lower than stated because spatial resolution was not included in the simulation. Mobile tumors near the dome of the liver were subject to the largest errors in either case. Conventional PET for 20 mm tumors was quantitative in cases of motion less than 15 mm because of canceling errors in blurring and attenuation, but the recovery factors were too low by as much as 30% in cases of motion greater than 15 mm. The 10 mm tumors were blurred by motion to a greater extent, causing a greater SUV underestimation than in the case of 20 mm tumors, and the 30 mm tumors were blurred less. Quantitative PET imaging near the diaphragm requires proper matching of attenuation information to the emission information. The problem of missed tumors near the diaphragm can be reduced by acquiring attenuation-correction information near end expiration. A simple PET/CT protocol requiring no gating equipment also addresses this problem.

Radioprotective activity of glutathione on cognitive ability in X-ray radiated tumor-bearing mice.

PubMed

Lu, Lina; Li, Zongli; Zuo, Yanhua; Zhao, Libo; Liu, Bin

2018-05-30

The use of X-ray for therapeutics always raises the problem of radiation hazards to living beings. In this research, we explored the radioprotective activity of glutathione (GSH) on cognitive ability of X-ray radiated tumor-bearing mice. Forty C57BL/6 mice were chosen to establish the GL261 glioma model and randomly divided into four groups: Model group, X-ray group, Pre-GSH group and Pos-GSH group. Morris water maze test was used to test cognitive ability. Moreover, histopathological observation of hippocampus was observed by hematoxylin and eosin (HE) staining. The protein expression of choline acetyl transferase (ChAT) was measured by western blot, simultaneously the contents of acetylcholinesterase (Ach), superoxide dismutase (SOD), methane dicarboxylic aldehyde (MDA),TNF-α and IL-6 were detected by the respective kit. There was a significant difference in X-ray group of the escape latency from the Model group (P<0.05). Besides, HE staining revealed that nucleus in hippocampus cells were pyknotic, glial cells were hyperplastic and the nerve cells were swelling in X-ray group. In X-ray group the expression of ChAT and Ache were decreased versus Model group. Finally, the cognitive ability in Pre-GSH and Pos-GSH group was enhanced than X-ray group, in which the cognitive ability of Pos-GSH group was higher than the Pre-GSH group. X-ray impaired the brain tissues and cognitive ability of tumor-bearing mice. The damages of brain tissues were alleviated by Pre-GSH and Pos-GSH protection and the efficacy of Pos-GSH protection was superior to Pre-GSH protection. Abbreviation Ach: Acetylcholinesterase; GSH: Glutathione; HE: Hematoxylin and eosin; MDA: methane dicarboxylic aldehyde; SOD: Superoxide dismutase; TV: Tumor volume; TW: Tumor weight.

Adaptive treatment-length optimization in spatiobiologically integrated radiotherapy

NASA Astrophysics Data System (ADS)

Ajdari, Ali; Ghate, Archis; Kim, Minsun

2018-04-01

Recent theoretical research on spatiobiologically integrated radiotherapy has focused on optimization models that adapt fluence-maps to the evolution of tumor state, for example, cell densities, as observed in quantitative functional images acquired over the treatment course. We propose an optimization model that adapts the length of the treatment course as well as the fluence-maps to such imaged tumor state. Specifically, after observing the tumor cell densities at the beginning of a session, the treatment planner solves a group of convex optimization problems to determine an optimal number of remaining treatment sessions, and a corresponding optimal fluence-map for each of these sessions. The objective is to minimize the total number of tumor cells remaining (TNTCR) at the end of this proposed treatment course, subject to upper limits on the biologically effective dose delivered to the organs-at-risk. This fluence-map is administered in future sessions until the next image is available, and then the number of sessions and the fluence-map are re-optimized based on the latest cell density information. We demonstrate via computer simulations on five head-and-neck test cases that such adaptive treatment-length and fluence-map planning reduces the TNTCR and increases the biological effect on the tumor while employing shorter treatment courses, as compared to only adapting fluence-maps and using a pre-determined treatment course length based on one-size-fits-all guidelines.

New extracellular factors in glioblastoma multiforme development: neurotensin, growth differentiation factor-15, sphingosine-1-phosphate and cytomegalovirus infection

PubMed Central

Korbecki, Jan; Gutowska, Izabela; Kojder, Ireneusz; Jeżewski, Dariusz; Goschorska, Marta; Łukomska, Agnieszka; Lubkowska, Anna; Chlubek, Dariusz; Baranowska-Bosiacka, Irena

2018-01-01

Recent years have seen considerable progress in understanding the biochemistry of cancer. For example, more significance is now assigned to the tumor microenvironment, especially with regard to intercellular signaling in the tumor niche which depends on many factors secreted by tumor cells. In addition, great progress has been made in understanding the influence of factors such as neurotensin, growth differentiation factor-15 (GDF-15), sphingosine-1-phosphate (S1P), and infection with cytomegalovirus (CMV) on the ‘hallmarks of cancer’ in glioblastoma multiforme. Therefore, in the present work we describe the influence of these factors on the proliferation and apoptosis of neoplastic cells, cancer stem cells, angiogenesis, migration and invasion, and cancer immune evasion in a glioblastoma multiforme tumor. In particular, we discuss the effect of neurotensin, GDF-15, S1P (including the drug FTY720), and infection with CMV on tumor-associated macrophages (TAM), microglial cells, neutrophil and regulatory T cells (Treg), on the tumor microenvironment. In order to better understand the role of the aforementioned factors in tumoral processes, we outline the latest models of intratumoral heterogeneity in glioblastoma multiforme. Based on the most recent reports, we discuss the problems of multi-drug therapy in treating glioblastoma multiforme. PMID:29467963

Computerized decision support system for mass identification in breast using digital mammogram: a study on GA-based neuro-fuzzy approaches.

PubMed

Das, Arpita; Bhattacharya, Mahua

2011-01-01

In the present work, authors have developed a treatment planning system implementing genetic based neuro-fuzzy approaches for accurate analysis of shape and margin of tumor masses appearing in breast using digital mammogram. It is obvious that a complicated structure invites the problem of over learning and misclassification. In proposed methodology, genetic algorithm (GA) has been used for searching of effective input feature vectors combined with adaptive neuro-fuzzy model for final classification of different boundaries of tumor masses. The study involves 200 digitized mammograms from MIAS and other databases and has shown 86% correct classification rate.

Cognitive deficits and predictors 3 years after diagnosis of a pilocytic astrocytoma in childhood.

PubMed

Aarsen, Femke K; Paquier, Philippe F; Arts, Willem-Frans; Van Veelen, Marie-Lise; Michiels, Erna; Lequin, Maarten; Catsman-Berrevoets, Coriene E

2009-07-20

PURPOSE To prospectively study cognitive deficits and predictors 3 years after diagnosis in a large series of pediatric patients treated for pilocytic astrocytoma (PA). PATIENTS AND METHODS Sixty-one of 67 children were grouped according to infratentorial, supratentorial midline, and supratentorial hemispheric site. Intelligence, memory, attention, language, visual-spatial, and executive functions were assessed. Included predictors were sex, age, relapse, diagnosis-assessment interval, hydrocephalus, kind of treatment, and tumor variables. Results All children with PA had problems with sustained attention and speed. In the infratentorial group, there also were deficits in verbal intelligence, visual-spatial memory, executive functioning, and naming. Verbal intelligence and verbal memory problems occurred in the brainstem tumor group. The supratentorial hemispheric tumor group had additional problems with selective attention and executive functioning, and the supratentorial midline tumor group displayed no extra impairments. More specifically, the dorsal supratentorial midline tumor group displayed problems with language and verbal memory. Predictors for lower cognitive functioning were hydrocephalus, radiotherapy, residual tumor size, and age; predictors for better functioning were chemotherapy or treatment of hydrocephalus. Almost 60% of children had problems with academic achievement, for which risk factors were relapse and younger age at diagnosis. CONCLUSION Despite normal intelligence at long-term follow-up, children treated for PA display invalidating cognitive impairments. Adequate treatment of hydrocephalus is important for a more favorable long-term cognitive outcome. Even children without initial severe deficits may develop cognitive impairments years after diagnosis, partly because of the phenomenon of growing into deficit, which has devastating implications for academic achievement and quality of life (QOL).

Genetically mediated Nf1 loss in mice promotes diverse radiation-induced tumors modeling second malignant neoplasms

PubMed Central

Choi, Grace; Huang, Brian; Pinarbasi, Emile; Braunstein, Steve E.; Horvai, Andrew E.; Kogan, Scott; Bhatia, Smita; Faddegon, Bruce; Nakamura, Jean L.

2013-01-01

Second malignant neoplasms (SMNs) are therapy-induced malignancies and a growing problem in cancer survivors, particularly survivors of childhood cancers. The lack of experimental models of SMNs has limited understanding of their pathogenesis. It is currently not possible to predict or prevent this devastating late complication. Individuals with Neurofibromatosis I (NF1) are at increased risk of developing therapy-induced cancers for unclear reasons. To model SMNs, we replicated clinical radiotherapy and delivered fractionated abdominal irradiation to Nf1+/− and wildtype mice. Similar to irradiated cancer survivors, irradiated wildtype and Nf1+/− mice developed diverse in-field malignancies. In Nf1+/− mice, fractionated irradiation promoted both classical NF1-associated malignancies and malignancies unassociated with the NF1 syndrome but typical of SMNs. Nf1 heterozygosity potentiated the mutagenic effects of irradiation, as evidenced by the significantly reduced survival after irradiation and tumor development that was often characterized by synchronous primary tumors. Interestingly, diverse radiation-induced tumors arising in wildtype and Nf1+/− mice shared a genetic signature characterized by monoallelic loss of Nf1 and the adjacent Trp53 allele. These findings implicate Nf1 loss as mediating tumorigenesis in a broad range of cell types and organs extending beyond the classical NF1 tumor histologies. Examining clinical SMN samples, we found LOH of NF1 in SMNs from non-NF1 patients. Nf1 heterozygosity confers broad susceptibility to genotoxin-induced tumorigenesis and this paradigm serves as an experimental platform for future studies of SMNs. PMID:23071067

Glycosylated Triterpenoids as Endosomal Escape Enhancers in Targeted Tumor Therapies

PubMed Central

Fuchs, Hendrik; Niesler, Nicole; Trautner, Alexandra; Sama, Simko; Jerz, Gerold; Panjideh, Hossein; Weng, Alexander

2017-01-01

Protein-based targeted toxins play an increasingly important role in targeted tumor therapies. In spite of their high intrinsic toxicity, their efficacy in animal models is low. A major reason for this is the limited entry of the toxin into the cytosol of the target cell, which is required to mediate the fatal effect. Target receptor bound and internalized toxins are mostly either recycled back to the cell surface or lysosomally degraded. This might explain why no antibody-targeted protein toxin has been approved for tumor therapeutic applications by the authorities to date although more than 500 targeted toxins have been developed within the last decades. To overcome the problem of insufficient endosomal escape, a number of strategies that make use of diverse chemicals, cell-penetrating or fusogenic peptides, and light-induced techniques were designed to weaken the membrane integrity of endosomes. This review focuses on glycosylated triterpenoids as endosomal escape enhancers and throws light on their structure, the mechanism of action, and on their efficacy in cell culture and animal models. Obstacles, challenges, opportunities, and future prospects are discussed. PMID:28536357

Health-related quality of life and emotional problems in children surviving brain tumor treatment: A descriptive study of 2 cohorts.

PubMed

Dessens, Arianne B; van Herwerden, Michael C; Aarsen, Femke K; Birnie, Erwin; Catsman-Berrevoets, Coriene E

2016-08-01

The survival of childhood brain tumors has improved in the past 30 years, but acquired brain injury due to damage caused by tumor invasion and side effects of different treatment modalities frequently occurs. This study focused on residual impairments, health-related quality of life (HRQoL), and emotional and behavioral problems in 2 cohorts of survivors diagnosed and treated for various types of brain tumors. Survivors in the 2004 cohort visited the Erasmus Medical Centre for standardized follow-up between 2003 and 2004, and in the 2014 cohort, between 2012 and 2014. Data of neurologically impairments of all children were extracted from medical records. Parents and survivors filled out questionnaires on quality of life and emotional and behavioral problems. In both cohorts, approximately 55% of the survivors displayed neurologic impairments. In comparison with the healthy reference group, a reduced parent-reported quality of life was found on the Motor, Cognition, and Autonomy (Cohort 2004) scales. Comparison between the cohorts showed that parents in the 2004 cohort reported a higher HRQoL on the Motor and Cognitive functioning scales. In the 2014 cohort, children reported less negative emotions than healthy children. No increase in emotional or behavioral problems were reported by children in both cohorts, whereas parents reported problems in social functioning and isolation related to a delay in emotional development. Children surviving brain tumor treatment have a reduced quality of life. The authors therefore recommend regular screening of HRQoL and emotional and behavioral problems and referral to specific aftercare.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sugano, Yasutaka; Mizuta, Masahiro; Takao, Seishin

Purpose: Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose–volume histograms for tumor and normal tissues of organs around the tumor. Methods: Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of themore » tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose–volume histogram. Results: It was found that the optimization of fractionation scheme incorporating the dose–volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8–32 fractions with a daily dose of 2.2–6.3 Gy. Conclusions: It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose–volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation.« less

Navigated Breast Tumor Excision Using Electromagnetically Tracked Ultrasound and Surgical Instruments.

PubMed

Ungi, Tamas; Gauvin, Gabrielle; Lasso, Andras; Yeo, Caitlin T; Pezeshki, Padina; Vaughan, Thomas; Carter, Kaci; Rudan, John; Engel, C Jay; Fichtinger, Gabor

2016-03-01

Lumpectomy, breast conserving tumor excision, is the standard surgical treatment in early stage breast cancer. A common problem with lumpectomy is that the tumor may not be completely excised, and additional surgery becomes necessary. We investigated if a surgical navigation system using intraoperative ultrasound improves the outcomes of lumpectomy and if such a system can be implemented in the clinical environment. Position sensors were applied on the tumor localization needle, the ultrasound probe, and the cautery, and 3-D navigation views were generated using real-time tracking information. The system was tested against standard wire-localization procedures on phantom breast models by eight surgical residents. Clinical safety and feasibility was tested in six palpable tumor patients undergoing lumpectomy by two experienced surgical oncologists. Navigation resulted in significantly less tissue excised compared to control procedures (10.3 ± 4.4 versus 18.6 ± 8.7 g, p = 0.01) and lower number of tumor-positive margins (1/8 versus 4/8) in the phantom experiments. Excision-tumor distance was also more consistently outside the tumor margins with navigation in phantoms. The navigation system has been successfully integrated in an operating room, and user experience was rated positively by surgical oncologists. Electromagnetic navigation may improve the outcomes of lumpectomy by making the tumor excision more accurate. Breast cancer is the most common cancer in women, and lumpectomy is its first choice treatment. Therefore, the improvement of lumpectomy outcomes has a significant impact on a large patient population.

Control of a HexaPOD treatment couch for robot-assisted radiotherapy.

PubMed

Hermann, Christian; Ma, Lei; Wilbert, Jürgen; Baier, Kurt; Schilling, Klaus

2012-10-01

Moving tumors, for example in the vicinity of the lungs, pose a challenging problem in radiotherapy, as healthy tissue should not be irradiated. Apart from gating approaches, one standard method is to irradiate the complete volume within which a tumor moves plus a safety margin containing a considerable volume of healthy tissue. This work deals with a system for tumor motion compensation using the HexaPOD® robotic treatment couch (Medical Intelligence GmbH, Schwabmünchen, Germany). The HexaPOD, carrying the patient during treatment, is instructed to perform translational movements such that the tumor motion, from the beams-eye view of the linear accelerator, is eliminated. The dynamics of the HexaPOD are characterized by time delays, saturations, and other non-linearities that make the design of control a challenging task. The focus of this work lies on two control methods for the HexaPOD that can be used for reference tracking. The first method uses a model predictive controller based on a model gained through system identification methods, and the second method uses a position control scheme useful for reference tracking. We compared the tracking performance of both methods in various experiments with real hardware using ideal reference trajectories, prerecorded patient trajectories, and human volunteers whose breathing motion was compensated by the system.

Optimal Down Regulation of mRNA Translation

NASA Astrophysics Data System (ADS)

Zarai, Yoram; Margaliot, Michael; Tuller, Tamir

2017-01-01

Down regulation of mRNA translation is an important problem in various bio-medical domains ranging from developing effective medicines for tumors and for viral diseases to developing attenuated virus strains that can be used for vaccination. Here, we study the problem of down regulation of mRNA translation using a mathematical model called the ribosome flow model (RFM). In the RFM, the mRNA molecule is modeled as a chain of n sites. The flow of ribosomes between consecutive sites is regulated by n + 1 transition rates. Given a set of feasible transition rates, that models the outcome of all possible mutations, we consider the problem of maximally down regulating protein production by altering the rates within this set of feasible rates. Under certain conditions on the feasible set, we show that an optimal solution can be determined efficiently. We also rigorously analyze two special cases of the down regulation optimization problem. Our results suggest that one must focus on the position along the mRNA molecule where the transition rate has the strongest effect on the protein production rate. However, this rate is not necessarily the slowest transition rate along the mRNA molecule. We discuss some of the biological implications of these results.

The Effects of Attention Problems on Psychosocial Functioning in Childhood Brain Tumor Survivors: A 2-Year Postcraniospinal Irradiation Follow-up.

PubMed

Oh, Yunhye; Seo, Hyunjung; Sung, Ki Woong; Joung, Yoo Sook

2017-03-01

To examine the psychosocial outcomes and impact of attention problems in survivors of pediatric brain tumor. The survivors' cognitive functioning was measured using the Wechsler Intelligence Scale for Children. The Child Behavior Checklist-Attention Problems scale was used to screen for attention problems, and participants were classified as having attention problems (n=15) or normal attention (n=36). Psychosocial functioning was examined with the Korean Personality Rating scale for Children (K-PRC) at precraniospinal radiation and at 2-year follow-up. The attention problem group showed significantly higher depression and externalizing symptoms (delinquency, hyperactivity) and more significant impairment in family relationships than did the normal attention group at baseline. At follow-up, the attention problem group demonstrated significantly more delinquency and impaired family and social relationships. With the K-PRC scores, except for the somatization, social relationship subscale, there were significant differences between groups, but not in terms of treatment by time interaction or within time. At follow-up, multiple linear regressions showed that age at diagnosis significantly predicted K-PRC somatization (B=-1.7, P=0.004) and social relationships (B=-1.7, P=0.004), baseline full-scale intelligence quotient predicted K-PRC depression (B=-0.4, P=0.032) and somatization (B=-0.3, P=0.015), and attention problems at baseline predicted K-PRC depression (B=-15.2, P=0.036) and social relationships (B=-11.6, P=0.016). Pediatric brain tumor survivors, in particular, patients with attention problems, had worse psychosocial functioning at baseline and follow-up. Attention problems at baseline need to be carefully evaluated in assessing psychosocial functioning of pediatric brain tumor survivors.

Optimization of targeted two-photon PDT triads for the treatment of head and neck cancers

NASA Astrophysics Data System (ADS)

Spangler, Charles W.; Starkey, Jean R.; Dubinina, Galyna; Fahlstrom, Carl; Shepard, Joyce

2012-02-01

Synthesis of new PDT triads that incorporate a tumor-killing porphyrin with large two-photon cross-section for 150 fs laser pulses (2000 GM) in the Near-infrared (NIR) at 840 nm, a NIR imaging agent, and a small peptide that targets over-expressed EGF receptors on the tumor surface. This triad formulation has been optimized over the past year to treat FADU Head and Neck SCC xenograft tumors in SCID mice. Effective PDT triad dose (1-10 mg/Kg) and laser operating parameters (840 nm, 15-45 min, 900 mW) have been established. Light, dark and PDT treatment toxicities were determined, showing no adverse effects. Previous experiments in phantom and mouse models indicate that tumors can be treated directly through the skin to effective depths between 2 and 5 cm. Treated mice demonstrated rapid tumor regression with some complete cures in as little as 15-20 days. No adverse effects were observed in any healthy tissue through which the focused laser beam passed before reaching the tumor site, and excellent healing occurred post treatment including rapid hair re-growth. Not all irradiation protocols lead to complete cures. Since two-photon PDT is carried out by rastering focused irradiation throughout the tumor, there is the possibility that as the treatment depth increases, some parts of the tumor may escape irradiation due to increased scattering, thus raising the possibility that tumor re-growth could be triggered by small islands of untreated cells, especially at the rapidly growing tumor margins, a problem we hope to alleviate by using image-guided two-photon PDT.

By inhibiting PFKFB3, aspirin overcomes sorafenib resistance in hepatocellular carcinoma.

PubMed

Li, Sainan; Dai, Weiqi; Mo, Wenhui; Li, Jingjing; Feng, Jiao; Wu, Liwei; Liu, Tong; Yu, Qiang; Xu, Shizan; Wang, Wenwen; Lu, Xiya; Zhang, Qinghui; Chen, Kan; Xia, Yujing; Lu, Jie; Zhou, Yingqun; Fan, Xiaoming; Xu, Ling; Guo, Chuanyong

2017-12-15

Hepatocellular carcinoma (HCC) is one of the few cancers with a continuous increase in incidence and mortality. Drug resistance is a major problem in the treatment of HCC. In this study, two sorafenib-resistant HCC cell lines and a nude mouse subcutaneously tumor model were used to explore the possible mechanisms leading to sorafenib resistance, and to investigate whether aspirin could increase the sensitivity of hepatoma cells to sorafenib. The combination of aspirin and sorafenib resulted in a synergistic antitumor effect against liver tumors both in vitro and in vivo. High glycolysis and PFKFB3 overexpression occupied a dominant position in sorafenib resistance, and can be targeted and overcome by aspirin. Aspirin plus sorafenib induced apoptosis in tumors without inducing weight loss, hepatotoxicity or inflammation. Our results suggest that aspirin overcomes sorafenib resistance and their combination may be an effective treatment approach for HCC. © 2017 UICC.

Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy

NASA Astrophysics Data System (ADS)

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2012-12-01

Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients.

Antitumor effect of combination of the inhibitors of two new oncotargets: proton pumps and reverse transcriptase.

PubMed

Lugini, Luana; Sciamanna, Ilaria; Federici, Cristina; Iessi, Elisabetta; Spugnini, Enrico Pierluigi; Fais, Stefano

2017-01-17

Tumor therapy needs new approaches in order to improve efficacy and reduce toxicity of the current treatments. The acidic microenvironment and the expression of high levels of endogenous non-telomerase reverse transcriptase (RT) are common features of malignant tumor cells. The anti-acidic proton pump inhibitor Lansoprazole (LAN) and the non-nucleoside RT inhibitor Efavirenz (EFV) have shown independent antitumor efficacy. LAN has shown to counteract drug tumor resistance. We tested the hypothesis that combination of LAN and EFV may improve the overall antitumor effects. We thus pretreated human metastatic melanoma cells with LAN and then with EFV, both in 2D and 3D spheroid models. We evaluated the treatment effect by proliferation and cell death/apoptosis assays in classical and in pulse administration experiments. The action of EFV was negatively affected by the tumor microenvironmental acidity, and LAN pretreatment overcame the problem. LAN potentiated the cytotoxicity of EFV to melanoma cells and, when administered during the drug interruption period, prevented the replacement of tumor cell growth.This study supports the implementation of the current therapies with combination of Proton Pumps and Reverse Transcriptase inhibitors.

Antitumor effect of combination of the inhibitors of two new oncotargets: proton pumps and reverse transcriptase

PubMed Central

Lugini, Luana; Sciamanna, Ilaria; Federici, Cristina; Iessi, Elisabetta; Spugnini, Enrico Pierluigi; Fais, Stefano

2017-01-01

Tumor therapy needs new approaches in order to improve efficacy and reduce toxicity of the current treatments. The acidic microenvironment and the expression of high levels of endogenous non-telomerase reverse transcriptase (RT) are common features of malignant tumor cells. The anti-acidic proton pump inhibitor Lansoprazole (LAN) and the non-nucleoside RT inhibitor Efavirenz (EFV) have shown independent antitumor efficacy. LAN has shown to counteract drug tumor resistance. We tested the hypothesis that combination of LAN and EFV may improve the overall antitumor effects. We thus pretreated human metastatic melanoma cells with LAN and then with EFV, both in 2D and 3D spheroid models. We evaluated the treatment effect by proliferation and cell death/apoptosis assays in classical and in pulse administration experiments. The action of EFV was negatively affected by the tumor microenvironmental acidity, and LAN pretreatment overcame the problem. LAN potentiated the cytotoxicity of EFV to melanoma cells and, when administered during the drug interruption period, prevented the replacement of tumor cell growth. This study supports the implementation of the current therapies with combination of Proton Pumps and Reverse Transcriptase inhibitors. PMID:27926505

Models of breast cancer growth and investigations of adjuvant surgical oophorectomy.

PubMed

Love, Richard R; Niederhuber, John E

2004-09-01

Clinical observations of the natural history of breast cancer and its response to a variety of therapeutic interventions have contributed to changing concepts about the growth and metastatic spread of this disease. Increased attention has been given to tumor cell dormancy and the occurrence of greatly delayed metastatic disease development, which has been important to rethinking therapy. Although gene profiling of breast tumors recently has highlighted the importance of individual tumor characteristics in patients' prognosis, considerable data also support the concept of breast cancer as a problem of macro- and microenvironmental regulatory imbalance and dynamic chaos. Observations of unexpectedly large survival benefits from adjuvant surgical oophorectomy done in the luteal phase of the menstrual cycle in premenopausal women are consistent with an interpretation that extratumoral interactions in the host environment are important in prognosis. These observations also suggest that a treatment paradigm shift from an exclusive focus on cell kill and specific tumor cell molecular targets to one focused also on broad host regulatory control may be useful. Clinical trials and laboratory mechanistic investigations based on these data and observations can determine the potential impact of therapeutic interventions targeting host system macro and micro tumor cell environments.

[Outstanding problems of normal and pathological morphology of the diffuse endocrine system].

PubMed

Iaglov, V V; Iaglova, N V

2011-01-01

The diffuse endocrine system (DES)--a mosaic-cellular endoepithelial gland--is the biggest part of the human endocrine system. Scientists used to consider cells of DES as neuroectodermal. According to modem data cells of DES are different cytogenetic types because they develop from the different embryonic blastophyllum. So that any hormone-active tumors originated from DES of the digestive, respiratory and urogenital system shouldn't be considered as neuroendocrinal tumors. The basic problems of DES morphology and pathology are the creation of scientifically substantiated histogenetic classification of DES tumors.

Ovarian Tumor-Stroma Interactions in an In Vivo Orthotopic Model

DTIC Science & Technology

2011-08-01

cancer cells to the novel environment. We have devised an Intravital Video Microscopy approach to this problem in which MOVCAR cells labeled with green...Ovarian cancer, gene expression, metastasis, intravital video microscopy 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER...placed in a dorsal skin-fold chamber for Intravital Video Microscopy (IVM). The minced pseudo-organ tissue revascularizes and recapitulates some of the

Phylogenetic Copy-Number Factorization of Multiple Tumor Samples.

PubMed

Zaccaria, Simone; El-Kebir, Mohammed; Klau, Gunnar W; Raphael, Benjamin J

2018-04-16

Cancer is an evolutionary process driven by somatic mutations. This process can be represented as a phylogenetic tree. Constructing such a phylogenetic tree from genome sequencing data is a challenging task due to the many types of mutations in cancer and the fact that nearly all cancer sequencing is of a bulk tumor, measuring a superposition of somatic mutations present in different cells. We study the problem of reconstructing tumor phylogenies from copy-number aberrations (CNAs) measured in bulk-sequencing data. We introduce the Copy-Number Tree Mixture Deconvolution (CNTMD) problem, which aims to find the phylogenetic tree with the fewest number of CNAs that explain the copy-number data from multiple samples of a tumor. We design an algorithm for solving the CNTMD problem and apply the algorithm to both simulated and real data. On simulated data, we find that our algorithm outperforms existing approaches that either perform deconvolution/factorization of mixed tumor samples or build phylogenetic trees assuming homogeneous tumor samples. On real data, we analyze multiple samples from a prostate cancer patient, identifying clones within these samples and a phylogenetic tree that relates these clones and their differing proportions across samples. This phylogenetic tree provides a higher resolution view of copy-number evolution of this cancer than published analyses.

Patient-specific semi-supervised learning for postoperative brain tumor segmentation.

PubMed

Meier, Raphael; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2014-01-01

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

a Novel Approach to Veterinary Spatial Epidemiology: Dasymetric Refinement of the Swiss Dog Tumor Registry Data

NASA Astrophysics Data System (ADS)

Boo, G.; Fabrikant, S. I.; Leyk, S.

2015-08-01

In spatial epidemiology, disease incidence and demographic data are commonly summarized within larger regions such as administrative units because of privacy concerns. As a consequence, analyses using these aggregated data are subject to the Modifiable Areal Unit Problem (MAUP) as the geographical manifestation of ecological fallacy. In this study, we create small area disease estimates through dasymetric refinement, and investigate the effects on predictive epidemiological models. We perform a binary dasymetric refinement of municipality-aggregated dog tumor incidence counts in Switzerland for the year 2008 using residential land as a limiting ancillary variable. This refinement is expected to improve the quality of spatial data originally aggregated within arbitrary administrative units by deconstructing them into discontinuous subregions that better reflect the underlying population distribution. To shed light on effects of this refinement, we compare a predictive statistical model that uses unrefined administrative units with one that uses dasymetrically refined spatial units. Model diagnostics and spatial distributions of model residuals are assessed to evaluate the model performances in different regions. In particular, we explore changes in the spatial autocorrelation of the model residuals due to spatial refinement of the enumeration units in a selected mountainous region, where the rugged topography induces great shifts of the analytical units i.e., residential land. Such spatial data quality refinement results in a more realistic estimation of the population distribution within administrative units, and thus, in a more accurate modeling of dog tumor incidence patterns. Our results emphasize the benefits of implementing a dasymetric modeling framework in veterinary spatial epidemiology.

Tuberous Sclerosis

MedlinePlus

... on where the tumors grow. They could include Skin problems, such as light patches and thickened skin Seizures Behavior problems Intellectual disabilities Kidney problems Some people have signs ...

TU-AB-202-11: Tumor Segmentation by Fusion of Multi-Tracer PET Images Using Copula Based Statistical Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lapuyade-Lahorgue, J; Ruan, S; Li, H

Purpose: Multi-tracer PET imaging is getting more attention in radiotherapy by providing additional tumor volume information such as glucose and oxygenation. However, automatic PET-based tumor segmentation is still a very challenging problem. We propose a statistical fusion approach to joint segment the sub-area of tumors from the two tracers FDG and FMISO PET images. Methods: Non-standardized Gamma distributions are convenient to model intensity distributions in PET. As a serious correlation exists in multi-tracer PET images, we proposed a new fusion method based on copula which is capable to represent dependency between different tracers. The Hidden Markov Field (HMF) model ismore » used to represent spatial relationship between PET image voxels and statistical dynamics of intensities for each modality. Real PET images of five patients with FDG and FMISO are used to evaluate quantitatively and qualitatively our method. A comparison between individual and multi-tracer segmentations was conducted to show advantages of the proposed fusion method. Results: The segmentation results show that fusion with Gaussian copula can receive high Dice coefficient of 0.84 compared to that of 0.54 and 0.3 of monomodal segmentation results based on individual segmentation of FDG and FMISO PET images. In addition, high correlation coefficients (0.75 to 0.91) for the Gaussian copula for all five testing patients indicates the dependency between tumor regions in the multi-tracer PET images. Conclusion: This study shows that using multi-tracer PET imaging can efficiently improve the segmentation of tumor region where hypoxia and glucidic consumption are present at the same time. Introduction of copulas for modeling the dependency between two tracers can simultaneously take into account information from both tracers and deal with two pathological phenomena. Future work will be to consider other families of copula such as spherical and archimedian copulas, and to eliminate partial volume effect by considering dependency between neighboring voxels.« less

A Reexamination of Active and Passive Tumor Targeting by Using Rod-Shaped Gold Nanocrystals and Covalently Conjugated Peptide Ligands

PubMed Central

Huang, Xiaohua; Peng, Xianghong; Wang, Yiqing; Wang, Yuxiang; Shin, Dong M.; El-Sayed, Mostafa A.; Nie, Shuming

2010-01-01

The targeted delivery of nanoparticles to solid tumors is one of the most important and challenging problems in cancer nanomedicine, but the detailed delivery mechanisms and design principles are still not well understood. Here we report quantitative tumor uptake studies for a class of elongated gold nanocrystals (called nanorods) that are covalently conjugated to tumor-targeting peptides. A major advantage in using gold as a “tracer” is that the accumulated gold in tumors and other organs can be quantitatively determined by elemental mass spectrometry (gold is not a natural element found in animals). Thus, colloidal gold nanorods are stabilized with a layer of polyethylene glycols (PEGs), and are conjugated to three different ligands: (i) a single-chain variable fragment (ScFv) peptide that recognizes the epidermal growth factor receptor (EGFR); (ii) an amino terminal fragment (ATF) peptide that recognizes the urokinase plasminogen activator receptor (uPAR); and (iii) a cyclic RGD peptide that recognizes the avb3 integrin receptor. Quantitative pharmacokinetic and biodistribution data show that these targeting ligands only marginally improve the total gold accumulation in xenograft tumor models in comparison with nontargeted controls, but their use could greatly alter the intracellular and extracellular nanoparticle distributions. When the gold nanorods are administered via intravenous injection, we also find that active molecular targeting of the tumor microenvironments (e.g., fibroblasts, macrophages, and vasculatures) does not significantly influence the tumor nanoparticle uptake. These results suggest that for photothermal cancer therapy, the preferred route of gold nanorod administration is intra-tumoral injection instead of intravenous injection. PMID:20863096

Laser dosimetry planning tool for colonoscopic tumor resection

NASA Astrophysics Data System (ADS)

Pelayo-Fernández, M. L.; Fanjul-Vélez, F.; Salas-García, I.; Zverev, M.; Arce-Diego, J. L.

2016-03-01

Gastrointestinal tumoral pathologies are quite common nowadays. Diseases such as gastric antral vascular ectasia (GAVE) or actinic proctitis may require endoscopic surgery. Argon Plasma Coagulated (APC) or radiofrequency are usually employed. However, they present disadvantages, such as the reduced treated area, magnetic resonance incompatibility, or an uncontrolled ablation depth. Optical surgery could avoid these problems and contribute to a better and controlled treatment result, either ablative or coagulative, in a minimally invasive, non-contact and non-ionizing way. The treatment area could also be increased by adequate optical fiber probe design. In this work laser surgery is analyzed for resection of colonic tumors. A Monte Carlo model is employed to study optical propagation, and an optical ablation approach allows the estimation of the resected volume. The ablation approach is based on plasma-induced ablation, particularly taking into account the freeelectron density generated in the tissue by the pulsed optical source. Several wavelengths, radii and malignant tissue types are considered, either healthy, adenomatous or even coagulated tissues. Optimum source parameters as a function of tumor geometry can be estimated for treatment planning.

NKTR-102 Efficacy versus irinotecan in a mouse model of brain metastases of breast cancer.

PubMed

Adkins, Chris E; Nounou, Mohamed I; Hye, Tanvirul; Mohammad, Afroz S; Terrell-Hall, Tori; Mohan, Neel K; Eldon, Michael A; Hoch, Ute; Lockman, Paul R

2015-10-13

Brain metastases are an increasing problem in women with invasive breast cancer. Strategies designed to treat brain metastases of breast cancer, particularly chemotherapeutics such as irinotecan, demonstrate limited efficacy. Conventional irinotecan distributes poorly to brain metastases; therefore, NKTR-102, a PEGylated irinotecan conjugate should enhance irinotecan and its active metabolite SN38 exposure in brain metastases leading to brain tumor cytotoxicity. Female nude mice were intracranially or intracardially implanted with human brain seeking breast cancer cells (MDA-MB-231Br) and dosed with irinotecan or NKTR-102 to determine plasma and tumor pharmacokinetics of irinotecan and SN38. Tumor burden and survival were evaluated in mice treated with vehicle, irinotecan (50 mg/kg), or NKTR-102 low and high doses (10 mg/kg, 50 mg/kg respectively). NKTR-102 penetrates the blood-tumor barrier and distributes to brain metastases. NKTR-102 increased and prolonged SN38 exposure (>20 ng/g for 168 h) versus conventional irinotecan (>1 ng/g for 4 h). Treatment with NKTR-102 extended survival time (from 35 days to 74 days) and increased overall survival for NKTR-102 low dose (30 % mice) and NKTR-102 high dose (50 % mice). Tumor burden decreased (37 % with 10 mg/kg NKTR-102 and 96 % with 50 mg/kg) and lesion sizes decreased (33 % with 10 mg/kg NKTR-102 and 83 % with 50 mg/kg NKTR-102) compared to conventional irinotecan treated animals. Elevated and prolonged tumor SN38 exposure after NKTR-102 administration appears responsible for increased survival in this model of breast cancer brain metastasis. Further, SN38 concentrations observed in this study are clinically achieved with 145 mg/m(2) NKTR-102, such as those used in the BEACON trial, underlining translational relevance of these results.

A decision aid for intensity-modulated radiation-therapy plan selection in prostate cancer based on a prognostic Bayesian network and a Markov model.

PubMed

Smith, Wade P; Doctor, Jason; Meyer, Jürgen; Kalet, Ira J; Phillips, Mark H

2009-06-01

The prognosis of cancer patients treated with intensity-modulated radiation-therapy (IMRT) is inherently uncertain, depends on many decision variables, and requires that a physician balance competing objectives: maximum tumor control with minimal treatment complications. In order to better deal with the complex and multiple objective nature of the problem we have combined a prognostic probabilistic model with multi-attribute decision theory which incorporates patient preferences for outcomes. The response to IMRT for prostate cancer was modeled. A Bayesian network was used for prognosis for each treatment plan. Prognoses included predicting local tumor control, regional spread, distant metastases, and normal tissue complications resulting from treatment. A Markov model was constructed and used to calculate a quality-adjusted life-expectancy which aids in the multi-attribute decision process. Our method makes explicit the tradeoffs patients face between quality and quantity of life. This approach has advantages over current approaches because with our approach risks of health outcomes and patient preferences determine treatment decisions.

[The Polish physicians's impressions from the First Otolaryngological International Congress in Copenhagen].

PubMed

Kierzek, Andrzej

2007-01-01

The problem of meetings and congresses of otologists and laryngologists from 1876 till 1928 is described widely. The First International Congress of Otorhinolaryngologists was performed in 1928 in Copenhagen. It was a unique meeting with numerous magnificent social entertainments with participation of several hundred physicians. The chief of editorial committee was Karl Schmigielow (1856-). The programmatic subject matters: the problems of otitis media, the problems of aural operations, the problems of postinflammatory complications of ear with intracranial complications, the problems of sinusitis, the septic complications of pharyngeal origin, the use of diathermy in treatment of tumors in E.N.T., the problems of malignant neoplasms of larynx, the problems of scleroma of upper respiratory tract, the problems of brain tumors were discussed with full particular. The labyrinthical report of Bronislaw B. Karbowski was well-disposed accepted.

Effect of elemental compositions on Monte Carlo dose calculations in proton therapy of eye tumors

NASA Astrophysics Data System (ADS)

Rasouli, Fatemeh S.; Farhad Masoudi, S.; Keshazare, Shiva; Jette, David

2015-12-01

Recent studies in eye plaque brachytherapy have found considerable differences between the dosimetric results by using a water phantom, and a complete human eye model. Since the eye continues to be simulated as water-equivalent tissue in the proton therapy literature, a similar study for investigating such a difference in treating eye tumors by protons is indispensable. The present study inquires into this effect in proton therapy utilizing Monte Carlo simulations. A three-dimensional eye model with elemental compositions is simulated and used to examine the dose deposition to the phantom. The beam is planned to pass through a designed beam line to moderate the protons to the desired energies for ocular treatments. The results are compared with similar irradiation to a water phantom, as well as to a material with uniform density throughout the whole volume. Spread-out Bragg peaks (SOBPs) are created by adding pristine peaks to cover a typical tumor volume. Moreover, the corresponding beam parameters recommended by the ICRU are calculated, and the isodose curves are computed. The results show that the maximum dose deposited in ocular media is approximately 5-7% more than in the water phantom, and about 1-1.5% less than in the homogenized material of density 1.05 g cm-3. Furthermore, there is about a 0.2 mm shift in the Bragg peak due to the tissue composition difference between the models. It is found that using the weighted dose profiles optimized in a water phantom for the realistic eye model leads to a small disturbance of the SOBP plateau dose. In spite of the plaque brachytherapy results for treatment of eye tumors, it is found that the differences between the simplified models presented in this work, especially the phantom containing the homogenized material, are not clinically significant in proton therapy. Taking into account the intrinsic uncertainty of the patient dose calculation for protons, and practical problems corresponding to applying patient-specific eye modeling, we found that the results of using a generic phantom containing homogenized material for proton therapy of eye tumors can be satisfactory for designing the beam.

Mathematical models of cytotoxic effects in endpoint tumor cell line assays: critical assessment of the application of a single parametric value as a standard criterion to quantify the dose-response effects and new unexplored proposal formats.

PubMed

Calhelha, Ricardo C; Martínez, Mireia A; Prieto, M A; Ferreira, Isabel C F R

2017-10-23

The development of convenient tools for describing and quantifying the effects of standard and novel therapeutic agents is essential for the research community, to perform more precise evaluations. Although mathematical models and quantification criteria have been exchanged in the last decade between different fields of study, there are relevant methodologies that lack proper mathematical descriptions and standard criteria to quantify their responses. Therefore, part of the relevant information that can be drawn from the experimental results obtained and the quantification of its statistical reliability are lost. Despite its relevance, there is not a standard form for the in vitro endpoint tumor cell lines' assays (TCLA) that enables the evaluation of the cytotoxic dose-response effects of anti-tumor drugs. The analysis of all the specific problems associated with the diverse nature of the available TCLA used is unfeasible. However, since most TCLA share the main objectives and similar operative requirements, we have chosen the sulforhodamine B (SRB) colorimetric assay for cytotoxicity screening of tumor cell lines as an experimental case study. In this work, the common biological and practical non-linear dose-response mathematical models are tested against experimental data and, following several statistical analyses, the model based on the Weibull distribution was confirmed as the convenient approximation to test the cytotoxic effectiveness of anti-tumor compounds. Then, the advantages and disadvantages of all the different parametric criteria derived from the model, which enable the quantification of the dose-response drug-effects, are extensively discussed. Therefore, model and standard criteria for easily performing the comparisons between different compounds are established. The advantages include a simple application, provision of parametric estimations that characterize the response as standard criteria, economization of experimental effort and enabling rigorous comparisons among the effects of different compounds and experimental approaches. In all experimental data fitted, the calculated parameters were always statistically significant, the equations proved to be consistent and the correlation coefficient of determination was, in most of the cases, higher than 0.98.

Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

PubMed

Prastawa, Marcel; Bullitt, Elizabeth; Gerig, Guido

2009-04-01

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).

Bayesian Multiscale Modeling of Closed Curves in Point Clouds

PubMed Central

Gu, Kelvin; Pati, Debdeep; Dunson, David B.

2014-01-01

Modeling object boundaries based on image or point cloud data is frequently necessary in medical and scientific applications ranging from detecting tumor contours for targeted radiation therapy, to the classification of organisms based on their structural information. In low-contrast images or sparse and noisy point clouds, there is often insufficient data to recover local segments of the boundary in isolation. Thus, it becomes critical to model the entire boundary in the form of a closed curve. To achieve this, we develop a Bayesian hierarchical model that expresses highly diverse 2D objects in the form of closed curves. The model is based on a novel multiscale deformation process. By relating multiple objects through a hierarchical formulation, we can successfully recover missing boundaries by borrowing structural information from similar objects at the appropriate scale. Furthermore, the model’s latent parameters help interpret the population, indicating dimensions of significant structural variability and also specifying a ‘central curve’ that summarizes the collection. Theoretical properties of our prior are studied in specific cases and efficient Markov chain Monte Carlo methods are developed, evaluated through simulation examples and applied to panorex teeth images for modeling teeth contours and also to a brain tumor contour detection problem. PMID:25544786

Performance characteristics of a visual-search human-model observer with sparse PET image data

NASA Astrophysics Data System (ADS)

Gifford, Howard C.

2012-02-01

As predictors of human performance in detection-localization tasks, statistical model observers can have problems with tasks that are primarily limited by target contrast or structural noise. Model observers with a visual-search (VS) framework may provide a more reliable alternative. This framework provides for an initial holistic search that identifies suspicious locations for analysis by a statistical observer. A basic VS observer for emission tomography focuses on hot "blobs" in an image and uses a channelized nonprewhitening (CNPW) observer for analysis. In [1], we investigated this model for a contrast-limited task with SPECT images; herein, a statisticalnoise limited task involving PET images is considered. An LROC study used 2D image slices with liver, lung and soft-tissue tumors. Human and model observers read the images in coronal, sagittal and transverse display formats. The study thus measured the detectability of tumors in a given organ as a function of display format. The model observers were applied under several task variants that tested their response to structural noise both at the organ boundaries alone and over the organs as a whole. As measured by correlation with the human data, the VS observer outperformed the CNPW scanning observer.

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

PubMed Central

Galván-Tejada, Carlos E.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.

2017-01-01

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions. PMID:28216571

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

PubMed

Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

2017-02-14

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

Discovery of cryptophycin-1 and BCN-183577: examples of strategies and problems in the detection of antitumor activity in mice.

PubMed

Corbett, T H; Valeriote, F A; Demchik, L; Lowichik, N; Polin, L; Panchapor, C; Pugh, S; White, K; Kushner, J; Rake, J; Wentland, M; Golakoti, T; Hetzel, C; Ogino, J; Patterson, G; Moore, R

1997-01-01

Historically, many new anticancer agents were first detected in a prescreen; usually consisting of a molecular/biochemical target or a cellular cytotoxicity assay. The agent then progressed to in vivo evaluation against transplanted human or mouse tumors. If the investigator had a large drug supply and ample resources, multiple tests were possible, with variations in tumor models, tumor and drug routes, dose-decrements, dose-schedules, number of groups, etc. However, in most large programs involving several hundred in vivo tests yearly, resource limitations and drug supply limitations have usually dictated a single trial. Under such restrictive conditions, we have implemented a flexible in vivo testing protocol. With this strategy, the tumor model is dictated by in vitro cellular sensitivity; drug route by water solubility (with water soluble agents injected intravenously); dosage decrement by drug supply, dose-schedule by toxicities encountered, etc. In this flexible design, many treatment parameters can be changed during the course of treatment (e.g., dose and schedule). The discovery of two active agents are presented (Cryptophycin-1, and Thioxanthone BCN 183577). Both were discovered by the intravenous route of administration. Both would have been missed if they were tested intraperitoneally, the usual drug route used in discovery protocols. It is also likely that they would have been missed with an easy to execute fixed protocol design, even if injected i.v.

Automated lung tumor segmentation for whole body PET volume based on novel downhill region growing

NASA Astrophysics Data System (ADS)

Ballangan, Cherry; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Feng, Dagan

2010-03-01

We propose an automated lung tumor segmentation method for whole body PET images based on a novel downhill region growing (DRG) technique, which regards homogeneous tumor hotspots as 3D monotonically decreasing functions. The method has three major steps: thoracic slice extraction with K-means clustering of the slice features; hotspot segmentation with DRG; and decision tree analysis based hotspot classification. To overcome the common problem of leakage into adjacent hotspots in automated lung tumor segmentation, DRG employs the tumors' SUV monotonicity features. DRG also uses gradient magnitude of tumors' SUV to improve tumor boundary definition. We used 14 PET volumes from patients with primary NSCLC for validation. The thoracic region extraction step achieved good and consistent results for all patients despite marked differences in size and shape of the lungs and the presence of large tumors. The DRG technique was able to avoid the problem of leakage into adjacent hotspots and produced a volumetric overlap fraction of 0.61 +/- 0.13 which outperformed four other methods where the overlap fraction varied from 0.40 +/- 0.24 to 0.59 +/- 0.14. Of the 18 tumors in 14 NSCLC studies, 15 lesions were classified correctly, 2 were false negative and 15 were false positive.

Network-based regularization for matched case-control analysis of high-dimensional DNA methylation data.

PubMed

Sun, Hokeun; Wang, Shuang

2013-05-30

The matched case-control designs are commonly used to control for potential confounding factors in genetic epidemiology studies especially epigenetic studies with DNA methylation. Compared with unmatched case-control studies with high-dimensional genomic or epigenetic data, there have been few variable selection methods for matched sets. In an earlier paper, we proposed the penalized logistic regression model for the analysis of unmatched DNA methylation data using a network-based penalty. However, for popularly applied matched designs in epigenetic studies that compare DNA methylation between tumor and adjacent non-tumor tissues or between pre-treatment and post-treatment conditions, applying ordinary logistic regression ignoring matching is known to bring serious bias in estimation. In this paper, we developed a penalized conditional logistic model using the network-based penalty that encourages a grouping effect of (1) linked Cytosine-phosphate-Guanine (CpG) sites within a gene or (2) linked genes within a genetic pathway for analysis of matched DNA methylation data. In our simulation studies, we demonstrated the superiority of using conditional logistic model over unconditional logistic model in high-dimensional variable selection problems for matched case-control data. We further investigated the benefits of utilizing biological group or graph information for matched case-control data. We applied the proposed method to a genome-wide DNA methylation study on hepatocellular carcinoma (HCC) where we investigated the DNA methylation levels of tumor and adjacent non-tumor tissues from HCC patients by using the Illumina Infinium HumanMethylation27 Beadchip. Several new CpG sites and genes known to be related to HCC were identified but were missed by the standard method in the original paper. Copyright © 2012 John Wiley & Sons, Ltd.

Appropriateness of tumor marker request: a case of study

PubMed Central

Trevisiol, Chiara; Fabricio, Aline S. C.

2017-01-01

Appropriateness is crucial to provide efficient and high-quality health services at affordable costs. Laboratory medicine is a sector of special interest for the investigation of inappropriateness, due to the high rate of technological innovation and its pivotal role in many diseases and clinical settings. Some subjective aspects related to either the patient or physician seem to have a major role on inappropriateness rates. Given the psychological impact of cancer on both patients and physicians, tumor markers represent a case of study for appropriateness. The assessment of inappropriateness of laboratory tests has been focused mainly on ordering patterns. Appropriateness can barely be appraised by matching the requested test with the clinical problem because clinical information on the test requisition form is usually inadequate. Monitoring inappropriateness through individual clinical information may be feasible in inpatient (clinical data are available), while an indirect approach should be used for outpatients. To estimate inappropriateness in outpatients our group developed innovative models based on comparison between the actually ordered and expected requests of tumor marker, calculated according to recommendations of clinical practice guidelines (CPGs) applied to figures of cancer prevalence. The implementation of the model at national scale in Italy led to recognize a very high rate of overordering of tumor markers. The model was further focused by a dedicated algorithm to be adapted to different clinical conditions or organizational settings by applying performance indicators to cohort-wide structured information in electronic health records (EHRs). With this novel approach, we showed that inappropriateness is multifaceted even within the specific category of tumour markers. The model was effective in identifying both over- and underordering. Implementation of evidence based information and monitoring their impact on the clinical practice are parts of the same, multistage, process aimed at the progressive improvement of health care. PMID:28758100

Multimodality animal rotation imaging system (Mars) for in vivo detection of intraperitoneal tumors.

PubMed

Pizzonia, John; Holmberg, Jennie; Orton, Sean; Alvero, Ayesha; Viteri, Oscar; McLaughlin, William; Feke, Gil; Mor, Gil

2012-01-01

PROBLEM Ovarian cancer stem cells (OCSCs) have been postulated as the potential source of recurrence and chemoresistance. Therefore identification of OvCSC and their complete removal is a pivotal stage for the treatment of ovarian cancer. The objective of the following study was to develop a new in vivo imaging model that allows for the detection and monitoring of OCSCs. METHOD OF STUDY  OCSCs were labeled with X-Sight 761 Nanospheres and injected intra-peritoneally (i.p.) and sub-cutaneously (s.c.) to Athymic nude mice. The Carestream In-Vivo Imaging System FX was used to obtain X-ray and, concurrently, near-infrared fluorescence images. Tumor images in the mouse were observed from different angles by automatic rotation of the mouse. RESULTS  X-Sight 761 Nanospheres labeled almost 100% of the cells. No difference on growth rate was observed between labeled and unlabeled cells. Tumors were observed and monitoring revealed strong signaling up to 21 days. CONCLUSION  We describe the use of near-infrared nanoparticle probes for in vivo imaging of metastatic ovarian cancer models. Visualization of multiple sites around the animals was enhanced with the use of the Carestream Multimodal Animal Rotation System. © 2011 John Wiley & Sons A/S.

Enhancing curcumin anticancer efficacy through di-block copolymer micelle encapsulation.

PubMed

Lv, Li; Shen, Yuanyuan; Liu, Jieying; Wang, Feihu; Li, Min; Li, Min; Guo, Aijie; Wang, Yun; Zhou, Dejian; Guo, Shengrong

2014-02-01

We report herein the development of a novel aqueous formulation and improved antitumor activity for curcumin by encapsulating it into a biocompatible and biodegradable poly(L-lactic acid) based poly(anhydride-ester)-b-poly(ethylene glycol) (PAE-b-PEG) micelle. The resulting curcumin loaded micelles were completely water-dispersible, overcoming the problem of poor water solubility that limited its efficacy and bioavailability. In vitro cellular studies revealed that the curcumin-loaded micelles were taken up mainly via endocytosis route and exhibited higher cytotoxicities toward model cancer cell lines (HeLa and EMT6) than free curcumin. An in vivo biodistribution study revealed that the curcumin-loaded micelles displayed significantly enhanced accumulation inside the tumor of EMT6 breast tumor-bearing mice. More impressively, the curcumin-loaded micelles showed stronger antitumor activity, higher anti-angiogenesis effects and induced apoptosis on the EMT6 breast tumor model bearing mice than free curcumin. Furthermore, the curcumin-loaded micelles showed no significant toxicity towards hemotological system, major organs or tissues in mice. Combined with a high antitumor activity and low toxic side-effects, the curcumin-loaded micelles developed here thus appear to be a highly attractive nanomedicine for effective, targeted cancer therapy.

Photodynamic therapy potentiates the paracrine endothelial stimulation by colorectal cancer

NASA Astrophysics Data System (ADS)

Lamberti, María Julia; Florencia Pansa, María; Emanuel Vera, Renzo; Belén Rumie Vittar, Natalia; Rivarola, Viviana Alicia

2014-11-01

Colorectal cancer (CRC) is the third most common cancer and the third leading cause of cancer death worldwide. Recurrence is a major problem and is often the ultimate cause of death. In this context, the tumor microenvironment influences tumor progression and is considered as a new essential feature that clearly impacts on treatment outcome, and must therefore be taken into consideration. Photodynamic therapy (PDT), oxygen, light and drug-dependent, is a novel treatment modality when CRC patients are inoperable. Tumor vasculature and parenchyma cells are both potential targets of PDT damage modulating tumor-stroma interactions. In biological activity assessment in photodynamic research, three-dimensional (3D) cultures are essential to integrate biomechanical, biochemical, and biophysical properties that better predict the outcome of oxygen- and drug-dependent medical therapies. Therefore, the objective of this study was to investigate the antitumor effect of methyl 5-aminolevulinic acid-PDT using a light emitting diode for the treatment of CRC cells in a scenario that mimics targeted tissue complexity, providing a potential bridge for the gap between 2D cultures and animal models. Since photodynamic intervention of the tumor microenvironment can effectively modulate the tumor-stroma interaction, it was proposed to characterize the endothelial response to CRC paracrine communication, if one of these two populations is photosensitized. In conclusion, we demonstrated that the dialogue between endothelial and tumor populations when subjected to lethal PDT conditions induces an increase in angiogenic phenotype, and we think that it should be carefully considered for the development of PDT therapeutic protocols.

Optimal distributed control of a diffuse interface model of tumor growth

NASA Astrophysics Data System (ADS)

Colli, Pierluigi; Gilardi, Gianni; Rocca, Elisabetta; Sprekels, Jürgen

2017-06-01

In this paper, a distributed optimal control problem is studied for a diffuse interface model of tumor growth which was proposed by Hawkins-Daruud et al in Hawkins-Daruud et al (2011 Int. J. Numer. Math. Biomed. Eng. 28 3-24). The model consists of a Cahn-Hilliard equation for the tumor cell fraction φ coupled to a reaction-diffusion equation for a function σ representing the nutrient-rich extracellular water volume fraction. The distributed control u monitors as a right-hand side of the equation for σ and can be interpreted as a nutrient supply or a medication, while the cost function, which is of standard tracking type, is meant to keep the tumor cell fraction under control during the evolution. We show that the control-to-state operator is Fréchet differentiable between appropriate Banach spaces and derive the first-order necessary optimality conditions in terms of a variational inequality involving the adjoint state variables. The financial support of the FP7-IDEAS-ERC-StG #256872 (EntroPhase) and of the project Fondazione Cariplo-Regione Lombardia MEGAsTAR ‘Matematica d’Eccellenza in biologia ed ingegneria come accelleratore di una nuona strateGia per l’ATtRattività dell’ateneo pavese’ is gratefully acknowledged. The paper also benefited from the support of the MIUR-PRIN Grant 2015PA5MP7 ‘Calculus of Variations’ for PC and GG, and the GNAMPA (Gruppo Nazionale per l’Analisi Matematica, la Probabilità e le loro Applicazioni) of INdAM (Istituto Nazionale di Alta Matematica) for PC, GG and ER.

Immune oncology, immune responsiveness and the theory of everything.

PubMed

Turan, Tolga; Kannan, Deepti; Patel, Maulik; Matthew Barnes, J; Tanlimco, Sonia G; Lu, Rongze; Halliwill, Kyle; Kongpachith, Sarah; Kline, Douglas E; Hendrickx, Wouter; Cesano, Alessandra; Butterfield, Lisa H; Kaufman, Howard L; Hudson, Thomas J; Bedognetti, Davide; Marincola, Francesco; Samayoa, Josue

2018-06-05

Anti-cancer immunotherapy is encountering its own checkpoint. Responses are dramatic and long lasting but occur in a subset of tumors and are largely dependent upon the pre-existing immune contexture of individual cancers. Available data suggest that three landscapes best define the cancer microenvironment: immune-active, immune-deserted and immune-excluded. This trichotomy is observable across most solid tumors (although the frequency of each landscape varies depending on tumor tissue of origin) and is associated with cancer prognosis and response to checkpoint inhibitor therapy (CIT). Various gene signatures (e.g. Immunological Constant of Rejection - ICR and Tumor Inflammation Signature - TIS) that delineate these landscapes have been described by different groups. In an effort to explain the mechanisms of cancer immune responsiveness or resistance to CIT, several models have been proposed that are loosely associated with the three landscapes. Here, we propose a strategy to integrate compelling data from various paradigms into a "Theory of Everything". Founded upon this unified theory, we also propose the creation of a task force led by the Society for Immunotherapy of Cancer (SITC) aimed at systematically addressing salient questions relevant to cancer immune responsiveness and immune evasion. This multidisciplinary effort will encompass aspects of genetics, tumor cell biology, and immunology that are pertinent to the understanding of this multifaceted problem.

Within-brain classification for brain tumor segmentation.

PubMed

Havaei, Mohammad; Larochelle, Hugo; Poulin, Philippe; Jodoin, Pierre-Marc

2016-05-01

In this paper, we investigate a framework for interactive brain tumor segmentation which, at its core, treats the problem of interactive brain tumor segmentation as a machine learning problem. This method has an advantage over typical machine learning methods for this task where generalization is made across brains. The problem with these methods is that they need to deal with intensity bias correction and other MRI-specific noise. In this paper, we avoid these issues by approaching the problem as one of within brain generalization. Specifically, we propose a semi-automatic method that segments a brain tumor by training and generalizing within that brain only, based on some minimum user interaction. We investigate how adding spatial feature coordinates (i.e., i, j, k) to the intensity features can significantly improve the performance of different classification methods such as SVM, kNN and random forests. This would only be possible within an interactive framework. We also investigate the use of a more appropriate kernel and the adaptation of hyper-parameters specifically for each brain. As a result of these experiments, we obtain an interactive method whose results reported on the MICCAI-BRATS 2013 dataset are the second most accurate compared to published methods, while using significantly less memory and processing power than most state-of-the-art methods.

Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI

NASA Astrophysics Data System (ADS)

Zhou, Mu; Hall, Lawrence O.; Goldgof, Dmitry B.; Russo, Robin; Gillies, Robert J.; Gatenby, Robert A.

2015-03-01

Brain tumor heterogeneity remains a challenge for probing brain cancer evolutionary dynamics. In light of evolution, it is a priority to inspect the cancer system from a time-domain perspective since it explicitly tracks the dynamics of cancer variations. In this paper, we study the problem of exploring brain tumor heterogeneity from temporal clinical magnetic resonance imaging (MRI) data. Our goal is to discover evidence-based knowledge from such temporal imaging data, where multiple clinical MRI scans from Glioblastoma multiforme (GBM) patients are generated during therapy. In particular, we propose a quantitative histogram-based approach that builds a prediction model to measure the difference in histograms obtained from pre- and post-treatment. The study could significantly assist radiologists by providing a metric to identify distinctive patterns within each tumor, which is crucial for the goal of providing patient-specific treatments. We examine the proposed approach for a practical application - clinical survival group prediction. Experimental results show that our approach achieved 90.91% accuracy.

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malinowski, Kathleen T.; Fischell Department of Bioengineering, University of Maryland, College Park, MD; McAvoy, Thomas J.

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precisionmore » in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.« less

Glial brain tumor detection by using symmetry analysis

NASA Astrophysics Data System (ADS)

Pedoia, Valentina; Binaghi, Elisabetta; Balbi, Sergio; De Benedictis, Alessandro; Monti, Emanuele; Minotto, Renzo

2012-02-01

In this work a fully automatic algorithm to detect brain tumors by using symmetry analysis is proposed. In recent years a great effort of the research in field of medical imaging was focused on brain tumors segmentation. The quantitative analysis of MRI brain tumor allows to obtain useful key indicators of disease progression. The complex problem of segmenting tumor in MRI can be successfully addressed by considering modular and multi-step approaches mimicking the human visual inspection process. The tumor detection is often an essential preliminary phase to solvethe segmentation problem successfully. In visual analysis of the MRI, the first step of the experts cognitive process, is the detection of an anomaly respect the normal tissue, whatever its nature. An healthy brain has a strong sagittal symmetry, that is weakened by the presence of tumor. The comparison between the healthy and ill hemisphere, considering that tumors are generally not symmetrically placed in both hemispheres, was used to detect the anomaly. A clustering method based on energy minimization through Graph-Cut is applied on the volume computed as a difference between the left hemisphere and the right hemisphere mirrored across the symmetry plane. Differential analysis involves the loss the knowledge of the tumor side. Through an histogram analysis the ill hemisphere is recognized. Many experiments are performed to assess the performance of the detection strategy on MRI volumes in presence of tumors varied in terms of shapes positions and intensity levels. The experiments showed good results also in complex situations.

Optical tomograph optimized for tumor detection inside highly absorbent organs

NASA Astrophysics Data System (ADS)

Boutet, Jérôme; Koenig, Anne; Hervé, Lionel; Berger, Michel; Dinten, Jean-Marc; Josserand, Véronique; Coll, Jean-Luc

2011-05-01

This paper presents a tomograph for small animal fluorescence imaging. The compact and cost-effective system described in this article was designed to address the problem of tumor detection inside highly absorbent heterogeneous organs, such as lungs. To validate the tomograph's ability to detect cancerous nodules inside lungs, in vivo tumor growth was studied on seven cancerous mice bearing murine mammary tumors marked with Alexa Fluor 700. They were successively imaged 10, 12, and 14 days after the primary tumor implantation. The fluorescence maps were compared over this time period. As expected, the reconstructed fluorescence increases with the tumor growth stage.

Mathematical modelling of the destruction degree of cancer under the influence of a RF hyperthermia

NASA Astrophysics Data System (ADS)

Paruch, Marek; Turchan, Łukasz

2018-01-01

The article presents the mathematical modeling of the phenomenon of artificial hyperthermia which is caused by the interaction of an electric field. The electric field is induced by the applicator positioned within the biological tissue with cancer. In addition, in order to estimate the degree of tumor destruction under the influence of high temperature an Arrhenius integral has been used. The distribution of electric potential in the domain considered is described by the Laplace system of equations, while the temperature field is described by the Pennes system of equations. These problems are coupled by source function being the additional component in the Pennes equation and resulting from the electric field action. The boundary element method is applied to solve the coupled problem connected with the heating of biological tissues.

Simulation of glioblastoma multiforme (GBM) tumor cells using ising model on the Creutz Cellular Automaton

NASA Astrophysics Data System (ADS)

Züleyha, Artuç; Ziya, Merdan; Selçuk, Yeşiltaş; Kemal, Öztürk M.; Mesut, Tez

2017-11-01

Computational models for tumors have difficulties due to complexity of tumor nature and capacities of computational tools, however, these models provide visions to understand interactions between tumor and its micro environment. Moreover computational models have potential to develop strategies for individualized treatments for cancer. To observe a solid brain tumor, glioblastoma multiforme (GBM), we present a two dimensional Ising Model applied on Creutz cellular automaton (CCA). The aim of this study is to analyze avascular spherical solid tumor growth, considering transitions between non tumor cells and cancer cells are like phase transitions in physical system. Ising model on CCA algorithm provides a deterministic approach with discrete time steps and local interactions in position space to view tumor growth as a function of time. Our simulation results are given for fixed tumor radius and they are compatible with theoretical and clinic data.

Improved decision making for prioritizing tumor targeting antibodies in human xenografts: Utility of fluorescence imaging to verify tumor target expression, antibody binding and optimization of dosage and application schedule.

PubMed

Dobosz, Michael; Haupt, Ute; Scheuer, Werner

2017-01-01

Preclinical efficacy studies of antibodies targeting a tumor-associated antigen are only justified when the expression of the relevant antigen has been demonstrated. Conventionally, antigen expression level is examined by immunohistochemistry of formalin-fixed paraffin-embedded tumor tissue section. This method represents the diagnostic "gold standard" for tumor target evaluation, but is affected by a number of factors, such as epitope masking and insufficient antigen retrieval. As a consequence, variances and discrepancies in histological staining results can occur, which may influence decision-making and therapeutic outcome. To overcome these problems, we have used different fluorescence-labeled therapeutic antibodies targeting human epidermal growth factor receptor (HER) family members and insulin-like growth factor-1 receptor (IGF1R) in combination with fluorescence imaging modalities to determine tumor antigen expression, drug-target interaction, and biodistribution and tumor saturation kinetics in non-small cell lung cancer xenografts. For this, whole-body fluorescence intensities of labeled antibodies, applied as a single compound or antibody mixture, were measured in Calu-1 and Calu-3 tumor-bearing mice, then ex vivo multispectral tumor tissue analysis at microscopic resolution was performed. With the aid of this simple and fast imaging method, we were able to analyze the tumor cell receptor status of HER1-3 and IGF1R, monitor the antibody-target interaction and evaluate the receptor binding sites of anti-HER2-targeting antibodies. Based on this, the most suitable tumor model, best therapeutic antibody, and optimal treatment dosage and application schedule was selected. Predictions drawn from obtained imaging data were in excellent concordance with outcome of conducted preclinical efficacy studies. Our results clearly demonstrate the great potential of combined in vivo and ex vivo fluorescence imaging for the preclinical development and characterization of monoclonal antibodies.

Epidemiological Study of Mammary Tumors in Female Dogs Diagnosed during the Period 2002-2012: A Growing Animal Health Problem

PubMed Central

Salas, Yaritza; Márquez, Adelys; Diaz, Daniel; Romero, Laura

2015-01-01

Epidemiological studies enable us to analyze disease behavior, define risk factors and establish fundamental prognostic criteria, with the purpose of studying different types of diseases. The aim of this study was to determine the epidemiological characteristics of canine mammary tumors diagnosed during the period 2002-2012. The study was based on a retrospective study consisting of 1,917 biopsies of intact dogs that presented mammary gland lesions. Biopsies were sent to the Department of Pathology FMVZ-UNAM diagnostic service. The annual incidence of mammary tumors was 16.8%: 47.7% (benign) and 47.5% (malignant). The highest number of cases was epithelial, followed by mixed tumors. The most commonly diagnosed tumors were tubular adenoma, papillary adenoma, tubular carcinoma, papillary carcinoma, solid carcinoma, complex carcinoma and carcinosarcoma. Pure breeds accounted for 80% of submissions, and the Poodle, Cocker Spaniel and German Shepherd were consistently affected. Adult female dogs (9 to 12 years old) were most frequently involved, followed by 5- to 8-year-old females. Some association between breeds with histological types of malignant tumors was observed, but no association was found between breeds and BN. Mammary tumors in intact dogs had a high incidence. Benign and malignant tumors had similar frequencies, with an increase in malignant tumors in the past four years of the study. Epithelial tumors were more common, and the most affected were old adult females, purebreds and small-sized dogs. Mammary tumors in dogs are an important animal health problem that needs to be solved by improving veterinary oncology services in Mexico. PMID:25992997

Epidemiological Study of Mammary Tumors in Female Dogs Diagnosed during the Period 2002-2012: A Growing Animal Health Problem.

PubMed

Salas, Yaritza; Márquez, Adelys; Diaz, Daniel; Romero, Laura

2015-01-01

Epidemiological studies enable us to analyze disease behavior, define risk factors and establish fundamental prognostic criteria, with the purpose of studying different types of diseases. The aim of this study was to determine the epidemiological characteristics of canine mammary tumors diagnosed during the period 2002-2012. The study was based on a retrospective study consisting of 1,917 biopsies of intact dogs that presented mammary gland lesions. Biopsies were sent to the Department of Pathology FMVZ-UNAM diagnostic service. The annual incidence of mammary tumors was 16.8%: 47.7% (benign) and 47.5% (malignant). The highest number of cases was epithelial, followed by mixed tumors. The most commonly diagnosed tumors were tubular adenoma, papillary adenoma, tubular carcinoma, papillary carcinoma, solid carcinoma, complex carcinoma and carcinosarcoma. Pure breeds accounted for 80% of submissions, and the Poodle, Cocker Spaniel and German Shepherd were consistently affected. Adult female dogs (9 to 12 years old) were most frequently involved, followed by 5- to 8-year-old females. Some association between breeds with histological types of malignant tumors was observed, but no association was found between breeds and BN. Mammary tumors in intact dogs had a high incidence. Benign and malignant tumors had similar frequencies, with an increase in malignant tumors in the past four years of the study. Epithelial tumors were more common, and the most affected were old adult females, purebreds and small-sized dogs. Mammary tumors in dogs are an important animal health problem that needs to be solved by improving veterinary oncology services in Mexico.

A Genetically Engineered Mouse Model of Sporadic Colorectal Cancer.

PubMed

Betzler, Alexander M; Kochall, Susan; Blickensdörfer, Linda; Garcia, Sebastian A; Thepkaysone, May-Linn; Nanduri, Lahiri K; Muders, Michael H; Weitz, Jürgen; Reissfelder, Christoph; Schölch, Sebastian

2017-07-06

Despite the advantages of easy applicability and cost-effectiveness, colorectal cancer mouse models based on tumor cell injection have severe limitations and do not accurately simulate tumor biology and tumor cell dissemination. Genetically engineered mouse models have been introduced to overcome these limitations; however, such models are technically demanding, especially in large organs such as the colon in which only a single tumor is desired. As a result, an immunocompetent, genetically engineered mouse model of colorectal cancer was developed which develops highly uniform tumors and can be used for tumor biology studies as well as therapeutic trials. Tumor development is initiated by surgical, segmental infection of the distal colon with adeno-cre virus in compound conditionally mutant mice. The tumors can be easily detected and monitored via colonoscopy. We here describe the surgical technique of segmental adeno-cre infection of the colon, the surveillance of the tumor via high-resolution colonoscopy and present the resulting colorectal tumors.

Validity of the semi-infinite tumor model in diffuse reflectance spectroscopy for epithelial cancer diagnosis: a Monte Carlo study

NASA Astrophysics Data System (ADS)

Zhu, Caigang; Liu, Quan

2011-08-01

The accurate understanding of optical properties of human tissues plays an important role in the optical diagnosis of early epithelial cancer. Many inverse models used to determine the optical properties of a tumor have assumed that the tumor was semi-infinite, which infers infinite width and length but finite thickness. However, this simplified assumption could lead to large errors for small tumor, especially at the early stages. We used a modified Monte Carlo code, which is able to simulate light transport in a layered tissue model with buried tumor-like targets, to investigate the validity of the semi-infinite tumor assumption in two common epithelial tissue models: a squamous cell carcinoma (SCC) tissue model and a basal cell carcinoma (BCC) tissue model. The SCC tissue model consisted of three layers, i.e. the top epithelium, the middle tumor and the bottom stroma. The BCC tissue model also consisted of three layers, i.e. the top epidermis, the middle tumor and the bottom dermis. Diffuse reflectance was simulated for two common fiber-optic probes. In one probe, both source and detector fibers were perpendicular to the tissue surface; while in the other, both fibers were tilted at 45 degrees relative to the normal axis of the tissue surface. It was demonstrated that the validity of the semi-infinite tumor model depends on both the fiber-optic probe configuration and the tumor dimensions. Two look-up tables, which relate the validity of the semi-infinite tumor model to the tumor width in terms of the source-detector separation, were derived to guide the selection of appropriate tumor models and fiber optic probe configuration for the optical diagnosis of early epithelial cancers.

Oncogenic HER2Δ16 suppresses miR-15a/16 and deregulates BCL-2 to promote endocrine resistance of breast tumors

PubMed Central

Cittelly, Diana M.; Das, Partha M.; Salvo, Virgilio A.; Fonseca, Juan P.; Burow, Matthew E.; Jones, Frank E.

2010-01-01

Tamoxifen is the most commonly prescribed therapy for patients with estrogen receptor (ER)α-positive breast tumors. Tumor resistance to tamoxifen remains a serious clinical problem especially in patients with tumors that also overexpress human epidermal growth factor receptor 2 (HER2). Current preclinical models of HER2 overexpression fail to recapitulate the clinical spectrum of endocrine resistance associated with HER2/ER-positive tumors. Here, we show that ectopic expression of a clinically important oncogenic isoform of HER2, HER2Δ16, which is expressed in >30% of ER-positive breast tumors, promotes tamoxifen resistance and estrogen independence of MCF-7 xenografts. MCF-7/HER2Δ16 cells evade tamoxifen through upregulation of BCL-2, whereas mediated suppression of BCL-2 expression or treatment of MCF-7/HER2Δ16 cells with the BCL-2 family pharmacological inhibitor ABT-737 restores tamoxifen sensitivity. Tamoxifen-resistant MCF-7/HER2Δ16 cells upregulate BCL-2 protein levels in response to suppressed ERα signaling mediated by estrogen withdrawal, tamoxifen treatment or fulvestrant treatment. In addition, HER2Δ16 expression results in suppression of BCL-2-targeting microRNAs miR-15a and miR-16. Reintroduction of miR-15a/16 reduced tamoxifen-induced BCL-2 expression and sensitized MCF-7/HER2Δ16 to tamoxifen. Conversely, inhibition of miR-15a/16 in tamoxifen-sensitive cells activated BCL-2 expression and promoted tamoxifen resistance. Our results suggest that HER2Δ16 expression promotes endocrine-resistant HER2/ERα-positive breast tumors and in contrast to wild-type HER2, preclinical models of HER2Δ16 overexpression recapitulate multiple phenotypes of endocrine-resistant human breast tumors. The mechanism of HER2Δ16 therapeutic evasion, involving tamoxifen-induced upregulation of BCL-2 and suppression of miR-15a/16, provides a template for unique therapeutic interventions combining tamoxifen with modulation of microRNAs and/or ABT-737-mediated BCL-2 inhibition and apoptosis. PMID:20876285

Mice with cancer-induced bone pain show a marked decline in day/night activity.

PubMed

Majuta, Lisa A; Guedon, Jean-Marc G; Mitchell, Stefanie A T; Kuskowski, Michael A; Mantyh, Patrick W

2017-09-01

Cancer-induced bone pain (CIBP) is the most common type of pain with cancer. In humans, this pain can be difficult to control and highly disabling. A major problem with CIBP in humans is that it increases on weight-bearing and/or movement of a tumor-bearing bone limiting the activity and functional status of the patient. Currently, there is less data concerning whether similar negative changes in activity occur in rodent models of CIBP. To determine whether there are marked changes in activity in a rodent model of CIBP and compare this to changes in skin hypersensitivity. Osteosarcoma cells were injected and confined to 1 femur of the adult male mouse. Every 7 days, spontaneous horizontal and vertical activities were assessed over a 20-hour day and night period using automated activity boxes. Mechanical hypersensitivity of the hind paw skin was assessed using von Frey testing. As the tumor cells grew within the femur, there was a significant decline in horizontal and vertical activity during the times of the day/night when the mice are normally most active. Mice also developed significant hypersensitivity in the skin of the hind paw in the tumor-bearing limb. Even when the tumor is confined to a single load-bearing bone, CIBP drives a significant loss of activity, which increases with disease progression. Understanding the mechanisms that drive this reduction in activity may allow the development of therapies that allow CIBP patients to better maintain their activity and functional status.

Isolation of Circulating Tumor Cells in an Orthotopic Mouse Model of Colorectal Cancer.

PubMed

Kochall, Susan; Thepkaysone, May-Linn; García, Sebastián A; Betzler, Alexander M; Weitz, Jürgen; Reissfelder, Christoph; Schölch, Sebastian

2017-07-18

Despite the advantages of easy applicability and cost-effectiveness, subcutaneous mouse models have severe limitations and do not accurately simulate tumor biology and tumor cell dissemination. Orthotopic mouse models have been introduced to overcome these limitations; however, such models are technically demanding, especially in hollow organs such as the large bowel. In order to produce uniform tumors which reliably grow and metastasize, standardized techniques of tumor cell preparation and injection are critical. We have developed an orthotopic mouse model of colorectal cancer (CRC) which develops highly uniform tumors and can be used for tumor biology studies as well as therapeutic trials. Tumor cells from either primary tumors, 2-dimensional (2D) cell lines or 3-dimensional (3D) organoids are injected into the cecum and, depending on the metastatic potential of the injected tumor cells, form highly metastatic tumors. In addition, CTCs can be found regularly. We here describe the technique of tumor cell preparation from both 2D cell lines and 3D organoids as well as primary tumor tissue, the surgical and injection techniques as well as the isolation of CTCs from the tumor-bearing mice, and present tips for troubleshooting.

A Novel Immunocompetent Mouse Model of Pancreatic Cancer with Robust Stroma: a Valuable Tool for Preclinical Evaluation of New Therapies

PubMed Central

Majumder, Kaustav; Arora, Nivedita; Modi, Shrey; Chugh, Rohit; Nomura, Alice; Giri, Bhuwan; Dawra, Rajinder; Ramakrishnan, Sundaram; Banerjee, Sulagna; Saluja, Ashok; Dudeja, Vikas

2017-01-01

A valid preclinical tumor model should recapitulate the tumor microenvironment. Immune and stromal components are absent in immunodeficient models of pancreatic cancer. While these components are present in genetically engineered models such as KrasG12D; Trp53R172H; Pdx-1Cre (KPC), immense variability in development of invasive disease makes them unsuitable for evaluation of novel therapies. We have generated a novel mouse model of pancreatic cancer by implanting tumor fragments from KPC mice into the pancreas of wild type mice. Three-millimeter tumor pieces from KPC mice were implanted into the pancreas of C57BL/6J mice. Four to eight weeks later, tumors were harvested, and stromal and immune components were evaluated. The efficacy of Minnelide, a novel compound which has been shown to be effective against pancreatic cancer in a number of preclinical murine models, was evaluated. In our model, consistent tumor growth and metastases were observed. Tumors demonstrated intense desmoplasia and leukocytic infiltration which was comparable to that in the genetically engineered KPC model and significantly more than that observed in KPC tumor-derived cell line implantation model. Minnelide treatment resulted in a significant decrease in the tumor weight and volume. This novel model demonstrates a consistent growth rate and tumor-associated mortality and recapitulates the tumor microenvironment. This convenient model is a valuable tool to evaluate novel therapies. PMID:26582596

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models.

PubMed

Yock, Adam D; Rao, Arvind; Dong, Lei; Beadle, Beth M; Garden, Adam S; Kudchadker, Rajat J; Court, Laurence E

2014-05-01

The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: -11.6%-23.8%) and 14.6% (range: -7.3%-27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: -6.8%-40.3%) and 13.1% (range: -1.5%-52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: -11.1%-20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

A stochastic model for tumor geometry evolution during radiation therapy in cervical cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yifang; Lee, Chi-Guhn; Chan, Timothy C. Y., E-mail: tcychan@mie.utoronto.ca

2014-02-15

Purpose: To develop mathematical models to predict the evolution of tumor geometry in cervical cancer undergoing radiation therapy. Methods: The authors develop two mathematical models to estimate tumor geometry change: a Markov model and an isomorphic shrinkage model. The Markov model describes tumor evolution by investigating the change in state (either tumor or nontumor) of voxels on the tumor surface. It assumes that the evolution follows a Markov process. Transition probabilities are obtained using maximum likelihood estimation and depend on the states of neighboring voxels. The isomorphic shrinkage model describes tumor shrinkage or growth in terms of layers of voxelsmore » on the tumor surface, instead of modeling individual voxels. The two proposed models were applied to data from 29 cervical cancer patients treated at Princess Margaret Cancer Centre and then compared to a constant volume approach. Model performance was measured using sensitivity and specificity. Results: The Markov model outperformed both the isomorphic shrinkage and constant volume models in terms of the trade-off between sensitivity (target coverage) and specificity (normal tissue sparing). Generally, the Markov model achieved a few percentage points in improvement in either sensitivity or specificity compared to the other models. The isomorphic shrinkage model was comparable to the Markov approach under certain parameter settings. Convex tumor shapes were easier to predict. Conclusions: By modeling tumor geometry change at the voxel level using a probabilistic model, improvements in target coverage and normal tissue sparing are possible. Our Markov model is flexible and has tunable parameters to adjust model performance to meet a range of criteria. Such a model may support the development of an adaptive paradigm for radiation therapy of cervical cancer.« less

3D tumor tissue analogs and their orthotopic implants for understanding tumor-targeting of microenvironment-responsive nanosized chemotherapy and radiation.

PubMed

Sethi, Pallavi; Jyoti, Amar; Swindell, Elden P; Chan, Ryan; Langner, Ulrich W; Feddock, Jonathan M; Nagarajan, Radhakrishnan; O'Halloran, Thomas V; Upreti, Meenakshi

2015-11-01

An appropriate representation of the tumor microenvironment in tumor models can have a pronounced impact on directing combinatorial treatment strategies and cancer nanotherapeutics. The present study develops a novel 3D co-culture spheroid model (3D TNBC) incorporating tumor cells, endothelial cells and fibroblasts as color-coded murine tumor tissue analogs (TTA) to better represent the tumor milieu of triple negative breast cancer in vitro. Implantation of TTA orthotopically in nude mice, resulted in enhanced growth and aggressive metastasis to ectopic sites. Subsequently, the utility of the model is demonstrated for preferential targeting of irradiated tumor endothelial cells via radiation-induced stromal enrichment of galectin-1 using anginex conjugated nanoparticles (nanobins) carrying arsenic trioxide and cisplatin. Demonstration of a multimodal nanotherapeutic system and inclusion of the biological response to radiation using an in vitro/in vivo tumor model incorporating characteristics of tumor microenvironment presents an advance in preclinical evaluation of existing and novel cancer nanotherapies. Existing in-vivo tumor models are established by implanting tumor cells into nude mice. Here, the authors described their approach 3D spheres containing tumor cells, enodothelial cells and fibroblasts. This would mimic tumor micro-environment more realistically. This interesting 3D model should reflect more accurately tumor response to various drugs and would enable the design of new treatment modalities. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

In Vitro Tumor Models: Advantages, Disadvantages, Variables, and Selecting the Right Platform.

PubMed

Katt, Moriah E; Placone, Amanda L; Wong, Andrew D; Xu, Zinnia S; Searson, Peter C

2016-01-01

In vitro tumor models have provided important tools for cancer research and serve as low-cost screening platforms for drug therapies; however, cancer recurrence remains largely unchecked due to metastasis, which is the cause of the majority of cancer-related deaths. The need for an improved understanding of the progression and treatment of cancer has pushed for increased accuracy and physiological relevance of in vitro tumor models. As a result, in vitro tumor models have concurrently increased in complexity and their output parameters further diversified, since these models have progressed beyond simple proliferation, invasion, and cytotoxicity screens and have begun recapitulating critical steps in the metastatic cascade, such as intravasation, extravasation, angiogenesis, matrix remodeling, and tumor cell dormancy. Advances in tumor cell biology, 3D cell culture, tissue engineering, biomaterials, microfabrication, and microfluidics have enabled rapid development of new in vitro tumor models that often incorporate multiple cell types, extracellular matrix materials, and spatial and temporal introduction of soluble factors. Other innovations include the incorporation of perfusable microvessels to simulate the tumor vasculature and model intravasation and extravasation. The drive toward precision medicine has increased interest in adapting in vitro tumor models for patient-specific therapies, clinical management, and assessment of metastatic potential. Here, we review the wide range of current in vitro tumor models and summarize their advantages, disadvantages, and suitability in modeling specific aspects of the metastatic cascade and drug treatment.

In Vitro Tumor Models: Advantages, Disadvantages, Variables, and Selecting the Right Platform

PubMed Central

Katt, Moriah E.; Placone, Amanda L.; Wong, Andrew D.; Xu, Zinnia S.; Searson, Peter C.

2016-01-01

In vitro tumor models have provided important tools for cancer research and serve as low-cost screening platforms for drug therapies; however, cancer recurrence remains largely unchecked due to metastasis, which is the cause of the majority of cancer-related deaths. The need for an improved understanding of the progression and treatment of cancer has pushed for increased accuracy and physiological relevance of in vitro tumor models. As a result, in vitro tumor models have concurrently increased in complexity and their output parameters further diversified, since these models have progressed beyond simple proliferation, invasion, and cytotoxicity screens and have begun recapitulating critical steps in the metastatic cascade, such as intravasation, extravasation, angiogenesis, matrix remodeling, and tumor cell dormancy. Advances in tumor cell biology, 3D cell culture, tissue engineering, biomaterials, microfabrication, and microfluidics have enabled rapid development of new in vitro tumor models that often incorporate multiple cell types, extracellular matrix materials, and spatial and temporal introduction of soluble factors. Other innovations include the incorporation of perfusable microvessels to simulate the tumor vasculature and model intravasation and extravasation. The drive toward precision medicine has increased interest in adapting in vitro tumor models for patient-specific therapies, clinical management, and assessment of metastatic potential. Here, we review the wide range of current in vitro tumor models and summarize their advantages, disadvantages, and suitability in modeling specific aspects of the metastatic cascade and drug treatment. PMID:26904541

Dynamical properties of a minimally parameterized mathematical model for metronomic chemotherapy.

PubMed

Schättler, Heinz; Ledzewicz, Urszula; Amini, Behrooz

2016-04-01

A minimally parameterized mathematical model for low-dose metronomic chemotherapy is formulated that takes into account angiogenic signaling between the tumor and its vasculature and tumor inhibiting effects of tumor-immune system interactions. The dynamical equations combine a model for tumor development under angiogenic signaling formulated by Hahnfeldt et al. with a model for tumor-immune system interactions by Stepanova. The dynamical properties of the model are analyzed. Depending on the parameter values, the system encompasses a variety of medically realistic scenarios that range from cases when (i) low-dose metronomic chemotherapy is able to eradicate the tumor (all trajectories converge to a tumor-free equilibrium point) to situations when (ii) tumor dormancy is induced (a unique, globally asymptotically stable benign equilibrium point exists) to (iii) multi-stable situations that have both persistent benign and malignant behaviors separated by the stable manifold of an unstable equilibrium point and finally to (iv) situations when tumor growth cannot be overcome by low-dose metronomic chemotherapy. The model forms a basis for a more general study of chemotherapy when the main components of a tumor's microenvironment are taken into account.

Structure of solid tumors and their vasculature: Implications for therapy with monoclonal antibodies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dvorak, H.F.; Nagy, J.A.; Dvorak, A.M.

Delivery of monoclonal antibodies to solid tumors is a vexing problem that must be solved if these antibodies are to realize their promise in therapy. Such success as has been achieved with monoclonal antibodies is attributable to the local hyperpermeability of the tumor vasculature, a property that favors antibody extravasation at tumor sites and that is mediated by a tumor-secreted vascular permeability factor. However, leaky tumor blood vessels are generally some distance removed from target tumor cells, separated by stroma and by other tumor cells that together represent significant barriers to penetration by extravasated monoclonal antibodies. For this reason, alternativemore » approaches may be attractive. These include the use of antibody-linked cytotoxins, which are able to kill tumor cells without immediate contact, and direction of antibodies against nontumor cell targets, for example, antigens unique to the tumor vascular endothelium or to tumor stroma. 50 refs.« less

Tumor-Cut: segmentation of brain tumors on contrast enhanced MR images for radiosurgery applications.

PubMed

Hamamci, Andac; Kucuk, Nadir; Karaman, Kutlay; Engin, Kayihan; Unal, Gozde

2012-03-01

In this paper, we present a fast and robust practical tool for segmentation of solid tumors with minimal user interaction to assist clinicians and researchers in radiosurgery planning and assessment of the response to the therapy. Particularly, a cellular automata (CA) based seeded tumor segmentation method on contrast enhanced T1 weighted magnetic resonance (MR) images, which standardizes the volume of interest (VOI) and seed selection, is proposed. First, we establish the connection of the CA-based segmentation to the graph-theoretic methods to show that the iterative CA framework solves the shortest path problem. In that regard, we modify the state transition function of the CA to calculate the exact shortest path solution. Furthermore, a sensitivity parameter is introduced to adapt to the heterogeneous tumor segmentation problem, and an implicit level set surface is evolved on a tumor probability map constructed from CA states to impose spatial smoothness. Sufficient information to initialize the algorithm is gathered from the user simply by a line drawn on the maximum diameter of the tumor, in line with the clinical practice. Furthermore, an algorithm based on CA is presented to differentiate necrotic and enhancing tumor tissue content, which gains importance for a detailed assessment of radiation therapy response. Validation studies on both clinical and synthetic brain tumor datasets demonstrate 80%-90% overlap performance of the proposed algorithm with an emphasis on less sensitivity to seed initialization, robustness with respect to different and heterogeneous tumor types, and its efficiency in terms of computation time.

Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.

PubMed

Han, Dongfeng; Bayouth, John; Song, Qi; Taurani, Aakant; Sonka, Milan; Buatti, John; Wu, Xiaodong

2011-01-01

Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we have proposed a general framework to use both PET and CT images simultaneously for tumor segmentation. Our method utilizes the strength of each imaging modality: the superior contrast of PET and the superior spatial resolution of CT. We formulate this problem as a Markov Random Field (MRF) based segmentation of the image pair with a regularized term that penalizes the segmentation difference between PET and CT. Our method simulates the clinical practice of delineating tumor simultaneously using both PET and CT, and is able to concurrently segment tumor from both modalities, achieving globally optimal solutions in low-order polynomial time by a single maximum flow computation. The method was evaluated on clinically relevant tumor segmentation problems. The results showed that our method can effectively make use of both PET and CT image information, yielding segmentation accuracy of 0.85 in Dice similarity coefficient and the average median hausdorff distance (HD) of 6.4 mm, which is 10% (resp., 16%) improvement compared to the graph cuts method solely using the PET (resp., CT) images.

Accounting for measurement error in biomarker data and misclassification of subtypes in the analysis of tumor data

PubMed Central

Nevo, Daniel; Zucker, David M.; Tamimi, Rulla M.; Wang, Molin

2017-01-01

A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps–clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses’ Health Study to demonstrate the utility of our method. PMID:27558651

3D multimodal MRI brain glioma tumor and edema segmentation: a graph cut distribution matching approach.

PubMed

Njeh, Ines; Sallemi, Lamia; Ayed, Ismail Ben; Chtourou, Khalil; Lehericy, Stephane; Galanaud, Damien; Hamida, Ahmed Ben

2015-03-01

This study investigates a fast distribution-matching, data-driven algorithm for 3D multimodal MRI brain glioma tumor and edema segmentation in different modalities. We learn non-parametric model distributions which characterize the normal regions in the current data. Then, we state our segmentation problems as the optimization of several cost functions of the same form, each containing two terms: (i) a distribution matching prior, which evaluates a global similarity between distributions, and (ii) a smoothness prior to avoid the occurrence of small, isolated regions in the solution. Obtained following recent bound-relaxation results, the optima of the cost functions yield the complement of the tumor region or edema region in nearly real-time. Based on global rather than pixel wise information, the proposed algorithm does not require an external learning from a large, manually-segmented training set, as is the case of the existing methods. Therefore, the ensuing results are independent of the choice of a training set. Quantitative evaluations over the publicly available training and testing data set from the MICCAI multimodal brain tumor segmentation challenge (BraTS 2012) demonstrated that our algorithm yields a highly competitive performance for complete edema and tumor segmentation, among nine existing competing methods, with an interesting computing execution time (less than 0.5s per image). Copyright © 2014 Elsevier Ltd. All rights reserved.

CXCL12 Chemokine Expression Suppresses Human Pancreatic Cancer Growth and Metastasis

PubMed Central

Roy, Ishan; Zimmerman, Noah P.; Mackinnon, A. Craig; Tsai, Susan; Evans, Douglas B.; Dwinell, Michael B.

2014-01-01

Pancreatic ductal adenocarcinoma is an unsolved health problem with nearly 75% of patients diagnosed with advanced disease and an overall 5-year survival rate near 5%. Despite the strong link between mortality and malignancy, the mechanisms behind pancreatic cancer dissemination and metastasis are poorly understood. Correlative pathological and cell culture analyses suggest the chemokine receptor CXCR4 plays a biological role in pancreatic cancer progression. In vivo roles for the CXCR4 ligand CXCL12 in pancreatic cancer malignancy were investigated. CXCR4 and CXCR7 were consistently expressed in normal and cancerous pancreatic ductal epithelium, established cell lines, and patient-derived primary cancer cells. Relative to healthy exocrine ducts, CXCL12 expression was pathologically repressed in pancreatic cancer tissue specimens and patient-derived cell lines. To test the functional consequences of CXCL12 silencing, pancreatic cancer cell lines stably expressingthe chemokine were engineered. Consistent with a role for CXCL12 as a tumor suppressor, cells producing the chemokine wereincreasingly adherent and migration deficient in vitro and poorly metastatic in vivo, compared to control cells. Further, CXCL12 reintroduction significantly reduced tumor growth in vitro, with significantly smaller tumors in vivo, leading to a pronounced survival advantage in a preclinical model. Together, these data demonstrate a functional tumor suppressive role for the normal expression of CXCL12 in pancreatic ducts, regulating both tumor growth andcellulardissemination to metastatic sites. PMID:24594697

Genetically Engineered Cancer Models, But Not Xenografts, Faithfully Predict Anticancer Drug Exposure in Melanoma Tumors

PubMed Central

Combest, Austin J.; Roberts, Patrick J.; Dillon, Patrick M.; Sandison, Katie; Hanna, Suzan K.; Ross, Charlene; Habibi, Sohrab; Zamboni, Beth; Müller, Markus; Brunner, Martin; Sharpless, Norman E.

2012-01-01

Background. Rodent studies are a vital step in the development of novel anticancer therapeutics and are used in pharmacokinetic (PK), toxicology, and efficacy studies. Traditionally, anticancer drug development has relied on xenograft implantation of human cancer cell lines in immunocompromised mice for efficacy screening of a candidate compound. The usefulness of xenograft models for efficacy testing, however, has been questioned, whereas genetically engineered mouse models (GEMMs) and orthotopic syngeneic transplants (OSTs) may offer some advantages for efficacy assessment. A critical factor influencing the predictability of rodent tumor models is drug PKs, but a comprehensive comparison of plasma and tumor PK parameters among xenograft models, OSTs, GEMMs, and human patients has not been performed. Methods. In this work, we evaluated the plasma and tumor dispositions of an antimelanoma agent, carboplatin, in patients with cutaneous melanoma compared with four different murine melanoma models (one GEMM, one human cell line xenograft, and two OSTs). Results. Using microdialysis to sample carboplatin tumor disposition, we found that OSTs and xenografts were poor predictors of drug exposure in human tumors, whereas the GEMM model exhibited PK parameters similar to those seen in human tumors. Conclusions. The tumor PKs of carboplatin in a GEMM of melanoma more closely resembles the tumor disposition in patients with melanoma than transplanted tumor models. GEMMs show promise in becoming an improved prediction model for intratumoral PKs and response in patients with solid tumors. PMID:22993143

A neurosurgical simulation of skull base tumors using a 3D printed rapid prototyping model containing mesh structures.

PubMed

Kondo, Kosuke; Harada, Naoyuki; Masuda, Hiroyuki; Sugo, Nobuo; Terazono, Sayaka; Okonogi, Shinichi; Sakaeyama, Yuki; Fuchinoue, Yutaka; Ando, Syunpei; Fukushima, Daisuke; Nomoto, Jun; Nemoto, Masaaki

2016-06-01

Deep regions are not visible in three-dimensional (3D) printed rapid prototyping (RP) models prepared from opaque materials, which is not the case with translucent images. The objectives of this study were to develop an RP model in which a skull base tumor was simulated using mesh, and to investigate its usefulness for surgical simulations by evaluating the visibility of its deep regions. A 3D printer that employs binder jetting and is mainly used to prepare plaster models was used. RP models containing a solid tumor, no tumor, and a mesh tumor were prepared based on computed tomography, magnetic resonance imaging, and angiographic data for four cases of petroclival tumor. Twelve neurosurgeons graded the three types of RP model into the following four categories: 'clearly visible,' 'visible,' 'difficult to see,' and 'invisible,' based on the visibility of the internal carotid artery, basilar artery, and brain stem through a craniotomy performed via the combined transpetrosal approach. In addition, the 3D positional relationships between these structures and the tumor were assessed. The internal carotid artery, basilar artery, and brain stem and the positional relationships of these structures with the tumor were significantly more visible in the RP models with mesh tumors than in the RP models with solid or no tumors. The deep regions of PR models containing mesh skull base tumors were easy to visualize. This 3D printing-based method might be applicable to various surgical simulations.

Tumor heterogeneity and progression: conceptual foundations for modeling.

PubMed

Greller, L D; Tobin, F L; Poste, G

1996-01-01

A conceptual foundation for modeling tumor progression, growth, and heterogeneity is presented. The purpose of such models is to aid understanding, test ideas, formulate experiments, and to model cancer 'in machina' to address the dynamic features of tumor cell heterogeneity, progression, and growth. The descriptive capabilities of such an approach provides a consistent language for qualitatively reasoning about tumor behavior. This approach provides a schema for building conceptual models that combine three key phenomenological driving elements: growth, progression, and genetic instability. The growth element encompasses processes contributing to changes in tumor bulk and is distinct from progression per se. The progression element subsumes a broad collection of processes underlying phenotypic progression. The genetics elements represents heritable changes which potentially affect tumor character and behavior. Models, conceptual and mathematical, can be built for different tumor situations by drawing upon the interaction of these three distinct driving elements. These models can be used as tools to explore a diversity of hypotheses concerning dynamic changes in cellular populations during tumor progression, including the generation of intratumor heterogeneity. Such models can also serve to guide experimentation and to gain insight into dynamic aspects of complex tumor behavior.

Genetically Engineered Mouse Models of Pituitary Tumors

PubMed Central

Cano, David A.; Soto-Moreno, Alfonso; Leal-Cerro, Alfonso

2014-01-01

Animal models constitute valuable tools for investigating the pathogenesis of cancer as well as for preclinical testing of novel therapeutics approaches. However, the pathogenic mechanisms of pituitary-tumor formation remain poorly understood, particularly in sporadic adenomas, thus, making it a challenge to model pituitary tumors in mice. Nevertheless, genetically engineered mouse models (GEMMs) of pituitary tumors have provided important insight into pituitary tumor biology. In this paper, we review various GEMMs of pituitary tumors, highlighting their contributions and limitations, and discuss opportunities for research in the field. PMID:25136513

Stochastic models for tumoral growth

NASA Astrophysics Data System (ADS)

Escudero, Carlos

2006-02-01

Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border and the surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor border is an optimal strategy adopted for minimizing the pressure and helping tumor development. Two stochastic partial differential equations are reported in this paper in order to correctly model the physical properties of tumoral growth in (1+1) and (2+1) dimensions. The advantage of these models is that they reproduce the correct geometry of the tumor and are defined in terms of polar variables. An analysis of these models allows us to quantitatively estimate the response of the tumor to an unfavorable perturbation during growth.

On the nature of cancer and why anticancer vaccines don't work.

PubMed

Prehn, Richmond T

2005-08-01

In this essay I suggest that the major difficulty in producing effective anti-cancer vaccines lies in the fact that most cancers have little immunogenicity because of a basic paucity of tumor-specific antigenicity. The lack of antigenicity, despite extensive genomic instability, could be explained if most tumor mutations occur in silenced genes. A further problem is that an immune reaction against tumor antigens, especially in moderate or low amount, may be stimulatory rather than inhibitory to tumor growth.

On the nature of cancer and why anticancer vaccines don't work

PubMed Central

Prehn, Richmond T

2005-01-01

In this essay I suggest that the major difficulty in producing effective anti-cancer vaccines lies in the fact that most cancers have little immunogenicity because of a basic paucity of tumor-specific antigenicity. The lack of antigenicity, despite extensive genomic instability, could be explained if most tumor mutations occur in silenced genes. A further problem is that an immune reaction against tumor antigens, especially in moderate or low amount, may be stimulatory rather than inhibitory to tumor growth. PMID:16060965

Optimal radiotherapy dose schedules under parametric uncertainty

NASA Astrophysics Data System (ADS)

Badri, Hamidreza; Watanabe, Yoichi; Leder, Kevin

2016-01-01

We consider the effects of parameter uncertainty on the optimal radiation schedule in the context of the linear-quadratic model. Our interest arises from the observation that if inter-patient variability in normal and tumor tissue radiosensitivity or sparing factor of the organs-at-risk (OAR) are not accounted for during radiation scheduling, the performance of the therapy may be strongly degraded or the OAR may receive a substantially larger dose than the allowable threshold. This paper proposes a stochastic radiation scheduling concept to incorporate inter-patient variability into the scheduling optimization problem. Our method is based on a probabilistic approach, where the model parameters are given by a set of random variables. Our probabilistic formulation ensures that our constraints are satisfied with a given probability, and that our objective function achieves a desired level with a stated probability. We used a variable transformation to reduce the resulting optimization problem to two dimensions. We showed that the optimal solution lies on the boundary of the feasible region and we implemented a branch and bound algorithm to find the global optimal solution. We demonstrated how the configuration of optimal schedules in the presence of uncertainty compares to optimal schedules in the absence of uncertainty (conventional schedule). We observed that in order to protect against the possibility of the model parameters falling into a region where the conventional schedule is no longer feasible, it is required to avoid extremal solutions, i.e. a single large dose or very large total dose delivered over a long period. Finally, we performed numerical experiments in the setting of head and neck tumors including several normal tissues to reveal the effect of parameter uncertainty on optimal schedules and to evaluate the sensitivity of the solutions to the choice of key model parameters.

Predicting Behavioral Problems in Craniopharyngioma Survivors after Conformal Radiation Therapy

PubMed Central

Dolson, Eugenia P.; Conklin, Heather M.; Li, Chenghong; Xiong, Xiaoping; Merchant, Thomas E.

2009-01-01

Background Although radiation therapy is a primary treatment for craniopharyngioma, it can exacerbate existing problems related to the tumor and pre-irradiation management. Survival is often marked by neurologic deficits, panhypopituitarism, diabetes insipidus, cognitive deficiencies and behavioral and social problems. Procedure The Achenbach Child Behavior Checklist (CBCL) was used to evaluate behavioral and social problems during the first five years of follow-up in 27 patients with craniopharyngioma treated with conformal radiation therapy. Results All group averages for the CBCL scales were within the age-typical range at pre-irradiation baseline. Extent of surgical resection was implicated in baseline differences for the Internalizing, Externalizing, Behavior Problem and Social scores. Significant longitudinal changes were found in Internalizing, Externalizing, Behavior Problem and School scores that correlated with tumor and treatment related factors. Conclusions The most common variables implicated in post-irradiation behavioral and social problems were CSF shunting, presence of an Ommaya reservoir, diabetes insipidus, and low pre-irradiation growth hormone levels. PMID:19191345

Development of a Model System to Evaluate Local Recurrence in Osteosarcoma and Assessment of the Effects of Bone Morphogenetic Protein-2.

PubMed

Geller, David S; Singh, Michael Y; Zhang, Wendong; Gill, Jonathan; Roth, Michael E; Kim, Mimi Y; Xie, Xianhong; Singh, Christopher K; Dorfman, Howard D; Villanueva-Siles, Esperanza; Park, Amy; Piperdi, Sajida; Gorlick, Richard

2015-07-01

It is increasingly relevant to better define what constitutes an adequate surgical margin in an effort to improve reconstructive longevity and functional outcomes following osteosarcoma surgery. In addition, nonunion remains a challenging problem in some patients following allograft reconstruction. Bone morphogenetic protein-2 (BMP-2) could enhance osseous union, but has been historically avoided due to concerns that it may promote tumor recurrence. An orthotopic xenograft murine model was utilized to describe the natural temporal course of osteosarcoma growth. Tumors were treated either with surgery alone, surgery and single-agent chemotherapy, or surgery and dual-agent chemotherapy to assess the relationship between surgical margin and local recurrence. The effect of BMP-2 on local recurrence was similarly assessed. Osteosarcoma tumor growth was categorized into reproducible phases. Margins greater than 997 μm resulted in local control following surgery alone. Margins greater than 36 μm resulted in local control following surgery and single-agent chemotherapy. Margins greater than 12 μm resulted in local control following surgery and dual-agent chemotherapy. The application of exogenous BMP-2 does not confer an increased risk of local recurrence. This model reliably reproduces the clinical, radiographic, and surgical conditions encountered in human osteosarcoma. It successfully incorporates relevant chemotherapy, further paralleling the human experience. Surgical margins required to achieve local control in osteosarcoma can be reduced using single-agent chemotherapy and further decreased using dual-agent chemotherapy. The application of BMP-2 does not increase local recurrence in this model. ©2014 American Association for Cancer Research.

Modeling Protective Anti-Tumor Immunity via Preventative Cancer Vaccines Using a Hybrid Agent-based and Delay Differential Equation Approach

PubMed Central

Kim, Peter S.; Lee, Peter P.

2012-01-01

A next generation approach to cancer envisions developing preventative vaccinations to stimulate a person's immune cells, particularly cytotoxic T lymphocytes (CTLs), to eliminate incipient tumors before clinical detection. The purpose of our study is to quantitatively assess whether such an approach would be feasible, and if so, how many anti-cancer CTLs would have to be primed against tumor antigen to provide significant protection. To understand the relevant dynamics, we develop a two-compartment model of tumor-immune interactions at the tumor site and the draining lymph node. We model interactions at the tumor site using an agent-based model (ABM) and dynamics in the lymph node using a system of delay differential equations (DDEs). We combine the models into a hybrid ABM-DDE system and investigate dynamics over a wide range of parameters, including cell proliferation rates, tumor antigenicity, CTL recruitment times, and initial memory CTL populations. Our results indicate that an anti-cancer memory CTL pool of 3% or less can successfully eradicate a tumor population over a wide range of model parameters, implying that a vaccination approach is feasible. In addition, sensitivity analysis of our model reveals conditions that will result in rapid tumor destruction, oscillation, and polynomial rather than exponential decline in the tumor population due to tumor geometry. PMID:23133347

Recapitulation of complex transport and action of drugs at tumor microenvironment using tumor-microenvironment-on-chip

PubMed Central

Han, Bumsoo; Qu, Chunjing; Park, Kinam; Konieczny, Stephen F.; Korc, Murray

2016-01-01

Targeted delivery aims to selectively distribute drugs to targeted tumor tissue but not to healthy tissue. This can address many of clinical challenges by maximizing the efficacy but minimizing the toxicity of anti-cancer drugs. However, complex tumor microenvironment poses various barriers hindering the transport of drugs and drug delivery systems. New tumor models that allow for the systematic study of these complex environments are highly desired to provide reliable test beds to develop drug delivery systems for targeted delivery. Recently, research efforts have yielded new in vitro tumor models, the so called tumor-microenvironment-on-chip, that recapitulate certain characteristics of the tumor microenvironment. These new models show benefits over other conventional tumor models, and have the potential to accelerate drug discovery and enable precision medicines. However, further research is warranted to overcome their limitations and to properly interpret the data obtained from these models. In this article, key features of the in vivo tumor microenvironment that are relevant to drug transport processes for targeted delivery was discussed, and the current status and challenges for developing in vitro transport model systems was reviewed. PMID:26688098

Computational Modeling of 3D Tumor Growth and Angiogenesis for Chemotherapy Evaluation

PubMed Central

Tang, Lei; van de Ven, Anne L.; Guo, Dongmin; Andasari, Vivi; Cristini, Vittorio; Li, King C.; Zhou, Xiaobo

2014-01-01

Solid tumors develop abnormally at spatial and temporal scales, giving rise to biophysical barriers that impact anti-tumor chemotherapy. This may increase the expenditure and time for conventional drug pharmacokinetic and pharmacodynamic studies. In order to facilitate drug discovery, we propose a mathematical model that couples three-dimensional tumor growth and angiogenesis to simulate tumor progression for chemotherapy evaluation. This application-oriented model incorporates complex dynamical processes including cell- and vascular-mediated interstitial pressure, mass transport, angiogenesis, cell proliferation, and vessel maturation to model tumor progression through multiple stages including tumor initiation, avascular growth, and transition from avascular to vascular growth. Compared to pure mechanistic models, the proposed empirical methods are not only easy to conduct but can provide realistic predictions and calculations. A series of computational simulations were conducted to demonstrate the advantages of the proposed comprehensive model. The computational simulation results suggest that solid tumor geometry is related to the interstitial pressure, such that tumors with high interstitial pressure are more likely to develop dendritic structures than those with low interstitial pressure. PMID:24404145

Parent-child communication and psychological adjustment in children with a brain tumor.

PubMed

Adduci, Annarita; Jankovic, Momcilo; Strazzer, Sandra; Massimino, Maura; Clerici, Carlo; Poggi, Geraldina

2012-08-01

Internalizing problems, anxiety, depression, withdrawal, and consequent social problems are frequently observed in children with brain tumors. The objective of this work is to describe the relationship between these psychological problems and the type of parent-child communication established about the disease. A group of 64 children surviving a brain tumor (aged 4-18 years) underwent psychological assessment by means of parent reports on the Child Behavior Checklist (CBCL) and the Vineland Adaptive Behavior Scales (VABS). A semi-structured interview with each child and their parents enabled us to classify the method of communication regarding the disease as "avoidance," "ineffective," and "effective." Demographic, clinical, and functional data relating to the disease were also collected. A significant relationship between the onset of Internalizing problems, withdrawal, anxiety-depression, and social problems and the presence of avoidance or ineffective communication about the disease was observed (P = 0.001, P = 0.001, P = 0.001, and P = 0.01, respectively). These psychological problems did not prove to be associated to demographic or clinical variables; however, they were found to be related to the children's residual functional problems. By contrast, the method of communication proved to be unrelated to clinical or functional variables, but it was associated to demographic variables such as sex and age at assessment. Effective (complete, truthful, consistent, comprehensible, gradual and continuous, and tailored) communication to the child about his/her condition proved to be associated with a better psychological outcome. Copyright © 2012 Wiley Periodicals, Inc.

Developing a Training Program in Breast Cancer Research to Decrease the Disparity of Morbidity and Mortality in Underserved/Minority Women

DTIC Science & Technology

2005-10-01

fingers and the ability of elderly minority women to detect breast tumor size? Research Model Function "* Range of Motion0. AblttoD ec Age S~Cormobidity...Future" National conference to end health disparities, Sept. 27-29 WS, NC Factors Affecting Breast Cancer Screening Adherence in Older African American...designated Historically Black College and University (HBCU) is committed to resolving some of the economic, social and health problems in the community in

Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

From a Content Delivery Portal to a Knowledge Management System for Standardized Cancer Documentation.

PubMed

Schlue, Danijela; Mate, Sebastian; Haier, Jörg; Kadioglu, Dennis; Prokosch, Hans-Ulrich; Breil, Bernhard

2017-01-01

Heterogeneous tumor documentation and its challenges of interpretation of medical terms lead to problems in analyses of data from clinical and epidemiological cancer registries. The objective of this project was to design, implement and improve a national content delivery portal for oncological terms. Data elements of existing handbooks and documentation sources were analyzed, combined and summarized by medical experts of different comprehensive cancer centers. Informatics experts created a generic data model based on an existing metadata repository. In order to establish a national knowledge management system for standardized cancer documentation, a prototypical tumor wiki was designed and implemented. Requirements engineering techniques were applied to optimize this platform. It is targeted to user groups such as documentation officers, physicians and patients. The linkage to other information sources like PubMed and MeSH was realized.

Comparing nonparametric Bayesian tree priors for clonal reconstruction of tumors.

PubMed

Deshwar, Amit G; Vembu, Shankar; Morris, Quaid

2015-01-01

Statistical machine learning methods, especially nonparametric Bayesian methods, have become increasingly popular to infer clonal population structure of tumors. Here we describe the treeCRP, an extension of the Chinese restaurant process (CRP), a popular construction used in nonparametric mixture models, to infer the phylogeny and genotype of major subclonal lineages represented in the population of cancer cells. We also propose new split-merge updates tailored to the subclonal reconstruction problem that improve the mixing time of Markov chains. In comparisons with the tree-structured stick breaking prior used in PhyloSub, we demonstrate superior mixing and running time using the treeCRP with our new split-merge procedures. We also show that given the same number of samples, TSSB and treeCRP have similar ability to recover the subclonal structure of a tumor…

A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Espinoza, I., E-mail: iespinoza@fis.puc.cl; Peschke, P.; Karger, C. P.

2015-01-15

Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii)more » hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the model, tumor shrinkage was found to be significantly more important for reoxygenation than angiogenesis or decreased oxygen consumption due to an increased fraction of dead cells. In the studied HNSSC-case, the TCD{sub 50} values (dose at 50% TCP) decreased from 71.0 Gy under hypoxic to 53.6 Gy under the oxic condition. Conclusions: The results obtained with the developed multiscale model are in accordance with expectations based on radiobiological principles and clinical experience. As the model is voxel-based, radiological imaging methods may help to provide the required 3D-characterization of the tumor prior to irradiation. For clinical application, the model has to be further validated with experimental and clinical data. If this is achieved, the model may be used to optimize fractionation schedules and dose distributions for the treatment of hypoxic tumors.« less

Establishment and characterization of intraperitoneal xenograft models by co-injection of human tumor cells and extracellular matrix gel

PubMed Central

YAO, YUQIN; ZHOU, YONGJUN; SU, XIAOLAN; DAI, LEI; YU, LIN; DENG, HONGXIN; GOU, LANTU; YANG, JINLIANG

2015-01-01

Establishing a feasible intraperitoneal (i.p.) xenograft model in nude mice is a good strategy to evaluate the antitumor effect of drugs in vivo. However, the manipulation of human cancer cells in establishing a stable peritoneal carcinomatosis model in nude mice is problematic. In the present study, the ovarian and colorectal peritoneal tumor models were successfully established in nude mice by co-injection of human tumor cells and extracellular matrix gel. In ovarian tumor models, the mean number tumor nodes was significantly higher in the experimental group (intraperitoneal tumor cell co-injection with ECM gel) compared with the PBS control group on the 30th day (21.0±3.0 vs. 3.6±2.5; P<0.05). The same results were observed in the colorectal peritoneal tumor models on the 28th day. The colorectal peritoneal tumor model was further used to evaluate the chemotherapy effect of irinotecan (CPT-11). The mean weight of peritoneal tumor nodes in CPT-11 treatment group was significantly less than that of the control group (0.81±0.16 vs. 2.18±0.21 g; P<0.05). The results confirmed the value of these i.p. xenograft models in nude mice as efficient and feasible tools for preclinical evaluation. PMID:26788149

The pivotal role of angiogenesis in a multi-scale modeling of tumor growth exhibiting the avascular and vascular phases.

PubMed

Salavati, Hooman; Soltani, M; Amanpour, Saeid

2018-05-06

The mechanisms involved in tumor growth mainly occur at the microenvironment, where the interactions between the intracellular, intercellular and extracellular scales mediate the dynamics of tumor. In this work, we present a multi-scale model of solid tumor dynamics to simulate the avascular and vascular growth as well as tumor-induced angiogenesis. The extracellular and intercellular scales are modeled using partial differential equations and cellular Potts model, respectively. Also, few biochemical and biophysical rules control the dynamics of intracellular level. On the other hand, the growth of melanoma tumors is modeled in an animal in-vivo study to evaluate the simulation. The simulation shows that the model successfully reproduces a completed image of processes involved in tumor growth such as avascular and vascular growth as well as angiogenesis. The model incorporates the phenotypes of cancerous cells including proliferating, quiescent and necrotic cells, as well as endothelial cells during angiogenesis. The results clearly demonstrate the pivotal effect of angiogenesis on the progression of cancerous cells. Also, the model exhibits important events in tumor-induced angiogenesis like anastomosis. Moreover, the computational trend of tumor growth closely follows the observations in the experimental study. Copyright © 2018 Elsevier Inc. All rights reserved.

The impact of including spatially longitudinal heterogeneities of vessel oxygen content and vascular fraction in 3D tumor oxygenation models on predicted radiation sensitivity.

PubMed

Lagerlöf, Jakob H; Kindblom, Jon; Bernhardt, Peter

2014-04-01

Oxygen distribution models have been used to analyze the influences of oxygen tensions on tissue response after radiotherapy. These distributions are often generated assuming constant oxygen tension in the blood vessels. However, as red blood cells progress through the vessels, oxygen is continuously released into the plasma and the surrounding tissue, resulting in longitudinally varying oxygen levels in the blood vessels. In the present study, the authors investigated whether a tumor oxygenation model that incorporated longitudinally varying oxygen levels would provide different predictions of necrotic fractions and radiosensitivity compared to commonly used models with a constant oxygen pressure. Our models simulated oxygen diffusion based on a Green's function approach and oxygen consumption according to the Michaelis-Menten equation. The authors constructed tumor models with different vascular fractions (VFs), from which they generated depth oxygenation curves and a look-up table of oxygen pressure gradients. The authors evaluated models of spherical tumors of various sizes, from 1 to 10(4) mg. The authors compared the results from a model with constant vessel oxygen (CVO) pressure to those from models with longitudinal variations in oxygen saturation and either a constant VF (CVF) or variable VF (VVF) within the tumor tissue. The authors monitored the necrotic fractions, defined as tumor regions with an oxygen pressure below 1 mmHg. Tumor radiation sensitivity was expressed as D99, the homogeneous radiation dose required for a tumor control probability of 0.99. In the CVO saturation model, no necrosis was observed, and decreasing the VF could only decrease the D99 by up to 10%. Furthermore, the D99 vs VF dependence was similar for different tumor masses. Compared to the CVO model, the extended CVF and VVF models provided clearly different results, including pronounced effects of VF and tumor size on the necrotic fraction and D99, necrotic fractions ranging from 0% to 97%, and a maximal D99 increment of 57%. Only minor differences were observed between different vessel architectures, i.e., CVF vs VVF. In the smallest tumor with a low necrotic fraction, the D99 strictly decreased with increasing blood velocity. Increasing blood velocity also decreased the necrotic fraction in all tumor sizes. VF had the most profound influence on both the necrotic fraction and on D99. Our present analysis of necrotic formation and the impact of tumor oxygenation on D99 demonstrated the importance of including longitudinal variations in vessel oxygen content in tumor models. For small tumors, radiosensitivity was particularly dependent on VF and slightly dependent on the blood velocity and vessel arrangement. These dependences decreased with increasing tumor size, because the necrotic fraction also increased, thereby decreasing the number of viable tumor cells that required sterilization. The authors anticipate that the present model will be useful for estimating tumor oxygenation and radiation response in future detailed studies. © 2014 American Association of Physicists in Medicine.

Tumor promotion and inhibition by phenobarbital in livers of conditional Apc-deficient mice.

PubMed

Braeuning, Albert; Gavrilov, Alina; Geissler, Miriam; Wenz, Christine; Colnot, Sabine; Templin, Markus F; Metzger, Ute; Römer, Michael; Zell, Andreas; Schwarz, Michael

2016-06-01

Activation of Wnt/β-catenin signaling is important for human and rodent hepatocarcinogenesis. In mice, the tumor promoter phenobarbital (PB) selects for hepatocellular tumors with activating β-catenin mutations via constitutive androstane receptor activation. PB-dependent tumor promotion was studied in mice with genetic inactivation of Apc, a negative regulator of β-catenin, to circumvent the problem of randomly induced mutations by chemical initiators and to allow monitoring of PB- and Wnt/β-catenin-dependent tumorigenesis in the absence of unknown genomic alterations. Moreover, the study was designed to investigate PB-induced proliferation of liver cells with activated β-catenin. PB treatment provided Apc-deficient hepatocytes with only a minor proliferative advantage, and additional connexin 32 deficiency did not affect the proliferative response. PB significantly promoted the outgrowth of Apc-deficient hepatocellular adenoma (HCA), but simultaneously inhibited the formation of Apc-deficient hepatocellular carcinoma (HCC). The probability of tumor promotion by PB was calculated to be much lower for hepatocytes with loss of Apc, as compared to mutational β-catenin activation. Comprehensive transcriptomic and phosphoproteomic characterization of HCA and HCC revealed molecular details of the two tumor types. HCC were characterized by a loss of differentiated hepatocellular gene expression, enhanced proliferative signaling, and massive over-activation of Wnt/β-catenin signaling. In conclusion, PB exerts a dual role in liver tumor formation by promoting the growth of HCA but inhibiting the growth of HCC. Data demonstrate that one and the same compound can produce opposite effects on hepatocarcinogenesis, depending on context, highlighting the necessity to develop a more differentiated view on the tumorigenicity of this model compound.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Local and systemic tumor immune dynamics

NASA Astrophysics Data System (ADS)

Enderling, Heiko

Tumor-associated antigens, stress proteins, and danger-associated molecular patterns are endogenous immune adjuvants that can both initiate and continually stimulate an immune response against a tumor. In retaliation, tumors can hijack intrinsic immune regulatory programs that are intended to prevent autoimmune disease, thereby facilitating continued growth despite the activated antitumor immune response. In metastatic disease, this ongoing tumor-immune battle occurs at each site. Adding an additional layer of complexity, T cells activated at one tumor site can cycle through the blood circulation system and extravasate in a different anatomic location to surveil a distant metastasis. We propose a mathematical modeling framework that incorporates the trafficking of activated T cells between metastatic sites. We extend an ordinary differential equation model of tumor-immune system interactions to multiple metastatic sites. Immune cells are activated in response to tumor burden and tumor cell death, and are recruited from tumor sites elsewhere in the body. A model of T cell trafficking throughout the circulatory system can inform the tumor-immune interaction model about the systemic distribution and arrival of T cells at specific tumor sites. Model simulations suggest that metastases not only contribute to immune surveillance, but also that this contribution varies between metastatic sites. Such information may ultimately help harness the synergy of focal therapy with the immune system to control metastatic disease.

Targeting Cancer Protein Profiles with Split-Enzyme Reporter Fragments to Achieve Chemical Resolution for Molecular Imaging

DTIC Science & Technology

2013-08-01

We next tested the utility of the construct to accumulate in tumors expressing EGFR using an orthotopic mouse model for brain tumors. Glioma cells...filament tumor marker, identified implanted cells within the orthotopic mouse model which were of human origin, i.e. Gli36Δ5 cells, and demonstrated that...forward into in vivo animal tumor model studies. • In vivo imaging of EGFR targeted-complex in orthotopic mouse model of brain tumor. • Ex vivo validation

Mice with cancer-induced bone pain show a marked decline in day/night activity

PubMed Central

Majuta, Lisa A.; Guedon, Jean-Marc G.; Mitchell, Stefanie A.T.; Kuskowski, Michael A.; Mantyh, Patrick W.

2017-01-01

Abstract Introduction: Cancer-induced bone pain (CIBP) is the most common type of pain with cancer. In humans, this pain can be difficult to control and highly disabling. A major problem with CIBP in humans is that it increases on weight-bearing and/or movement of a tumor-bearing bone limiting the activity and functional status of the patient. Currently, there is less data concerning whether similar negative changes in activity occur in rodent models of CIBP. Objectives: To determine whether there are marked changes in activity in a rodent model of CIBP and compare this to changes in skin hypersensitivity. Methods: Osteosarcoma cells were injected and confined to 1 femur of the adult male mouse. Every 7 days, spontaneous horizontal and vertical activities were assessed over a 20-hour day and night period using automated activity boxes. Mechanical hypersensitivity of the hind paw skin was assessed using von Frey testing. Results: As the tumor cells grew within the femur, there was a significant decline in horizontal and vertical activity during the times of the day/night when the mice are normally most active. Mice also developed significant hypersensitivity in the skin of the hind paw in the tumor-bearing limb. Conclusion: Even when the tumor is confined to a single load-bearing bone, CIBP drives a significant loss of activity, which increases with disease progression. Understanding the mechanisms that drive this reduction in activity may allow the development of therapies that allow CIBP patients to better maintain their activity and functional status. PMID:29392229

2016 Children's Tumor Foundation conference on neurofibromatosis type 1, neurofibromatosis type 2, and schwannomatosis.

PubMed

Fisher, Michael J; Belzberg, Allan J; de Blank, Peter; De Raedt, Thomas; Elefteriou, Florent; Ferner, Rosalie E; Giovannini, Marco; Harris, Gordon J; Kalamarides, Michel; Karajannis, Matthias A; Kim, AeRang; Lázaro, Conxi; Le, Lu Q; Li, Wei; Listernick, Robert; Martin, Staci; Morrison, Helen; Pasmant, Eric; Ratner, Nancy; Schorry, Elisabeth; Ullrich, Nicole J; Viskochil, David; Weiss, Brian; Widemann, Brigitte C; Zhu, Yuan; Bakker, Annette; Serra, Eduard

2018-05-01

Organized and hosted by the Children's Tumor Foundation (CTF), the Neurofibromatosis (NF) conference is the premier annual gathering for clinicians and researchers interested in neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN). The 2016 edition constituted a blend of clinical and basic aspects of NF research that helped in clarifying different advances in the field. The incorporation of next generation sequencing is changing the way genetic diagnostics is performed for NF and related disorders, providing solutions to problems like genetic heterogeneity, overlapping clinical manifestations, or the presence of mosaicism. The transformation from plexiform neurofibroma (PNF) to malignant peripheral nerve sheath tumor (MPNST) is being clarified, along with new management and treatments for benign and premalignant tumors. Promising new cellular and in vivo models for understanding the musculoskeletal abnormalities in NF1, the development of NF2 or SWN associated schwannomas, and clarifying the cells that give rise to NF1-associated optic pathway glioma were presented. The interaction of neurofibromin and SPRED1 was described comprehensively, providing functional insight that will help in the interpretation of pathogenicity of certain missense variants identified in NF1 and Legius syndrome patients. Novel promising imaging techniques are being developed, as well as new integrative and holistic management models for patients that take into account psychological, social, and biological factors. Importantly, new therapeutic approaches for schwannomas, meningiomas, ependymomas, PNF, and MPNST are being pursued. This report highlights the major advances that were presented at the 2016 CTF NF conference. © 2018 Wiley Periodicals, Inc.

[Modern biomaterials as hemostatic dressings in kidney nephron sparing surgery (NSS)--murine model. A preliminary report].

PubMed

Nowacki, Maciej; Jundziłł, Arkadiusz; Bieniek, Miłosz; Kowalczyk, Tomasz; Kloskowski, Tomasz; Drewa, Tomasz

2012-01-01

Kidney cancer is now days, one of the main problems in oncological urology. More frequent cases detection of this type of cancer and the implementation of modern methods of treatment, involves the public and good diagnostic radiological imaging methods. Approximately 40% of renal tumors are detected clinically as a changes in T1N0M0 stage. This means that in these patients, surgery can be performed using the method of nephron sparing surgery (NSS), far from consisting the implementation of radical nephrectomy. Unfortunately, despite the saving nature of this type of treatment, NSS methods are associated with local recurrence of tumor formation. Another problem is intra operative bleeding, that's why in order to stop this negative process surgeons currently use hemostatic dressings. Potentially and clinically significant solution could be a combination of this two main problematics points of concern, through the use of modern biomaterials coated on oncostatic substances as a haemostatic dressings, to the prevention of tumor recurrence. The aim of this work, was to present preliminary report of the use of advanced biomaterials, as haemostatic dressings in an experimental technique of nephron sparing surgery on an murine model. In the experiment we use two types of biomaterials and the standard haemostatic dressing used in the nephron sparing surgery (NSS) as a control. We use a polycaprolactone biomaterial obtained by electrospinning. As a second type of biomaterial, we use a homogeneous material with a structure similar to wool, also obtained from medical polycaprolactone by electrospinning. As an murine (in vivo) model in the study, we use 10 C57BL/J mice (with the local ethical committee permission). 8 mice were used in the present study, 2 mice were constituted as a separate control for obtaining the bleeding data. Kidney melanoma cells were implanted under the C57B1/J B16 mouse kidney fibrous capsule, one week before NSS. After 3 weeks the animals were sacrificed for comparison of hemostatic dressings function. Used biomaterials fulfilled their role as a hameostatic dresings. The material (Type I) was convenient and good for suturing. Haemostatic action times were as follows: (Type I) - 30 seconds. (Type III) - 50 seconds. In the control group were also observed, a proper hemostatic function after 30 seconds. In sectional observation was also found in 3 kidneys section preparation samples, a local tumor recurrence and metastasis to the other tissues of the abdomen. The tested biomaterials fulfill their hemostatic effect on kidney after NSS, without any significant difference acording to a standard hemostatic dressing used clinically. This data may be a potential factor for use in further studies to determine their continued relevance in the prevention of local tumor recurrence after nephron sparing surgery.

Vaginal delivery of carboplatin-loaded thermosensitive hydrogel to prevent local cervical cancer recurrence in mice.

PubMed

Wang, Xue; Wang, Jin; Wu, Wenbin; Li, Hongjun

2016-11-01

Local tumor recurrence after cervical cancer surgery remains a clinical problem. Vaginal delivery of thermosensitive hydrogel may be suited to reduce tumor relapse rate with more efficacy and safety. A pilot study was carried out to evaluate the efficacy of carboplatin-loaded poloxamer hydrogel to prevent local recurrence of cervical cancer after surgery. In vivo vaginal retention evaluation of 27% poloxamer hydrogel in mice was proven to be a suitable vaginal drug delivery formulation due to its low gelation temperature. A mimic orthotopic cervical/vaginal cancer recurrence model after surgery was established by injecting murine cervical cancer cell line U14 into the vaginal submucosa to simulate the residual tumor cells infiltrated in the surgical site, followed by drug administration 24 h later to interfere with the formation/recurrence of the tumor. By infusing fluorescein sodium-loaded hydrogel into the vagina of mice, a maximized accumulation of fluorescein sodium (Flu) in the vagina was achieved and few signals were observed in other organs. When used in the prevention of the cervical cancer formation/recurrence in mice, the carboplatin-loaded poloxamer hydrogel exhibited great efficacy and systemic safety. In conclusion, thermosensitive hydrogel presents a simple, practical approach for the local drug delivery via vagina against cervical cancer recurrence.

Initiation and Characterization of Small Cell Lung Cancer Patient-Derived Xenografts from Ultrasound-Guided Transbronchial Needle Aspirates

PubMed Central

Anderson, Wade C.; Boyd, Michael B.; Aguilar, Jorge; Pickell, Brett; Laysang, Amy; Pysz, Marybeth A.; Bheddah, Sheila; Ramoth, Johanna; Slingerland, Brian C.; Dylla, Scott J.; Rubio, Edmundo R.

2015-01-01

Small cell lung cancer (SCLC) is a devastating disease with limited treatment options. Due to its early metastatic nature and rapid growth, surgical resection is rare. Standard of care treatment regimens remain largely unchanged since the 1980’s, and five-year survival lingers near 5%. Patient-derived xenograft (PDX) models have been established for other tumor types, amplifying material for research and serving as models for preclinical experimentation; however, limited availability of primary tissue has curtailed development of these models for SCLC. The objective of this study was to establish PDX models from commonly collected fine needle aspirate biopsies of primary SCLC tumors, and to assess their utility as research models of primary SCLC tumors. These transbronchial needle aspirates efficiently engrafted as xenografts, and tumor histomorphology was similar to primary tumors. Resulting tumors were further characterized by H&E and immunohistochemistry, cryopreserved, and used to propagate tumor-bearing mice for the evaluation of standard of care chemotherapy regimens, to assess their utility as models for tumors in SCLC patients. When treated with Cisplatin and Etoposide, tumor-bearing mice responded similarly to patients from whom the tumors originated. Here, we demonstrate that PDX tumor models can be efficiently established from primary SCLC transbronchial needle aspirates, even after overnight shipping, and that resulting xenograft tumors are similar to matched primary tumors in cancer patients by both histology and chemo-sensitivity. This method enables physicians at non-research institutions to collaboratively contribute to the rapid establishment of extensive PDX collections of SCLC, enabling experimentation with clinically relevant tissues and development of improved therapies for SCLC patients. PMID:25955027

Surgical planning and manual image fusion based on 3D model facilitate laparoscopic partial nephrectomy for intrarenal tumors.

PubMed

Chen, Yuanbo; Li, Hulin; Wu, Dingtao; Bi, Keming; Liu, Chunxiao

2014-12-01

Construction of three-dimensional (3D) model of renal tumor facilitated surgical planning and imaging guidance of manual image fusion in laparoscopic partial nephrectomy (LPN) for intrarenal tumors. Fifteen patients with intrarenal tumors underwent LPN between January and December 2012. Computed tomography-based reconstruction of the 3D models of renal tumors was performed using Mimics 12.1 software. Surgical planning was performed through morphometry and multi-angle visual views of the tumor model. Two-step manual image fusion superimposed 3D model images onto 2D laparoscopic images. The image fusion was verified by intraoperative ultrasound. Imaging-guided laparoscopic hilar clamping and tumor excision was performed. Manual fusion time, patient demographics, surgical details, and postoperative treatment parameters were analyzed. The reconstructed 3D tumor models accurately represented the patient's physiological anatomical landmarks. The surgical planning markers were marked successfully. Manual image fusion was flexible and feasible with fusion time of 6 min (5-7 min). All surgeries were completed laparoscopically. The median tumor excision time was 5.4 min (3.5-10 min), whereas the median warm ischemia time was 25.5 min (16-32 min). Twelve patients (80 %) demonstrated renal cell carcinoma on final pathology, and all surgical margins were negative. No tumor recurrence was detected after a media follow-up of 1 year (3-15 months). The surgical planning and two-step manual image fusion based on 3D model of renal tumor facilitated visible-imaging-guided tumor resection with negative margin in LPN for intrarenal tumor. It is promising and moves us one step closer to imaging-guided surgery.

A 3-D model of tumor progression based on complex automata driven by particle dynamics.

PubMed

Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z

2009-12-01

The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.

Tumor-volume simulation during radiotherapy for head-and-neck cancer using a four-level cell population model.

PubMed

Chvetsov, Alexei V; Dong, Lei; Palta, Jantinder R; Amdur, Robert J

2009-10-01

To develop a fast computational radiobiologic model for quantitative analysis of tumor volume during fractionated radiotherapy. The tumor-volume model can be useful for optimizing image-guidance protocols and four-dimensional treatment simulations in proton therapy that is highly sensitive to physiologic changes. The analysis is performed using two approximations: (1) tumor volume is a linear function of total cell number and (2) tumor-cell population is separated into four subpopulations: oxygenated viable cells, oxygenated lethally damaged cells, hypoxic viable cells, and hypoxic lethally damaged cells. An exponential decay model is used for disintegration and removal of oxygenated lethally damaged cells from the tumor. We tested our model on daily volumetric imaging data available for 14 head-and-neck cancer patients treated with an integrated computed tomography/linear accelerator system. A simulation based on the averaged values of radiobiologic parameters was able to describe eight cases during the entire treatment and four cases partially (50% of treatment time) with a maximum 20% error. The largest discrepancies between the model and clinical data were obtained for small tumors, which may be explained by larger errors in the manual tumor volume delineation procedure. Our results indicate that the change in gross tumor volume for head-and-neck cancer can be adequately described by a relatively simple radiobiologic model. In future research, we propose to study the variation of model parameters by fitting to clinical data for a cohort of patients with head-and-neck cancer and other tumors. The potential impact of other processes, like concurrent chemotherapy, on tumor volume should be evaluated.

Establishment of a tumor neovascularization animal model with biomaterials in rabbit corneal pouch.

PubMed

Chu, Yu-Ping; Li, Hong-Chuan; Ma, Ling; Xia, Yang

2018-06-01

The present animal model of tumor neovascularization most often used by researchers is zebrafish. For studies on human breast cancer cell neovascularization, a new animal model was established to enable a more convenient study of tumor neovascularization. A sodium alginate-gelatin blend gel system was used to design the new animal model. The model was established using rabbit corneal pouch implantation. Then, the animal model was validated by human breast cancer cell lines MCF-7-Kindlin-2 and MCF-7-CMV. The experiment intuitively observed the relationship between tumor and neovascularization, and demonstrated the advantages of this animal model in the study of tumor neovascularization. The use of sodium alginate-gelatin blends to establish tumor neovascularization in a rabbit corneal pouch is a novel and ideal method for the study of neovascularization. It may be a better animal model for expanding the research in this area. Copyright © 2018 Elsevier Inc. All rights reserved.

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

2008-04-01

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Tissue engineered tumor models.

PubMed

Ingram, M; Techy, G B; Ward, B R; Imam, S A; Atkinson, R; Ho, H; Taylor, C R

2010-08-01

Many research programs use well-characterized tumor cell lines as tumor models for in vitro studies. Because tumor cells grown as three-dimensional (3-D) structures have been shown to behave more like tumors in vivo than do cells growing in monolayer culture, a growing number of investigators now use tumor cell spheroids as models. Single cell type spheroids, however, do not model the stromal-epithelial interactions that have an important role in controlling tumor growth and development in vivo. We describe here a method for generating, reproducibly, more realistic 3-D tumor models that contain both stromal and malignant epithelial cells with an architecture that closely resembles that of tumor microlesions in vivo. Because they are so tissue-like we refer to them as tumor histoids. They can be generated reproducibly in substantial quantities. The bioreactor developed to generate histoid constructs is described and illustrated. It accommodates disposable culture chambers that have filled volumes of either 10 or 64 ml, each culture yielding on the order of 100 or 600 histoid particles, respectively. Each particle is a few tenths of a millimeter in diameter. Examples of histological sections of tumor histoids representing cancers of breast, prostate, colon, pancreas and urinary bladder are presented. Potential applications of tumor histoids include, but are not limited to, use as surrogate tumors for pre-screening anti-solid tumor pharmaceutical agents, as reference specimens for immunostaining in the surgical pathology laboratory and use in studies of invasive properties of cells or other aspects of tumor development and progression. Histoids containing nonmalignant cells also may have potential as "seeds" in tissue engineering. For drug testing, histoids probably will have to meet certain criteria of size and tumor cell content. Using a COPAS Plus flow cytometer, histoids containing fluorescent tumor cells were analyzed successfully and sorted using such criteria.

Engineering cancer microenvironments for in vitro 3-D tumor models

PubMed Central

Asghar, Waseem; El Assal, Rami; Shafiee, Hadi; Pitteri, Sharon; Paulmurugan, Ramasamy; Demirci, Utkan

2017-01-01

The natural microenvironment of tumors is composed of extracellular matrix (ECM), blood vasculature, and supporting stromal cells. The physical characteristics of ECM as well as the cellular components play a vital role in controlling cancer cell proliferation, apoptosis, metabolism, and differentiation. To mimic the tumor microenvironment outside the human body for drug testing, two-dimensional (2-D) and murine tumor models are routinely used. Although these conventional approaches are employed in preclinical studies, they still present challenges. For example, murine tumor models are expensive and difficult to adopt for routine drug screening. On the other hand, 2-D in vitro models are simple to perform, but they do not recapitulate natural tumor microenvironment, because they do not capture important three-dimensional (3-D) cell–cell, cell–matrix signaling pathways, and multi-cellular heterogeneous components of the tumor microenvironment such as stromal and immune cells. The three-dimensional (3-D) in vitro tumor models aim to closely mimic cancer microenvironments and have emerged as an alternative to routinely used methods for drug screening. Herein, we review recent advances in 3-D tumor model generation and highlight directions for future applications in drug testing. PMID:28458612

Genomic characterization of explant tumorgraft models derived from fresh patient tumor tissue

PubMed Central

2012-01-01

Background There is resurgence within drug and biomarker development communities for the use of primary tumorgraft models as improved predictors of patient tumor response to novel therapeutic strategies. Despite perceived advantages over cell line derived xenograft models, there is limited data comparing the genotype and phenotype of tumorgrafts to the donor patient tumor, limiting the determination of molecular relevance of the tumorgraft model. This report directly compares the genomic characteristics of patient tumors and the derived tumorgraft models, including gene expression, and oncogenic mutation status. Methods Fresh tumor tissues from 182 cancer patients were implanted subcutaneously into immune-compromised mice for the development of primary patient tumorgraft models. Histological assessment was performed on both patient tumors and the resulting tumorgraft models. Somatic mutations in key oncogenes and gene expression levels of resulting tumorgrafts were compared to the matched patient tumors using the OncoCarta (Sequenom, San Diego, CA) and human gene microarray (Affymetrix, Santa Clara, CA) platforms respectively. The genomic stability of the established tumorgrafts was assessed across serial in vivo generations in a representative subset of models. The genomes of patient tumors that formed tumorgrafts were compared to those that did not to identify the possible molecular basis to successful engraftment or rejection. Results Fresh tumor tissues from 182 cancer patients were implanted into immune-compromised mice with forty-nine tumorgraft models that have been successfully established, exhibiting strong histological and genomic fidelity to the originating patient tumors. Comparison of the transcriptomes and oncogenic mutations between the tumorgrafts and the matched patient tumors were found to be stable across four tumorgraft generations. Not only did the various tumors retain the differentiation pattern, but supporting stromal elements were preserved. Those genes down-regulated specifically in tumorgrafts were enriched in biological pathways involved in host immune response, consistent with the immune deficiency status of the host. Patient tumors that successfully formed tumorgrafts were enriched for cell signaling, cell cycle, and cytoskeleton pathways and exhibited evidence of reduced immunogenicity. Conclusions The preservation of the patient’s tumor genomic profile and tumor microenvironment supports the view that primary patient tumorgrafts provide a relevant model to support the translation of new therapeutic strategies and personalized medicine approaches in oncology. PMID:22709571

Galectin-1 Inhibitor OTX008 Induces Tumor Vessel Normalization and Tumor Growth Inhibition in Human Head and Neck Squamous Cell Carcinoma Models.

PubMed

Koonce, Nathan A; Griffin, Robert J; Dings, Ruud P M

2017-12-09

Galectin-1 is a hypoxia-regulated protein and a prognostic marker in head and neck squamous cell carcinomas (HNSCC). Here we assessed the ability of non-peptidic galectin-1 inhibitor OTX008 to improve tumor oxygenation levels via tumor vessel normalization as well as tumor growth inhibition in two human HNSCC tumor models, the human laryngeal squamous carcinoma SQ20B and the human epithelial type 2 HEp-2. Tumor-bearing mice were treated with OTX008, Anginex, or Avastin and oxygen levels were determined by fiber-optics and molecular marker pimonidazole binding. Immuno-fluorescence was used to determine vessel normalization status. Continued OTX008 treatment caused a transient reoxygenation in SQ20B tumors peaking on day 14, while a steady increase in tumor oxygenation was observed over 21 days in the HEp-2 model. A >50% decrease in immunohistochemical staining for tumor hypoxia verified the oxygenation data measured using a partial pressure of oxygen (pO₂) probe. Additionally, OTX008 induced tumor vessel normalization as tumor pericyte coverage increased by approximately 40% without inducing any toxicity. Moreover, OTX008 inhibited tumor growth as effectively as Anginex and Avastin, except in the HEp-2 model where Avastin was found to suspend tumor growth. Galectin-1 inhibitor OTX008 transiently increased overall tumor oxygenation via vessel normalization to various degrees in both HNSCC models. These findings suggest that targeting galectin-1-e.g., by OTX008-may be an effective approach to treat cancer patients as stand-alone therapy or in combination with other standards of care.

Emergence of Convolutional Neural Network in Future Medicine: Why and How. A Review on Brain Tumor Segmentation

NASA Astrophysics Data System (ADS)

Alizadeh Savareh, Behrouz; Emami, Hassan; Hajiabadi, Mohamadreza; Ghafoori, Mahyar; Majid Azimi, Seyed

2018-03-01

Manual analysis of brain tumors magnetic resonance images is usually accompanied by some problem. Several techniques have been proposed for the brain tumor segmentation. This study will be focused on searching popular databases for related studies, theoretical and practical aspects of Convolutional Neural Network surveyed in brain tumor segmentation. Based on our findings, details about related studies including the datasets used, evaluation parameters, preferred architectures and complementary steps analyzed. Deep learning as a revolutionary idea in image processing, achieved brilliant results in brain tumor segmentation too. This can be continuing until the next revolutionary idea emerging.

A medaka model of cancer allowing direct observation of transplanted tumor cells in vivo at a cellular-level resolution.

PubMed

Hasegawa, Sumitaka; Maruyama, Kouichi; Takenaka, Hikaru; Furukawa, Takako; Saga, Tsuneo

2009-08-18

The recent success with small fish as an animal model of cancer with the aid of fluorescence technique has attracted cancer modelers' attention because it would be possible to directly visualize tumor cells in vivo in real time. Here, we report a medaka model capable of allowing the observation of various cell behaviors of transplanted tumor cells, such as cell proliferation and metastasis, which were visualized easily in vivo. We established medaka melanoma (MM) cells stably expressing GFP and transplanted them into nonirradiated and irradiated medaka. The tumor cells were grown at the injection sites in medaka, and the spatiotemporal changes were visualized under a fluorescence stereoscopic microscope at a cellular-level resolution, and even at a single-cell level. Tumor dormancy and metastasis were also observed. Interestingly, in irradiated medaka, accelerated tumor growth and metastasis of the transplanted tumor cells were directly visualized. Our medaka model provides an opportunity to visualize in vivo tumor cells "as seen in a culture dish" and would be useful for in vivo tumor cell biology.

Emergent Stratification in Solid Tumors Selects for Reduced Cohesion of Tumor Cells: A Multi-Cell, Virtual-Tissue Model of Tumor Evolution Using CompuCell3D.

PubMed

Swat, Maciej H; Thomas, Gilberto L; Shirinifard, Abbas; Clendenon, Sherry G; Glazier, James A

2015-01-01

Tumor cells and structure both evolve due to heritable variation of cell behaviors and selection over periods of weeks to years (somatic evolution). Micro-environmental factors exert selection pressures on tumor-cell behaviors, which influence both the rate and direction of evolution of specific behaviors, especially the development of tumor-cell aggression and resistance to chemotherapies. In this paper, we present, step-by-step, the development of a multi-cell, virtual-tissue model of tumor somatic evolution, simulated using the open-source CompuCell3D modeling environment. Our model includes essential cell behaviors, microenvironmental components and their interactions. Our model provides a platform for exploring selection pressures leading to the evolution of tumor-cell aggression, showing that emergent stratification into regions with different cell survival rates drives the evolution of less cohesive cells with lower levels of cadherins and higher levels of integrins. Such reduced cohesivity is a key hallmark in the progression of many types of solid tumors.

Emergent Stratification in Solid Tumors Selects for Reduced Cohesion of Tumor Cells: A Multi-Cell, Virtual-Tissue Model of Tumor Evolution Using CompuCell3D

PubMed Central

Swat, Maciej H.; Thomas, Gilberto L.; Shirinifard, Abbas; Clendenon, Sherry G.; Glazier, James A.

2015-01-01

Tumor cells and structure both evolve due to heritable variation of cell behaviors and selection over periods of weeks to years (somatic evolution). Micro-environmental factors exert selection pressures on tumor-cell behaviors, which influence both the rate and direction of evolution of specific behaviors, especially the development of tumor-cell aggression and resistance to chemotherapies. In this paper, we present, step-by-step, the development of a multi-cell, virtual-tissue model of tumor somatic evolution, simulated using the open-source CompuCell3D modeling environment. Our model includes essential cell behaviors, microenvironmental components and their interactions. Our model provides a platform for exploring selection pressures leading to the evolution of tumor-cell aggression, showing that emergent stratification into regions with different cell survival rates drives the evolution of less cohesive cells with lower levels of cadherins and higher levels of integrins. Such reduced cohesivity is a key hallmark in the progression of many types of solid tumors. PMID:26083246

On a Nonlinear Model for Tumor Growth: Global in Time Weak Solutions

NASA Astrophysics Data System (ADS)

Donatelli, Donatella; Trivisa, Konstantina

2014-07-01

We investigate the dynamics of a class of tumor growth models known as mixed models. The key characteristic of these type of tumor growth models is that the different populations of cells are continuously present everywhere in the tumor at all times. In this work we focus on the evolution of tumor growth in the presence of proliferating, quiescent and dead cells as well as a nutrient. The system is given by a multi-phase flow model and the tumor is described as a growing continuum Ω with boundary ∂Ω both of which evolve in time. Global-in-time weak solutions are obtained using an approach based on penalization of the boundary behavior, diffusion and viscosity in the weak formulation.

[Neumann's tumor or congenital epulis of the newborn].

PubMed

Cantaloube, D; Rives, J M; Larroque, G; Charrier, J L; Seurat, P

1988-01-01

Congenital epulis is a rare benign gingival tumor affecting mainly female neonates. Histology shows characteristic granular cells. Although diagnosis and therapy fail to raise particular problems, this is not the case for histopathogenesis of lesion. Two cases observed recently in West Africa are reported.

A comparative assessment of preclinical chemotherapeutic response of tumors using quantitative non-Gaussian diffusion MRI

PubMed Central

Xu, Junzhong; Li, Ke; Smith, R. Adam; Waterton, John C.; Zhao, Ping; Ding, Zhaohua; Does, Mark D.; Manning, H. Charles; Gore, John C.

2016-01-01

Background Diffusion-weighted MRI (DWI) signal attenuation is often not mono-exponential (i.e. non-Gaussian diffusion) with stronger diffusion weighting. Several non-Gaussian diffusion models have been developed and may provide new information or higher sensitivity compared with the conventional apparent diffusion coefficient (ADC) method. However the relative merits of these models to detect tumor therapeutic response is not fully clear. Methods Conventional ADC, and three widely-used non-Gaussian models, (bi-exponential, stretched exponential, and statistical model), were implemented and compared for assessing SW620 human colon cancer xenografts responding to barasertib, an agent known to induce apoptosis via polyploidy. Bayesian Information Criterion (BIC) was used for model selection among all three non-Gaussian models. Results All of tumor volume, histology, conventional ADC, and three non-Gaussian DWI models could show significant differences between control and treatment groups after four days of treatment. However, only the non-Gaussian models detected significant changes after two days of treatment. For any treatment or control group, over 65.7% of tumor voxels indicate the bi-exponential model is strongly or very strongly preferred. Conclusion Non-Gaussian DWI model-derived biomarkers are capable of detecting tumor earlier chemotherapeutic response of tumors compared with conventional ADC and tumor volume. The bi-exponential model provides better fitting compared with statistical and stretched exponential models for the tumor and treatment models used in the current work. PMID:27919785

The impact of including spatially longitudinal heterogeneities of vessel oxygen content and vascular fraction in 3D tumor oxygenation models on predicted radiation sensitivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lagerlöf, Jakob H., E-mail: Jakob@radfys.gu.se; Kindblom, Jon; Bernhardt, Peter

2014-04-15

Purpose: Oxygen distribution models have been used to analyze the influences of oxygen tensions on tissue response after radiotherapy. These distributions are often generated assuming constant oxygen tension in the blood vessels. However, as red blood cells progress through the vessels, oxygen is continuously released into the plasma and the surrounding tissue, resulting in longitudinally varying oxygen levels in the blood vessels. In the present study, the authors investigated whether a tumor oxygenation model that incorporated longitudinally varying oxygen levels would provide different predictions of necrotic fractions and radiosensitivity compared to commonly used models with a constant oxygen pressure. Methods:more » Our models simulated oxygen diffusion based on a Green's function approach and oxygen consumption according to the Michaelis-Menten equation. The authors constructed tumor models with different vascular fractions (VFs), from which they generated depth oxygenation curves and a look-up table of oxygen pressure gradients. The authors evaluated models of spherical tumors of various sizes, from 1 to 10{sup 4} mg. The authors compared the results from a model with constant vessel oxygen (CVO) pressure to those from models with longitudinal variations in oxygen saturation and either a constant VF (CVF) or variable VF (VVF) within the tumor tissue. The authors monitored the necrotic fractions, defined as tumor regions with an oxygen pressure below 1 mmHg. Tumor radiation sensitivity was expressed as D{sub 99,} the homogeneous radiation dose required for a tumor control probability of 0.99. Results: In the CVO saturation model, no necrosis was observed, and decreasing the VF could only decrease the D{sub 99} by up to 10%. Furthermore, the D{sub 99} vs VF dependence was similar for different tumor masses. Compared to the CVO model, the extended CVF and VVF models provided clearly different results, including pronounced effects of VF and tumor size on the necrotic fraction and D{sub 99}, necrotic fractions ranging from 0% to 97%, and a maximal D{sub 99} increment of 57%. Only minor differences were observed between different vessel architectures, i.e., CVF vs VVF. In the smallest tumor with a low necrotic fraction, the D{sub 99} strictly decreased with increasing blood velocity. Increasing blood velocity also decreased the necrotic fraction in all tumor sizes. VF had the most profound influence on both the necrotic fraction and on D{sub 99}. Conclusions: Our present analysis of necrotic formation and the impact of tumor oxygenation on D{sub 99} demonstrated the importance of including longitudinal variations in vessel oxygen content in tumor models. For small tumors, radiosensitivity was particularly dependent on VF and slightly dependent on the blood velocity and vessel arrangement. These dependences decreased with increasing tumor size, because the necrotic fraction also increased, thereby decreasing the number of viable tumor cells that required sterilization. The authors anticipate that the present model will be useful for estimating tumor oxygenation and radiation response in future detailed studies.« less

JP-8 jet fuel exposure potentiates tumor development in two experimental model systems.

PubMed

Harris, D T; Sakiestewa, D; Titone, D; He, X; Hyde, J; Witten, M

2007-11-01

The US Air Force has implemented the widespread use of JP-8 jet fuel in its operations, although a thorough understanding of its potential effects upon exposed personnel is unclear. Previous work has reported that JP-8 exposure is immunosuppressive. Exposure of mice to JP-8 for 1 h/day resulted in immediate secretion of two immunosuppressive agents; namely, interleukin-10 (IL-10) and prostaglandin E2 (PGE2). Thus, it was of interest to determine if jet fuel exposure might promote tumor growth and metastasis. The syngeneic B16 tumor model was used for these studies. Animals were injected intravenously with tumor cells, and lung colonies were enumerated. Animals were also examined for metastatic spread of the tumor. Mice were either exposed to 1000 mg/m3 JP-8 (1 h/ day) for 7 days before tumor injection or were exposed to JP-8 at the time of tumor injection. All animals were killed 17 days after tumor injection. In the present study, JP8 exposure potentiated the growth and metastases of B16 tumors in an animal model. Exposure of mice to JP-8 for 1 h/day before tumor induction resulted in an approximately 8.7-fold increase in tumors, whereas those mice exposed to JP8 at the time of tumor induction had a 5.6-fold increase in tumor numbers. Thus, low concentration JP-8 jet fuel exposures have significant immune suppressive effects on the immune system that can result in increased tumor formation and metastases. We have now extended the observations to an experimental subcutaneous tumor model. JP8 exposure at the time of tumor induction in this model did not affect the growth of the tumor. However, JP8-exposed, tumor-bearing animals died at an accelerated rate as compared with air-exposed, tumor-bearing mice.

A Catalytic Role for Proangiogenic Marrow-Derived Cells in Tumor Neovascularization

PubMed Central

Seandel, Marco; Butler, Jason; Lyden, David; Rafii, Shahin

2010-01-01

Small numbers of proangiogenic bone marrow-derived cells (BMDCs) can play pivotal roles in tumor progression. In this issue of Cancer Cell, two papers, utilizing different tumor angiogenesis models, both find that activated MMP-9 delivered by BMDCs modulates neovessel remodeling, thereby promoting tumor growth. The changes in microvascular anatomy induced by MMP-9-expressing BMDCs are strikingly different between the preirradiated tumor vascular bed model employed by Ahn and Brown and the invasive glioblastoma model utilized by Du et al., likely mirroring the complexity of the real tumor microenvironment and the intricacy of roles of different BMDC populations in mediating tumor neoangiogenesis. PMID:18328420

Parametric study of different contributors to tumor thermal profile

NASA Astrophysics Data System (ADS)

Tepper, Michal; Gannot, Israel

2014-03-01

Treating cancer is one of the major challenges of modern medicine. There is great interest in assessing tumor development in in vivo animal and human models, as well as in in vitro experiments. Existing methods are either limited by cost and availability or by their low accuracy and reproducibility. Thermography holds the potential of being a noninvasive, low-cost, irradiative and easy-to-use method for tumor monitoring. Tumors can be detected in thermal images due to their relatively higher or lower temperature compared to the temperature of the healthy skin surrounding them. Extensive research is performed to show the validity of thermography as an efficient method for tumor detection and the possibility of extracting tumor properties from thermal images, showing promising results. However, deducing from one type of experiment to others is difficult due to the differences in tumor properties, especially between different types of tumors or different species. There is a need in a research linking different types of tumor experiments. In this research, parametric analysis of possible contributors to tumor thermal profiles was performed. The effect of tumor geometric, physical and thermal properties was studied, both independently and together, in phantom model experiments and computer simulations. Theoretical and experimental results were cross-correlated to validate the models used and increase the accuracy of simulated complex tumor models. The contribution of different parameters in various tumor scenarios was estimated and the implication of these differences on the observed thermal profiles was studied. The correlation between animal and human models is discussed.

Cancer evolution: mathematical models and computational inference.

PubMed

Beerenwinkel, Niko; Schwarz, Roland F; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI

NASA Astrophysics Data System (ADS)

Pei, Linmin; Reza, Syed M. S.; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M.

2017-03-01

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. To model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI.

PubMed

Pei, Linmin; Reza, Syed M S; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M

2017-02-11

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. In order to model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Antitumor activity of erlotinib (OSI-774, Tarceva) alone or in combination in human non-small cell lung cancer tumor xenograft models.

PubMed

Higgins, Brian; Kolinsky, Kenneth; Smith, Melissa; Beck, Gordon; Rashed, Mohammad; Adames, Violeta; Linn, Michael; Wheeldon, Eric; Gand, Laurent; Birnboeck, Herbert; Hoffmann, Gerhard

2004-06-01

Our objective was the preclinical assessment of the pharmacokinetics, monotherapy and combined antitumor activity of the epidermal growth factor receptor (HER1/EGFR) tyrosine kinase inhibitor erlotinib in athymic nude mice bearing non-small cell lung cancer (NSCLC) xenograft models. Immunohistochemistry determined the HER1/EGFR status of the NSCLC tumor models. Pharmacokinetic studies assessed plasma drug concentrations of erlotinib in tumor- and non-tumor-bearing athymic nude mice. These were followed by maximum tolerated dose (MTD) studies for erlotinib and each chemotherapy. Erlotinib was then assessed alone and in combination with these chemotherapies in the NSCLC xenograft models. Complete necropsies were performed on most of the animals in each study to further assess antitumor or toxic effects. Erlotinib monotherapy dose-dependently inhibited tumor growth in the H460a tumor model, correlating with circulating levels of drug. There was antitumor activity at the MTD with each agent tested in both the H460a and A549 tumor models (erlotinib 100 mg/kg: 71 and 93% tumor growth inhibition; gemcitabine 120 mg/kg: 93 and 75% tumor growth inhibition; cisplatin 6 mg/kg: 81 and 88% tumor growth inhibition). When each compound was given at a fraction of the MTD, tumor growth inhibition was suboptimal. Combinations of gemcitabine or cisplatin with erlotinib were assessed at 25% of the MTD to determine efficacy. In both NSCLC models, doses of gemcitabine (30 mg/kg) or cisplatin (1.5 mg/kg) with erlotinib (25 mg/kg) at 25% of the MTD were well tolerated. For the slow growing A549 tumor, there was significant tumor growth inhibition in the gemcitabine/erlotinib and cisplatin/erlotinib combinations (above 100 and 98%, respectively), with partial regressions. For the faster growing H460a tumor, there was significant but less remarkable tumor growth inhibition in these same combinations (86 and 53% respectively). These results show that in NSCLC xenograft tumors with similar levels of EGFR expression, the antitumor activity of erlotinib is robust both as monotherapy and in combination with chemotherapies.

Cancer log-kill revisited.

PubMed

Norton, Larry

2014-01-01

At the root of science lie basic rules, if we can discover or deduce them. This is not an abstract project but practical; if we can understand the why then perhaps we can rationally intervene. One of the unifying unsolved problems in physics is the hypothetical "Theory of Everything." In a similar vein, we can ask whether our own field contains such hidden fundamental truths and, if so, how we can use them to develop better therapies and outcomes for our patients. Modern oncology has developed as drugs and translational science have matured over the 50 years since ASCO's founding, but almost from that beginning tumor modeling has been a key tool. Through this general approach Norton and Simon changed our understanding of cancer biology and response to therapy when they described the fit of Gompertzian curves to both clinical and animal observations of tumor growth. The practical relevance of these insights has only grown with the development of DNA sequencing promising a raft of new targets (and drugs). In that regard, Larry Norton's contribution to this year's Educational Book reminds us to always think creatively about the fundamental problems of tumor growth and metastases as well as therapeutic response. Demonstrating the creativity and thoughtfulness that have marked his remarkable career, he now incorporates a newer concept of self-seeding to further explain why Gompertzian growth occurs and, in the process, provides a novel potential therapeutic target. As you read his elegantly presented discussion, consider how this understanding, wisely applied to the modern era of targeted therapies, might speed the availability of better treatments. But even more instructive is his personal model-not only the Norton-Simon Hypothesis-of how to live and approach science, biology, patients and their families, as well as the broader community. He shows that with energy, enthusiasm, optimism, intellect, and hard work we can make the world better. Clifford A. Hudis, MD, FACP, 2013-2014 ASCO President.

Accounting for measurement error in biomarker data and misclassification of subtypes in the analysis of tumor data.

PubMed

Nevo, Daniel; Zucker, David M; Tamimi, Rulla M; Wang, Molin

2016-12-30

A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps-clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses' Health Study to demonstrate the utility of our method. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Detection of molecular signatures of oral squamous cell carcinoma and normal epithelium - application of a novel methodology for unsupervised segmentation of imaging mass spectrometry data.

PubMed

Widlak, Piotr; Mrukwa, Grzegorz; Kalinowska, Magdalena; Pietrowska, Monika; Chekan, Mykola; Wierzgon, Janusz; Gawin, Marta; Drazek, Grzegorz; Polanska, Joanna

2016-06-01

Intra-tumor heterogeneity is a vivid problem of molecular oncology that could be addressed by imaging mass spectrometry. Here we aimed to assess molecular heterogeneity of oral squamous cell carcinoma and to detect signatures discriminating normal and cancerous epithelium. Tryptic peptides were analyzed by MALDI-IMS in tissue specimens from five patients with oral cancer. Novel algorithm of IMS data analysis was developed and implemented, which included Gaussian mixture modeling for detection of spectral components and iterative k-means algorithm for unsupervised spectra clustering performed in domain reduced to a subset of the most dispersed components. About 4% of the detected peptides showed significantly different abundances between normal epithelium and tumor, and could be considered as a molecular signature of oral cancer. Moreover, unsupervised clustering revealed two major sub-regions within expert-defined tumor areas. One of them showed molecular similarity with histologically normal epithelium. The other one showed similarity with connective tissue, yet was markedly different from normal epithelium. Pathologist's re-inspection of tissue specimens confirmed distinct features in both tumor sub-regions: foci of actual cancer cells or cancer microenvironment-related cells prevailed in corresponding areas. Hence, molecular differences detected during automated segmentation of IMS data had an apparent reflection in real structures present in tumor. © 2016 The Authors. Proteomics Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

TH-A-BRF-02: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - Modeling Tumor Evolution for Adaptive Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Lee, CG; Chan, TCY

2014-06-15

Purpose: To develop mathematical models of tumor geometry changes under radiotherapy that may support future adaptive paradigms. Methods: A total of 29 cervical patients were scanned using MRI, once for planning and weekly thereafter for treatment monitoring. Using the tumor volumes contoured by a radiologist, three mathematical models were investigated based on the assumption of a stochastic process of tumor evolution. The “weekly MRI” model predicts tumor geometry for the following week from the last two consecutive MRI scans, based on the voxel transition probability. The other two models use only the first pair of consecutive MRI scans, and themore » transition probabilities were estimated via tumor type classified from the entire data set. The classification is based on either measuring the tumor volume (the “weekly volume” model), or implementing an auxiliary “Markov chain” model. These models were compared to a constant volume approach that represents the current clinical practice, using various model parameters; e.g., the threshold probability β converts the probability map into a tumor shape (larger threshold implies smaller tumor). Model performance was measured using volume conformity index (VCI), i.e., the union of the actual target and modeled target volume squared divided by product of these two volumes. Results: The “weekly MRI” model outperforms the constant volume model by 26% on average, and by 103% for the worst 10% of cases in terms of VCI under a wide range of β. The “weekly volume” and “Markov chain” models outperform the constant volume model by 20% and 16% on average, respectively. They also perform better than the “weekly MRI” model when β is large. Conclusion: It has been demonstrated that mathematical models can be developed to predict tumor geometry changes for cervical cancer undergoing radiotherapy. The models can potentially support adaptive radiotherapy paradigm by reducing normal tissue dose. This research was supported in part by the Ontario Consortium for Adaptive Interventions in Radiation Oncology (OCAIRO) funded by the Ontario Research Fund (ORF) and the MITACS Accelerate Internship Program.« less

A hybrid approach to survival model building using integration of clinical and molecular information in censored data.

PubMed

Choi, Ickwon; Kattan, Michael W; Wells, Brian J; Yu, Changhong

2012-01-01

In medical society, the prognostic models, which use clinicopathologic features and predict prognosis after a certain treatment, have been externally validated and used in practice. In recent years, most research has focused on high dimensional genomic data and small sample sizes. Since clinically similar but molecularly heterogeneous tumors may produce different clinical outcomes, the combination of clinical and genomic information, which may be complementary, is crucial to improve the quality of prognostic predictions. However, there is a lack of an integrating scheme for clinic-genomic models due to the P ≥ N problem, in particular, for a parsimonious model. We propose a methodology to build a reduced yet accurate integrative model using a hybrid approach based on the Cox regression model, which uses several dimension reduction techniques, L₂ penalized maximum likelihood estimation (PMLE), and resampling methods to tackle the problem. The predictive accuracy of the modeling approach is assessed by several metrics via an independent and thorough scheme to compare competing methods. In breast cancer data studies on a metastasis and death event, we show that the proposed methodology can improve prediction accuracy and build a final model with a hybrid signature that is parsimonious when integrating both types of variables.

Multicellular detachment generates metastatic spheroids during intra-abdominal dissemination in epithelial ovarian cancer.

PubMed

Al Habyan, Sara; Kalos, Christina; Szymborski, Joseph; McCaffrey, Luke

2018-05-23

Ovarian cancer is the most lethal gynecological cancer, where survival rates have had modest improvement over the last 30 years. Metastasis of cancer cells is a major clinical problem, and patient mortality occurs when ovarian cancer cells spread beyond the confinement of ovaries. Disseminated ovarian cancer cells typically spread within the abdomen, where ascites accumulation aids in their transit. Metastatic ascites contain multicellular spheroids, which promote chemo-resistance and recurrence. However, little is known about the origin and mechanisms through which spheroids arise. Using live-imaging of 3D culture models and animal models, we report that epithelial ovarian cancer (EOC) cells, the most common type of ovarian cancer, can spontaneously detach as either single cells or clusters. We report that clusters are more resistant to anoikis and have a potent survival advantage over single cells. Using in vivo lineage tracing, we found that multicellular spheroids arise preferentially from collective detachment, rather than aggregation in the abdomen. Finally, we report that multicellular spheroids from collective detachment are capable of seeding intra-abdominal metastases that retain intra-tumoral heterogeneity from the primary tumor.

Finding minimum gene subsets with heuristic breadth-first search algorithm for robust tumor classification

PubMed Central

2012-01-01

Background Previous studies on tumor classification based on gene expression profiles suggest that gene selection plays a key role in improving the classification performance. Moreover, finding important tumor-related genes with the highest accuracy is a very important task because these genes might serve as tumor biomarkers, which is of great benefit to not only tumor molecular diagnosis but also drug development. Results This paper proposes a novel gene selection method with rich biomedical meaning based on Heuristic Breadth-first Search Algorithm (HBSA) to find as many optimal gene subsets as possible. Due to the curse of dimensionality, this type of method could suffer from over-fitting and selection bias problems. To address these potential problems, a HBSA-based ensemble classifier is constructed using majority voting strategy from individual classifiers constructed by the selected gene subsets, and a novel HBSA-based gene ranking method is designed to find important tumor-related genes by measuring the significance of genes using their occurrence frequencies in the selected gene subsets. The experimental results on nine tumor datasets including three pairs of cross-platform datasets indicate that the proposed method can not only obtain better generalization performance but also find many important tumor-related genes. Conclusions It is found that the frequencies of the selected genes follow a power-law distribution, indicating that only a few top-ranked genes can be used as potential diagnosis biomarkers. Moreover, the top-ranked genes leading to very high prediction accuracy are closely related to specific tumor subtype and even hub genes. Compared with other related methods, the proposed method can achieve higher prediction accuracy with fewer genes. Moreover, they are further justified by analyzing the top-ranked genes in the context of individual gene function, biological pathway, and protein-protein interaction network. PMID:22830977

Performance analysis of successive over relaxation method for solving glioma growth model

NASA Astrophysics Data System (ADS)

Hussain, Abida; Faye, Ibrahima; Muthuvalu, Mohana Sundaram

2016-11-01

Brain tumor is one of the prevalent cancers in the world that lead to death. In light of the present information of the properties of gliomas, mathematical models have been developed by scientists to quantify the proliferation and invasion dynamics of glioma. In this study, one-dimensional glioma growth model is considered, and finite difference method is used to discretize the problem. Then, two stationary methods, namely Gauss-Seidel (GS) and Successive Over Relaxation (SOR) are used to solve the governing algebraic system. The performance of the methods are evaluated in terms of number of iteration and computational time. On the basis of performance analysis, SOR method is shown to be more superior compared to GS method.

Identification of tumor evolution patterns by means of inductive logic programming.

PubMed

Bevilacqua, Vitoantonio; Chiarappa, Patrizia; Mastronardi, Giuseppe; Menolascina, Filippo; Paradiso, Angelo; Tommasi, Stefania

2008-06-01

In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained on a real-world dataset, we try to give some hints about further approach to the knowledge-driven validations of such hypotheses.

Semi-automated delineation of breast cancer tumors and subsequent materialization using three-dimensional printing (rapid prototyping).

PubMed

Schulz-Wendtland, Rüdiger; Harz, Markus; Meier-Meitinger, Martina; Brehm, Barbara; Wacker, Till; Hahn, Horst K; Wagner, Florian; Wittenberg, Thomas; Beckmann, Matthias W; Uder, Michael; Fasching, Peter A; Emons, Julius

2017-03-01

Three-dimensional (3D) printing has become widely available, and a few cases of its use in clinical practice have been described. The aim of this study was to explore facilities for the semi-automated delineation of breast cancer tumors and to assess the feasibility of 3D printing of breast cancer tumors. In a case series of five patients, different 3D imaging methods-magnetic resonance imaging (MRI), digital breast tomosynthesis (DBT), and 3D ultrasound-were used to capture 3D data for breast cancer tumors. The volumes of the breast tumors were calculated to assess the comparability of the breast tumor models, and the MRI information was used to render models on a commercially available 3D printer to materialize the tumors. The tumor volumes calculated from the different 3D methods appeared to be comparable. Tumor models with volumes between 325 mm 3 and 7,770 mm 3 were printed and compared with the models rendered from MRI. The materialization of the tumors reflected the computer models of them. 3D printing (rapid prototyping) appears to be feasible. Scenarios for the clinical use of the technology might include presenting the model to the surgeon to provide a better understanding of the tumor's spatial characteristics in the breast, in order to improve decision-making in relation to neoadjuvant chemotherapy or surgical approaches. J. Surg. Oncol. 2017;115:238-242. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Evolution of Antibody-Drug Conjugate Tumor Disposition Model to Predict Preclinical Tumor Pharmacokinetics of Trastuzumab-Emtansine (T-DM1).

PubMed

Singh, Aman P; Maass, Katie F; Betts, Alison M; Wittrup, K Dane; Kulkarni, Chethana; King, Lindsay E; Khot, Antari; Shah, Dhaval K

2016-07-01

A mathematical model capable of accurately characterizing intracellular disposition of ADCs is essential for a priori predicting unconjugated drug concentrations inside the tumor. Towards this goal, the objectives of this manuscript were to: (1) evolve previously published cellular disposition model of ADC with more intracellular details to characterize the disposition of T-DM1 in different HER2 expressing cell lines, (2) integrate the improved cellular model with the ADC tumor disposition model to a priori predict DM1 concentrations in a preclinical tumor model, and (3) identify prominent pathways and sensitive parameters associated with intracellular activation of ADCs. The cellular disposition model was augmented by incorporating intracellular ADC degradation and passive diffusion of unconjugated drug across tumor cells. Different biomeasures and chemomeasures for T-DM1, quantified in the companion manuscript, were incorporated into the modified model of ADC to characterize in vitro pharmacokinetics of T-DM1 in three HER2+ cell lines. When the cellular model was integrated with the tumor disposition model, the model was able to a priori predict tumor DM1 concentrations in xenograft mice. Pathway analysis suggested different contribution of antigen-mediated and passive diffusion pathways for intracellular unconjugated drug exposure between in vitro and in vivo systems. Global and local sensitivity analyses revealed that non-specific deconjugation and passive diffusion of the drug across tumor cell membrane are key parameters for drug exposure inside a cell. Finally, a systems pharmacokinetic model for intracellular processing of ADCs has been proposed to highlight our current understanding about the determinants of ADC activation inside a cell.

Integration of Oncogenes via Sleeping Beauty as a Mouse Model of HPV16+ Oral Tumors and Immunologic Control.

PubMed

Lin, Yi-Hsin; Yang, Ming-Chieh; Tseng, Ssu-Hsueh; Jiang, Rosie; Yang, Andrew; Farmer, Emily; Peng, Shiwen; Henkle, Talia; Chang, Yung-Nien; Hung, Chien-Fu; Wu, T-C

2018-01-23

Human papillomavirus type 16 (HPV16) is the etiologic factor for cervical cancer and a subset of oropharyngeal cancers. Although several prophylactic HPV vaccines are available, no effective therapeutic strategies to control active HPV diseases exist. Tumor implantation models are traditionally used to study HPV-associated buccal tumors. However, they fail to address precancerous phases of disease progression and display tumor microenvironments distinct from those observed in patients. Previously, K14-E6/E7 transgenic mouse models have been used to generate spontaneous tumors. However, the rate of tumor formation is inconsistent, and the host often develops immune tolerance to the viral oncoproteins. We developed a preclinical, spontaneous, HPV16 + buccal tumor model using submucosal injection of oncogenic plasmids expressing HPV16-E6/E7, NRas G12V , luciferase, and sleeping beauty (SB) transposase, followed by electroporation in the buccal mucosa. We evaluated responses to immunization with a pNGVL4a-CRT/E7(detox) therapeutic HPV DNA vaccine and tumor cell migration to distant locations. Mice transfected with plasmids encoding HPV16-E6/E7, NRas G12V , luciferase, and SB transposase developed tumors within 3 weeks. We also found transient anti-CD3 administration is required to generate tumors in immunocompetent mice. Bioluminescence signals from luciferase correlated strongly with tumor growth, and tumors expressed HPV16-associated markers. We showed that pNGVL4a-CRT/E7(detox) administration resulted in antitumor immunity in tumor-bearing mice. Lastly, we demonstrated that the generated tumor could migrate to tumor-draining lymph nodes. Our model provides an efficient method to induce spontaneous HPV + tumor formation, which can be used to identify effective therapeutic interventions, analyze tumor migration, and conduct tumor biology research. Cancer Immunol Res; 6(3); 1-15. ©2018 AACR. ©2018 American Association for Cancer Research.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

Morphogenesis and Complexity of the Tumor Patterns

NASA Astrophysics Data System (ADS)

Izquierdo-Kulich, E.; Nieto-Villar, J. M.

A mechanism to describe the apoptosis process at mesoscopic level through p53 is proposed in this paper. A deterministic model given by three differential equations is deduced from the mesoscopic approach, which exhibits sustained oscillations caused by a supercritical Andronov-Hopf bifurcation. Taking as hypothesis that the p53 sustained oscillation is the fundamental mechanism for apoptosis regulation; the model predicts that it is necessary a strict control of p53 to stimulated it, which is an important consideration to established new therapy strategy to fight cancer. The mathematical modeling of tumor growth allows us to describe the most important regularities of these systems. A stochastic model, based on the most important processes that take place at the level of individual cells, is proposed to predict the dynamical behavior of the expected radius of the tumor and its fractal dimension. It was found that the tumor has a characteristic fractal dimension, which contains the necessary information to predict the tumor growth until it reaches a stationary state. The mathematical modeling of tumor growth is an approach to explain the complex nature of these systems. A model that describes tumor growth was obtained by using a mesoscopic formalism and fractal dimension. This model theoretically predicts the relation between the morphology of the cell pattern and the mitosis/apoptosis quotient that helps to predict tumor growth from tumoral cells fractal dimension. The relation between the tumor macroscopic morphology and the cell pattern morphology is also determined. This could explain why the interface fractal dimension decreases with the increase of the cell pattern fractal dimension and consequently with the increase of the mitosis/apoptosis relation. Indexes to characterize tumoral cell proliferation and invasion capacities are proposed and used to predict the growth of different types of tumors. These indexes also show that the proliferation capacity is directly proportional to the invasion capacity. The proposed model assumes: i) only interface cells proliferate and invade the host, and ii) the fractal dimension of tumoral cell patterns, can reproduce the Gompertzian growth law. A mathematical model was obtained to describe the relation between the tissue morphology of cervix carcinoma and both dynamic processes of mitosis and apoptosis, and an expression to quantify the tumor aggressiveness, which in this context is associated with the tumor growth rate. The proposed model was applied to Stage III cervix carcinoma in vivo studies. In this study we found that the apoptosis rate was significantly smaller in the tumor tissues and both the mitosis rate and aggressiveness index decrease with Stage III patient's age. These quantitative results correspond to observed behavior in clinical and genetics studies. Finally, the entropy production rate was determined for avascular tumor growth. The proposed formula relates the fractal dimension of the tumor contour with the quotient between mitosis and apoptosis rate, which can be used to characterize the degree of proliferation of tumor cells. The entropy production rate was determined for fourteen tumor cell lines as a physical function of cancer robustness. The entropy production rate is a hallmark that allows us the possibility of prognosis of tumor proliferation and invasion capacities, key factors to improve cancer therapy.

Effectivity of pazopanib treatment in orthotopic models of human testicular germ cell tumors

PubMed Central

2013-01-01

Background Cisplatin (CDDP) resistance in testicular germ cell tumors (GCTs) is still a clinical challenge, and one associated with poor prognosis. The purpose of this work was to test pazopanib, an anti-tumoral and anti-angiogenic multikinase inhibitor, and its combination with lapatinib (an anti-ErbB inhibitor) in mouse orthotopic models of human testicular GCTs. Methods We used two different models of human testicular GCTs orthotopically grown in nude mice; a CDDP-sensitive choriocarcinoma (TGT38) and a new orthotopic model generated from a metastatic GCT refractory to first-line CDDP chemotherapy (TGT44). Nude mice implanted with these orthotopic tumors were treated with the inhibitors and the effect on tumoral growth and angiogenesis was evaluated. Results TGT44 refractory tumor had an immunohistochemical profile similar to the original metastasis, with characteristics of yolk sac tumor. TGT44 did not respond when treated with cisplatin. In contrast, pazopanib had an anti-angiogenic effect and anti-tumor efficacy in this model. Pazopanib in combination with lapatinib in TGT38, an orthotopic model of choriocarcinoma had an additive effect blocking tumor growth. Conclusions We present pazopanib as a possible agent for the alternative treatment of CDDP-sensitive and CDDP-refractory GCT patients, alone or in combination with anti-ErbB therapies. PMID:23937707

Improving oncoplastic breast tumor bed localization for radiotherapy planning using image registration algorithms

NASA Astrophysics Data System (ADS)

Wodzinski, Marek; Skalski, Andrzej; Ciepiela, Izabela; Kuszewski, Tomasz; Kedzierawski, Piotr; Gajda, Janusz

2018-02-01

Knowledge about tumor bed localization and its shape analysis is a crucial factor for preventing irradiation of healthy tissues during supportive radiotherapy and as a result, cancer recurrence. The localization process is especially hard for tumors placed nearby soft tissues, which undergo complex, nonrigid deformations. Among them, breast cancer can be considered as the most representative example. A natural approach to improving tumor bed localization is the use of image registration algorithms. However, this involves two unusual aspects which are not common in typical medical image registration: the real deformation field is discontinuous, and there is no direct correspondence between the cancer and its bed in the source and the target 3D images respectively. The tumor no longer exists during radiotherapy planning. Therefore, a traditional evaluation approach based on known, smooth deformations and target registration error are not directly applicable. In this work, we propose alternative artificial deformations which model the tumor bed creation process. We perform a comprehensive evaluation of the most commonly used deformable registration algorithms: B-Splines free form deformations (B-Splines FFD), different variants of the Demons and TV-L1 optical flow. The evaluation procedure includes quantitative assessment of the dedicated artificial deformations, target registration error calculation, 3D contour propagation and medical experts visual judgment. The results demonstrate that the currently, practically applied image registration (rigid registration and B-Splines FFD) are not able to correctly reconstruct discontinuous deformation fields. We show that the symmetric Demons provide the most accurate soft tissues alignment in terms of the ability to reconstruct the deformation field, target registration error and relative tumor volume change, while B-Splines FFD and TV-L1 optical flow are not an appropriate choice for the breast tumor bed localization problem, even though the visual alignment seems to be better than for the Demons algorithm. However, no algorithm could recover the deformation field with sufficient accuracy in terms of vector length and rotation angle differences.

A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

PubMed Central

Ortega-Martorell, Sandra; Ruiz, Héctor; Vellido, Alfredo; Olier, Iván; Romero, Enrique; Julià-Sapé, Margarida; Martín, José D.; Jarman, Ian H.; Arús, Carles; Lisboa, Paulo J. G.

2013-01-01

Background The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal. Methodology/Principal Findings Non-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification. Conclusions/Significance We show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing. PMID:24376744

Correlation of FMISO simulations with pimonidazole-stained tumor xenografts: A question of O{sub 2} consumption?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wack, L. J., E-mail: linda-jacqueline.wack@med.uni

Purpose: To compare a dedicated simulation model for hypoxia PET against tumor microsections stained for different parameters of the tumor microenvironment. The model can readily be adapted to a variety of conditions, such as different human head and neck squamous cell carcinoma (HNSCC) xenograft tumors. Methods: Nine different HNSCC tumor models were transplanted subcutaneously into nude mice. Tumors were excised and immunoflourescently labeled with pimonidazole, Hoechst 33342, and CD31, providing information on hypoxia, perfusion, and vessel distribution, respectively. Hoechst and CD31 images were used to generate maps of perfused blood vessels on which tissue oxygenation and the accumulation of themore » hypoxia tracer FMISO were mathematically simulated. The model includes a Michaelis–Menten relation to describe the oxygen consumption inside tissue. The maximum oxygen consumption rate M{sub 0} was chosen as the parameter for a tumor-specific optimization as it strongly influences tracer distribution. M{sub 0} was optimized on each tumor slice to reach optimum correlations between FMISO concentration 4 h postinjection and pimonidazole staining intensity. Results: After optimization, high pixel-based correlations up to R{sup 2} = 0.85 were found for individual tissue sections. Experimental pimonidazole images and FMISO simulations showed good visual agreement, confirming the validity of the approach. Median correlations per tumor model varied significantly (p < 0.05), with R{sup 2} ranging from 0.20 to 0.54. The optimum maximum oxygen consumption rate M{sub 0} differed significantly (p < 0.05) between tumor models, ranging from 2.4 to 5.2 mm Hg/s. Conclusions: It is feasible to simulate FMISO distributions that match the pimonidazole retention patterns observed in vivo. Good agreement was obtained for multiple tumor models by optimizing the oxygen consumption rate, M{sub 0}, whose optimum value differed significantly between tumor models.« less

Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation.

PubMed

Unkelbach, Jan; Menze, Bjoern H; Konukoglu, Ender; Dittmann, Florian; Le, Matthieu; Ayache, Nicholas; Shih, Helen A

2014-02-07

Glioblastoma differ from many other tumors in the sense that they grow infiltratively into the brain tissue instead of forming a solid tumor mass with a defined boundary. Only the part of the tumor with high tumor cell density can be localized through imaging directly. In contrast, brain tissue infiltrated by tumor cells at low density appears normal on current imaging modalities. In current clinical practice, a uniform margin, typically two centimeters, is applied to account for microscopic spread of disease that is not directly assessable through imaging. The current treatment planning procedure can potentially be improved by accounting for the anisotropy of tumor growth, which arises from different factors: anatomical barriers such as the falx cerebri represent boundaries for migrating tumor cells. In addition, tumor cells primarily spread in white matter and infiltrate gray matter at lower rate. We investigate the use of a phenomenological tumor growth model for treatment planning. The model is based on the Fisher-Kolmogorov equation, which formalizes these growth characteristics and estimates the spatial distribution of tumor cells in normal appearing regions of the brain. The target volume for radiotherapy planning can be defined as an isoline of the simulated tumor cell density. This paper analyzes the model with respect to implications for target volume definition and identifies its most critical components. A retrospective study involving ten glioblastoma patients treated at our institution has been performed. To illustrate the main findings of the study, a detailed case study is presented for a glioblastoma located close to the falx. In this situation, the falx represents a boundary for migrating tumor cells, whereas the corpus callosum provides a route for the tumor to spread to the contralateral hemisphere. We further discuss the sensitivity of the model with respect to the input parameters. Correct segmentation of the brain appears to be the most crucial model input. We conclude that the tumor growth model provides a method to account for anisotropic growth patterns of glioma, and may therefore provide a tool to make target delineation more objective and automated.

Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation

NASA Astrophysics Data System (ADS)

Unkelbach, Jan; Menze, Bjoern H.; Konukoglu, Ender; Dittmann, Florian; Le, Matthieu; Ayache, Nicholas; Shih, Helen A.

2014-02-01

Glioblastoma differ from many other tumors in the sense that they grow infiltratively into the brain tissue instead of forming a solid tumor mass with a defined boundary. Only the part of the tumor with high tumor cell density can be localized through imaging directly. In contrast, brain tissue infiltrated by tumor cells at low density appears normal on current imaging modalities. In current clinical practice, a uniform margin, typically two centimeters, is applied to account for microscopic spread of disease that is not directly assessable through imaging. The current treatment planning procedure can potentially be improved by accounting for the anisotropy of tumor growth, which arises from different factors: anatomical barriers such as the falx cerebri represent boundaries for migrating tumor cells. In addition, tumor cells primarily spread in white matter and infiltrate gray matter at lower rate. We investigate the use of a phenomenological tumor growth model for treatment planning. The model is based on the Fisher-Kolmogorov equation, which formalizes these growth characteristics and estimates the spatial distribution of tumor cells in normal appearing regions of the brain. The target volume for radiotherapy planning can be defined as an isoline of the simulated tumor cell density. This paper analyzes the model with respect to implications for target volume definition and identifies its most critical components. A retrospective study involving ten glioblastoma patients treated at our institution has been performed. To illustrate the main findings of the study, a detailed case study is presented for a glioblastoma located close to the falx. In this situation, the falx represents a boundary for migrating tumor cells, whereas the corpus callosum provides a route for the tumor to spread to the contralateral hemisphere. We further discuss the sensitivity of the model with respect to the input parameters. Correct segmentation of the brain appears to be the most crucial model input. We conclude that the tumor growth model provides a method to account for anisotropic growth patterns of glioma, and may therefore provide a tool to make target delineation more objective and automated.

In Vivo Imaging Reveals Significant Tumor Vascular Dysfunction and Increased Tumor Hypoxia-Inducible Factor-1α Expression Induced by High Single-Dose Irradiation in a Pancreatic Tumor Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maeda, Azusa; Department of Medical Biophysics, University of Toronto, Toronto, Ontario; Chen, Yonghong

Purpose: To investigate the effect of high-dose irradiation on pancreatic tumor vasculature and microenvironment using in vivo imaging techniques. Methods and Materials: A BxPC3 pancreatic tumor xenograft was established in a dorsal skinfold window chamber model and a subcutaneous hind leg model. Tumors were irradiated with a single dose of 4, 12, or 24 Gy. The dorsal skinfold window chamber model was used to assess tumor response, vascular function and permeability, platelet and leukocyte adhesion to the vascular endothelium, and tumor hypoxia for up to 14 days after 24-Gy irradiation. The hind leg model was used to monitor tumor size, hypoxia, and vascularitymore » for up to 65 days after 24-Gy irradiation. Tumors were assessed histologically to validate in vivo observations. Results: In vivo fluorescence imaging revealed temporary vascular dysfunction in tumors irradiated with a single dose of 4 to 24 Gy, but most significantly with a single dose of 24 Gy. Vascular functional recovery was observed by 14 days after irradiation in a dose-dependent manner. Furthermore, irradiation with 24 Gy caused platelet and leukocyte adhesion to the vascular endothelium within hours to days after irradiation. Vascular permeability was significantly higher in irradiated tumors compared with nonirradiated controls 14 days after irradiation. This observation corresponded with increased expression of hypoxia-inducible factor-1α in irradiated tumors. In the hind leg model, irradiation with a single dose of 24 Gy led to tumor growth delay, followed by tumor regrowth. Conclusions: Irradiation of the BxPC3 tumors with a single dose of 24 Gy caused transient vascular dysfunction and increased expression of hypoxia-inducible factor-1α. Such biological changes may impact tumor response to high single-dose and hypofractionated irradiation, and further investigations are needed to better understand the clinical outcomes of stereotactic body radiation therapy.« less

Model construction of nursing service satisfaction in hospitalized tumor patients.

PubMed

Chen, Yongyi; Liu, Jingshi; Xiao, Shuiyuan; Liu, Xiangyu; Tang, Xinhui; Zhou, Yujuan

2014-01-01

This study aims to construct a satisfaction model on nursing service in hospitalized tumor patients. Using questionnaires, data about hospitalized tumor patients' expectation, quality perception and satisfaction of hospital nursing service were obtained. A satisfaction model of nursing service in hospitalized tumor patients was established through empirical study and by structural equation method. This model was suitable for tumor specialized hospital, with reliability and validity. Patient satisfaction was significantly affected by quality perception and patient expectation. Patient satisfaction and patient loyalty was also affected by disease pressure. Hospital brand was positively correlated with patient satisfaction and patient loyalty, negatively correlated with patient complaint. Patient satisfaction was positively correlated with patient loyalty, patient complaints, and quality perception, and negatively correlated with disease pressure and patient expectation. The satisfaction model on nursing service in hospitalized tumor patients fits well. By this model, the quality of hospital nursing care may be improved.

Model construction of nursing service satisfaction in hospitalized tumor patients

PubMed Central

Chen, Yongyi; Liu, Jingshi; Xiao, Shuiyuan; Liu, Xiangyu; Tang, Xinhui; Zhou, Yujuan

2014-01-01

This study aims to construct a satisfaction model on nursing service in hospitalized tumor patients. Using questionnaires, data about hospitalized tumor patients’ expectation, quality perception and satisfaction of hospital nursing service were obtained. A satisfaction model of nursing service in hospitalized tumor patients was established through empirical study and by structural equation method. This model was suitable for tumor specialized hospital, with reliability and validity. Patient satisfaction was significantly affected by quality perception and patient expectation. Patient satisfaction and patient loyalty was also affected by disease pressure. Hospital brand was positively correlated with patient satisfaction and patient loyalty, negatively correlated with patient complaint. Patient satisfaction was positively correlated with patient loyalty, patient complaints, and quality perception, and negatively correlated with disease pressure and patient expectation. The satisfaction model on nursing service in hospitalized tumor patients fits well. By this model, the quality of hospital nursing care may be improved. PMID:25419410

A new ODE tumor growth modeling based on tumor population dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oroji, Amin; Omar, Mohd bin; Yarahmadian, Shantia

2015-10-22

In this paper a new mathematical model for the population of tumor growth treated by radiation is proposed. The cells dynamics population in each state and the dynamics of whole tumor population are studied. Furthermore, a new definition of tumor lifespan is presented. Finally, the effects of two main parameters, treatment parameter (q), and repair mechanism parameter (r) on tumor lifespan are probed, and it is showed that the change in treatment parameter (q) highly affects the tumor lifespan.

Physiologically based pharmacokinetic and pharmacodynamic modeling of an antagonist (SM-406/AT-406) of multiple inhibitor of apoptosis proteins (IAPs) in a mouse xenograft model of human breast cancer.

PubMed

Zhang, Tao; Li, Yanyan; Zou, Peng; Yu, Jing-yu; McEachern, Donna; Wang, Shaomeng; Sun, Duxin

2013-09-01

The inhibitors of apoptosis proteins (IAPs) are a class of key apoptosis regulators overexpressed or dysregulated in cancer. SM-406/AT-406 is a potent and selective small molecule mimetic of Smac that antagonizes the inhibitor of apoptosis proteins (IAPs). A physiologically based pharmacokinetic and pharmacodynamic (PBPK-PD) model was developed to predict the tissue concentration-time profiles of SM-406, the related onco-protein levels in tumor, and the tumor growth inhibition in a mouse model bearing human breast cancer xenograft. In the whole body physiologically based pharmacokinetic (PBPK) model for pharmacokinetics characterization, a well stirred (perfusion rate-limited) model was used to describe SM-406 pharmacokinetics in the lung, heart, kidney, intestine, liver and spleen, and a diffusion rate-limited (permeability limited) model was used for tumor. Pharmacodynamic (PD) models were developed to correlate the SM-406 concentration in tumor to the cIAP1 degradation, pro-caspase 8 decrease, CL-PARP accumulation and tumor growth inhibition. The PBPK-PD model well described the experimental pharmacokinetic data, the pharmacodynamic biomarker responses and tumor growth. This model may be helpful to predict tumor and plasma SM-406 concentrations in the clinic. Copyright © 2013 John Wiley & Sons, Ltd.

Modeling growth and dissemination of lymphoma in a co-evolving lymph node: a diffuse-domain approach

NASA Astrophysics Data System (ADS)

Chuang, Yao-Li; Cristini, Vittorio; Chen, Ying; Li, Xiangrong; Frieboes, Hermann; Lowengrub, John

2013-03-01

While partial differential equation models of tumor growth have successfully described various spatiotemporal phenomena observed for in-vitro tumor spheroid experiments, one challenge towards taking these models to further study in-vivo tumors is that instead of relatively static tissue culture with regular boundary conditions, in-vivo tumors are often confined in organ tissues that co-evolve with the tumor growth. Here we adopt a recently developed diffuse-domain method to account for the co-evolving domain boundaries, adapting our previous in-vitro tumor model for the development of lymphoma encapsulated in a lymph node, which may swell or shrink due to proliferation and dissemination of lymphoma cells and treatment by chemotherapy. We use the model to study the induced spatial heterogeneity, which may arise as an emerging phenomenon in experimental observations and model analysis. Spatial heterogeneity is believed to lead to tumor infiltration patterns and reduce the efficacy of chemotherapy, leaving residuals that cause cancer relapse after the treatment. Understanding the spatiotemporal evolution of in-vivo tumors can be an essential step towards more effective strategies of curing cancer. Supported by NIH-PSOC grant 1U54CA143907-01.

Thermoneutrality, Mice, and Cancer: A Heated Opinion.

PubMed

Hylander, Bonnie L; Repasky, Elizabeth A

2016-04-01

The 'mild' cold stress caused by standard sub-thermoneutral housing temperatures used for laboratory mice in research institutes is sufficient to significantly bias conclusions drawn from murine models of several human diseases. We review the data leading to this conclusion, discuss the implications for research and suggest ways to reduce problems in reproducibility and experimental transparency caused by this housing variable. We have found that these cool temperatures suppress endogenous immune responses, skewing tumor growth data and the severity of graft versus host disease, and also increase the therapeutic resistance of tumors. Owing to the potential for ambient temperature to affect energy homeostasis as well as adrenergic stress, both of which could contribute to biased outcomes in murine cancer models, housing temperature should be reported in all publications and considered as a potential source of variability in results between laboratories. Researchers and regulatory agencies should work together to determine whether changes in housing parameters would enhance the use of mouse models in cancer research, as well as for other diseases. Finally, for many years agencies such as the National Cancer Institute (NCI) have encouraged the development of newer and more sophisticated mouse models for cancer research, but we believe that, without an appreciation of how basic murine physiology is affected by ambient temperature, even data from these models is likely to be compromised. Copyright © 2016 Elsevier Inc. All rights reserved.

Quantum biological channel modeling and capacity calculation.

PubMed

Djordjevic, Ivan B

2012-12-10

Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors), and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i) storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii) replication errors introduced during DNA replication process, (iii) transcription errors introduced during DNA to mRNA transcription, and (iv) translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.

Tumor Suppressor Genes: A Key to the Cancer Puzzle?

ERIC Educational Resources Information Center

Oppenheimer, Steven B.

1991-01-01

Author describes developments in understanding of tumor suppressor genes or antioncogenes that he feels is most important breakthrough in solving cancer problem. Describes 1969 starting work of Harris with mouse fibroblast genes and later work of Knudson with retinoblastoma cells. Provides evidence that deletion of chromosome that results in the…

Establishment, maintenance and in vitro and in vivo applications of primary human glioblastoma multiforme (GBM) xenograft models for translational biology studies and drug discovery.

PubMed

Carlson, Brett L; Pokorny, Jenny L; Schroeder, Mark A; Sarkaria, Jann N

2011-03-01

Development of clinically relevant tumor model systems for glioblastoma multiforme (GBM) is important for advancement of basic and translational biology. One model that has gained wide acceptance in the neuro-oncology community is the primary xenograft model. This model entails the engraftment of patient tumor specimens into the flank of nude mice and subsequent serial passage of these tumors in the flank of mice. These tumors are then used to establish short-term explant cultures or intracranial xenografts. This unit describes detailed procedures for establishment, maintenance, and utilization of a primary GBM xenograft panel for the purpose of using them as tumor models for basic or translational studies.

Social networks help to infer causality in the tumor microenvironment.

PubMed

Crespo, Isaac; Doucey, Marie-Agnès; Xenarios, Ioannis

2016-03-15

Networks have become a popular way to conceptualize a system of interacting elements, such as electronic circuits, social communication, metabolism or gene regulation. Network inference, analysis, and modeling techniques have been developed in different areas of science and technology, such as computer science, mathematics, physics, and biology, with an active interdisciplinary exchange of concepts and approaches. However, some concepts seem to belong to a specific field without a clear transferability to other domains. At the same time, it is increasingly recognized that within some biological systems--such as the tumor microenvironment--where different types of resident and infiltrating cells interact to carry out their functions, the complexity of the system demands a theoretical framework, such as statistical inference, graph analysis and dynamical models, in order to asses and study the information derived from high-throughput experimental technologies. In this article we propose to adopt and adapt the concepts of influence and investment from the world of social network analysis to biological problems, and in particular to apply this approach to infer causality in the tumor microenvironment. We showed that constructing a bidirectional network of influence between cell and cell communication molecules allowed us to determine the direction of inferred regulations at the expression level and correctly recapitulate cause-effect relationships described in literature. This work constitutes an example of a transfer of knowledge and concepts from the world of social network analysis to biomedical research, in particular to infer network causality in biological networks. This causality elucidation is essential to model the homeostatic response of biological systems to internal and external factors, such as environmental conditions, pathogens or treatments.

Radiotherapy and chemotherapy change vessel tree geometry and metastatic spread in a small cell lung cancer xenograft mouse tumor model

PubMed Central

Bethge, Anja; Schumacher, Udo

2017-01-01

Background Tumor vasculature is critical for tumor growth, formation of distant metastases and efficiency of radio- and chemotherapy treatments. However, how the vasculature itself is affected during cancer treatment regarding to the metastatic behavior has not been thoroughly investigated. Therefore, the aim of this study was to analyze the influence of hypofractionated radiotherapy and cisplatin chemotherapy on vessel tree geometry and metastasis formation in a small cell lung cancer xenograft mouse tumor model to investigate the spread of malignant cells during different treatments modalities. Methods The biological data gained during these experiments were fed into our previously developed computer model “Cancer and Treatment Simulation Tool” (CaTSiT) to model the growth of the primary tumor, its metastatic deposit and also the influence on different therapies. Furthermore, we performed quantitative histology analyses to verify our predictions in xenograft mouse tumor model. Results According to the computer simulation the number of cells engrafting must vary considerably to explain the different weights of the primary tumor at the end of the experiment. Once a primary tumor is established, the fractal dimension of its vasculature correlates with the tumor size. Furthermore, the fractal dimension of the tumor vasculature changes during treatment, indicating that the therapy affects the blood vessels’ geometry. We corroborated these findings with a quantitative histological analysis showing that the blood vessel density is depleted during radiotherapy and cisplatin chemotherapy. The CaTSiT computer model reveals that chemotherapy influences the tumor’s therapeutic susceptibility and its metastatic spreading behavior. Conclusion Using a system biological approach in combination with xenograft models and computer simulations revealed that the usage of chemotherapy and radiation therapy determines the spreading behavior by changing the blood vessel geometry of the primary tumor. PMID:29107953

Nonlinear bioheat transfer models and multi-objective numerical optimization of the cryosurgery operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kudryashov, Nikolay A.; Shilnikov, Kirill E.

Numerical computation of the three dimensional problem of the freezing interface propagation during the cryosurgery coupled with the multi-objective optimization methods is used in order to improve the efficiency and safety of the cryosurgery operations performing. Prostate cancer treatment and cutaneous cryosurgery are considered. The heat transfer in soft tissue during the thermal exposure to low temperature is described by the Pennes bioheat model and is coupled with an enthalpy method for blurred phase change computations. The finite volume method combined with the control volume approximation of the heat fluxes is applied for the cryosurgery numerical modeling on the tumormore » tissue of a quite arbitrary shape. The flux relaxation approach is used for the stability improvement of the explicit finite difference schemes. The method of the additional heating elements mounting is studied as an approach to control the cellular necrosis front propagation. Whereas the undestucted tumor tissue and destucted healthy tissue volumes are considered as objective functions, the locations of additional heating elements in cutaneous cryosurgery and cryotips in prostate cancer cryotreatment are considered as objective variables in multi-objective problem. The quasi-gradient method is proposed for the searching of the Pareto front segments as the multi-objective optimization problem solutions.« less

SU-E-T-751: Three-Component Kinetic Model of Tumor Growth and Radiation Response for Stereotactic Radiosurgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watanabe, Y; Dahlman, E; Leder, K

Purpose: To develop and study a kinetic model of tumor growth and its response to stereotactic radiosurgery (SRS) by assuming that the cells in irradiated tumor volume were made of three types. Methods: A set of ordinary differential equations (ODEs) were derived for three types of cells and a tumor growth rate. It is assumed that the cells were composed of actively proliferating cells, lethally damaged-dividing cells, and non-dividing cells. We modeled the tumor volume growth with a time-dependent growth rate to simulate the saturation of growth. After SRS, the proliferating cells were permanently damaged and converted to the lethallymore » damaged cells. The amount of damaged cells were estimated by the LQ-model. The damaged cells gradually stopped dividing/proliferating and died with a constant rate. The dead cells were cleared from their original location with a constant rate. The total tumor volume was the sum of the three components. The ODEs were numerically solved with appropriate initial conditions for a given dosage. The proposed model was used to model an animal experiment, for which the temporal change of a rhabdomyosarcoma tumor volume grown in a rat was measured with time resolution sufficient to test the model. Results: To fit the model to the experimental data, the following characteristics were needed with the model parameters. The α-value in the LQ-model was smaller than the commonly used value; furthermore, it decreased with increasing dose. At the same time, the tumor growth rate after SRS had to increase. Conclusions: The new 3-component model of tumor could simulate the experimental data very well. The current study suggested that the radiation sensitivity and the growth rate of the proliferating tumor cells may change after irradiation and it depended on the dosage used for SRS. These preliminary observations must be confirmed by future animal experiments.« less

Guided molecular missiles for tumor-targeting chemotherapy--case studies using the second-generation taxoids as warheads.

PubMed

Ojima, Iwao

2008-01-01

A long-standing problem in cancer chemotherapy is the lack of tumor-specific treatments. Traditional chemotherapy relies on the premise that rapidly proliferating cancer cells are more likely to be killed by a cytotoxic agent. In reality, however, cytotoxic agents have very little or no specificity, which leads to systemic toxicity, causing undesirable severe side effects. Therefore, the development of innovative and efficacious tumor-specific drug delivery protocols or systems is urgently needed. A rapidly growing tumor requires various nutrients and vitamins. Thus, tumor cells overexpress many tumor-specific receptors, which can be used as targets to deliver cytotoxic agents into tumors. This Account presents our research program on the discovery and development of novel and efficient drug delivery systems, possessing tumor-targeting ability and efficacy against various cancer types, especially multidrug-resistant tumors. In general, a tumor-targeting drug delivery system consists of a tumor recognition moiety and a cytotoxic warhead connected directly or through a suitable linker to form a conjugate. The conjugate, which can be regarded as a "guided molecular missile", should be systemically nontoxic, that is, the linker must be stable in blood circulation, but upon internalization into the cancer cell, the conjugate should be readily cleaved to regenerate the active cytotoxic warhead. These novel "guided molecular missiles" are conjugates of the highly potent second-generation taxoid anticancer agents with tumor-targeting molecules through mechanism-based cleavable linkers. These conjugates are specifically delivered to tumors and internalized into tumor cells, and the potent taxoid anticancer agents are released from the linker into the cytoplasm. We have successfully used omega-3 polyunsaturated fatty acids, in particular DHA, and monoclonal antibodies (for EGFR) as tumor-targeting molecules for the conjugates, which exhibited remarkable efficacy against human tumor xenografts in animal models. We have developed self-immolative disulfide linkers wherein the glutathione-triggered cascade drug release takes place to generate the original anticancer agent. The use of disulfide linkers is attractive beacuse it takes into account the fact that the concentration of glutathione is much higher (>1000 times) in tumor cells than in blood plasma. In order to monitor and elucidate the mechanism of tumor-targeting, internalization, and drug release, several fluorescent and fluorogenic probes using biotin as the tumor-targeting module were developed and used. Then, the progressive occurrence of the designed receptor-mediated endocytosis, drug release, and drug binding to the target protein (microtubules) has been successfully observed and confirmed by means of confocal fluorescence microscopy. These "guided molecular missiles" provide bright prospects for the development of highly efficacious new generation drugs for cancer chemotherapy.

Orbital Osteoblastoma: Technical Innovations in Resection and Reconstruction Using Virtual Surgery Simulation.

PubMed

Novelli, Giorgio; Gramegna, Marco; Tonellini, Gabriele; Valente, Gabriella; Boni, Pietro; Bozzetti, Alberto; Sozzi, Davide

2016-09-01

Osteoblastoma is a benign tumor of bone, representing less than 1% of bone tumors. Craniomaxillofacial localizations account for up to 15% of the total and frequently involve the posterior mandible. Endo-orbital localization is very rare, with most occurring in young patients. Very few of these tumors become malignant. Orbital localization requires radical removal of the tumor followed by careful surgical reconstruction of the orbit to avoid subsequent aesthetic or functional problems. Here, we present a clinical case of this condition and describe a surgical protocol that uses and integrates state-of-the art technologies to achieve orbital reconstruction.

Tumor affinity of radiolabeled peanut agglutinin compared with that of Ga-67 citrate in animal models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yokoyama, K.; Aburano, T.; Watanabe, N.

1985-05-01

Peanut agglutinin (PNA) binds avidly to the immunodominant group of the tumor associated T antigen. The purpose of this study was to evaluate oncodiagnostic potential of radiolabeled PNA in animal models. PNA was labeled with I-125 or I-131 by Iodogen and also with In-111 by cyclic DTPA anhydride. The biological activity of PNA was examined by a hemaglutination titer with a photometer before and after labeling. Animal tumor models used were Lewis Lung Cancer(LLC), B-16 Melanotic Melanoma(MM), Yoshida Sarcoma(YS), Ehrlich Ascites Tumor(EAT and Hepatoma AH109A(HAH). Inflammatory tissue induced by turpentine oil was used as an abscess model. Serial scintigraphic imagesmore » were obtained following IV injections of 100 ..mu..Ci of I-131 or In-111-DTPA-PNA. The tumor affinity of Ga-67 citrate was studied to compare that of radiolabeled PNA. Tissue biodistribution was studied in EAT bearing mice. All of these tumor models except HAH were clearly visible by radiolabeled PNA without subtraction techniques. In the models of LLC and EAT, PNA showed the better accumulation into the tumor tissue than Ga-67 citrate. In YS and MM, PNA represented almost the same accumulation as Ga-67 citrate. The localization of PNA into abscess tissue wasn't found although Ga-67 citrate markedly accumulated into abscess tissue as well as tumor tissue. The clearance of PNA from tumor was slower than those from any other organs. Tumor to muscle ratio was 5.1 at 48hrs. and tumor to blood ratio increased with time to 2.3 at 96hrs. These results suggested that radiolabeled PNA may have a potential in the detection of tumor.« less

Mathematical modeling of tumor-induced immunosuppression by myeloid-derived suppressor cells: Implications for therapeutic targeting strategies.

PubMed

Shariatpanahi, Seyed Peyman; Shariatpanahi, Seyed Pooya; Madjidzadeh, Keivan; Hassan, Moustapha; Abedi-Valugerdi, Manuchehr

2018-04-07

Myeloid-derived suppressor cells (MDSCs) belong to immature myeloid cells that are generated and accumulated during the tumor development. MDSCs strongly suppress the anti-tumor immunity and provide conditions for tumor progression and metastasis. In this study, we present a mathematical model based on ordinary differential equations (ODE) to describe tumor-induced immunosuppression caused by MDSCs. The model consists of four equations and incorporates tumor cells, cytotoxic T cells (CTLs), natural killer (NK) cells and MDSCs. We also provide simulation models that evaluate or predict the effects of anti-MDSC drugs (e.g., l-arginine and 5-Fluorouracil (5-FU)) on the tumor growth and the restoration of anti-tumor immunity. The simulated results obtained using our model were in good agreement with the corresponding experimental findings on the expansion of splenic MDSCs, immunosuppressive effects of these cells at the tumor site and effectiveness of l-arginine and 5-FU on the re-establishment of antitumor immunity. Regarding this latter issue, our predictive simulation results demonstrated that intermittent therapy with low-dose 5-FU alone could eradicate the tumors irrespective of their origins and types. Furthermore, at the time of tumor eradication, the number of CTLs prevailed over that of cancer cells and the number of splenic MDSCs returned to the normal levels. Finally, our predictive simulation results also showed that the addition of l-arginine supplementation to the intermittent 5-FU therapy reduced the time of the tumor eradication and the number of iterations for 5-FU treatment. Thus, the present mathematical model provides important implications for designing new therapeutic strategies that aim to restore antitumor immunity by targeting MDSCs. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Methods for increasing the immunogenicity of vaccines].

PubMed

Kündig, T M

2000-09-14

In the past years, enormous efforts have been undertaken to develop vaccine strategies against cancer. The aim is to have the immune system generate what are called killer cells that can specifically recognize the tumor. The surface of tumor cells contains MHC/HLA antigens which present short-chain peptides of tumor specific antigens. A large number of these oligopeptide antigens have been characterized in recent years. They are now available for use as tumor-specific vaccines. The problem is, however, that the immune response of producing T killer cells is very inefficient when these oligopeptide antigens are injected. As the physiological function of these killer cells virus-infected cells, a process associated with substantial tissue damage, the immune system has learned to use these killer cells with reticence over the course of evolution, in other words, when the life of the host is threatened. This does not happen until pathogens start to spread via lymphogenous or hematogenous pathways. And then it takes a certain amount of time after the invader is present for replication to take place. Since the oligopeptide antigens used as vaccines have a very short half-life in the tissue, not enough of them get to the lymph nodes and stay there for enough time to efficiently induce an immune response. Using a mouse model, we were able to show that the efficiency of the vaccine can be increased a million-fold by directly injecting the vaccine into a lymph node or the spleen which imitates lymphogenous or hematogenous spread. The efficiency of the "inactivated vaccine" can be enhanced even more by continuous administration of the vaccine over several days, simulating an especially dangerous virus replication. The evidence gathered in this mouse model was transferred to a clinical trial. The melanoma-specific inactivated vaccine is infused directly into a lymph node of tumor patients. The infusion is continued for several days. Booster vaccines are given every two weeks.

Tyrosine kinase inhibitors show different anti-brain metastases efficacy in NSCLC: A direct comparative analysis of icotinib, gefitinib, and erlotinib in a nude mouse model.

PubMed

Tan, Jianlong; Li, Min; Zhong, Wen; Hu, Chengping; Gu, Qihua; Xie, Yali

2017-11-17

Brain metastasis is an increasing problem in non-small cell lung cancer (NSCLC) patients. Tyrosine kinase inhibitors (TKIs), including gefitinib, erlotinib, and icotinib, are reported to be effective in patients with brain metastases. However, direct comparative studies of the pharmacokinetics and efficacy of these three drugs in treating brain metastases are lacking. In the present investigation, we found that gefitinib penetrated the blood-tumor barrier and was distributed to brain metastases more effectively than erlotinib or icotinib in a nude mouse model. The 1-h ratio of brain metastases to plasma concentration for gefitinib, erlotinib, and icotinib was 9.82±1.03%, 4.83±0.25%, and 2.62±0.21%, respectively. The 2-h ratio of brain metastases to plasma concentration for gefitinib, erlotinib, and icotinib was 15.11±2.00%, 5.73±1.31%, and 2.69±0.31%, respectively. Gefitinib exhibited the strongest antitumor activity ( p gefitinib vs. erlotinib =0.005; p gefitinib vs. icotinib =0.002). Notably, erlotinib exhibited a better treatment efficacy than icotinib ( p =0.037). Consistently, immunohistochemical data showed that TKIs differentially inhibit the proliferation of metastatical tumor cells. Gefitinib and erlotinib markedly inhibited the proliferation of tumor cells, while there were more ki-67-positive tumor cells in the icotinib group. Additionally, gefitinib inhibited the phosphorylation of EGFR better than the other drugs, whereas pEGFR expression levels in erlotinib groups were lower than levels in the icotinib group ( p gefitinib vs. erlotinib =0.995; p gefitinib vs. icotinib =0.028; p erlotinib vs. icotinib =0.042).Altogether, our findings suggest that gefitinib and erlotinib can inhibit the growth of PC-9-luc brain tumors. Gefitinib demonstrated better antitumor activity and penetration rate in brain metastases than erlotinib or icotinib.

Tyrosine kinase inhibitors show different anti-brain metastases efficacy in NSCLC: A direct comparative analysis of icotinib, gefitinib, and erlotinib in a nude mouse model

PubMed Central

Tan, Jianlong; Li, Min; Zhong, Wen; Hu, Chengping; Gu, Qihua; Xie, Yali

2017-01-01

Brain metastasis is an increasing problem in non-small cell lung cancer (NSCLC) patients. Tyrosine kinase inhibitors (TKIs), including gefitinib, erlotinib, and icotinib, are reported to be effective in patients with brain metastases. However, direct comparative studies of the pharmacokinetics and efficacy of these three drugs in treating brain metastases are lacking. In the present investigation, we found that gefitinib penetrated the blood-tumor barrier and was distributed to brain metastases more effectively than erlotinib or icotinib in a nude mouse model. The 1-h ratio of brain metastases to plasma concentration for gefitinib, erlotinib, and icotinib was 9.82±1.03%, 4.83±0.25%, and 2.62±0.21%, respectively. The 2-h ratio of brain metastases to plasma concentration for gefitinib, erlotinib, and icotinib was 15.11±2.00%, 5.73±1.31%, and 2.69±0.31%, respectively. Gefitinib exhibited the strongest antitumor activity (pgefitinib vs. erlotinib=0.005; pgefitinib vs. icotinib=0.002). Notably, erlotinib exhibited a better treatment efficacy than icotinib (p=0.037). Consistently, immunohistochemical data showed that TKIs differentially inhibit the proliferation of metastatical tumor cells. Gefitinib and erlotinib markedly inhibited the proliferation of tumor cells, while there were more ki-67-positive tumor cells in the icotinib group. Additionally, gefitinib inhibited the phosphorylation of EGFR better than the other drugs, whereas pEGFR expression levels in erlotinib groups were lower than levels in the icotinib group (pgefitinib vs. erlotinib=0.995; pgefitinib vs. icotinib=0.028; perlotinib vs. icotinib=0.042).Altogether, our findings suggest that gefitinib and erlotinib can inhibit the growth of PC-9-luc brain tumors. Gefitinib demonstrated better antitumor activity and penetration rate in brain metastases than erlotinib or icotinib. PMID:29228726

Multivariate analysis of prognostic factors in male breast cancer in Serbia.

PubMed

Sipetic-Grujicic, Sandra Branko; Murtezani, Zafir Hajdar; Neskovic-Konstatinovic, Zora Borivoje; Marinkovic, Jelena Milutin; Kovcin, Vladimir Nikola; Andric, Zoran Gojko; Kostic, Sanja Vladeta; Ratkov, Isidora Stojan; Maksimovic, Jadranka Milutin

2014-01-01

The aim of this study was to analyze the demographic and clinical characteristics of male breast cancer patients in Serbia, and furthermore to determine overall survival and predictive factors for prognosis. In the period of 1996-2006 histopathological diagnosis of breast cancer was made in 84 males at the Institute for Oncology and Radiology of Serbia. For statistical analyses the Kaplan-Meier method, long-rank test and Cox proportional hazards regression model were used. The mean age at diagnosis with breast cancer was 64.3±10.5 years with a range from 35-84 years. Nearly 80% of the tumors showed ductal histology. About 44% had early tumor stages (I and II) whereas 46.4% and 9.5% of the male exhibited stages III and IV, respectively. Only 7.1% of male patients were grade one. One-fifth of all patients had tumors measuring ≤2 cm, and 14.3% larger than 5 cm. Lymph node metastasis was recorded in 40.4% patients and 47% relapse. Estrogen and progesterone receptor expression was positive in 66.7% and 58.3%, respectively. Among 14.3% of individuals tumor was HER2 positive. About two-thirds of all male patients had radical mastectomy (66.7%). Adjuvant hormonal (tamoxifene), systematic chemotherapy (CMF or FAC) and adjuvant radiotherapy were given to 59.5%, 35.7% and 29.8% patients respectively. Overall survival rates at five and ten years for male breast cancer were 55.0% and 43.9%, respectively. According to the multivariate Cox regression predictive model, a lower initial disease stage, a lower tumor grade, application of adjuvant hormone therapy and no relapse occurrence were significant independent predictors for good overall survival. Results of the treatment would be better if disease is discovered earlier and therefore health education and screening are an imperative in solving this problem.

Radioimmunotherapy with monoclonal antibodies. A new horizon in nuclear medicine therapy?

PubMed

Sautter-Bihl, M L; Bihl, H

1994-08-01

Radioimmunotherapy (RIT) with labeled tumor-associated monoclonal antibodies (MAbs) is a promising concept in oncology, which essentially consists of biological targeting of ionising radiation to tumors. Some encouraging clinical results have been achieved with RIT. However, there are severe problems associated with both understanding the mechanisms and predicting the effectiveness of RIT. This paper reviews the results of some major clinical trials, especially in malignant lymphomas and in some solid tumors. Furthermore, problems with RIT are described such as the significance of dose inhomogeneity and dose-rate effects, the appropriate dose calculation method, the toxicity of RIT and the development of HAMAs. It is suggested that newer technologies including chimeric antibodies, multiple-step targeting protocols, bone marrow transplantation, parallel application of external radiation, heat or bioreductive drugs will enable RIT to make an essential contribution to strategies for combating cancer.

Advancing bioluminescence imaging technology for the evaluation of anticancer agents in the MDA-MB-435-HAL-Luc mammary fat pad and subrenal capsule tumor models.

PubMed

Zhang, Cathy; Yan, Zhengming; Arango, Maria E; Painter, Cory L; Anderes, Kenna

2009-01-01

Tumors grafted s.c. or under the mammary fat pad (MFP) rarely develop efficient metastasis. By applying bioluminescence imaging (BLI) technology, the MDA-MB-435-HAL-Luc subrenal capsule (SRC) model was compared with the MFP model for disease progression, metastatic potential, and response to therapy. The luciferase-expressing MDA-MB-435-HAL-Luc cell line was used in both MFP and SRC models. BLI technology allowed longitudinal assessment of disease progression and the therapeutic response to PD-0332991, Avastin, and docetaxel. Immunohistochemical analysis of Ki67 and CD31 staining in the primary tumors was compared in these models. Caliper measurement was used in the MFP model to validate the BLI quantification of primary tumors. The primary tumors in MDA-MB-435-HAL-Luc MFP and SRC models displayed comparable growth rates and vascularity. However, tumor-bearing mice in the SRC model developed lung metastases much earlier (4 weeks) than in the MFP model (>7 weeks), and the metastatic progression contributed significantly to the survival time. In the MFP model, BLI and caliper measurements were comparable for quantifying palpable tumors, but BLI offered an advantage for detecting the primary tumors that fell below a palpable threshold and for visualizing metastases. In the SRC model, BLI allowed longitudinal assessment of the antitumor and antimetastatic effects of PD-0332991, Avastin, and docetaxel, and the results correlated with the survival benefits of these agents. The MDA-MB-435-HAL-Luc SRC model and the MFP model displayed differences in disease progression. BLI is an innovative approach for developing animal models and creates opportunities for improving preclinical evaluations of anticancer agents.

Immunohistochemical detection of tumor suppressor gene p53 protein in feline injection site-associated sarcomas.

PubMed

Nambiar, P R; Jackson, M L; Ellis, J A; Chelack, B J; Kidney, B A; Haines, D M

2001-03-01

Sarcomas associated with injection sites are a rare but important problem in cats. Immunohistochemical detection of p53 protein may correlate to mutation of the p53 tumor suppressor gene, a gene known to be important in oncogenesis. The expression of nuclear p53 protein in 40 feline injection site-assocated sarcomas was examined by immunohistochemical staining. In 42.5% (17/40), tumor cell nuclei were stained darkly; in 20% (8/40), tumor cell nuclei were stained palely; and in 37.5% (15/40), tumor cell nuclei were unstained. Immunohistochemical detection of p53 protein in a proportion of injection site-associated sarcomas suggests that mutation of the p53 gene may play a role in the pathogenesis of these tumors.

Investigation of Particle Accumulation, Chemosensitivity and Thermosensitivity for Effective Solid Tumor Therapy Using Thermosensitive Liposomes and Hyperthermia.

PubMed

Lokerse, Wouter J M; Bolkestein, Michiel; Ten Hagen, Timo L M; de Jong, Marion; Eggermont, Alexander M M; Grüll, Holger; Koning, Gerben A

2016-01-01

Doxorubicin (Dox) loaded thermosensitive liposomes (TSLs) have shown promising results for hyperthermia-induced local drug delivery to solid tumors. Typically, the tumor is heated to hyperthermic temperatures (41-42 °C), which induced intravascular drug release from TSLs within the tumor tissue leading to high local drug concentrations (1-step delivery protocol). Next to providing a trigger for drug release, hyperthermia (HT) has been shown to be cytotoxic to tumor tissue, to enhance chemosensitivity and to increase particle extravasation from the vasculature into the tumor interstitial space. The latter can be exploited for a 2-step delivery protocol, where HT is applied prior to i.v. TSL injection to enhance tumor uptake, and after 4 hours waiting time for a second time to induce drug release. In this study, we compare the 1- and 2-step delivery protocols and investigate which factors are of importance for a therapeutic response. In murine B16 melanoma and BFS-1 sarcoma cell lines, HT induced an enhanced Dox uptake in 2D and 3D models, resulting in enhanced chemosensitivity. In vivo, therapeutic efficacy studies were performed for both tumor models, showing a therapeutic response for only the 1-step delivery protocol. SPECT/CT imaging allowed quantification of the liposomal accumulation in both tumor models at physiological temperatures and after a HT treatment. A simple two compartment model was used to derive respective rates for liposomal uptake, washout and retention, showing that the B16 model has a twofold higher liposomal uptake compared to the BFS-1 tumor. HT increases uptake and retention of liposomes in both tumors models by the same factor of 1.66 maintaining the absolute differences between the two models. Histology showed that HT induced apoptosis, blood vessel integrity and interstitial structures are important factors for TSL accumulation in the investigated tumor types. However, modeling data indicated that the intraliposomal Dox fraction did not reach therapeutic relevant concentrations in the tumor tissue in a 2-step delivery protocol due to the leaking of the drug from its liposomal carrier providing an explanation for the observed lack of efficacy.

Drug delivery to solid tumors: the predictive value of the multicellular tumor spheroid model for nanomedicine screening.

PubMed

Millard, Marie; Yakavets, Ilya; Zorin, Vladimir; Kulmukhamedova, Aigul; Marchal, Sophie; Bezdetnaya, Lina

2017-01-01

The increasing number of publications on the subject shows that nanomedicine is an attractive field for investigations aiming to considerably improve anticancer chemotherapy. Based on selective tumor targeting while sparing healthy tissue, carrier-mediated drug delivery has been expected to provide significant benefits to patients. However, despite reduced systemic toxicity, most nanodrugs approved for clinical use have been less effective than previously anticipated. The gap between experimental results and clinical outcomes demonstrates the necessity to perform comprehensive drug screening by using powerful preclinical models. In this context, in vitro three-dimensional models can provide key information on drug behavior inside the tumor tissue. The multicellular tumor spheroid (MCTS) model closely mimics a small avascular tumor with the presence of proliferative cells surrounding quiescent cells and a necrotic core. Oxygen, pH and nutrient gradients are similar to those of solid tumor. Furthermore, extracellular matrix (ECM) components and stromal cells can be embedded in the most sophisticated spheroid design. All these elements together with the physicochemical properties of nanoparticles (NPs) play a key role in drug transport, and therefore, the MCTS model is appropriate to assess the ability of NP to penetrate the tumor tissue. This review presents recent developments in MCTS models for a better comprehension of the interactions between NPs and tumor components that affect tumor drug delivery. MCTS is particularly suitable for the high-throughput screening of new nanodrugs.

Lassa-Vesicular Stomatitis Chimeric Virus Safely Destroys Brain Tumors

PubMed Central

Wollmann, Guido; Drokhlyansky, Eugene; Davis, John N.; Cepko, Connie

2015-01-01

ABSTRACT High-grade tumors in the brain are among the deadliest of cancers. Here, we took a promising oncolytic virus, vesicular stomatitis virus (VSV), and tested the hypothesis that the neurotoxicity associated with the virus could be eliminated without blocking its oncolytic potential in the brain by replacing the neurotropic VSV glycoprotein with the glycoprotein from one of five different viruses, including Ebola virus, Marburg virus, lymphocytic choriomeningitis virus (LCMV), rabies virus, and Lassa virus. Based on in vitro infections of normal and tumor cells, we selected two viruses to test in vivo. Wild-type VSV was lethal when injected directly into the brain. In contrast, a novel chimeric virus (VSV-LASV-GPC) containing genes from both the Lassa virus glycoprotein precursor (GPC) and VSV showed no adverse actions within or outside the brain and targeted and completely destroyed brain cancer, including high-grade glioblastoma and melanoma, even in metastatic cancer models. When mice had two brain tumors, intratumoral VSV-LASV-GPC injection in one tumor (glioma or melanoma) led to complete tumor destruction; importantly, the virus moved contralaterally within the brain to selectively infect the second noninjected tumor. A chimeric virus combining VSV genes with the gene coding for the Ebola virus glycoprotein was safe in the brain and also selectively targeted brain tumors but was substantially less effective in destroying brain tumors and prolonging survival of tumor-bearing mice. A tropism for multiple cancer types combined with an exquisite tumor specificity opens a new door to widespread application of VSV-LASV-GPC as a safe and efficacious oncolytic chimeric virus within the brain. IMPORTANCE Many viruses have been tested for their ability to target and kill cancer cells. Vesicular stomatitis virus (VSV) has shown substantial promise, but a key problem is that if it enters the brain, it can generate adverse neurologic consequences, including death. We tested a series of chimeric viruses containing genes coding for VSV, together with a gene coding for the glycoprotein from other viruses, including Ebola virus, Lassa virus, LCMV, rabies virus, and Marburg virus, which was substituted for the VSV glycoprotein gene. Ebola and Lassa chimeric viruses were safe in the brain and targeted brain tumors. Lassa-VSV was particularly effective, showed no adverse side effects even when injected directly into the brain, and targeted and destroyed two different types of deadly brain cancer, including glioblastoma and melanoma. PMID:25878115

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

PubMed

Pereira, Sergio; Pinto, Adriano; Alves, Victor; Silva, Carlos A

2016-05-01

Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3 ×3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0.88, 0.83, 0.77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0.78, 0.65, and 0.75 for the complete, core, and enhancing regions, respectively.

Study on fluorouracil-chitosan nanoparticle preparation and its antitumor effect.

PubMed

Chen, Gaimin; Gong, Rudong

2016-05-01

To successfully prepare fluorouracil-chitosan nanoparticles, and further analyze its anti-tumor activity mechanism, this paper makes a comprehensive study of existing preparation prescription and makes a detailed analysis of fluorouracil-chitosan in vitro release and pharmacodynamic behavior of animals. Two-step synthesis method is adopted to prepare 5-FU-CS-mPEG prodrugs, and infrared, (1)H NMR and differential thermal analysis are adopted to analyze characterization synthetic products of prepared drugs. To ensure clinical efficacy of prepared drugs, UV spectrophotometry is adopted for determination of drug loading capacity of prepared drugs, transmission electron microscopy is adopted to observe the appearance, dynamic dialysis method is used to observe in vitro drug release of prepared drugs and fitting of various release models is done. Anti-tumor effect is studied via level of animal pharmacodynamics. After the end of the experiment, tumor inhibition rate, spleen index and thymus index of drugs are calculated. Experimental results show that the prepared drugs are qualified in terms of regular shape, dispersion, drug content, etc. Animal pharmacodynamics experiments have shown that concentration level of drug loading capacity of prepared drugs has a direct impact on anti-tumor rate. The higher the concentration, the higher the anti-tumor rate. Results of pathological tissue sections of mice show that the prepared drugs cause varying degrees of damage to receptor cells, resulting in cell necrosis or apoptosis problem. It can thus be concluded that ion gel method is an effective method to prepare drug-loading nanoparticles, with prepared nanoparticles evenly distributed in regular shape which demonstrate good slow-release characteristics in receptor vitro and vivo. At the same time, after completion of drug preparation, relatively strong anti-tumor activity can be generated for the receptor, so this mode of preparation enjoys broad prospects for development.

Radiation-induced equilibrium is a balance between tumor cell proliferation and T cell-mediated killing

PubMed Central

Liang, Hua; Deng, Liufu; Chmura, Steven; Burnette, Byron; Liadis, Nicole; Darga, Thomas; Beckett, Michael A.; Lingen, Mark W.; Witt, MaryEllyn; Weichselbaum, Ralph R.; Fu, Yang-Xin

2013-01-01

Local failures following radiation therapy are multifactorial and the contributions of the tumor and the host are complex. Current models of tumor equilibrium suggest that a balance exists between cell birth and cell death due to insufficient angiogenesis, immune effects, or intrinsic cellular factors. We investigated whether host immune responses contribute to radiation induced tumor equilibrium in animal models. We report an essential role for immune cells and their cytokines in suppressing tumor cell regrowth in two experimental animal model systems. Depletion of T cells or neutralization of interferon-gamma reversed radiation-induced equilibrium leading to tumor regrowth. We also demonstrate that PD-L1 blockade augments T cell responses leading to rejection of tumors in radiation induced equilibrium. We identify an active interplay between tumor cells and immune cells that occurs in radiation-induced tumor equilibrium and suggest a potential role for disruption of the PD-L1/PD-1 axis in increasing local tumor control. PMID:23630355

Emergent Behaviors from a Cellular Automaton Model for Invasive Tumor Growth in Heterogeneous Microenvironments

PubMed Central

Jiao, Yang; Torquato, Salvatore

2011-01-01

Understanding tumor invasion and metastasis is of crucial importance for both fundamental cancer research and clinical practice. In vitro experiments have established that the invasive growth of malignant tumors is characterized by the dendritic invasive branches composed of chains of tumor cells emanating from the primary tumor mass. The preponderance of previous tumor simulations focused on non-invasive (or proliferative) growth. The formation of the invasive cell chains and their interactions with the primary tumor mass and host microenvironment are not well understood. Here, we present a novel cellular automaton (CA) model that enables one to efficiently simulate invasive tumor growth in a heterogeneous host microenvironment. By taking into account a variety of microscopic-scale tumor-host interactions, including the short-range mechanical interactions between tumor cells and tumor stroma, degradation of the extracellular matrix by the invasive cells and oxygen/nutrient gradient driven cell motions, our CA model predicts a rich spectrum of growth dynamics and emergent behaviors of invasive tumors. Besides robustly reproducing the salient features of dendritic invasive growth, such as least-resistance paths of cells and intrabranch homotype attraction, we also predict nontrivial coupling between the growth dynamics of the primary tumor mass and the invasive cells. In addition, we show that the properties of the host microenvironment can significantly affect tumor morphology and growth dynamics, emphasizing the importance of understanding the tumor-host interaction. The capability of our CA model suggests that sophisticated in silico tools could eventually be utilized in clinical situations to predict neoplastic progression and propose individualized optimal treatment strategies. PMID:22215996

Gaussian process inference for estimating pharmacokinetic parameters of dynamic contrast-enhanced MR images.

PubMed

Wang, Shijun; Liu, Peter; Turkbey, Baris; Choyke, Peter; Pinto, Peter; Summers, Ronald M

2012-01-01

In this paper, we propose a new pharmacokinetic model for parameter estimation of dynamic contrast-enhanced (DCE) MRI by using Gaussian process inference. Our model is based on the Tofts dual-compartment model for the description of tracer kinetics and the observed time series from DCE-MRI is treated as a Gaussian stochastic process. The parameter estimation is done through a maximum likelihood approach and we propose a variant of the coordinate descent method to solve this likelihood maximization problem. The new model was shown to outperform a baseline method on simulated data. Parametric maps generated on prostate DCE data with the new model also provided better enhancement of tumors, lower intensity on false positives, and better boundary delineation when compared with the baseline method. New statistical parameter maps from the process model were also found to be informative, particularly when paired with the PK parameter maps.

Tumor cell culture on collagen-chitosan scaffolds as three-dimensional tumor model: A suitable model for tumor studies.

PubMed

Mahmoudzadeh, Aziz; Mohammadpour, Hemn

2016-07-01

Tumor cells naturally live in three-dimensional (3D) microenvironments, while common laboratory tests and evaluations are done in two-dimensional (2D) plates. This study examined the impact of cultured 4T1 cancer cells in a 3D collagen-chitosan scaffold compared with 2D plate cultures. Collagen-chitosan scaffolds were provided and passed confirmatory tests. 4T1 tumor cells were cultured on scaffolds and then tumor cells growth rate, resistance to X-ray radiation, and cyclophosphamide as a chemotherapy drug were analyzed. Furthermore, 4T1 cells were extracted from the scaffold model and were injected into the mice. Tumor growth rate, survival rate, and systemic immune responses were evaluated. Our results showed that 4T1 cells infiltrated the scaffolds pores and constructed a 3D microenvironment. Furthermore, 3D cultured tumor cells showed a slower proliferation rate, increased levels of survival to the X-ray irradiation, and enhanced resistance to chemotherapy drugs in comparison with 2D plate cultures. Transfer of extracted cells to the mice caused enhanced tumor volume and decreased life span. This study indicated that collagen-chitosan nanoscaffolds provide a suitable model of tumor that would be appropriate for tumor studies. Copyright © 2016. Published by Elsevier B.V.

Personalized Cancer Medicine: An Organoid Approach.

PubMed

Aboulkheyr Es, Hamidreza; Montazeri, Leila; Aref, Amir Reza; Vosough, Massoud; Baharvand, Hossein

2018-04-01

Personalized cancer therapy applies specific treatments to each patient. Using personalized tumor models with similar characteristics to the original tumors may result in more accurate predictions of drug responses in patients. Tumor organoid models have several advantages over pre-existing models, including conserving the molecular and cellular composition of the original tumor. These advantages highlight the tremendous potential of tumor organoids in personalized cancer therapy, particularly preclinical drug screening and predicting patient responses to selected treatment regimens. Here, we highlight the advantages, challenges, and translational potential of tumor organoids in personalized cancer therapy and focus on gene-drug associations, drug response prediction, and treatment selection. Finally, we discuss how microfluidic technology can contribute to immunotherapy drug screening in tumor organoids. Copyright © 2017 Elsevier Ltd. All rights reserved.

Drug screening in 3D in vitro tumor models: overcoming current pitfalls of efficacy read-outs.

PubMed

Santo, Vítor E; Rebelo, Sofia P; Estrada, Marta F; Alves, Paula M; Boghaert, Erwin; Brito, Catarina

2017-01-01

There is cumulating evidence that in vitro 3D tumor models with increased physiological relevance can improve the predictive value of pre-clinical research and ultimately contribute to achieve decisions earlier during the development of cancer-targeted therapies. Due to the role of tumor microenvironment in the response of tumor cells to therapeutics, the incorporation of different elements of the tumor niche on cell model design is expected to contribute to the establishment of more predictive in vitro tumor models. This review is focused on the several challenges and adjustments that the field of oncology research is facing to translate these advanced tumor cells models to drug discovery, taking advantage of the progress on culture technologies, imaging platforms, high throughput and automated systems. The choice of 3D cell model, the experimental design, choice of read-outs and interpretation of data obtained from 3D cell models are critical aspects when considering their implementation in drug discovery. In this review, we foresee some of these aspects and depict the potential directions of pre-clinical oncology drug discovery towards improved prediction of drug efficacy. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Production of 3D Tumor Spheroids for Cancer Drug Discovery

PubMed Central

Sant, Shilpa; Johnston, Paul A.

2017-01-01

New cancer drug approval rates are ≤ 5% despite significant investments in cancer research, drug discovery and development. One strategy to improve the rate of success of new cancer drugs transitioning into the clinic would be to more closely align the cellular models used in the early lead discovery with pre-clinical animal models and patient tumors. For solid tumors, this would mandate the development and implementation of three dimensional (3D) in vitro tumor models that more accurately recapitulate human solid tumor architecture and biology. Recent advances in tissue engineering and regenerative medicine have provided new techniques for 3D spheroid generation and a variety of in vitro 3D cancer models are being explored for cancer drug discovery. Although homogeneous assay methods and high content imaging approaches to assess tumor spheroid morphology, growth and viability have been developed, the implementation of 3D models in HTS remains challenging due to reasons that we discuss in this review. Perhaps the biggest obstacle to achieve acceptable HTS assay performance metrics occurs in 3D tumor models that produce spheroids with highly variable morphologies and/or sizes. We highlight two methods that produce uniform size-controlled 3D multicellular tumor spheroids that are compatible with cancer drug research and HTS; tumor spheroids formed in ultra-low attachment microplates, or in polyethylene glycol dimethacrylate hydrogel microwell arrays. PMID:28647083

Lung tumor motion prediction during lung brachytherapy using finite element model

NASA Astrophysics Data System (ADS)

Shirzadi, Zahra; Sadeghi Naini, Ali; Samani, Abbas

2012-02-01

A biomechanical model is proposed to predict deflated lung tumor motion caused by diaphragm respiratory motion. This model can be very useful for targeting the tumor in tumor ablative procedures such as lung brachytherapy. To minimize motion within the target lung, these procedures are performed while the lung is deflated. However, significant amount of tissue deformation still occurs during respiration due to the diaphragm contact forces. In the absence of effective realtime image guidance, biomechanical models can be used to estimate tumor motion as a function of diaphragm's position. To develop this model, Finite Element Method (FEM) was employed. To demonstrate the concept, we conducted an animal study of an ex-vivo porcine deflated lung with a tumor phantom. The lung was deformed by compressing a diaphragm mimicking cylinder against it. Before compression, 3D-CT image of this lung was acquired, which was segmented and turned into FE mesh. The lung tissue was modeled as hyperelastic material with a contact loading to calculate the lung deformation and tumor motion during respiration. To validate the results from FE model, the motion of a small area on the surface close to the tumor was tracked while the lung was being loaded by the cylinder. Good agreement was demonstrated between the experiment results and simulation results. Furthermore, the impact of tissue hyperelastic parameters uncertainties in the FE model was investigated. For this purpose, we performed in-silico simulations with different hyperelastic parameters. This study demonstrated that the FEM was accurate and robust for tumor motion prediction.

Cytosolic phospholipaseA2 inhibition with PLA-695 radiosensitizes tumors in lung cancer animal models.

PubMed

Thotala, Dinesh; Craft, Jeffrey M; Ferraro, Daniel J; Kotipatruni, Rama P; Bhave, Sandeep R; Jaboin, Jerry J; Hallahan, Dennis E

2013-01-01

Lung cancer remains the leading cause of cancer deaths in the United States and the rest of the world. The advent of molecularly directed therapies holds promise for improvement in therapeutic efficacy. Cytosolic phospholipase A2 (cPLA2) is associated with tumor progression and radioresistance in mouse tumor models. Utilizing the cPLA2 specific inhibitor PLA-695, we determined if cPLA2 inhibition radiosensitizes non small cell lung cancer (NSCLC) cells and tumors. Treatment with PLA-695 attenuated radiation induced increases of phospho-ERK and phospho-Akt in endothelial cells. NSCLC cells (LLC and A549) co-cultured with endothelial cells (bEND3 and HUVEC) and pre-treated with PLA-695 showed radiosensitization. PLA-695 in combination with irradiation (IR) significantly reduced migration and proliferation in endothelial cells (HUVEC & bEND3) and induced cell death and attenuated invasion by tumor cells (LLC &A549). In a heterotopic tumor model, the combination of PLA-695 and radiation delayed growth in both LLC and A549 tumors. LLC and A549 tumors treated with a combination of PLA-695 and radiation displayed reduced tumor vasculature. In a dorsal skin fold model of LLC tumors, inhibition of cPLA2 in combination with radiation led to enhanced destruction of tumor blood vessels. The anti-angiogenic effects of PLA-695 and its enhancement of the efficacy of radiotherapy in mouse models of NSCLC suggest that clinical trials for its capacity to improve radiotherapy outcomes are warranted.

Tailored chemokine receptor modification improves homing of adoptive therapy T cells in a spontaneous tumor model.

PubMed

Garetto, Stefano; Sardi, Claudia; Martini, Elisa; Roselli, Giuliana; Morone, Diego; Angioni, Roberta; Cianciotti, Beatrice Claudia; Trovato, Anna Elisa; Franchina, Davide Giuseppe; Castino, Giovanni Francesco; Vignali, Debora; Erreni, Marco; Marchesi, Federica; Rumio, Cristiano; Kallikourdis, Marinos

2016-07-12

In recent years, tumor Adoptive Cell Therapy (ACT), using administration of ex vivo-enhanced T cells from the cancer patient, has become a promising therapeutic strategy. However, efficient homing of the anti-tumoral T cells to the tumor or metastatic site still remains a substantial hurdle. Yet the tumor site itself attracts both tumor-promoting and anti-tumoral immune cell populations through the secretion of chemokines. We attempted to identify these chemokines in a model of spontaneous metastasis, in order to "hijack" their function by expressing matching chemokine receptors on the cytotoxic T cells used in ACT, thus allowing us to enhance the recruitment of these therapeutic cells. Here we show that this enabled the modified T cells to preferentially home into spontaneous lymph node metastases in the TRAMP model, as well as in an inducible tumor model, E.G7-OVA. Due to the improved homing, the modified CD8+ T cells displayed an enhanced in vivo protective effect, as seen by a significant delay in E.G7-OVA tumor growth. These results offer a proof of principle for the tailored application of chemokine receptor modification as a means of improving T cell homing to the target tumor, thus enhancing ACT efficacy. Surprisingly, we also uncover that the formation of the peri-tumoral fibrotic capsule, which has been shown to impede T cell access to tumor, is partially dependent on host T cell presence. This finding, which would be impossible to observe in immunodeficient model studies, highlights possible conflicting roles that T cells may play in a therapeutic context.

Ranitidine modifies myeloid cell populations and inhibits breast tumor development and spread in mice

PubMed Central

Vila-Leahey, Ava; Oldford, Sharon A.; Marignani, Paola A.; Wang, Jun; Haidl, Ian D.; Marshall, Jean S.

2016-01-01

ABSTRACT Histamine receptor 2 (H2) antagonists are widely used clinically for the control of gastrointestinal symptoms, but also impact immune function. They have been reported to reduce tumor growth in established colon and lung cancer models. Histamine has also been reported to modify populations of myeloid-derived suppressor cells (MDSCs). We have examined the impact of the widely used H2 antagonist ranitidine, on both myeloid cell populations and tumor development and spread, in three distinct models of breast cancer that highlight different stages of cancer progression. Oral ranitidine treatment significantly decreased the monocytic MDSC population in the spleen and bone marrow both alone and in the context of an orthotopic breast tumor model. H2 antagonists ranitidine and famotidine, but not H1 or H4 antagonists, significantly inhibited lung metastasis in the 4T1 model. In the E0771 model, ranitidine decreased primary tumor growth while omeprazole treatment had no impact on tumor development. Gemcitabine treatment prevented the tumor growth inhibition associated with ranitidine treatment. In keeping with ranitidine-induced changes in myeloid cell populations in non-tumor-bearing mice, ranitidine also delayed the onset of spontaneous tumor development, and decreased the number of tumors that developed in LKB1−/−/NIC mice. These results indicate that ranitidine alters monocyte populations associated with MDSC activity, and subsequently impacts breast tumor development and outcome. Ranitidine has potential as an adjuvant therapy or preventative agent in breast cancer and provides a novel and safe approach to the long-term reduction of tumor-associated immune suppression. PMID:27622015

The Application of Heptamethine Cyanine Dye DZ-1 and Indocyanine Green for Imaging and Targeting in Xenograft Models of Hepatocellular Carcinoma

PubMed Central

Zhang, Caiqin; Zhao, Yong; Zhang, He; Chen, Xue; Zhao, Ningning; Tan, Dengxu; Zhang, Hai; Shi, Changhong

2017-01-01

Near infrared fluorescence (NIRF) imaging has strong potential for widespread use in noninvasive tumor imaging. Indocyanine green (ICG) is the only Food and Drug Administration (FDA) -approved NIRF dye for clinical diagnosis; however, it is unstable and poorly targets tumors. DZ-1 is a novel heptamethine cyanine NIRF dye, suitable for imaging and tumor targeting. Here, we compared the fluorescence intensity and metabolism of DZ-1 and ICG. Additionally, we assayed their specificities and abilities to target tumor cells, using cultured hepatocellular carcinoma (HCC) cell lines, a nude mouse subcutaneous xenograft model of liver cancer, and a rabbit orthotopic transplantation model. We found that DZ-1 accumulates in tumor tissue and specifically recognizes HCC in subcutaneous and orthotopic models. The NIRF intensity of DZ-1 was one order of magnitude stronger than that of ICG, and DZ-1 showed excellent intraoperative tumor targeting in the rabbit model. Importantly, ICG accumulated at tumor sites, as well as in the liver and kidney. Furthermore, DZ-1 analog-gemcitabine conjugate (NIRG) exhibited similar tumor-specific targeting and imaging properties, including inhibition of tumor growth, in HCC patient-derived xenograft (PDX) mice. DZ-1 and NIRG demonstrated superior tumor-targeting specificity, compared to ICG. We show that DZ-1 is an effective molecular probe for specific imaging, targeting, and therapy in HCC. PMID:28635650

The Application of Heptamethine Cyanine Dye DZ-1 and Indocyanine Green for Imaging and Targeting in Xenograft Models of Hepatocellular Carcinoma.

PubMed

Zhang, Caiqin; Zhao, Yong; Zhang, He; Chen, Xue; Zhao, Ningning; Tan, Dengxu; Zhang, Hai; Shi, Changhong

2017-06-21

Near infrared fluorescence (NIRF) imaging has strong potential for widespread use in noninvasive tumor imaging. Indocyanine green (ICG) is the only Food and Drug Administration (FDA) -approved NIRF dye for clinical diagnosis; however, it is unstable and poorly targets tumors. DZ-1 is a novel heptamethine cyanine NIRF dye, suitable for imaging and tumor targeting. Here, we compared the fluorescence intensity and metabolism of DZ-1 and ICG. Additionally, we assayed their specificities and abilities to target tumor cells, using cultured hepatocellular carcinoma (HCC) cell lines, a nude mouse subcutaneous xenograft model of liver cancer, and a rabbit orthotopic transplantation model. We found that DZ-1 accumulates in tumor tissue and specifically recognizes HCC in subcutaneous and orthotopic models. The NIRF intensity of DZ-1 was one order of magnitude stronger than that of ICG, and DZ-1 showed excellent intraoperative tumor targeting in the rabbit model. Importantly, ICG accumulated at tumor sites, as well as in the liver and kidney. Furthermore, DZ-1 analog-gemcitabine conjugate (NIRG) exhibited similar tumor-specific targeting and imaging properties, including inhibition of tumor growth, in HCC patient-derived xenograft (PDX) mice. DZ-1 and NIRG demonstrated superior tumor-targeting specificity, compared to ICG. We show that DZ-1 is an effective molecular probe for specific imaging, targeting, and therapy in HCC.

Brain tumor modeling: glioma growth and interaction with chemotherapy

NASA Astrophysics Data System (ADS)

Banaem, Hossein Y.; Ahmadian, Alireza; Saberi, Hooshangh; Daneshmehr, Alireza; Khodadad, Davood

2011-10-01

In last decade increasingly mathematical models of tumor growths have been studied, particularly on solid tumors which growth mainly caused by cellular proliferation. In this paper we propose a modified model to simulate the growth of gliomas in different stages. Glioma growth is modeled by a reaction-advection-diffusion. We begin with a model of untreated gliomas and continue with models of polyclonal glioma following chemotherapy. From relatively simple assumptions involving homogeneous brain tissue bounded by a few gross anatomical landmarks (ventricles and skull) the models have been expanded to include heterogeneous brain tissue with different motilities of glioma cells in grey and white matter. Tumor growth is characterized by a dangerous change in the control mechanisms, which normally maintain a balance between the rate of proliferation and the rate of apoptosis (controlled cell death). Result shows that this model closes to clinical finding and can simulate brain tumor behavior properly.

Model-Based Radiation Dose Correction for Yttrium-90 Microsphere Treatment of Liver Tumors With Central Necrosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Ching-Sheng; Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; Lin, Ko-Han

Purpose: The objectives of this study were to model and calculate the absorbed fraction {phi} of energy emitted from yttrium-90 ({sup 90}Y) microsphere treatment of necrotic liver tumors. Methods and Materials: The tumor necrosis model was proposed for the calculation of {phi} over the spherical shell region. Two approaches, the semianalytic method and the probabilistic method, were adopted. In the former method, the range--energy relationship and the sampling of electron paths were applied to calculate the energy deposition within the target region, using the straight-ahead and continuous-slowing-down approximation (CSDA) method. In the latter method, the Monte Carlo PENELOPE code wasmore » used to verify results from the first method. Results: The fraction of energy, {phi}, absorbed from {sup 90}Y by 1-cm thickness of tumor shell from microsphere distribution by CSDA with complete beta spectrum was 0.832 {+-} 0.001 and 0.833 {+-} 0.001 for smaller (r{sub T} = 5 cm) and larger (r{sub T} = 10 cm) tumors (where r is the radii of the tumor [T] and necrosis [N]). The fraction absorbed depended mainly on the thickness of the tumor necrosis configuration, rather than on tumor necrosis size. The maximal absorbed fraction {phi} that occurred in tumors without central necrosis for each size of tumor was different: 0.950 {+-} 0.000, and 0.975 {+-} 0.000 for smaller (r{sub T} = 5 cm) and larger (r{sub T} = 10 cm) tumors, respectively (p < 0.0001). Conclusions: The tumor necrosis model was developed for dose calculation of {sup 90}Y microsphere treatment of hepatic tumors with central necrosis. With this model, important information is provided regarding the absorbed fraction applicable to clinical {sup 90}Y microsphere treatment.« less

Classification of brain tumors using texture based analysis of T1-post contrast MR scans in a preclinical model

NASA Astrophysics Data System (ADS)

Tang, Tien T.; Zawaski, Janice A.; Francis, Kathleen N.; Qutub, Amina A.; Gaber, M. Waleed

2018-02-01

Accurate diagnosis of tumor type is vital for effective treatment planning. Diagnosis relies heavily on tumor biopsies and other clinical factors. However, biopsies do not fully capture the tumor's heterogeneity due to sampling bias and are only performed if the tumor is accessible. An alternative approach is to use features derived from routine diagnostic imaging such as magnetic resonance (MR) imaging. In this study we aim to establish the use of quantitative image features to classify brain tumors and extend the use of MR images beyond tumor detection and localization. To control for interscanner, acquisition and reconstruction protocol variations, the established workflow was performed in a preclinical model. Using glioma (U87 and GL261) and medulloblastoma (Daoy) models, T1-weighted post contrast scans were acquired at different time points post-implant. The tumor regions at the center, middle, and peripheral were analyzed using in-house software to extract 32 different image features consisting of first and second order features. The extracted features were used to construct a decision tree, which could predict tumor type with 10-fold cross-validation. Results from the final classification model demonstrated that middle tumor region had the highest overall accuracy at 79%, while the AUC accuracy was over 90% for GL261 and U87 tumors. Our analysis further identified image features that were unique to certain tumor region, although GL261 tumors were more homogenous with no significant differences between the central and peripheral tumor regions. In conclusion our study shows that texture features derived from MR scans can be used to classify tumor type with high success rates. Furthermore, the algorithm we have developed can be implemented with any imaging datasets and may be applicable to multiple tumor types to determine diagnosis.

[Tumor cells transfer between the patient and laboratory animal as a basic methodological approach to the study of cancerogenesis and identification of biomarkers].

PubMed

Klos, D; Stašek, M; Loveček, M; Skalický, P; Vrba, R; Aujeský, R; Havlík, R; Neoral, Č; Varanashi, L; Hajdúch, M; Vrbková, J; Džubák, P

The investigation of prognostic and predictive factors for early diagnosis of tumors, their surveillance and monitoring of the impact of therapeutic modalities using hybrid laboratory models in vitro/in vivo is an experimental approach with a significant potential. It is preconditioned by the preparation of in vivo tumor models, which may face a number of potential technical difficulties. The assessment of technical success of grafting and xenotransplantation based on the type of the tumor or cell line is important for the preparation of these models and their further use for proteomic and genomic analyses. Surgically harvested gastrointestinal tract tumor tissue was processed or stable cancer cell lines were cultivated; the viability was assessed, and subsequently the cells were inoculated subcutaneously to SCID mice with an individual duration of tumor growth, followed by its extraction. We analysed 140 specimens of tumor tissue including 17 specimens of esophageal cancer (viability 13/successful inoculations 0), 13 tumors of the cardia (11/0), 39 gastric tumors (24/4), 47 pancreatic tumors (34/1) and 24 specimens of colorectal cancer (22/9). 3 specimens were excluded due to histological absence of the tumor (complete remission after neoadjuvant therapy in 2 cases of esophageal carcinoma, 1 case of chronic pancreatitis). We observed successful inoculation in 17 of 28 tumor cell lines. The probability of successful grafting to the mice model in tumors of the esophagus, stomach and pancreas is significantly lower in comparison with colorectal carcinoma and cell lines generated tumors. The success rate is enhanced upon preservation of viability of the harvested tumor tissue, which depends on the sequence of clinical and laboratory algorithms with a high level of cooperation.Key words: proteomic analysis - xenotransplantation - prognostic and predictive factors - gastrointestinal tract tumors.

MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data.

PubMed

Fan, Yu; Xi, Liu; Hughes, Daniel S T; Zhang, Jianjun; Zhang, Jianhua; Futreal, P Andrew; Wheeler, David A; Wang, Wenyi

2016-08-24

Subclonal mutations reveal important features of the genetic architecture of tumors. However, accurate detection of mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We develop MuSE ( http://bioinformatics.mdanderson.org/main/MuSE ), Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of the tumor and normal tissue at each reference base. MuSE adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.

Cooperative effects of aminopeptidase N (CD13) expressed by nonmalignant and cancer cells within the tumor microenvironment.

PubMed

Guzman-Rojas, Liliana; Rangel, Roberto; Salameh, Ahmad; Edwards, Julianna K; Dondossola, Eleonora; Kim, Yun-Gon; Saghatelian, Alan; Giordano, Ricardo J; Kolonin, Mikhail G; Staquicini, Fernanda I; Koivunen, Erkki; Sidman, Richard L; Arap, Wadih; Pasqualini, Renata

2012-01-31

Processes that promote cancer progression such as angiogenesis require a functional interplay between malignant and nonmalignant cells in the tumor microenvironment. The metalloprotease aminopeptidase N (APN; CD13) is often overexpressed in tumor cells and has been implicated in angiogenesis and cancer progression. Our previous studies of APN-null mice revealed impaired neoangiogenesis in model systems without cancer cells and suggested the hypothesis that APN expressed by nonmalignant cells might promote tumor growth. We tested this hypothesis by comparing the effects of APN deficiency in allografted malignant (tumor) and nonmalignant (host) cells on tumor growth and metastasis in APN-null mice. In two independent tumor graft models, APN activity in both the tumors and the host cells cooperate to promote tumor vascularization and growth. Loss of APN expression by the host and/or the malignant cells also impaired lung metastasis in experimental mouse models. Thus, cooperation in APN expression by both cancer cells and nonmalignant stromal cells within the tumor microenvironment promotes angiogenesis, tumor growth, and metastasis.

Dynamics of melanoma tumor therapy with vesicular stomatitis virus: explaining the variability in outcomes using mathematical modeling.

PubMed

Rommelfanger, D M; Offord, C P; Dev, J; Bajzer, Z; Vile, R G; Dingli, D

2012-05-01

Tumor selective, replication competent viruses are being tested for cancer gene therapy. This approach introduces a new therapeutic paradigm due to potential replication of the therapeutic agent and induction of a tumor-specific immune response. However, the experimental outcomes are quite variable, even when studies utilize highly inbred strains of mice and the same cell line and virus. Recognizing that virotherapy is an exercise in population dynamics, we utilize mathematical modeling to understand the variable outcomes observed when B16ova malignant melanoma tumors are treated with vesicular stomatitis virus in syngeneic, fully immunocompetent mice. We show how variability in the initial tumor size and the actual amount of virus delivered to the tumor have critical roles on the outcome of therapy. Virotherapy works best when tumors are small, and a robust innate immune response can lead to superior tumor control. Strategies that reduce tumor burden without suppressing the immune response and methods that maximize the amount of virus delivered to the tumor should optimize tumor control in this model system.

Intra-adrenal murine TH-MYCN neuroblastoma tumors grow more aggressive and exhibit a distinct tumor microenvironment relative to their subcutaneous equivalents.

PubMed

Kroesen, Michiel; Brok, Ingrid C; Reijnen, Daphne; van Hout-Kuijer, Maaike A; Zeelenberg, Ingrid S; Den Brok, Martijn H; Hoogerbrugge, Peter M; Adema, Gosse J

2015-05-01

In around half of the patients with neuroblastoma (NBL), the primary tumor is located in one of the adrenal glands. We have previously reported on a transplantable TH-MYCN model of subcutaneous (SC) growing NBL in C57Bl/6 mice for immunological studies. In this report, we describe an orthotopic TH-MYCN transplantable model where the tumor cells were injected intra-adrenally (IA) by microsurgery. Strikingly, 9464D cells grew out much faster in IA tumors compared to the subcutis. Tumors were infiltrated by equal numbers of lymphocytes and myeloid cells. Within the myeloid cell population, however, tumor-infiltrating macrophages were more abundant in IA tumors compared to SC tumors and expressed lower levels of MHC class II, indicative of a more immunosuppressive phenotype. Using 9464D cells stably expressing firefly luciferase, enhanced IA tumor growth could be confirmed using bioluminescence. Collectively, these data show that the orthotopic IA localization of TH-MYCN cells impacts the NBL tumor microenvironment, resulting in a more stringent NBL model to study novel immunotherapeutic approaches for NBL.

A stapled peptide antagonist of MDM2 carried by polymeric micelles sensitizes glioblastoma to temozolomide treatment through p53 activation

PubMed Central

Chen, Xishan; Tai, Lingyu; Gao, Jie; Qian, Jianchang; Zhang, Mingfei; Li, Beibei; Xie, Cao; Lu, Linwei; Lu, Wuyuan; Lu, Weiyue

2017-01-01

Antagonizing MDM2 and MDMX to activate the tumor suppressor protein p53 is an attractive therapeutic paradigm for the treatment of glioblastoma multiforme (GBM). However, challenges remain with respect to the poor ability of p53 activators to efficiently cross the blood–brain barrier and/or blood–brain tumor barrier and to specifically target tumor cells. To circumvent these problems, we developed a cyclic RGD peptide-conjugated poly(-ethylene glycol)-co-poly(lactic acid) polymeric micelle (RGD-M) that carried a stapled peptide antagonist of both MDM2 and MDMX (sPMI). The peptide-carrying micelle RGD-M/sPMI was prepared via film-hydration method with high encapsulation efficiency and loading capacity as well as ideal size distribution. Micelle encapsulation dramatically increased the solubility of sPMI, thus alleviating its serum sequestration. In vitro studies showed that RGD-M/sPMI efficiently inhibited the proliferation of glioma cells in the presence of serum by activating the p53 signaling pathway. Further, RGD-M/sPMI exerted potent tumor growth inhibitory activity against human glioblastoma in nude mouse xenograft models. Importantly, the combination of RGD-M/sPMI and temozolomide — a standard chemotherapy drug for GBM increased antitumor efficacy against glioblastoma in experimental animals. Our results validate a combination therapy using p53 activators with temozolomide as a more effective treatment for GBM. PMID:26428461

Ginsenoside-Rb1 targets chemotherapy-resistant ovarian cancer stem cells via simultaneous inhibition of Wnt/β-catenin signaling and epithelial-to-mesenchymal transition

PubMed Central

Deng, Shan; Wong, Chris Kong Chu; Lai, Hung-Cheng; Wong, Alice Sze Tsai

2017-01-01

Chemoresistance is a major clinical problem compromising the successful treatment of cancer. One exciting approach is the eradication of cancer stem/tumor-initiating cells (jointly CSCs), which account for tumor initiation, progression, and drug resistance. Here we show for the first time, with mechanism-based evidence, that ginsenoside-Rb1, a natural saponin isolated from the rhizome of Panax quinquefolius and notoginseng, exhibits potent cytotoxicity on CSCs. Rb1 and its metabolite compound K could effectively suppress CSC self-renewal without regrowth. Rb1 and compound K treatment also sensitized the CSCs to clinically relevant doses of cisplatin and paclitaxel. These effects were associated with the Wnt/β-catenin signaling pathway by downregulating β-catenin/T-cell factor-dependent transcription and expression of its target genes ATP-binding cassette G2 and P-glycoprotein. We also identified reversal of epithelial-to-mesenchymal transition as a new player in the Rb1 and compound K-mediated inhibition of CSCs. Rb1 and compound K treatment also inhibited the self-renewal of CSCs derived from ovarian carcinoma patients as well as in xenograft tumor model. Moreover, we did not observe toxicity in response to doses of Rb1 and compound K that produced an anti-CSC effect. Therefore, Rb1 should be explored further as a promising nutraceutical prototype of treating refractory tumors. PMID:27825116

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study

PubMed Central

Catanzaro, Daniele; Schäffer, Alejandro A.; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with Synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints. PMID:26353381

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.

PubMed

Catanzaro, Daniele; Shackney, Stanley E; Schaffer, Alejandro A; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints.

Predictive oncology: multidisciplinary, multi-scale in-silico modeling linking phenotype, morphology and growth

PubMed Central

Sanga, Sandeep; Frieboes, Hermann B.; Zheng, Xiaoming; Gatenby, Robert; Bearer, Elaine L.; Cristini, Vittorio

2007-01-01

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically review advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we propose and discuss a multi-scale, i.e., from the molecular to the gross tumor scale, mathematical and computational “first-principle” approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We demonstrate that this methodology, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as phenotype-diagnostic tool and thus to predict collective and individual tumor cell invasion of surrounding host. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior. PMID:17629503

siRNA-loaded cationic liposomes for cancer therapy: Development, characterization and efficacy evaluation

NASA Astrophysics Data System (ADS)

Ying, Bo

Cancer is a major health problem in the United States and many other parts of the world. However, cancer treatment is severely limited by the lack of highly effective cytotoxic agents and selective delivery methods which can serve as the "magic bullet" (first raised by Dr. Paul Ehrlich, the goal of targeting a specific location without causing harm to surrounding tissues or to more distant regions in the body). The revolutionary finding that tumors cannot grow beyond a microscopic size without dedicated blood supply provided a highly effective alternative for the treatment of cancer. Currently, anti-angiogenic therapy and the discovery of RNA interference makes it possible to treat some conditions by silencing disorder-causing genes of targeting cells which are otherwise difficult to eradicate with more conventional therapies. However, before siRNA technology could be widely used as a therapeutic approach, the construct must be efficiently and safely delivered to target cells. Strategies used for siRNA delivery should minimize uptake by phagocytes, enzymatic degradation by nucleases and should be taken up preferentially, if not specifically, by the intended cell population. Kinesin spindle proteins (KSP) are the motor proteins which play critical roles during mitosis. Different from tubulins which are also present in post-mitotic cells, such as axons, KSP is exclusively expressed in mitotic cells, which makes them the ideal target for anti-mitotics. In the present study, we intend to develop, characterize and evaluate a liposome-based delivery system which can deliver KSP siRNA selectively to the tumor vasculature (thus inhibiting angiogenesis, destroying tumor vasculature and eventually, eradicating tumor growth). We first developed ten different liposome preparation types with different compositions of lipids. Next, the capacity for loading siRNA and efficiency of targeting the tumor vascular supply was evaluated using relevant cellular and tumor models. Pegylated cationic liposomes (PCLs) were selected as carriers for siRNA. Based on the silencing efficiency of siRNA formulated with different PCLs, DOPC based cationic liposomes, over DOPE based nanosystems, with a modest amount of polyetheleneglycol was selected to deliver KSP siRNA to tumor-bearing mice. Efficacy studies revealed that tumor suppression was observed when KSP siRNA was delivered using PCLs, but not in mice that received naked KSP siRNA or KSP siRNA in commercially available transfecting agents. The results were further supported by MRI (magnetic resonance imaging) analysis. To evaluate the role that vasculature supply plays in the development of the tumor, we also performed tumor response studies using a tumor model consisting of tumor cells which are resistant to KSP siRNA. The results showed that a prolonged suppression of tumor growth was achieved only when a large dose (5mg/kg) KSP siRNA was administered, but not with the administration of a relatively low dose (2mg/kg) of siRNA, suggesting that a combined treatment approach containing both anti-vasculature and anti-cancer agents should be considered to achieve the best treatment outcome. Finally, it was confirmed by qRT-PCR that the tumor growth inhibition was due to the successful knock-down of KSP mRNA.

Predictive Modeling of Neuroblastoma Growth Dynamics in Xenograft Model After Bevacizumab Anti-VEGF Therapy.

PubMed

He, Yixuan; Kodali, Anita; Wallace, Dorothy I

2018-06-14

Neuroblastoma is the leading cause of cancer death in young children. Although treatment for neuroblastoma has improved, the 5-year survival rate of patients still remains less than half. Recent studies have indicated that bevacizumab, an anti-VEGF drug used in treatment of several other cancer types, may be effective for treating neuroblastoma as well. However, its effect on neuroblastoma has not been well characterized. While traditional experiments are costly and time-consuming, mathematical models are capable of simulating complex systems quickly and inexpensively. In this study, we present a model of vascular tumor growth of neuroblastoma IMR-32 that is complex enough to replicate experimental data across a range of tumor cell properties measured in a suite of in vitro and in vivo experiments. The model provides quantitative insight into tumor vasculature, predicting a linear relationship between vasculature and tumor volume. The tumor growth model was coupled with known pharmacokinetics and pharmacodynamics of the VEGF blocker bevacizumab to study its effect on neuroblastoma growth dynamics. The results of our model suggest that total administered bevacizumab concentration per week, as opposed to dosage regimen, is the major determining factor in tumor suppression. Our model also establishes an exponentially decreasing relationship between administered bevacizumab concentration and tumor growth rate.

Oncolytic potency and reduced virus tumor-specificity in oncolytic virotherapy. A mathematical modelling approach.

PubMed

Mahasa, Khaphetsi Joseph; Eladdadi, Amina; de Pillis, Lisette; Ouifki, Rachid

2017-01-01

In the present paper, we address by means of mathematical modeling the following main question: How can oncolytic virus infection of some normal cells in the vicinity of tumor cells enhance oncolytic virotherapy? We formulate a mathematical model describing the interactions between the oncolytic virus, the tumor cells, the normal cells, and the antitumoral and antiviral immune responses. The model consists of a system of delay differential equations with one (discrete) delay. We derive the model's basic reproductive number within tumor and normal cell populations and use their ratio as a metric for virus tumor-specificity. Numerical simulations are performed for different values of the basic reproduction numbers and their ratios to investigate potential trade-offs between tumor reduction and normal cells losses. A fundamental feature unravelled by the model simulations is its great sensitivity to parameters that account for most variation in the early or late stages of oncolytic virotherapy. From a clinical point of view, our findings indicate that designing an oncolytic virus that is not 100% tumor-specific can increase virus particles, which in turn, can further infect tumor cells. Moreover, our findings indicate that when infected tissues can be regenerated, oncolytic viral infection of normal cells could improve cancer treatment.

Pituitary tumors. Current concepts in diagnosis and management.

PubMed Central

Aron, D C; Tyrrell, J B; Wilson, C B

1995-01-01

Diagnostic advances have resulted in earlier and more frequent recognition of pituitary tumors. Pituitary tumors cause problems owing to the hormones they secrete or the effects of an expanding sellar mass--hypopituitarism, visual field abnormalities, and neurologic deficits. Prolactin-secreting tumors (prolactinomas), which cause amenorrhea, galactorrhea, and hypogonadism, constitute the most common type of primary pituitary tumors, followed by growth hormone-secreting tumors, which cause acromegaly, and corticotropin-secreting tumors, which cause Cushing's syndrome. Hypersecretion of thyroid-stimulating hormone, the gonadotrophins, or alpha-subunits is unusual. Nonfunctional tumors currently represent only 10% of all clinically diagnosed pituitary adenomas, and some of these are alpha-subunit-secreting adenomas. Insights into the pathogenesis and biologic behavior of these usually benign tumors have been gained from genetic studies. We review some of the recent advances and salient features of the diagnosis and management of pituitary tumors, including biochemical and radiologic diagnosis, transsphenoidal surgery, radiation therapy, and medical therapy. Each type of lesion requires a comprehensive but individualized treatment approach, and regardless of the mode of therapy, careful follow-up is essential. Images PMID:7747500

A multiplexed microfluidic system for evaluation of dynamics of immune-tumor interactions.

PubMed

Moore, N; Doty, D; Zielstorff, M; Kariv, I; Moy, L Y; Gimbel, A; Chevillet, J R; Lowry, N; Santos, J; Mott, V; Kratchman, L; Lau, T; Addona, G; Chen, H; Borenstein, J T

2018-05-25

Recapitulation of the tumor microenvironment is critical for probing mechanisms involved in cancer, and for evaluating the tumor-killing potential of chemotherapeutic agents, targeted therapies and immunotherapies. Microfluidic devices have emerged as valuable tools for both mechanistic studies and for preclinical evaluation of therapeutic agents, due to their ability to precisely control drug concentrations and gradients of oxygen and other species in a scalable and potentially high throughput manner. Most existing in vitro microfluidic cancer models are comprised of cultured cancer cells embedded in a physiologically relevant matrix, collocated with vascular-like structures. However, the recent emergence of immune checkpoint inhibitors (ICI) as a powerful therapeutic modality against many cancers has created a need for preclinical in vitro models that accommodate interactions between tumors and immune cells, particularly for assessment of unprocessed tumor fragments harvested directly from patient biopsies. Here we report on a microfluidic model, termed EVIDENT (ex vivo immuno-oncology dynamic environment for tumor biopsies), that accommodates up to 12 separate tumor biopsy fragments interacting with flowing tumor-infiltrating lymphocytes (TILs) in a dynamic microenvironment. Flow control is achieved with a single pump in a simple and scalable configuration, and the entire system is constructed using low-sorption materials, addressing two principal concerns with existing microfluidic cancer models. The system sustains tumor fragments for multiple days, and permits real-time, high-resolution imaging of the interaction between autologous TILs and tumor fragments, enabling mapping of TIL-mediated tumor killing and testing of various ICI treatments versus tumor response. Custom image analytic algorithms based on machine learning reported here provide automated and quantitative assessment of experimental results. Initial studies indicate that the system is capable of quantifying temporal levels of TIL infiltration and tumor death, and that the EVIDENT model mimics the known in vivo tumor response to anti-PD-1 ICI treatment of flowing TILs relative to isotype control treatments for syngeneic mouse MC38 tumors.

Optimal policies of non-cross-resistant chemotherapy on Goldie and Coldman's cancer model.

PubMed

Chen, Jeng-Huei; Kuo, Ya-Hui; Luh, Hsing Paul

2013-10-01

Mathematical models can be used to study the chemotherapy on tumor cells. Especially, in 1979, Goldie and Coldman proposed the first mathematical model to relate the drug sensitivity of tumors to their mutation rates. Many scientists have since referred to this pioneering work because of its simplicity and elegance. Its original idea has also been extended and further investigated in massive follow-up studies of cancer modeling and optimal treatment. Goldie and Coldman, together with Guaduskas, later used their model to explain why an alternating non-cross-resistant chemotherapy is optimal with a simulation approach. Subsequently in 1983, Goldie and Coldman proposed an extended stochastic based model and provided a rigorous mathematical proof to their earlier simulation work when the extended model is approximated by its quasi-approximation. However, Goldie and Coldman's analytic study of optimal treatments majorly focused on a process with symmetrical parameter settings, and presented few theoretical results for asymmetrical settings. In this paper, we recast and restate Goldie, Coldman, and Guaduskas' model as a multi-stage optimization problem. Under an asymmetrical assumption, the conditions under which a treatment policy can be optimal are derived. The proposed framework enables us to consider some optimal policies on the model analytically. In addition, Goldie, Coldman and Guaduskas' work with symmetrical settings can be treated as a special case of our framework. Based on the derived conditions, this study provides an alternative proof to Goldie and Coldman's work. In addition to the theoretical derivation, numerical results are included to justify the correctness of our work. Copyright © 2013 Elsevier Inc. All rights reserved.

Nanomedicine strategies for sustained, controlled, and targeted treatment of cancer stem cells of the digestive system.

PubMed

Xie, Fang-Yuan; Xu, Wei-Heng; Yin, Chuan; Zhang, Guo-Qing; Zhong, Yan-Qiang; Gao, Jie

2016-10-15

Cancer stem cells (CSCs) constitute a small proportion of the cancer cells that have self-renewal capacity and tumor-initiating ability. They have been identified in a variety of tumors, including tumors of the digestive system. CSCs exhibit some unique characteristics, which are responsible for cancer metastasis and recurrence. Consequently, the development of effective therapeutic strategies against CSCs plays a key role in increasing the efficacy of cancer therapy. Several potential approaches to target CSCs of the digestive system have been explored, including targeting CSC surface markers and signaling pathways, inducing the differentiation of CSCs, altering the tumor microenvironment or niche, and inhibiting ATP-driven efflux transporters. However, conventional therapies may not successfully eradicate CSCs owing to various problems, including poor solubility, stability, rapid clearance, poor cellular uptake, and unacceptable cytotoxicity. Nanomedicine strategies, which include drug, gene, targeted, and combinational delivery, could solve these problems and significantly improve the therapeutic index. This review briefly summarizes the ongoing development of strategies and nanomedicine-based therapies against CSCs of the digestive system.

Nanomedicine strategies for sustained, controlled, and targeted treatment of cancer stem cells of the digestive system

PubMed Central

Xie, Fang-Yuan; Xu, Wei-Heng; Yin, Chuan; Zhang, Guo-Qing; Zhong, Yan-Qiang; Gao, Jie

2016-01-01

Cancer stem cells (CSCs) constitute a small proportion of the cancer cells that have self-renewal capacity and tumor-initiating ability. They have been identified in a variety of tumors, including tumors of the digestive system. CSCs exhibit some unique characteristics, which are responsible for cancer metastasis and recurrence. Consequently, the development of effective therapeutic strategies against CSCs plays a key role in increasing the efficacy of cancer therapy. Several potential approaches to target CSCs of the digestive system have been explored, including targeting CSC surface markers and signaling pathways, inducing the differentiation of CSCs, altering the tumor microenvironment or niche, and inhibiting ATP-driven efflux transporters. However, conventional therapies may not successfully eradicate CSCs owing to various problems, including poor solubility, stability, rapid clearance, poor cellular uptake, and unacceptable cytotoxicity. Nanomedicine strategies, which include drug, gene, targeted, and combinational delivery, could solve these problems and significantly improve the therapeutic index. This review briefly summarizes the ongoing development of strategies and nanomedicine-based therapies against CSCs of the digestive system. PMID:27795813

Smart Photosensitizer: Tumor-Triggered Oncotherapy by Self-Assembly Photodynamic Nanodots.

PubMed

Jia, Yuhua; Li, Jinyu; Chen, Jincan; Hu, Ping; Jiang, Longguang; Chen, Xueyuan; Huang, Mingdong; Chen, Zhuo; Xu, Peng

2018-05-09

Clinical photosensitizers suffer from the disadvantages of fast photobleaching and high systemic toxicities because of the off-target photodynamic effects. To address these problems, we report a self-assembled pentalysine-phthalocyanine assembly nanodots (PPAN) fabricated by an amphipathic photosensitizer-peptide conjugate. We triggered the photodynamic therapy effects of photosensitizers by precisely controlling the assembly and disintegration of the nanodots. In physiological aqueous conditions, PPAN exhibited a size-tunable spherical conformation with a highly positive shell of the polypeptides and a hydrophobic core of the π-stacking Pc moieties. The assembly conformation suppressed the fluorescence and the reactive oxygen species generation of the monomeric photosensitizer molecules (mono-Pc) and thus declined the photobleaching and off-target photodynamic effects. However, tumor cells disintegrated PPAN and released the mono-Pc molecules, which exhibited fluorescence for detection and the photodynamic effects for the elimination of the tumor tissues. The molecular dynamics simulations revealed the various assembly configurations of PPAN and illustrated the assembly mechanism. At the cellular level, PPAN exhibited a remarkable phototoxicity to breast cancer cells with the IC 50 values in a low nanomolar range. By using the subcutaneous and orthotopic breast cancer animal models, we also demonstrated the excellent antitumor efficacies of PPAN in vivo.

An Orthotopic Mouse Model of Spontaneous Breast Cancer Metastasis.

PubMed

Paschall, Amy V; Liu, Kebin

2016-08-14

Metastasis is the primary cause of mortality of breast cancer patients. The mechanism underlying cancer cell metastasis, including breast cancer metastasis, is largely unknown and is a focus in cancer research. Various breast cancer spontaneous metastasis mouse models have been established. Here, we report a simplified procedure to establish orthotopic transplanted breast cancer primary tumor and resultant spontaneous metastasis that mimic human breast cancer metastasis. Combined with the bioluminescence live tumor imaging, this mouse model allows tumor growth and progression kinetics to be monitored and quantified. In this model, a low dose (1 x 10(4) cells) of 4T1-Luc breast cancer cells was injected into BALB/c mouse mammary fat pad using a tuberculin syringe. Mice were injected with luciferin and imaged at various time points using a bioluminescent imaging system. When the primary tumors grew to the size limit as in the IACUC-approved protocol (approximately 30 days), mice were anesthetized under constant flow of 2% isoflurane and oxygen. The tumor area was sterilized with 70% ethanol. The mouse skin around the tumor was excised to expose the tumor which was removed with a pair of sterile scissors. Removal of the primary tumor extends the survival of the 4T-1 tumor-bearing mice for one month. The mice were then repeatedly imaged for metastatic tumor spreading to distant organs. Therapeutic agents can be administered to suppress tumor metastasis at this point. This model is simple and yet sensitive in quantifying breast cancer cell growth in the primary site and progression kinetics to distant organs, and thus is an excellent model for studying breast cancer growth and progression, and for testing anti-metastasis therapeutic and immunotherapeutic agents in vivo.

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions: An Illustration for Metastatic Castration-Resistant Prostate Cancer.

PubMed

Degeling, Koen; Schivo, Stefano; Mehra, Niven; Koffijberg, Hendrik; Langerak, Rom; de Bono, Johann S; IJzerman, Maarten J

2017-12-01

With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required. To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions. An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed. Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure. Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Targeted two-photon photodynamic therapy for the treatment of subcutaneous tumors

NASA Astrophysics Data System (ADS)

Spangler, Charles W.; Starkey, Jean R.; Meng, Fanqing; Gong, Aijun; Drobizhev, Mikhail; Rebane, Aleksander; Moss, B.

2005-04-01

Photodynamic therapy (PDT) has developed into a mature technology over the past several years, and is currently being exploited for the treatment of a variety of cancerous tumors, and more recently for age-related wet macular degeneration of the eye. However, there are still some unresolved problems with PDT that are retarding a more general acceptance in clinical settings, and thus, for the most part, the treatment of most cancerous rumors still involves some combination of invasive surgery, chemotherapy and radiation treatment, particularly subcutaneous tumors. Currently approved PDT agents are activated in the Visible portion of the spectrum below 700 nm, Laser light in this spectral region cannot penetrate the skin more than a few millimeters, and it would be more desirable if PDT could be initiated deep in the Near-infrared (NIR) in the tissue transparency window (700-1000 nm). MPA Technologies, Inc. and Rasiris, Inc. have been co-developing new porphyrin PDT designed to have greatly enhanced intrinsic two-photon cross-sections (>800 GM units) whose two-photon absorption maxima lie deep in the tissue transparency window (ca. 780-850 nm), and have solubility characteristics that would allow for direct IV injection into animal models. Classical PDT also suffers from the lengthy time necessary for accumulation at the tumor site, a relative lack of discrimination between healthy and diseased tissue, particularly at the tumor margins, and difficulty in clearing from the system in a reasonable amount of time post-PDT. We have recently discovered a new design paradigm for the delivery of our two-photon activated PDT agents by incorporating the porphyrins into a triad ensemble that includes a small molecule targeting agent that directs the triad to over-expressed tumor receptor sites, and a NIR one-photon imaging agent that allows the tracking of the triad in terms of accumulation and clearance rates. We are currently using these new two-photon PDT triads in efficacy studies with two breast cancer cell lines, both in vitro and in vivo. Both of these cell lines have been transfected with luciferase genes that allow implanted tumor growth and PDT efficacy to be monitored in living mouse models over time by following the rise and decay of the bioluminescence signals.

A tissue-engineered subcutaneous pancreatic cancer model for antitumor drug evaluation.

PubMed

He, Qingyi; Wang, Xiaohui; Zhang, Xing; Han, Huifang; Han, Baosan; Xu, Jianzhong; Tang, Kanglai; Fu, Zhiren; Yin, Hao

2013-01-01

The traditional xenograft subcutaneous pancreatic cancer model is notorious for its low incidence of tumor formation, inconsistent results for the chemotherapeutic effects of drug molecules of interest, and a poor predictive capability for the clinical efficacy of novel drugs. These drawbacks are attributed to a variety of factors, including inoculation of heterogeneous tumor cells from patients with different pathological histories, and use of poorly defined Matrigel(®). In this study, we aimed to tissue-engineer a pancreatic cancer model that could readily cultivate a pancreatic tumor derived from highly homogenous CD24(+)CD44(+) pancreatic cancer stem cells delivered by a well defined electrospun scaffold of poly(glycolide-co-trimethylene carbonate) and gelatin. The scaffold supported in vitro tumorigenesis from CD24(+)CD44(+) cancer stem cells for up to 7 days without inducing apoptosis. Moreover, CD24(+)CD44(+) cancer stem cells delivered by the scaffold grew into a native-like mature pancreatic tumor within 8 weeks in vivo and exhibited accelerated tumorigenesis as well as a higher incidence of tumor formation than the traditional model. In the scaffold model, we discovered that oxaliplatin-gemcitabine (OXA-GEM), a chemotherapeutic regimen, induced tumor regression whereas gemcitabine alone only capped tumor growth. The mechanistic study attributed the superior antitumorigenic performance of OXA-GEM to its ability to induce apoptosis of CD24(+)CD44(+) cancer stem cells. Compared with the traditional model, the scaffold model demonstrated a higher incidence of tumor formation and accelerated tumor growth. Use of a tiny population of highly homogenous CD24(+)CD44(+) cancer stem cells delivered by a well defined scaffold greatly reduces the variability associated with the traditional model, which uses a heterogeneous tumor cell population and poorly defined Matrigel. The scaffold model is a robust platform for investigating the antitumorigenesis mechanism of novel chemotherapeutic drugs with a special focus on cancer stem cells.

A Murine Xenograft Model for Human CD30+ Anaplastic Large Cell Lymphoma

PubMed Central

Pfeifer, Walther; Levi, Edi; Petrogiannis-Haliotis, Tina; Lehmann, Leslie; Wang, Zhenxi; Kadin, Marshall E.

1999-01-01

To develop a model for the biology and treatment of CD30+ anaplastic large cell lymphoma (ALCL), we transplanted leukemic tumor cells from a 22-month-old girl with multiple relapsed ALCL. Tumor cells were inoculated intraperitoneally into a 4-week-old SCID/bg mouse and produced a disseminated tumor within 8 weeks; this tumor was serially transplanted by subcutaneous injections to other mice. Morphology, immunohistochemistry, and molecular genetics which demonstrated the NPM-ALK fusion protein, resulting from the t(2;5)(p23;q35), confirmed the identity of the xenograft with the original tumor. The tumor produced transcripts for interleukin-1α, tumor necrosis factor-α, and interferon-γ which could explain the patient’s B-symptoms. Treatment of mice with monoclonal antibody (HeFi-1) which activates CD30 antigen administered on day 1 after tumor transplantation prevented tumor growth. Treatment with HeFi-1 after tumors had reached a 0.2 cm3 volume caused tumor growth arrest and prevention of tumor dissemination. We conclude that transplantation of CD30+ ALCL to SCID/bg mice may provide a valuable model for the study of the biology and design of treatment modalities for CD30+ ALCL. PMID:10514417

MRI-Based Computational Model of Heterogeneous Tracer Transport following Local Infusion into a Mouse Hind Limb Tumor

PubMed Central

Magdoom, Kulam Najmudeen; Pishko, Gregory L.; Rice, Lori; Pampo, Chris; Siemann, Dietmar W.; Sarntinoranont, Malisa

2014-01-01

Systemic drug delivery to solid tumors involving macromolecular therapeutic agents is challenging for many reasons. Amongst them is their chaotic microvasculature which often leads to inadequate and uneven uptake of the drug. Localized drug delivery can circumvent such obstacles and convection-enhanced delivery (CED) - controlled infusion of the drug directly into the tissue - has emerged as a promising delivery method for distributing macromolecules over larger tissue volumes. In this study, a three-dimensional MR image-based computational porous media transport model accounting for realistic anatomical geometry and tumor leakiness was developed for predicting the interstitial flow field and distribution of albumin tracer following CED into the hind-limb tumor (KHT sarcoma) in a mouse. Sensitivity of the model to changes in infusion flow rate, catheter placement and tissue hydraulic conductivity were investigated. The model predictions suggest that 1) tracer distribution is asymmetric due to heterogeneous porosity; 2) tracer distribution volume varies linearly with infusion volume within the whole leg, and exponentially within the tumor reaching a maximum steady-state value; 3) infusion at the center of the tumor with high flow rates leads to maximum tracer coverage in the tumor with minimal leakage outside; and 4) increasing the tissue hydraulic conductivity lowers the tumor interstitial fluid pressure and decreases the tracer distribution volume within the whole leg and tumor. The model thus predicts that the interstitial fluid flow and drug transport is sensitive to porosity and changes in extracellular space. This image-based model thus serves as a potential tool for exploring the effects of transport heterogeneity in tumors. PMID:24619021

Inflammatory models drastically alter tumor growth and the immune microenvironment in hepatocellular carcinoma.

PubMed

Markowitz, Geoffrey J; Michelotti, Gregory A; Diehl, Anna Mae; Wang, Xiao-Fan

2015-04-01

Initiation and progression of hepatocellular carcinoma (HCC) is intimately associated with a chronically diseased liver tissue. This diseased liver tissue background is a drastically different microenvironment from the healthy liver, especially with regard to immune cell prevalence and presence of mediators of immune function. To better understand the consequences of liver disease on tumor growth and the interplay with its microenvironment, we utilized two standard methods of fibrosis induction and orthotopic implantation of tumors into the inflamed and fibrotic liver to mimic the liver condition in human HCC patients. Compared to non-diseased controls, tumor growth was significantly enhanced under fibrotic conditions. The immune cells that infiltrated the tumors were also drastically different, with decreased numbers of natural killer cells but greatly increased numbers of immune-suppressive CD11b + Gr1 hi myeloid cells in both models of fibrosis. In addition, there were model-specific differences: Increased numbers of CD11b + myeloid cells and CD4 + CD25 + T cells were found in tumors in the bile duct ligation model but not in the carbon tetrachloride model. Induction of fibrosis altered the cytokine production of implanted tumor cells, which could have farreaching consequences on the immune infiltrate and its functionality. Taken together, this work demonstrates that the combination of fibrosis induction with orthotopic tumor implantation results in a markedly different tumor microenvironment and tumor growth kinetics, emphasizing the necessity for more accurate modeling of HCC progression in mice, which takes into account the drastic changes in the tissue caused by chronic liver disease.

Squamous cell carcinoma of the anal sac in five dogs.

PubMed

Esplin, D G; Wilson, S R; Hullinger, G A

2003-05-01

Tumors of the perianal area of dogs are common and include multiple tumor types. Whereas perianal adenomas occur often, adenocarcinomas of the apocrine glands of the anal sac occur less frequently. A review of the literature revealed no reports of squamous cell carcinomas arising from the epithelial lining of the anal sac. Squamous cell carcinomas originating from the lining of the anal sac were diagnosed in five dogs. Microscopically, the tumors consisted of variably sized invasive nests and cords of epithelial cells displaying squamous differentiation. Four of the five dogs were euthanatized because of problems associated with local infiltration by the tumors. In the fifth dog, there was no evidence of tumor 7 months after surgical removal, but further follow up was not available.

Light at night and melatonin have opposite effects on breast cancer tumors in mice assessed by growth rates and global DNA methylation.

PubMed

Schwimmer, Hagit; Metzer, Avishag; Pilosof, Yonit; Szyf, Moshe; Machnes, Ziv M; Fares, Fuad; Harel, Orna; Haim, Abraham

2014-02-01

Light-at-night (LAN) is a worldwide problem co-distributed with breast cancer prevalence. We hypothesized that exposure to LAN is coincided with a decreased melatonin (MLT) secretion level, followed by epigenetic modifications and resulted in higher breast cancer tumors growth-rate. Accordingly, we studied the effect of LAN exposure and exogenous MLT on breast cancer tumors growth-rate. 4T1 cells were inoculated into BALB/c short day-acclimated mice, resulting in tumors growth. Growth rates were followed under various light exposures and global DNA methylations were measured. Results demonstrated the positive effect of LAN on tumors growth-rate, reversed by MLT through global DNA methylation.

Blind Biobanking of the Prostatectomy Specimen: Critical Evaluation of the Existing Techniques and Development of the New 4-Level Tissue Extraction Model With High Sampling Efficacy.

PubMed

Tolkach, Yuri; Eminaga, Okyaz; Wötzel, Fabian; Huss, Sebastian; Bettendorf, Olaf; Eltze, Elke; Abbas, Mahmoud; Imkamp, Florian; Semjonow, Axel

2017-03-01

Fresh tissue is mandatory to perform high-quality translation studies. Several models for tissue extraction from prostatectomy specimens without guidance by frozen sections are already introduced. However, little is known about the sampling efficacy of these models, which should provide representative tissue in adequate volumes, account for multifocality and heterogeneity of tumor, not violate the routine final pathological examination, and perform quickly without frozen section-based histological control. The aim of the study was to evaluate the sampling efficacy of the existing tissue extraction models without guidance by frozen sections ("blind") and to develop an optimized model for tissue extraction. Five hundred thirty-three electronic maps of the tumor distribution in prostates from a single-center cohort of the patients subjected to radical prostatectomy were used for analysis. Six available models were evaluated in silico for their sampling efficacy. Additionally, a novel model achieving the best sampling efficacy was developed. The available models showed high efficacies for sampling "any part" from the tumor (up to 100%), but were uniformly low in efficacy to sample all tumor foci from the specimens (with the best technique sampling only 51.6% of the all tumor foci). The novel 4-level extraction model achieved a sampling efficacy of 93.1% for all tumor foci. The existing "blind" tissue extraction models from prostatectomy specimens without frozen sections control are suitable to target tumor tissues but these tissues do not represent the whole tumor. The novel 4-level model provides the highest sampling efficacy and a promising potential for integration into routine. Prostate 77: 396-405, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Internal and External Triggering Mechanism of "Smart" Nanoparticle-Based DDSs in Targeted Tumor Therapy.

PubMed

Qiana, Xian-Ling; Li, Jun; Wei, Ran; Lin, Hui; Xiong, Li-Xia

2018-05-09

Anticancer chemotherapeutics have a lot of problems via conventional drug delivery systems (DDSs), including non-specificity, burst release, severe side-effects, and damage to normal cells. Owing to its potential to circumventing these problems, nanotechnology has gained increasing attention in targeted tumor therapy. Chemotherapeutic drugs or genes encapsulated in nanoparticles could be used to target therapies to the tumor site in three ways: "passive", "active", and "smart" targeting. To summarize the mechanisms of various internal and external "smart" stimulating factors on the basis of findings from in vivo and in vitro studies. A thorough search of PubMed was conducted in order to identify the majority of trials, studies and novel articles related to the subject. Activated by internal triggering factors (pH, redox, enzyme, hypoxia, etc.) or external triggering factors (temperature, light of different wavelengths, ultrasound, magnetic fields, etc.), "smart" DDSs exhibit targeted delivery to the tumor site, and controlled release of chemotherapeutic drugs or genes. In this review article, we summarize and classify the internal and external triggering mechanism of "smart" nanoparticle-based DDSs in targeted tumor therapy, and the most recent research advances are illustrated for better understanding. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A TCP model for external beam treatment of intermediate-risk prostate cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, Sean; Putten, Wil van der

2013-03-15

Purpose: Biological models offer the ability to predict clinical outcomes. The authors describe a model to predict the clinical response of intermediate-risk prostate cancer to external beam radiotherapy for a variety of fractionation regimes. Methods: A fully heterogeneous population averaged tumor control probability model was fit to clinical outcome data for hyper, standard, and hypofractionated treatments. The tumor control probability model was then employed to predict the clinical outcome of extreme hypofractionation regimes, as utilized in stereotactic body radiotherapy. Results: The tumor control probability model achieves an excellent level of fit, R{sup 2} value of 0.93 and a root meanmore » squared error of 1.31%, to the clinical outcome data for hyper, standard, and hypofractionated treatments using realistic values for biological input parameters. Residuals Less-Than-Or-Slanted-Equal-To 1.0% are produced by the tumor control probability model when compared to clinical outcome data for stereotactic body radiotherapy. Conclusions: The authors conclude that this tumor control probability model, used with the optimized radiosensitivity values obtained from the fit, is an appropriate mechanistic model for the analysis and evaluation of external beam RT plans with regard to tumor control for these clinical conditions.« less

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

The Neuro-Oncology Branch (NOB), Center for Cancer Research (CCR), National Cancer Institute (NCI) of the National Institutes of Health (NIH) is seeking outstanding postdoctoral candidates interested in studying metabolic and cell signaling pathways in the context of brain cancers through construction of computational models amenable to formal computational analysis and simulation. The ability to closely collaborate with the modern metabolomics center developed at CCR provides a unique opportunity for a postdoctoral candidate with a strong theoretical background and interest in demonstrating the incredible potential of computational approaches to solve problems from scientific disciplines and improve lives. The candidate will be given the opportunity to both construct data-driven models, as well as biologically validate the models by demonstrating the ability to predict the effects of altering tumor metabolism in laboratory and clinical settings.

Simulation of Complex Transport of Nanoparticles around a Tumor Using Tumor-Microenvironment-on-Chip

PubMed Central

Kwak, Bongseop; Ozcelikkale, Altug; Shin, Crystal S.; Park, Kinam; Han, Bumsoo

2014-01-01

Delivery of therapeutic agents selectively to tumor tissue, which is referred as “targeted delivery,” is one of the most ardently pursued goals of cancer therapy. Recent advances in nanotechnology enable numerous types of nanoparticles (NPs) whose properties can be designed for targeted delivery to tumors. In spite of promising early results, the delivery and therapeutic efficacy of the majority of NPs are still quite limited. This is mainly attributed to the limitation of currently available tumor models to test these NPs and systematically study the effects of complex transport and pathophysiological barriers around the tumors. In this study, thus, we developed a new in vitro tumor model to recapitulate the tumor microenvironment determining the transport around tumors. This model, named tumor-microenvironment-on-chip (T-MOC), consists of 3-dimensional microfluidic channels where tumor cells and endothelial cells are cultured within extracellular matrix under perfusion of interstitial fluid. Using this T-MOC platform, the transport of NPs and its variation due to tumor microenvironmental parameters have been studied including cut-off pore size, interstitial fluid pressure, and tumor tissue microstructure. The results suggest that T-MOC is capable of simulating the complex transport around the tumor, and providing detailed information about NP transport behavior. This finding confirms that NPs should be designed considering their dynamic interactions with tumor microenvironment. PMID:25194778

TMOD-05. MOLECULAR CHARACTERIZATION OF ORTHOTOPIC PATIENT-DERIVED XENOGRAFT MODELS OF PEDIATRIC BRAIN TUMORS AND THEIR USE IN PRECLINICAL EXPERIMENTS

PubMed Central

Brabetz, Sebastian; Schmidt, Christin; Groebner, Susanne N.; Mack, Norman; Seker-Cin, Huriye; Jones, David T.W.; Chavez, Lukas; Milde, Till; Witt, Olaf; Leary, Sarah E.; Li, Xiao-Nan; Wechsler-Reya, Robert J.; Olson, James M.; Pfister, Stefan M.; Kool, Marcel

2017-01-01

Abstract Genomic studies have shown that multiple molecular subtypes of pediatric brain tumors exist that are biologically and clinically highly distinct. These findings ask for novel subtype specific treatments. To develop these we need more and better preclinical models that correctly reflect the proper tumor (sub)type. Orthotopic patient-derived xenograft (PDX) models generated by intracranial injection of primary patient material into the brain of NSG mice offer the unique possibility to test novel substances in primary patient tissue in an in vivo environment. Prior to drug selection and testing, extensive molecular characterizations of PDX and matching primary tumor/blood (DNA methylation, DNA sequencing, and gene expression) are needed to see how the PDX represents the original disease and to learn about targetable oncogenic drivers in each model. In collaboration with several groups around the world we have generated and fully characterized thus far 75 PDX models reflecting 15 distinct subtypes of pediatric brain cancer. PDX models always retain their molecular subtype and in the vast majority of cases also mutations and copy number alterations compared to matching primary tumors. Most aggressive tumors, harboring MYC(N) amplifications, are overrepresented in the cohort, but also subtypes which have not been available for preclinical testing before due to lack of genetically engineered mouse models or suitable cell lines, such as Group 4 medulloblastoma, are included. All models and corresponding molecular data will become available for the community for preclinical research. Examples of such preclinical experiments will be presented. PDX models of pediatric brain tumors are still quite rare. Our repertoire of PDX models and corresponding molecular characterizations allow researchers all over the world to find the right models for their specific scientific questions. It will provide an unprecedented resource to study tumor biology and pave the way for improving treatment strategies for children with malignant brain tumors.

Corruption of the Fas Pathway Delays the Pulmonary Clearance of Murine Osteosarcoma Cells, Enhances Their Metastatic Potential, and Reduces the Effect of Aerosol Gemcitabine

PubMed Central

Gordon, Nancy; Koshkina, Nadezhda V.; Jia, Shu-Fang; Khanna, Chand; Mendoza, Arnulfo; Worth, Laura L.; Kleinerman, Eugenie S.

2015-01-01

Purpose Pulmonary metastases continue to be a significant problem in osteosarcoma. Apoptosis dysfunction is known to influence tumor development. Fas (CD95, APO-1)/FasL is one of the most extensively studied apoptotic pathways. Because FasL is constitutively expressed in the lung, cells that express Fas should be eliminated by lung endothelium. Cells with low or no cell surface Fas expression may be able to evade this innate defense mechanism. The purpose of these studies was to evaluate Fas expression in osteosarcoma lung metastases and the effect of gemcitabine on Fas expression and tumor growth. Experimental Design and Results Using the K7M2 murine osteosarcoma model, Fas expression was quantified using immunohistochemistry. High levels of Fas were present in primary tumors, but no Fas expression was present in actively growing lung metastases. Blocking the Fas pathway using Fas-associated death domain dominant-negative delayed tumor cell clearance from the lung and increased metastatic potential. Treatment of mice with aerosol gemcitabine resulted in increased Fas expression and subsequent tum or regression. Conclusions We conclude that corruption of the Fas pathway is critical to the ability of osteosarcoma cells to grow in the lung. Agents such as gemcitabine that up-regulate cell surface Fas expression may therefore be effective in treating osteosarcoma lung metastases. These data also suggest that an additional mechanism by which gemcitabine induces regression of osteosarcoma lung metastases is mediated by enhancing the sensitivity of the tumor cells to the constitutive FasL in the lung. PMID:17671136

Tumor tropism of intravenously injected human-induced pluripotent stem cell-derived neural stem cells and their gene therapy application in a metastatic breast cancer model.

PubMed

Yang, Jing; Lam, Dang Hoang; Goh, Sally Sallee; Lee, Esther Xingwei; Zhao, Ying; Tay, Felix Chang; Chen, Can; Du, Shouhui; Balasundaram, Ghayathri; Shahbazi, Mohammad; Tham, Chee Kian; Ng, Wai Hoe; Toh, Han Chong; Wang, Shu

2012-05-01

Human pluripotent stem cells can serve as an accessible and reliable source for the generation of functional human cells for medical therapies. In this study, we used a conventional lentiviral transduction method to derive human-induced pluripotent stem (iPS) cells from primary human fibroblasts and then generated neural stem cells (NSCs) from the iPS cells. Using a dual-color whole-body imaging technology, we demonstrated that after tail vein injection, these human NSCs displayed a robust migratory capacity outside the central nervous system in both immunodeficient and immunocompetent mice and homed in on established orthotopic 4T1 mouse mammary tumors. To investigate whether the iPS cell-derived NSCs can be used as a cellular delivery vehicle for cancer gene therapy, the cells were transduced with a baculoviral vector containing the herpes simplex virus thymidine kinase suicide gene and injected through tail vein into 4T1 tumor-bearing mice. The transduced NSCs were effective in inhibiting the growth of the orthotopic 4T1 breast tumor and the metastatic spread of the cancer cells in the presence of ganciclovir, leading to prolonged survival of the tumor-bearing mice. The use of iPS cell-derived NSCs for cancer gene therapy bypasses the sensitive ethical issue surrounding the use of cells derived from human fetal tissues or human embryonic stem cells. This approach may also help to overcome problems associated with allogeneic transplantation of other types of human NSCs. Copyright © 2012 AlphaMed Press.

Pasireotide and octreotide antiproliferative effects and sst2 trafficking in human pancreatic neuroendocrine tumor cultures.

PubMed

Mohamed, Amira; Blanchard, Marie-Pierre; Albertelli, Manuela; Barbieri, Federica; Brue, Thierry; Niccoli, Patricia; Delpero, Jean-Robert; Monges, Genevieve; Garcia, Stephane; Ferone, Diego; Florio, Tullio; Enjalbert, Alain; Moutardier, Vincent; Schonbrunn, Agnes; Gerard, Corinne; Barlier, Anne; Saveanu, Alexandru

2014-10-01

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) raise difficult therapeutic problems despite the emergence of targeted therapies. Somatostatin analogs (SSA) remain pivotal therapeutic drugs. However, the tachyphylaxis and the limited antitumoral effects observed with the classical somatostatin 2 (sst2) agonists (octreotide and lanreotide) led to the development of new SSA, such as the pan sst receptor agonist pasireotide. Our aim was to compare the effects of pasireotide and octreotide on cell survival, chromogranin A (CgA) secretion, and sst2 phosphorylation/trafficking in pancreatic NET (pNET) primary cells from 15 tumors. We established and characterized the primary cultures of human pancreatic tumors (pNETs) as powerful preclinical models for understanding the biological effects of SSA. At clinically relevant concentrations (1-10 nM), pasireotide was at least as efficient as octreotide in inhibiting CgA secretion and cell viability through caspase-dependent apoptosis during short treatments, irrespective of the expression levels of the different sst receptors or the WHO grade of the parental tumor. Interestingly, unlike octreotide, which induces a rapid and persistent partial internalization of sst2 associated with its phosphorylation on Ser341/343, pasireotide did not phosphorylate sst2 and induced a rapid and transient internalization of the receptor followed by a persistent recycling at the cell surface. These results provide the first evidence, to our knowledge, of striking differences in the dynamics of sst2 trafficking in pNET cells treated with the two SSAs, but with similar efficiency in the control of CgA secretion and cell viability. © 2014 Society for Endocrinology.

A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment

PubMed Central

Nör, Jacques Eduardo

2018-01-01

Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth. PMID:29351275

Mathematical and Computational Modeling for Tumor Virotherapy with Mediated Immunity.

PubMed

Timalsina, Asim; Tian, Jianjun Paul; Wang, Jin

2017-08-01

We propose a new mathematical modeling framework based on partial differential equations to study tumor virotherapy with mediated immunity. The model incorporates both innate and adaptive immune responses and represents the complex interaction among tumor cells, oncolytic viruses, and immune systems on a domain with a moving boundary. Using carefully designed computational methods, we conduct extensive numerical simulation to the model. The results allow us to examine tumor development under a wide range of settings and provide insight into several important aspects of the virotherapy, including the dependence of the efficacy on a few key parameters and the delay in the adaptive immunity. Our findings also suggest possible ways to improve the virotherapy for tumor treatment.

A nonlinear competitive model of the prostate tumor growth under intermittent androgen suppression.

PubMed

Yang, Jing; Zhao, Tong-Jun; Yuan, Chang-Qing; Xie, Jing-Hui; Hao, Fang-Fang

2016-09-07

Hormone suppression has been the primary modality of treatment for prostate cancer. However long-term androgen deprivation may induce androgen-independent (AI) recurrence. Intermittent androgen suppression (IAS) is a potential way to delay or avoid the AI relapse. Mathematical models of tumor growth and treatment are simple while they are capable of capturing the essence of complicated interactions. Game theory models have analyzed that tumor cells can enhance their fitness by adopting genetically determined survival strategies. In this paper, we consider the survival strategies as the competitive advantage of tumor cells and propose a new model to mimic the prostate tumor growth in IAS therapy. Then we investigate the competition effect in tumor development by numerical simulations. The results indicate that successfully IAS-controlled states can be achieved even though the net growth rate of AI cells is positive for any androgen level. There is crucial difference between the previous models and the new one in the phase diagram of successful and unsuccessful tumor control by IAS administration, which means that the suggestions from the models for medication can be different. Furthermore we introduce quadratic logistic terms to the competition model to simulate the tumor growth in the environment with a finite carrying capacity considering the nutrients or inhibitors. The simulations show that the tumor growth can reach an equilibrium state or an oscillatory state with the net growth rate of AI cells being androgen independent. Our results suggest that the competition and the restraint of a limited environment can enhance the possibility of relapse prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

MicroRNA Silencing Improves the Tumor Specificity of Adenoviral Transgene Expression

PubMed Central

Card, Paul B.; Hogg, Richard T.; del Alcazar, Carlos Gil

2012-01-01

Adenoviral technology has been thoroughly evaluated for delivering genetic material to tumor tissue and the surrounding microenvironment. Almost any gene can be cloned into an adenovirus (Ad) vector, which when combined with strong, constitutively active promoters permit up to a million-fold amplification of the transgene in a single adenoviral particle, thus facilitating their use in cancer therapy and imaging. However, widespread infection of the liver and other non-targeted tissues by Ad vectors is a substantial problem that often results in significant liver inflammation and hepatotoxicity at doses required to achieve efficient tumor transduction. miR-122 is a highly expressed liver-specific microRNA that provides a unique opportunity for down-regulating adenoviral transgene expression in liver tissue. The binding of endogenous miRNAs to complementary miRNA targeting elements (miRTs) incorporated into the 3′ untranslated region of adenoviral transgenes interferes with message stability and/or protein translation, and miRT elements against miR-122 (miRT-122) can selectively reduce adenoviral transgene expression in the liver. Previous studies using miR-122-based regulation, with and without other types of transcriptional targeting, have yielded promising preliminary results. However, investigations to date evaluating miRT-122 elements for improving tumor specificity have used either non-tumor bearing animals or direct intratumoral injection as the mode of delivery. In the present study, we confirmed the ability of miRT-122 sequences to selectively down-regulate adenoviral luciferase expression in the liver in vitro and in vivo, and show that this strategy can improve tumor specific transgene expression in a HT1080 human fibrosarcoma model. Rapid growth and the inefficient flow of blood through tumor neovasculature often results in profound hypoxia, which provides additional opportunities for targeting solid tumors and their microenvironment using vectors incorporating hypoxia-responsive promoters to drive transgene expression. We therefore employed a combinatorial approach using miRT-122 elements with hypoxia-responsive transcriptional targeting to further improve the tumor specific expression of an adenoviral reporter gene. Results from this investigation reveal that miRT122 elements alone decrease off-target liver expression and improve tumor specificity of adenoviral vectors. Furthermore, increased tumor specificity can be achieved by combining miRT-122 elements with hypoxia-responsive promoters. PMID:22555510

The development of Wilms tumor: from WT1 and microRNA to animal models.

PubMed

Tian, Fang; Yourek, Gregory; Shi, Xiaolei; Yang, Yili

2014-08-01

Wilms tumor recapitulates the development of the kidney and represents a unique opportunity to understand the relationship between normal and tumor development. This has been illustrated by the findings that mutations of Wnt/β-catenin pathway-related WT1, β-catenin, and WTX together account for about one-third of Wilms tumor cases. While intense efforts are being made to explore the genetic basis of the other two-thirds of tumor cases, it is worth noting that, epigenetic changes, particularly the loss of imprinting of the DNA region encoding the major fetal growth factor IGF2, which results in its biallelic over-expression, are closely associated with the development of many Wilms tumors. Recent investigations also revealed that mutations of Drosha and Dicer, the RNases required for miRNA generation, and Dis3L2, the 3'-5' exonuclease that normally degrades miRNAs and mRNAs, could cause predisposition to Wilms tumors, demonstrating that miRNA can play a pivotal role in Wilms tumor development. Interestingly, Lin28, a direct target of miRNA let-7 and potent regulator of stem cell self-renewal and differentiation, is significantly elevated in some Wilms tumors, and enforced expression of Lin28 during kidney development could induce Wilms tumor. With the success in establishing mice nephroblastoma models through over-expressing IGF2 and deleting WT1, and advances in understanding the ENU-induced rat model, we are now able to explore the molecular and cellular mechanisms induced by these genetic, epigenetic, and miRNA alterations in animal models to understand the development of Wilms tumor. These animal models may also serve as valuable systems to assess new treatment targets and strategies for Wilms tumor. Copyright © 2014 Elsevier B.V. All rights reserved.

Psychosocial profile of pediatric brain tumor survivors with neurocognitive complaints.

PubMed

de Ruiter, Marieke Anna; Schouten-van Meeteren, Antoinette Yvonne Narda; van Vuurden, Dannis Gilbert; Maurice-Stam, Heleen; Gidding, Corrie; Beek, Laura Rachel; Granzen, Bernd; Oosterlaan, Jaap; Grootenhuis, Martha Alexandra

2016-02-01

With more children surviving a brain tumor, neurocognitive consequences of the tumor and its treatment become apparent, which could affect psychosocial functioning. The present study therefore aimed to assess psychosocial functioning of pediatric brain tumor survivors (PBTS) in detail. Psychosocial functioning of PBTS (8-18 years) with parent-reported neurocognitive complaints was compared to normative data on health-related quality of life (HRQOL), self-esteem, psychosocial adjustment, and executive functioning (one-sample t tests) and to a sibling control group on fatigue (independent-samples t test). Self-, parent-, and teacher-report questionnaires were included, where appropriate, providing complementary information. Eighty-two PBTS (mean age 13.4 years, SD 3.2, 49 % males) and 43 healthy siblings (mean age 14.3, SD 2.4, 40 % males) were included. As compared to the normative population, PBTS themselves reported decreased physical, psychological, and generic HRQOL (d = 0.39-0.62, p < 0.008). Compared to siblings, increased fatigue-related concentration problems (d = 0.57, p < 0.01) were reported, although self-reported self-esteem and psychosocial adjustment seemed not to be affected. Parents of PBTS reported more psychosocial (d = 0.81, p < 0.000) and executive problems (d = 0.35-0.43, p < 0.016) in their child than parents of children in the normative population. Teachers indicated more psychosocial adjustment problems for female PBTS aged 8-11 years than for the female normative population (d = 0.69, p < 0.025), but they reported no more executive problems. PBTS with parent-reported neurocognitive complaints showed increased psychosocial problems, as reported by PBTS, parents, and teachers. Systematic screening of psychosocial functioning is necessary so that tailored support from professionals can be offered to PBTS with neurocognitive complaints.

A comparison of the COG and MCNP codes in computational neutron capture therapy modeling, Part II: gadolinium neutron capture therapy models and therapeutic effects.

PubMed

Wangerin, K; Culbertson, C N; Jevremovic, T

2005-08-01

The goal of this study was to evaluate the COG Monte Carlo radiation transport code, developed and tested by Lawrence Livermore National Laboratory, for gadolinium neutron capture therapy (GdNCT) related modeling. The validity of COG NCT model has been established for this model, and here the calculation was extended to analyze the effect of various gadolinium concentrations on dose distribution and cell-kill effect of the GdNCT modality and to determine the optimum therapeutic conditions for treating brain cancers. The computational results were compared with the widely used MCNP code. The differences between the COG and MCNP predictions were generally small and suggest that the COG code can be applied to similar research problems in NCT. Results for this study also showed that a concentration of 100 ppm gadolinium in the tumor was most beneficial when using an epithermal neutron beam.

Cytosolic PhospholipaseA2 Inhibition with PLA-695 Radiosensitizes Tumors in Lung Cancer Animal Models

PubMed Central

Ferraro, Daniel J.; Kotipatruni, Rama P.; Bhave, Sandeep R.; Jaboin, Jerry J.; Hallahan, Dennis E.

2013-01-01

Lung cancer remains the leading cause of cancer deaths in the United States and the rest of the world. The advent of molecularly directed therapies holds promise for improvement in therapeutic efficacy. Cytosolic phospholipase A2 (cPLA2) is associated with tumor progression and radioresistance in mouse tumor models. Utilizing the cPLA2 specific inhibitor PLA-695, we determined if cPLA2 inhibition radiosensitizes non small cell lung cancer (NSCLC) cells and tumors. Treatment with PLA-695 attenuated radiation induced increases of phospho-ERK and phospho-Akt in endothelial cells. NSCLC cells (LLC and A549) co-cultured with endothelial cells (bEND3 and HUVEC) and pre-treated with PLA-695 showed radiosensitization. PLA-695 in combination with irradiation (IR) significantly reduced migration and proliferation in endothelial cells (HUVEC & bEND3) and induced cell death and attenuated invasion by tumor cells (LLC &A549). In a heterotopic tumor model, the combination of PLA-695 and radiation delayed growth in both LLC and A549 tumors. LLC and A549 tumors treated with a combination of PLA-695 and radiation displayed reduced tumor vasculature. In a dorsal skin fold model of LLC tumors, inhibition of cPLA2 in combination with radiation led to enhanced destruction of tumor blood vessels. The anti-angiogenic effects of PLA-695 and its enhancement of the efficacy of radiotherapy in mouse models of NSCLC suggest that clinical trials for its capacity to improve radiotherapy outcomes are warranted. PMID:23894523

Targeting the tumor microenvironment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kenny, P.A.; Lee, G.Y.; Bissell, M.J.

2006-11-07

Despite some notable successes cancer remains, for the most part, a seemingly intractable problem. There is, however, a growing appreciation that targeting the tumor epithelium in isolation is not sufficient as there is an intricate mutually sustaining synergy between the tumor epithelial cells and their surrounding stroma. As the details of this dialogue emerge, new therapeutic targets have been proposed. The FDA has already approved drugs targeting microenvironmental components such as VEGF and aromatase and many more agents are in the pipeline. In this article, we describe some of the 'druggable' targets and processes within the tumor microenvironment and reviewmore » the approaches being taken to disrupt these interactions.« less

Tumor Control Probability Modeling for Stereotactic Body Radiation Therapy of Early-Stage Lung Cancer Using Multiple Bio-physical Models

PubMed Central

Liu, Feng; Tai, An; Lee, Percy; Biswas, Tithi; Ding, George X.; El Naqa, Isaam; Grimm, Jimm; Jackson, Andrew; Kong, Feng-Ming (Spring); LaCouture, Tamara; Loo, Billy; Miften, Moyed; Solberg, Timothy; Li, X Allen

2017-01-01

Purpose To analyze pooled clinical data using different radiobiological models and to understand the relationship between biologically effective dose (BED) and tumor control probability (TCP) for stereotactic body radiotherapy (SBRT) of early-stage non-small cell lung cancer (NSCLC). Method and Materials The clinical data of 1-, 2-, 3-, and 5-year actuarial or Kaplan-Meier TCP from 46 selected studies were collected for SBRT of NSCLC in the literature. The TCP data were separated for Stage T1 and T2 tumors if possible, otherwise collected for combined stages. BED was calculated at isocenters using six radiobiological models. For each model, the independent model parameters were determined from a fit to the TCP data using the least chi-square (χ2) method with either one set of parameters regardless of tumor stages or two sets for T1 and T2 tumors separately. Results The fits to the clinic data yield consistent results of large α/β ratios of about 20 Gy for all models investigated. The regrowth model that accounts for the tumor repopulation and heterogeneity leads to a better fit to the data, compared to other 5 models where the fits were indistinguishable between the models. The models based on the fitting parameters predict that the T2 tumors require about additional 1 Gy physical dose at isocenters per fraction (≤5 fractions) to achieve the optimal TCP when compared to the T1 tumors. Conclusion This systematic analysis of a large set of published clinical data using different radiobiological models shows that local TCP for SBRT of early-stage NSCLC has strong dependence on BED with large α/β ratios of about 20 Gy. The six models predict that a BED (calculated with α/β of 20) of 90 Gy is sufficient to achieve TCP ≥ 95%. Among the models considered, the regrowth model leads to a better fit to the clinical data. PMID:27871671

In vivo PET/CT in a human glioblastoma chicken chorioallantoic membrane model: a new tool for oncology and radiotracer development.

PubMed

Warnock, Geoff; Turtoi, Andrei; Blomme, Arnaud; Bretin, Florian; Bahri, Mohamed Ali; Lemaire, Christian; Libert, Lionel Cyrille; Seret, Alain E J J; Luxen, André; Castronovo, Vincenzo; Plenevaux, Alain R E G

2013-10-01

For many years the laboratory mouse has been used as the standard model for in vivo oncology research, particularly in the development of novel PET tracers, but the growth of tumors on chicken chorioallantoic membrane (CAM) provides a more rapid, low cost, and ethically sustainable alternative. For the first time, to our knowledge, we demonstrate the feasibility of in vivo PET and CT imaging in a U87 glioblastoma tumor model on chicken CAM, with the aim of applying this model for screening of novel PET tracers. U87 glioblastoma cells were implanted on the CAM at day 11 after fertilization and imaged at day 18. A small-animal imaging cell was used to maintain incubation and allow anesthesia using isoflurane. Radiotracers were injected directly into the exposed CAM vasculature. Sodium (18)F-fluoride was used to validate the imaging protocol, demonstrating that image-degrading motion can be removed with anesthesia. Tumor glucose metabolism was imaged using (18)F-FDG, and tumor protein synthesis was imaged using 2-(18)F-fluoro-l-tyrosine. Anatomic images were obtained by contrast-enhanced CT, facilitating clear delineation of the tumor, delineation of tracer uptake in tumor versus embryo, and accurate volume measurements. PET imaging of tumor glucose metabolism and protein synthesis was successfully demonstrated in the CAM U87 glioblastoma model. Catheterization of CAM blood vessels facilitated dynamic imaging of glucose metabolism with (18)F-FDG and demonstrated the ability to study PET tracer uptake over time in individual tumors, and CT imaging improved the accuracy of tumor volume measurements. We describe the novel application of PET/CT in the CAM tumor model, with optimization of typical imaging protocols. PET imaging in this valuable tumor model could prove particularly useful for rapid, high-throughput screening of novel radiotracers.

Oxygen-dependent regulation of tumor growth and metastasis in human breast cancer xenografts.

PubMed

Yttersian Sletta, Kristine; Tveitarås, Maria K; Lu, Ning; Engelsen, Agnete S T; Reed, Rolf K; Garmann-Johnsen, Annette; Stuhr, Linda

2017-01-01

Tumor hypoxia is relevant for tumor growth, metabolism, resistance to chemotherapy and metastasis. We have previously shown that hyperoxia, using hyperbaric oxygen treatment (HBOT), attenuates tumor growth and shifts the phenotype from mesenchymal to epithelial (MET) in the DMBA-induced mammary tumor model. This study describes the effect of HBOT on tumor growth, angiogenesis, chemotherapy efficacy and metastasis in a triple negative MDA-MB-231 breast cancer model, and evaluates tumor growth using a triple positive BT-474 breast cancer model. 5 x 105 cancer cells were injected s.c. in the groin area of NOD/SCID female mice. The BT-474 group was supplied with Progesterone and Estradiol pellets 2-days prior to tumor cell injection. Mice were divided into controls (1 bar, pO2 = 0.2 bar) or HBOT (2.5 bar, pO2 = 2.5 bar, 90 min, every third day until termination of the experiments). Treatment effects were determined by assessment of tumor growth, proliferation (Ki67-staining), angiogenesis (CD31-staining), metastasis (immunostaining), EMT markers (western blot), stromal components collagen type I, Itgb1 and FSP1 (immunostaining) and chemotherapeutic efficacy (5FU). HBOT significantly suppressed tumor growth in both the triple positive and negative tumors, and both MDA-MB-231 and BT-474 showed a decrease in proliferation after HBOT. No differences were found in angiogenesis or 5FU efficacy between HBOT and controls. Nevertheless, HBOT significantly reduced both numbers and total area of the metastastatic lesions, as well as reduced expression of N-cadherin, Axl and collagen type I measured in the MDA-MB-231 model. No change in stromal Itgb1 and FSP1 was found in either tumor model. Despite the fact that behavior and prognosis of the triple positive and negative subtypes of cancer are different, the HBOT had a similar suppressive effect on tumor growth, indicating that they share a common oxygen dependent anti-tumor mechanism. Furthermore, HBOT significantly reduced the number and area of metastatic lesions in the triple negative model as well as a significant reduction in the EMT markers N-cadherin, Axl and density of collagen type I.

How I Manage Breast Problems in Athletes.

ERIC Educational Resources Information Center

Haycock, Christine E.

1987-01-01

This article reviews the anatomy of the breast and describes injuries and disorders that occur in both men and women, including runner's nipples, bicyclist's nipples, tumors, and trauma. Management of these problems and various types of sports bras are discussed. (Author/MT)

A Rigorous Sharp Interface Limit of a Diffuse Interface Model Related to Tumor Growth

NASA Astrophysics Data System (ADS)

Rocca, Elisabetta; Scala, Riccardo

2017-06-01

In this paper, we study the rigorous sharp interface limit of a diffuse interface model related to the dynamics of tumor growth, when a parameter ɛ, representing the interface thickness between the tumorous and non-tumorous cells, tends to zero. More in particular, we analyze here a gradient-flow-type model arising from a modification of the recently introduced model for tumor growth dynamics in Hawkins-Daruud et al. (Int J Numer Math Biomed Eng 28:3-24, 2011) (cf. also Hilhorst et al. Math Models Methods Appl Sci 25:1011-1043, 2015). Exploiting the techniques related to both gradient flows and gamma convergence, we recover a condition on the interface Γ relating the chemical and double-well potentials, the mean curvature, and the normal velocity.

Neurosurgical Virtual Reality Simulation for Brain Tumor Using High-definition Computer Graphics: A Review of the Literature.

PubMed

Kin, Taichi; Nakatomi, Hirofumi; Shono, Naoyuki; Nomura, Seiji; Saito, Toki; Oyama, Hiroshi; Saito, Nobuhito

2017-10-15

Simulation and planning of surgery using a virtual reality model is becoming common with advances in computer technology. In this study, we conducted a literature search to find trends in virtual simulation of surgery for brain tumors. A MEDLINE search for "neurosurgery AND (simulation OR virtual reality)" retrieved a total of 1,298 articles published in the past 10 years. After eliminating studies designed solely for education and training purposes, 28 articles about the clinical application remained. The finding that the vast majority of the articles were about education and training rather than clinical applications suggests that several issues need be addressed for clinical application of surgical simulation. In addition, 10 of the 28 articles were from Japanese groups. In general, the 28 articles demonstrated clinical benefits of virtual surgical simulation. Simulation was particularly useful in better understanding complicated spatial relations of anatomical landmarks and in examining surgical approaches. In some studies, Virtual reality models were used on either surgical navigation system or augmented reality technology, which projects virtual reality images onto the operating field. Reported problems were difficulties in standardized, objective evaluation of surgical simulation systems; inability to respond to tissue deformation caused by surgical maneuvers; absence of the system functionality to reflect features of tissue (e.g., hardness and adhesion); and many problems with image processing. The amount of description about image processing tended to be insufficient, indicating that the level of evidence, risk of bias, precision, and reproducibility need to be addressed for further advances and ultimately for full clinical application.

Nonlinear ghost waves accelerate the progression of high-grade brain tumors

NASA Astrophysics Data System (ADS)

Pardo, Rosa; Martínez-González, Alicia; Pérez-García, Víctor M.

2016-10-01

We study a reduced continuous model describing the evolution of high grade gliomas in response to hypoxic events through the interplay of different cellular phenotypes. We show that hypoxic events, even when sporadic and/or limited in space, may have a crucial role on the acceleration of high grade gliomas growth. Our modeling approach is based on two cellular phenotypes. One of them is more migratory and a second one is more proliferative. Transitions between both phenotypes are driven by the local oxygen values, assumed in this simple model to be uniform. Surprisingly, even very localized in time hypoxia events leading to transient migratory populations have the potential to accelerate the tumor's invasion speed up to speeds close to those of the migratory phenotype. The high invasion speed persists for times much longer than the lifetime of the hypoxic event. Moreover, the phenomenon is observed both when the migratory cells form a persistent wave of cells located on the invasion front and when they form a evanescent "ghost" wave disappearing after a short time by decay to the more proliferative phenotype. Our findings are obtained through numerical simulations of the model equations both in 1D and higher dimensional scenarios. We also provide a deeper mathematical analysis of some aspects of the problem such as the conditions for the existence of persistent waves of cells with a more migratory phenotype.

A Big Bang model of human colorectal tumor growth

PubMed Central

Sottoriva, Andrea; Kang, Haeyoun; Ma, Zhicheng; Graham, Trevor A.; Salomon, Matthew P.; Zhao, Junsong; Marjoram, Paul; Siegmund, Kimberly; Press, Michael F.; Shibata, Darryl; Curtis, Christina

2015-01-01

What happens in the early, still undetectable human malignancy is unknown because direct observations are impractical. Here we present and validate a “Big Bang” model, whereby tumors grow predominantly as a single expansion producing numerous intermixed sub-clones that are not subject to stringent selection, and where both public (clonal) and most detectable private (subclonal) alterations arise early during growth. Genomic profiling of 349 individual glands from 15 colorectal tumors revealed the absence of selective sweeps, uniformly high intra-tumor heterogeneity (ITH), and sub-clone mixing in distant regions, as postulated by our model. We also verified the prediction that most detectable ITH originates from early private alterations, and not from later clonal expansions, thus exposing the profile of the primordial tumor. Moreover, some tumors appear born-to-be-bad, with sub-clone mixing indicative of early malignant potential. This new model provides a quantitative framework to interpret tumor growth dynamics and the origins of ITH with significant clinical implications. PMID:25665006

A transplantable TH-MYCN transgenic tumor model in C57Bl/6 mice for preclinical immunological studies in neuroblastoma.

PubMed

Kroesen, Michiel; Nierkens, Stefan; Ansems, Marleen; Wassink, Melissa; Orentas, Rimas J; Boon, Louis; den Brok, Martijn H; Hoogerbrugge, Peter M; Adema, Gosse J

2014-03-15

Current multimodal treatments for patients with neuroblastoma (NBL), including anti-disialoganglioside (GD2) monoclonal antibody (mAb) based immunotherapy, result in a favorable outcome in around only half of the patients with advanced disease. To improve this, novel immunocombinational strategies need to be developed and tested in autologous preclinical NBL models. A genetically well-explored autologous mouse model for NBL is the TH-MYCN model. However, the immunobiology of the TH-MYCN model remains largely unexplored. We developed a mouse model using a transplantable TH-MYCN cell line in syngeneic C57Bl/6 mice and characterized the immunobiology of this model. In this report, we show the relevance and opportunities of this model to study immunotherapy for human NBL. Similar to human NBL cells, syngeneic TH-MYCN-derived 9464D cells endogenously express the tumor antigen GD2 and low levels of MHC Class I. The presence of the adaptive immune system had little or no influence on tumor growth, showing the low immunogenicity of the NBL cells. In contrast, depletion of NK1.1+ cells resulted in enhanced tumor outgrowth in both wild-type and Rag1(-/-) mice, showing an important role for NK cells in the natural anti-NBL immune response. Analysis of the tumor infiltrating leukocytes ex vivo revealed the presence of both tumor associated myeloid cells and T regulatory cells, thus mimicking human NBL tumors. Finally, anti-GD2 mAb mediated NBL therapy resulted in ADCC in vitro and delayed tumor outgrowth in vivo. We conclude that the transplantable TH-MYCN model represents a relevant model for the development of novel immunocombinatorial approaches for NBL patients. © 2013 UICC.

Orthotopic tumorgrafts in nude mice: A new method to study human prostate cancer.

PubMed

Saar, Matthias; Körbel, Christina; Linxweiler, Johannes; Jung, Volker; Kamradt, Jörn; Hasenfus, Andrea; Stöckle, Michael; Unteregger, Gerhard; Menger, Michael D

2015-10-01

In vivo model systems in prostate cancer research that authentically reproduce tumor growth are still sparse. While orthotopic implantation is technically difficult, particularly in the mouse, most models favor subcutaneous tumor growth. This however provides little information about natural tumor growth behavior and tumor stroma interaction. Furthermore, established prostate cancer cell lines grown as in vivo xenografts are not able to reflect the variety of tumor specific growth patterns and growth behavior in men. Primary cell cultures are difficult to handle and an induction of orthotopic tumors has not been successful yet. Therefore, a tumorgraft model using tumor tissue from prostatectomy specimens was developed. Balb/c nude mice were used to graft fresh prostate tumor tissue by renal subcapsular and orthotopic implantation. Testosterone propionate was supplemented. Animals were tracked by means of 30 MHz ultrasound to monitor tumor engraftment and growth. Autopsy, histology, PSA measurements as well as immunostaining and PCR for human tissue were performed to confirm orthotopic tumor growth. Renal subcapsular engraftment was seen in 2 of 3 mice. Orthotopic engraftment was observed in 7 of 11 animals (63.6%) with an overall engraftment of 5 out of 9 patient specimens (55.6%). Ultrasound confirmed the tumor growth over time. Of interest, the tumorgrafts not only retained essential features of the parental tumors, but also stained positive for tumor specific markers such as AR, PSA, and AMACR. Tumor positive animals showed highly elevated serum PSA levels with confirmation of a human specific PCR sequence and a human endothelial cell lining in the tumor vessels. Standardized implantation of fresh tumor tissue in nude mice prostates generates tumorgrafts with histological properties of organ-confined prostate cancer. These tumorgrafts display a new approach for an optimized in vivo model of prostate cancer and will allow further investigations on specific pathways of tumor initiation and progression as well as therapeutic response. © 2015 Wiley Periodicals, Inc.

Novel, improved grading system(s) for IDH-mutant astrocytic gliomas.

PubMed

Shirahata, Mitsuaki; Ono, Takahiro; Stichel, Damian; Schrimpf, Daniel; Reuss, David E; Sahm, Felix; Koelsche, Christian; Wefers, Annika; Reinhardt, Annekathrin; Huang, Kristin; Sievers, Philipp; Shimizu, Hiroaki; Nanjo, Hiroshi; Kobayashi, Yusuke; Miyake, Yohei; Suzuki, Tomonari; Adachi, Jun-Ichi; Mishima, Kazuhiko; Sasaki, Atsushi; Nishikawa, Ryo; Bewerunge-Hudler, Melanie; Ryzhova, Marina; Absalyamova, Oksana; Golanov, Andrey; Sinn, Peter; Platten, Michael; Jungk, Christine; Winkler, Frank; Wick, Antje; Hänggi, Daniel; Unterberg, Andreas; Pfister, Stefan M; Jones, David T W; van den Bent, Martin; Hegi, Monika; French, Pim; Baumert, Brigitta G; Stupp, Roger; Gorlia, Thierry; Weller, Michael; Capper, David; Korshunov, Andrey; Herold-Mende, Christel; Wick, Wolfgang; Louis, David N; von Deimling, Andreas

2018-04-23

According to the 2016 World Health Organization Classification of Tumors of the Central Nervous System (2016 CNS WHO), IDH-mutant astrocytic gliomas comprised WHO grade II diffuse astrocytoma, IDH-mutant (AII IDHmut ), WHO grade III anaplastic astrocytoma, IDH-mutant (AAIII IDHmut ), and WHO grade IV glioblastoma, IDH-mutant (GBM IDHmut ). Notably, IDH gene status has been made the major criterion for classification while the manner of grading has remained unchanged: it is based on histological criteria that arose from studies which antedated knowledge of the importance of IDH status in diffuse astrocytic tumor prognostic assessment. Several studies have now demonstrated that the anticipated differences in survival between the newly defined AII IDHmut and AAIII IDHmut have lost their significance. In contrast, GBM IDHmut still exhibits a significantly worse outcome than its lower grade IDH-mutant counterparts. To address the problem of establishing prognostically significant grading for IDH-mutant astrocytic gliomas in the IDH era, we undertook a comprehensive study that included assessment of histological and genetic approaches to prognosis in these tumors. A discovery cohort of 211 IDH-mutant astrocytic gliomas with an extended observation was subjected to histological review, image analysis, and DNA methylation studies. Tumor group-specific methylation profiles and copy number variation (CNV) profiles were established for all gliomas. Algorithms for automated CNV analysis were developed. All tumors exhibiting 1p/19q codeletion were excluded from the series. We developed algorithms for grading, based on molecular, morphological and clinical data. Performance of these algorithms was compared with that of WHO grading. Three independent cohorts of 108, 154 and 224 IDH-mutant astrocytic gliomas were used to validate this approach. In the discovery cohort several molecular and clinical parameters were of prognostic relevance. Most relevant for overall survival (OS) was CDKN2A/B homozygous deletion. Other parameters with major influence were necrosis and the total number of CNV. Proliferation as assessed by mitotic count, which is a key parameter in 2016 CNS WHO grading, was of only minor influence. Employing the parameters most relevant for OS in our discovery set, we developed two models for grading these tumors. These models performed significantly better than WHO grading in both the discovery and the validation sets. Our novel algorithms for grading IDH-mutant astrocytic gliomas overcome the challenges caused by introduction of IDH status into the WHO classification of diffuse astrocytic tumors. We propose that these revised approaches be used for grading of these tumors and incorporated into future WHO criteria.

Accessing key steps of human tumor progression in vivo by using an avian embryo model

NASA Astrophysics Data System (ADS)

Hagedorn, Martin; Javerzat, Sophie; Gilges, Delphine; Meyre, Aurélie; de Lafarge, Benjamin; Eichmann, Anne; Bikfalvi, Andreas

2005-02-01

Experimental in vivo tumor models are essential for comprehending the dynamic process of human cancer progression, identifying therapeutic targets, and evaluating antitumor drugs. However, current rodent models are limited by high costs, long experimental duration, variability, restricted accessibility to the tumor, and major ethical concerns. To avoid these shortcomings, we investigated whether tumor growth on the chick chorio-allantoic membrane after human glioblastoma cell grafting would replicate characteristics of the human disease. Avascular tumors consistently formed within 2 days, then progressed through vascular endothelial growth factor receptor 2-dependent angiogenesis, associated with hemorrhage, necrosis, and peritumoral edema. Blocking of vascular endothelial growth factor receptor 2 and platelet-derived growth factor receptor signaling pathways by using small-molecule receptor tyrosine kinase inhibitors abrogated tumor development. Gene regulation during the angiogenic switch was analyzed by oligonucleotide microarrays. Defined sample selection for gene profiling permitted identification of regulated genes whose functions are associated mainly with tumor vascularization and growth. Furthermore, expression of known tumor progression genes identified in the screen (IL-6 and cysteine-rich angiogenic inducer 61) as well as potential regulators (lumican and F-box-only 6) follow similar patterns in patient glioma. The model reliably simulates key features of human glioma growth in a few days and thus could considerably increase the speed and efficacy of research on human tumor progression and preclinical drug screening. angiogenesis | animal model alternatives | glioblastoma

Is cancer a pure growth curve or does it follow a kinetics of dynamical structural transformation?

PubMed

González, Maraelys Morales; Joa, Javier Antonio González; Cabrales, Luis Enrique Bergues; Pupo, Ana Elisa Bergues; Schneider, Baruch; Kondakci, Suleyman; Ciria, Héctor Manuel Camué; Reyes, Juan Bory; Jarque, Manuel Verdecia; Mateus, Miguel Angel O'Farril; González, Tamara Rubio; Brooks, Soraida Candida Acosta; Cáceres, José Luis Hernández; González, Gustavo Victoriano Sierra

2017-03-07

Unperturbed tumor growth kinetics is one of the more studied cancer topics; however, it is poorly understood. Mathematical modeling is a useful tool to elucidate new mechanisms involved in tumor growth kinetics, which can be relevant to understand cancer genesis and select the most suitable treatment. The classical Kolmogorov-Johnson-Mehl-Avrami as well as the modified Kolmogorov-Johnson-Mehl-Avrami models to describe unperturbed fibrosarcoma Sa-37 tumor growth are used and compared with the Gompertz modified and Logistic models. Viable tumor cells (1×10 5 ) are inoculated to 28 BALB/c male mice. Modified Gompertz, Logistic, Kolmogorov-Johnson-Mehl-Avrami classical and modified Kolmogorov-Johnson-Mehl-Avrami models fit well to the experimental data and agree with one another. A jump in the time behaviors of the instantaneous slopes of classical and modified Kolmogorov-Johnson-Mehl-Avrami models and high values of these instantaneous slopes at very early stages of tumor growth kinetics are observed. The modified Kolmogorov-Johnson-Mehl-Avrami equation can be used to describe unperturbed fibrosarcoma Sa-37 tumor growth. It reveals that diffusion-controlled nucleation/growth and impingement mechanisms are involved in tumor growth kinetics. On the other hand, tumor development kinetics reveals dynamical structural transformations rather than a pure growth curve. Tumor fractal property prevails during entire TGK.

Modeling triple-negative breast cancer heterogeneity: effects of stromal macrophages, fibroblasts and tumor vasculature.

PubMed

Norton, Kerri-Ann; Jin, Kideok; Popel, Aleksander S

2018-05-08

A hallmark of breast tumors is its spatial heterogeneity that includes its distribution of cancer stem cells and progenitor cells, but also heterogeneity in the tumor microenvironment. In this study we focus on the contributions of stromal cells, specifically macrophages, fibroblasts, and endothelial cells on tumor progression. We develop a computational model of triple-negative breast cancer based on our previous work and expand it to include macrophage infiltration, fibroblasts, and angiogenesis. In vitro studies have shown that the secretomes of tumor-educated macrophages and fibroblasts increase both the migration and proliferation rates of triple-negative breast cancer cells. In vivo studies also demonstrated that blocking signaling of selected secreted factors inhibits tumor growth and metastasis in mouse xenograft models. We investigate the influences of increased migration and proliferation rates on tumor growth, the effect of the presence on fibroblasts or macrophages on growth and morphology, and the contributions of macrophage infiltration on tumor growth. We find that while the presence of macrophages increases overall tumor growth, the increase in macrophage infiltration does not substantially increase tumor growth and can even stifle tumor growth at excessive rates. Copyright © 2018. Published by Elsevier Ltd.

Depression, suicide ideation, and thyroid tumors among ukrainian adolescents exposed as children to chernobyl radiation.

PubMed

Contis, George; Foley, Thomas P

2015-05-01

The Chernobyl Childhood Illness Program (CCIP) was a humanitarian assistance effort funded by the United States Congress. Its purpose was to assist the Ukrainian Government to identify and treat adolescents who developed mental and physical problems following their exposure as young children to Chernobyl radiation. Thirteen years after the Chernobyl nuclear plant accident in 1986, the CCIP examined 116,655 Ukrainian adolescents for thyroid diseases. Of these, 115,191 were also screened for depression, suicide ideation, and psychological problems. The adolescents lived in five of Ukraine's seven most Chernobyl radiation contaminated provinces. They were up to 6 years of age or in utero when exposed to nuclear fallout, or were born up to 45 months after Chernobyl. Ukrainian endocrinologist and ultrasonographers used physical examination and ultrasonography of the neck to evaluate the adolescents for thyroid tumors. The adolescents were then screened for depression by the Children's Depression Inventory (CDI). After this, Ukrainian psychologists conducted individual psychological interviews to corroborate the adolescents' CDI responses. Papillary thyroid carcinoma was diagnosed in eight adolescents, a high prevalence rate similar to that reported by other studies from the Soviet Union. Screening identified thyroid nodules in 1,967 adolescents (1.7%). Depression was diagnosed in 15,399 adolescents (13.2%), suicide ideation in 813 (5.3%), and attempted suicide in 354 (2.3%). Underlying components of the participants' depression were negative mood, interpersonal difficulties, negative self-esteem, ineffectiveness, and anhedonia. Depression was greater in females (77%). Those with thyroid and psychological problems were referred for treatment. The adolescents screened by CCIP represent the largest Ukrainian cohort exposed to Chernobyl radiation as children who were evaluated for both thyroid tumors and depression. The group had an increased prevalence of thyroid cancer, thyroid tumors, depression, and suicide ideation. CCIP demonstrated that psychological problems among Chernobyl exposed adolescents began earlier in life than previously reported. They also experienced socioeconomic problems from their relocation from radiation-affected areas and from the Soviet's inadequate responses to their health needs. CCIP's findings underscore the requirement that governments prepare plans to deal promptly with the diagnosis and treatment of nuclear accident victims' medical and psychological problems.

Distributed delays in a hybrid model of tumor-immune system interplay.

PubMed

Caravagna, Giulio; Graudenzi, Alex; d'Onofrio, Alberto

2013-02-01

A tumor is kinetically characterized by the presence of multiple spatio-temporal scales in which its cells interplay with, for instance, endothelial cells or Immune system effectors, exchanging various chemical signals. By its nature, tumor growth is an ideal object of hybrid modeling where discrete stochastic processes model low-numbers entities, and mean-field equations model abundant chemical signals. Thus, we follow this approach to model tumor cells, effector cells and Interleukin-2, in order to capture the Immune surveillance effect. We here present a hybrid model with a generic delay kernel accounting that, due to many complex phenomena such as chemical transportation and cellular differentiation, the tumor-induced recruitment of effectors exhibits a lag period. This model is a Stochastic Hybrid Automata and its semantics is a Piecewise Deterministic Markov process where a two-dimensional stochastic process is interlinked to a multi-dimensional mean-field system. We instantiate the model with two well-known weak and strong delay kernels and perform simulations by using an algorithm to generate trajectories of this process. Via simulations and parametric sensitivity analysis techniques we (i) relate tumor mass growth with the two kernels, we (ii) measure the strength of the Immune surveillance in terms of probability distribution of the eradication times, and (iii) we prove, in the oscillatory regime, the existence of a stochastic bifurcation resulting in delay-induced tumor eradication.

What underlies the diversity of brain tumors?

PubMed Central

Swartling, Fredrik J.; Hede, Sanna-Maria; Weiss, William A.

2012-01-01

Glioma and medulloblastoma represent the most commonly occurring malignant brain tumors in adults and in children respectively. Recent genomic and transcriptional approaches present a complex group of diseases, and delineate a number of molecular subgroups within tumors that share a common histopathology. Differences in cells of origin, regional niches, developmental timing and genetic events all contribute to this heterogeneity. In an attempt to recapitulate the diversity of brain tumors, an increasing array of genetically engineered mouse models (GEMMs) has been developed. These models often utilize promoters and genetic drivers from normal brain development, and can provide insight into specific cells from which these tumors originate. GEMMs show promise in both developmental biology and developmental therapeutics. This review describes numerous murine brain tumor models in the context of normal brain development, and the potential for these animals to impact brain tumor research. PMID:23085857

The Smo/Smo model: hedgehog-induced medulloblastoma with 90% incidence and leptomeningeal spread.

PubMed

Hatton, Beryl A; Villavicencio, Elisabeth H; Tsuchiya, Karen D; Pritchard, Joel I; Ditzler, Sally; Pullar, Barbara; Hansen, Stacey; Knoblaugh, Sue E; Lee, Donghoon; Eberhart, Charles G; Hallahan, Andrew R; Olson, James M

2008-03-15

Toward the goal of generating a mouse medulloblastoma model with increased tumor incidence, we developed a homozygous version of our ND2:SmoA1 model. Medulloblastomas form in 94% of homozygous Smo/Smo mice by 2 months of age. Tumor formation is, thus, predictable by age, before the symptomatic appearance of larger lesions. This high incidence and early onset of tumors is ideal for preclinical studies because mice can be enrolled before symptom onset and with a greater latency period before late-stage disease. Smo/Smo tumors also display leptomeningeal dissemination of neoplastic cells to the brain and spine, which occurs in many human cases. Despite an extended proliferation of granule neuron precursors (GNP) in the postnatal external granular layer (EGL), the internal granular layer formed normally in Smo/Smo mice and tumor formation occurred only in localized foci on the superficial surface of the molecular layer. Thus, tumor formation is not simply the result of over proliferation of GNPs within the EGL. Moreover, Smo/Smo medulloblastomas were transplantable and serially passaged in vivo, demonstrating the aggressiveness of tumor cells and their transformation beyond a hyperplastic state. The Smo/Smo model is the first mouse medulloblastoma model to show leptomeningeal spread. The adherence to human pathology, high incidence, and early onset of tumors thus make Smo/Smo mice an efficient model for preclinical studies.

Establishment and Characterization of a Tumor Stem Cell-Based Glioblastoma Invasion Model.

PubMed

Jensen, Stine Skov; Meyer, Morten; Petterson, Stine Asferg; Halle, Bo; Rosager, Ann Mari; Aaberg-Jessen, Charlotte; Thomassen, Mads; Burton, Mark; Kruse, Torben A; Kristensen, Bjarne Winther

2016-01-01

Glioblastoma is the most frequent and malignant brain tumor. Recurrence is inevitable and most likely connected to tumor invasion and presence of therapy resistant stem-like tumor cells. The aim was therefore to establish and characterize a three-dimensional in vivo-like in vitro model taking invasion and tumor stemness into account. Glioblastoma stem cell-like containing spheroid (GSS) cultures derived from three different patients were established and characterized. The spheroids were implanted in vitro into rat brain slice cultures grown in stem cell medium and in vivo into brains of immuno-compromised mice. Invasion was followed in the slice cultures by confocal time-lapse microscopy. Using immunohistochemistry, we compared tumor cell invasion as well as expression of proliferation and stem cell markers between the models. We observed a pronounced invasion into brain slice cultures both by confocal time-lapse microscopy and immunohistochemistry. This invasion closely resembled the invasion in vivo. The Ki-67 proliferation indexes in spheroids implanted into brain slices were lower than in free-floating spheroids. The expression of stem cell markers varied between free-floating spheroids, spheroids implanted into brain slices and tumors in vivo. The established invasion model kept in stem cell medium closely mimics tumor cell invasion into the brain in vivo preserving also to some extent the expression of stem cell markers. The model is feasible and robust and we suggest the model as an in vivo-like model with a great potential in glioma studies and drug discovery.

Identification of aberrantly expressed circRNAs in subgroup J avian leucosis virus induced tumor livers by RNA sequencing

USDA-ARS?s Scientific Manuscript database

ALV-J (subgroup J avian leucosis virus) is a kind of oncogenic exogenous retrovirus and diseases associated with ALV-J have caused severe reproduction problems in the poultry industry worldwide. However, the pathogenesis of ALV-J-induced tumor formation is still unclear. In recent years, circRNAs ar...

PEGylated lipid nanocapsules with improved drug encapsulation and controlled release properties.

PubMed

Hervella, Pablo; Alonso-Sande, Maria; Ledo, Francisco; Lucero, Maria L; Alonso, Maria J; Garcia-Fuentes, Marcos

2014-01-01

Drugs with poor lipid and water solubility are some of the most challenging to formulate in nanocarriers, typically resulting in low encapsulation efficiencies and uncontrolled release profiles. PEGylated nanocapsules (PEG-NC) are known for their amenability to diverse modifications that allow the formation of domains with different physicochemical properties, an interesting feature to address a drug encapsulation problem. We explored this problem by encapsulating in PEG-NC the promising anticancer drug candidate F10320GD1, used herein as a model for compounds with such characteristics. The nanocarriers were prepared from Miglyol(®), lecithin and PEG-sterate through a solvent displacement technique. The resulting system was a homogeneous suspension of particles with size around 200 nm. F10320GD1 encapsulation was found to be very poor (<15%) if PEG-NC were prepared using water as continuous phase; but we were able to improve this value to 85% by fixing the pH of the continuous phase to 9. Interestingly, this modification also improved the controlled release properties and the chemical stability of the formulation during storage. These differences in pharmaceutical properties together with physicochemical data suggest that the pH of the continuous phase used for PEG-NC preparation can modify drug allocation, from the external shell towards the inner lipid core of the nanocapsules. Finally, we tested the bioactivity of the drug-loaded PEG-NC in several tumor cell lines, and also in endothelial cells. The results indicated that drug encapsulation led to an improvement on drug cytotoxicity in tumor cells, but not in non-tumor endothelial cells. Altogether, the data confirms that PEG-NC show adequate delivery properties for F10320GD1, and underlines its possible utility as an anticancer therapy.

Molecular subtype-specific immunocompetent models of high-grade urothelial carcinoma reveal differential neoantigen expression and response to immunotherapy.

PubMed

Saito, Ryoichi; Smith, Christof C; Utsumi, Takanobu; Bixby, Lisa M; Kardos, Jordan; Wobker, Sara E; Stewart, Kyle G; Chai, Shengjie; Manocha, Ujjawal; Byrd, Kevin Matthew; Damrauer, Jeffrey S; Williams, Scott E; Vincent, Benjamin G; Kim, William Y

2018-05-21

High-grade urothelial cancer contains intrinsic molecular subtypes that exhibit differences in underlying tumor biology and can be divided into luminal-like and basal-like subtypes. We describe here the first subtype-specific murine models of bladder cancer and show that Upk3a-CreERT2; Trp53L/L; PtenL/L; Rosa26LSL-Luc (UPPL: luminal-like) and BBN (basal-like) tumors are more faithful to human bladder cancer than the widely-used MB49 cells. Following engraftment into immunocompetent C57BL/6 mice, BBN tumors were more responsive to PD-1 inhibition than UPPL tumors. Responding tumors within the BBN model showed differences in immune microenvironment composition, including increased ratios of CD8+:CD4+ and memory:regulatory T cells. Finally, we predicted and confirmed immunogenicity of tumor neoantigens in each model. These UPPL and BBN models will be a valuable resource for future studies examining bladder cancer biology and immunotherapy. Copyright ©2018, American Association for Cancer Research.

3D microvascular model recapitulates the diffuse large B-cell lymphoma tumor microenvironment in vitro.

PubMed

Mannino, Robert G; Santiago-Miranda, Adriana N; Pradhan, Pallab; Qiu, Yongzhi; Mejias, Joscelyn C; Neelapu, Sattva S; Roy, Krishnendu; Lam, Wilbur A

2017-01-31

Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer that affects ∼22 000 people in the United States yearly. Understanding the complex cellular interactions of the tumor microenvironment is critical to the success and development of DLBCL treatment strategies. In vitro platforms that successfully model the complex tumor microenvironment without introducing the variability of in vivo systems are vital for understanding these interactions. To date, no such in vitro model exists that can accurately recapitulate the interactions that occur between immune cells, cancer cells, and endothelial cells in the tumor microenvironment of DLBCL. To that end, we developed a lymphoma-on-chip model consisting of a hydrogel based tumor model traversed by a vascularized, perfusable, round microchannel that successfully recapitulates key complexities and interactions of the in vivo tumor microenvironment in vitro. We have shown that the perfusion capabilities of this technique allow us to study targeted treatment strategies, as well as to model the diffusion of infused reagents spatiotemporally. Furthermore, this model employs a novel fabrication technique that utilizes common laboratory materials, and allows for the microfabrication of multiplex microvascular environments without the need for advanced microfabrication facilities. Through our facile microfabrication process, we are able to achieve micro vessels within a tumor model that are highly reliable and precise over the length of the vessel. Overall, we have developed a tool that enables researchers from many diverse disciplines to study previously inaccessible aspects of the DLBCL tumor microenvironment, with profound implications for drug delivery and design.

3D microvascular model recapitulates the diffuse large B-cell lymphoma tumor microenvironment in vitro

PubMed Central

Mannino, Robert G.; Santiago-Miranda, Adriana N.; Pradhan, Pallab; Qiu, Yongzhi; Mejias, Joscelyn C.; Neelapu, Sattva S.; Roy, Krishnendu; Lam, Wilbur A.

2017-01-01

Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer that affects ~22,000 people in the United States yearly. Understanding the complex cellular interactions of the tumor microenvironment is critical to the success and development of DLBCL treatment strategies. In vitro platforms that successfully model the complex tumor microenvironment without introducing the variability of in vivo systems are vital for understanding these interactions. To date, no such in vitro model exists that can accurately recapitulate the interactions that occur between immune cells, cancer cells, and endothelial cells in the tumor microenvironment of DLBCL. To that end, we developed a lymphoma-on-chip model consisting of a hydrogel based tumor model traversed by a vascularized, perfusable, round microchannel that successfully recapitulates key complexities and interactions of the in vivo tumor microenvironment in vitro. We have shown that the perfusion capabilities of this technique allow us to study targeted treatment strategies, as well as to model the diffusion of infused reagents spatiotemporally. Furthermore, this model employs a novel fabrication technique that utilizes common laboratory materials, and allows for the microfabrication of multiplex microvascular environments without the need for advanced microfabrication facilities. Through our facile microfabrication process, we are able to achieve micro vessels within a tumor model that are highly reliable and precise over the length of the vessel. Overall, we have developed a tool that enables researchers from many diverse disciplines to study previously inaccessible aspects of the DLBCL tumor microenvironment, with profound implications for drug delivery and design. PMID:28054086

Building a high-resolution T2-weighted MR-based probabilistic model of tumor occurrence in the prostate.

PubMed

Nagarajan, Mahesh B; Raman, Steven S; Lo, Pechin; Lin, Wei-Chan; Khoshnoodi, Pooria; Sayre, James W; Ramakrishna, Bharath; Ahuja, Preeti; Huang, Jiaoti; Margolis, Daniel J A; Lu, David S K; Reiter, Robert E; Goldin, Jonathan G; Brown, Matthew S; Enzmann, Dieter R

2018-02-19

We present a method for generating a T2 MR-based probabilistic model of tumor occurrence in the prostate to guide the selection of anatomical sites for targeted biopsies and serve as a diagnostic tool to aid radiological evaluation of prostate cancer. In our study, the prostate and any radiological findings within were segmented retrospectively on 3D T2-weighted MR images of 266 subjects who underwent radical prostatectomy. Subsequent histopathological analysis determined both the ground truth and the Gleason grade of the tumors. A randomly chosen subset of 19 subjects was used to generate a multi-subject-derived prostate template. Subsequently, a cascading registration algorithm involving both affine and non-rigid B-spline transforms was used to register the prostate of every subject to the template. Corresponding transformation of radiological findings yielded a population-based probabilistic model of tumor occurrence. The quality of our probabilistic model building approach was statistically evaluated by measuring the proportion of correct placements of tumors in the prostate template, i.e., the number of tumors that maintained their anatomical location within the prostate after their transformation into the prostate template space. Probabilistic model built with tumors deemed clinically significant demonstrated a heterogeneous distribution of tumors, with higher likelihood of tumor occurrence at the mid-gland anterior transition zone and the base-to-mid-gland posterior peripheral zones. Of 250 MR lesions analyzed, 248 maintained their original anatomical location with respect to the prostate zones after transformation to the prostate. We present a robust method for generating a probabilistic model of tumor occurrence in the prostate that could aid clinical decision making, such as selection of anatomical sites for MR-guided prostate biopsies.

A comparison of continuous- and discrete- time three-state models for rodent tumorigenicity experiments.

PubMed Central

Lindsey, J C; Ryan, L M

1994-01-01

The three-state illness-death model provides a useful way to characterize data from a rodent tumorigenicity experiment. Most parametrizations proposed recently in the literature assume discrete time for the death process and either discrete or continuous time for the tumor onset process. We compare these approaches with a third alternative that uses a piecewise continuous model on the hazards for tumor onset and death. All three models assume proportional hazards to characterize tumor lethality and the effect of dose on tumor onset and death rate. All of the models can easily be fitted using an Expectation Maximization (EM) algorithm. The piecewise continuous model is particularly appealing in this context because the complete data likelihood corresponds to a standard piecewise exponential model with tumor presence as a time-varying covariate. It can be shown analytically that differences between the parameter estimates given by each model are explained by varying assumptions about when tumor onsets, deaths, and sacrifices occur within intervals. The mixed-time model is seen to be an extension of the grouped data proportional hazards model [Mutat. Res. 24:267-278 (1981)]. We argue that the continuous-time model is preferable to the discrete- and mixed-time models because it gives reasonable estimates with relatively few intervals while still making full use of the available information. Data from the ED01 experiment illustrate the results. PMID:8187731

A Big Bang model of human colorectal tumor growth.

PubMed

Sottoriva, Andrea; Kang, Haeyoun; Ma, Zhicheng; Graham, Trevor A; Salomon, Matthew P; Zhao, Junsong; Marjoram, Paul; Siegmund, Kimberly; Press, Michael F; Shibata, Darryl; Curtis, Christina

2015-03-01

What happens in early, still undetectable human malignancies is unknown because direct observations are impractical. Here we present and validate a 'Big Bang' model, whereby tumors grow predominantly as a single expansion producing numerous intermixed subclones that are not subject to stringent selection and where both public (clonal) and most detectable private (subclonal) alterations arise early during growth. Genomic profiling of 349 individual glands from 15 colorectal tumors showed an absence of selective sweeps, uniformly high intratumoral heterogeneity (ITH) and subclone mixing in distant regions, as postulated by our model. We also verified the prediction that most detectable ITH originates from early private alterations and not from later clonal expansions, thus exposing the profile of the primordial tumor. Moreover, some tumors appear 'born to be bad', with subclone mixing indicative of early malignant potential. This new model provides a quantitative framework to interpret tumor growth dynamics and the origins of ITH, with important clinical implications.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project.

PubMed

de Hoogt, Ronald; Estrada, Marta F; Vidic, Suzana; Davies, Emma J; Osswald, Annika; Barbier, Michael; Santo, Vítor E; Gjerde, Kjersti; van Zoggel, Hanneke J A A; Blom, Sami; Dong, Meng; Närhi, Katja; Boghaert, Erwin; Brito, Catarina; Chong, Yolanda; Sommergruber, Wolfgang; van der Kuip, Heiko; van Weerden, Wytske M; Verschuren, Emmy W; Hickman, John; Graeser, Ralph

2017-11-21

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project

PubMed Central

de Hoogt, Ronald; Estrada, Marta F.; Vidic, Suzana; Davies, Emma J.; Osswald, Annika; Barbier, Michael; Santo, Vítor E.; Gjerde, Kjersti; van Zoggel, Hanneke J. A. A.; Blom, Sami; Dong, Meng; Närhi, Katja; Boghaert, Erwin; Brito, Catarina; Chong, Yolanda; Sommergruber, Wolfgang; van der Kuip, Heiko; van Weerden, Wytske M.; Verschuren, Emmy W.; Hickman, John; Graeser, Ralph

2017-01-01

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented. PMID:29160867

Role of Constitutive Behavior and Tumor-Host Mechanical Interactions in the State of Stress and Growth of Solid Tumors

PubMed Central

Papageorgis, Panagiotis; Odysseos, Andreani D.; Stylianopoulos, Triantafyllos

2014-01-01

Mechanical forces play a crucial role in tumor patho-physiology. Compression of cancer cells inhibits their proliferation rate, induces apoptosis and enhances their invasive and metastatic potential. Additionally, compression of intratumor blood vessels reduces the supply of oxygen, nutrients and drugs, affecting tumor progression and treatment. Despite the great importance of the mechanical microenvironment to the pathology of cancer, there are limited studies for the constitutive modeling and the mechanical properties of tumors and on how these parameters affect tumor growth. Also, the contribution of the host tissue to the growth and state of stress of the tumor remains unclear. To this end, we performed unconfined compression experiments in two tumor types and found that the experimental stress-strain response is better fitted to an exponential constitutive equation compared to the widely used neo-Hookean and Blatz-Ko models. Subsequently, we incorporated the constitutive equations along with the corresponding values of the mechanical properties - calculated by the fit - to a biomechanical model of tumor growth. Interestingly, we found that the evolution of stress and the growth rate of the tumor are independent from the selection of the constitutive equation, but depend strongly on the mechanical interactions with the surrounding host tissue. Particularly, model predictions - in agreement with experimental studies - suggest that the stiffness of solid tumors should exceed a critical value compared with that of the surrounding tissue in order to be able to displace the tissue and grow in size. With the use of the model, we estimated this critical value to be on the order of 1.5. Our results suggest that the direct effect of solid stress on tumor growth involves not only the inhibitory effect of stress on cancer cell proliferation and the induction of apoptosis, but also the resistance of the surrounding tissue to tumor expansion. PMID:25111061

Identification of Allelic Imbalance with a Statistical Model for Subtle Genomic Mosaicism

PubMed Central

Xia, Rui; Vattathil, Selina; Scheet, Paul

2014-01-01

Genetic heterogeneity in a mixed sample of tumor and normal DNA can confound characterization of the tumor genome. Numerous computational methods have been proposed to detect aberrations in DNA samples from tumor and normal tissue mixtures. Most of these require tumor purities to be at least 10–15%. Here, we present a statistical model to capture information, contained in the individual's germline haplotypes, about expected patterns in the B allele frequencies from SNP microarrays while fully modeling their magnitude, the first such model for SNP microarray data. Our model consists of a pair of hidden Markov models—one for the germline and one for the tumor genome—which, conditional on the observed array data and patterns of population haplotype variation, have a dependence structure induced by the relative imbalance of an individual's inherited haplotypes. Together, these hidden Markov models offer a powerful approach for dealing with mixtures of DNA where the main component represents the germline, thus suggesting natural applications for the characterization of primary clones when stromal contamination is extremely high, and for identifying lesions in rare subclones of a tumor when tumor purity is sufficient to characterize the primary lesions. Our joint model for germline haplotypes and acquired DNA aberration is flexible, allowing a large number of chromosomal alterations, including balanced and imbalanced losses and gains, copy-neutral loss-of-heterozygosity (LOH) and tetraploidy. We found our model (which we term J-LOH) to be superior for localizing rare aberrations in a simulated 3% mixture sample. More generally, our model provides a framework for full integration of the germline and tumor genomes to deal more effectively with missing or uncertain features, and thus extract maximal information from difficult scenarios where existing methods fail. PMID:25166618

Multifractal texture estimation for detection and segmentation of brain tumors.

PubMed

Islam, Atiq; Reza, Syed M S; Iftekharuddin, Khan M

2013-11-01

A stochastic model for characterizing tumor texture in brain magnetic resonance (MR) images is proposed. The efficacy of the model is demonstrated in patient-independent brain tumor texture feature extraction and tumor segmentation in magnetic resonance images (MRIs). Due to complex appearance in MRI, brain tumor texture is formulated using a multiresolution-fractal model known as multifractional Brownian motion (mBm). Detailed mathematical derivation for mBm model and corresponding novel algorithm to extract spatially varying multifractal features are proposed. A multifractal feature-based brain tumor segmentation method is developed next. To evaluate efficacy, tumor segmentation performance using proposed multifractal feature is compared with that using Gabor-like multiscale texton feature. Furthermore, novel patient-independent tumor segmentation scheme is proposed by extending the well-known AdaBoost algorithm. The modification of AdaBoost algorithm involves assigning weights to component classifiers based on their ability to classify difficult samples and confidence in such classification. Experimental results for 14 patients with over 300 MRIs show the efficacy of the proposed technique in automatic segmentation of tumors in brain MRIs. Finally, comparison with other state-of-the art brain tumor segmentation works with publicly available low-grade glioma BRATS2012 dataset show that our segmentation results are more consistent and on the average outperforms these methods for the patients where ground truth is made available.

Multifractal Texture Estimation for Detection and Segmentation of Brain Tumors

PubMed Central

Islam, Atiq; Reza, Syed M. S.

2016-01-01

A stochastic model for characterizing tumor texture in brain magnetic resonance (MR) images is proposed. The efficacy of the model is demonstrated in patient-independent brain tumor texture feature extraction and tumor segmentation in magnetic resonance images (MRIs). Due to complex appearance in MRI, brain tumor texture is formulated using a multiresolution-fractal model known as multifractional Brownian motion (mBm). Detailed mathematical derivation for mBm model and corresponding novel algorithm to extract spatially varying multifractal features are proposed. A multifractal feature-based brain tumor segmentation method is developed next. To evaluate efficacy, tumor segmentation performance using proposed multifractal feature is compared with that using Gabor-like multiscale texton feature. Furthermore, novel patient-independent tumor segmentation scheme is proposed by extending the well-known AdaBoost algorithm. The modification of AdaBoost algorithm involves assigning weights to component classifiers based on their ability to classify difficult samples and confidence in such classification. Experimental results for 14 patients with over 300 MRIs show the efficacy of the proposed technique in automatic segmentation of tumors in brain MRIs. Finally, comparison with other state-of-the art brain tumor segmentation works with publicly available low-grade glioma BRATS2012 dataset show that our segmentation results are more consistent and on the average outperforms these methods for the patients where ground truth is made available. PMID:23807424

Modelling gene expression profiles related to prostate tumor progression using binary states

PubMed Central

2013-01-01

Background Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression. Methods We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random permutated datasets. Results We show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings. Conclusions Results suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies. PMID:23721350

Canine spontaneous glioma: A translational model system for convection-enhanced delivery

PubMed Central

Dickinson, Peter J.; LeCouteur, Richard A.; Higgins, Robert J.; Bringas, John R.; Larson, Richard F.; Yamashita, Yoji; Krauze, Michal T.; Forsayeth, John; Noble, Charles O.; Drummond, Daryl C.; Kirpotin, Dmitri B.; Park, John W.; Berger, Mitchel S.; Bankiewicz, Krystof S.

2010-01-01

Canine spontaneous intracranial tumors bear striking similarities to their human tumor counterparts and have the potential to provide a large animal model system for more realistic validation of novel therapies typically developed in small rodent models. We used spontaneously occurring canine gliomas to investigate the use of convection-enhanced delivery (CED) of liposomal nanoparticles, containing topoisomerase inhibitor CPT-11. To facilitate visualization of intratumoral infusions by real-time magnetic resonance imaging (MRI), we included identically formulated liposomes loaded with Gadoteridol. Real-time MRI defined distribution of infusate within both tumor and normal brain tissues. The most important limiting factor for volume of distribution within tumor tissue was the leakage of infusate into ventricular or subarachnoid spaces. Decreased tumor volume, tumor necrosis, and modulation of tumor phenotype correlated with volume of distribution of infusate (Vd), infusion location, and leakage as determined by real-time MRI and histopathology. This study demonstrates the potential for canine spontaneous gliomas as a model system for the validation and development of novel therapeutic strategies for human brain tumors. Data obtained from infusions monitored in real time in a large, spontaneous tumor may provide information, allowing more accurate prediction and optimization of infusion parameters. Variability in Vd between tumors strongly suggests that real-time imaging should be an essential component of CED therapeutic trials to allow minimization of inappropriate infusions and accurate assessment of clinical outcomes. PMID:20488958

Radiotherapy of meningioma: a treatment in need of radiobiological research.

PubMed

Pinzi, Valentina; Bisogno, Ilaria; Prada, Francesco; Ciusani, Emilio; Fariselli, Laura

2018-05-18

Meningiomas account for one third of primary intracranial tumors, nevertheless information on meningioma cell lines and in vivo models is scant. Although radiotherapy is one of the most relevant therapeutic options for the treatment patients with meningioma, radiobiological research to understand tumor responses to this treatment is far from being thoroughly understood. The aim of this report is to provide a comprehensive picture of the current literature on this field, so as to foster s research in this regard. We carried out a review of meningioma radiobiology based on a peer-reviewed PubMed search. As a result of our study, we can confirm that the main limitation of radiobiological research into meningioma is the paucity of robust in vitro and in vivo models. Alternative approaches to overcome the already identified problems, and to allow better understanding of the entire histopathological spectrum of meningiomas have been explored. A radiobiological perspective of meningioma may help to improve clinical results both in terms of tumour control and healthy tissue sparing. Although we are far from drawing any conclusions, this review can lead researchers to identify some cues for future areas of study.

Novel cancer vaccines prepared by anchoring cytokines to tumor cells avoiding gene transfection

NASA Astrophysics Data System (ADS)

Nizard, Philippe; Gross, David-Alexandre; Chenal, Alexandre; Beaumelle, Bruno; Kosmatopoulos, Konstadinos; Gillet, Daniel

2002-06-01

Cytokines have a strong potential for triggering anticancer immunity if released in the tumor microenvironment. Successful vaccines have been engineered using tumor cells genetically modified to secrete the cytokines. Unfortunately, this approach remains difficult and hazardous to perform in the clinic. We describe a new way of combining cytokines with tumor cells to prepare anticancer vaccines. This consists in anchoring recombinant cytokines to the membrane of killed tumor cells. Attachment is mediated by a fragment of diphtheria toxin (T) genetically connected to the cytokine. It is triggered by an acid pH pulse. The method was applied to IL-2, a potent anti-tumor cytokine. IL-2 anchored to the surface of tumor cells by the T anchor retained its IL-2 activity and remained exposed several days. Interestingly, vaccination of mice with these modified tumor cells induced a protective anti-tumor immunity mediated by tumor-specific cytotoxic T lymphocytes. This procedure presents several advantages as compared to the conventional approaches based on the transfection of tumor cells with cytokine genes. It does not require the culture of tumor cells from the patients and eliminates the safety problems connected with viral vectors while allowing the control of the amount of cytokines delivered with the vaccine.

[Experimental tumors of the central nervous system: standardisation of a model in rats using the 9L glioma cells].

PubMed

Michailowsky, Custódio; Niura, Flavio Key; do Valle, Angela C; Sonohara, Shigueko; Meneguin, Thales D'Alessandro; Tsanaclis, Ana Maria C

2003-06-01

A number of experimental models have been established during the last decades in order to study tumor biology and the effects of treatment or manipulation of the microenvironment of malignant glial tumors. Even though those models have been well characterised and are, to a certain extent, easily reproducible, there are limitations as to their use and to the interpretation of the results. The aim of this study is to standardize a model of a malignant glial tumor and detect possible events able to modify its development. 9L cells were inoculated intracerebrally in 48 Sprague-Dawley rats; from these, 25 animals were also implanted with a device containing electrodes for the registration of the electroencephalogramm. Animals were daily evaluated by neurologic examination. Twenty four animals developed tumor - 10 animals died either in the immediate pos-operatory period or during evolution; 14 animals did not develop tumor. Macroscopically the tumor was well demarcated from the adjacent brain; by light microscopy the tumor exhibited malignant characteristics as well as extensive infiltration of the brain parenchyma. Diagnosis was that of a malignant astrocytoma. The use of the stereotaxic frame and care to infuse a small volume of liquid containing cells during a period of 120 seconds were the most important procedures to obtain sucess in the model. Additional care should be taken in counting cells in the Neubauer camera and in maintaining cells in constant agitation before injecting the tumor-containing solution. The model here developed was efficient besides being of low cost and of relatively easy execution.

Prediction of Therapy Tumor-Absorbed Dose Estimates in I-131 Radioimmunotherapy Using Tracer Data Via a Mixed-Model Fit to Time Activity

PubMed Central

Koral, Kenneth F.; Avram, Anca M.; Kaminski, Mark S.; Dewaraja, Yuni K.

2012-01-01

Abstract Background For individualized treatment planning in radioimmunotherapy (RIT), correlations must be established between tracer-predicted and therapy-delivered absorbed doses. The focus of this work was to investigate this correlation for tumors. Methods The study analyzed 57 tumors in 19 follicular lymphoma patients treated with I-131 tositumomab and imaged with SPECT/CT multiple times after tracer and therapy administrations. Instead of the typical least-squares fit to a single tumor's measured time-activity data, estimation was accomplished via a biexponential mixed model in which the curves from multiple subjects were jointly estimated. The tumor-absorbed dose estimates were determined by patient-specific Monte Carlo calculation. Results The mixed model gave realistic tumor time-activity fits that showed the expected uptake and clearance phases even with noisy data or missing time points. Correlation between tracer and therapy tumor-residence times (r=0.98; p<0.0001) and correlation between tracer-predicted and therapy-delivered mean tumor-absorbed doses (r=0.86; p<0.0001) were very high. The predicted and delivered absorbed doses were within±25% (or within±75 cGy) for 80% of tumors. Conclusions The mixed-model approach is feasible for fitting tumor time-activity data in RIT treatment planning when individual least-squares fitting is not possible due to inadequate sampling points. The good correlation between predicted and delivered tumor doses demonstrates the potential of using a pretherapy tracer study for tumor dosimetry-based treatment planning in RIT. PMID:22947086

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

Opposite Effects of Coinjection and Distant Injection of Mesenchymal Stem Cells on Breast Tumor Cell Growth.

PubMed

Zheng, Huilin; Zou, Weibin; Shen, Jiaying; Xu, Liang; Wang, Shu; Fu, Yang-Xin; Fan, Weimin

2016-09-01

: Mesenchymal stem cells (MSCs) usually promote tumor growth and metastasis. By using a breast tumor 4T1 cell-based animal model, this study determined that coinjection and distant injection of allogeneic bone marrow-derived MSCs with tumor cells could exert different effects on tumor growth. Whereas the coinjection of MSCs with 4T1 cells promoted tumor growth, surprisingly, the injection of MSCs at a site distant from the 4T1 cell inoculation site suppressed tumor growth. We further observed that, in the distant injection model, MSCs decreased the accumulation of myeloid-derived suppressor cells and regulatory T cells in tumor tissues by enhancing proinflammatory factors such as interferon-γ, tumor necrosis factor-α, Toll-like receptor (TLR)-3, and TLR-4, promoting host antitumor immunity and inhibiting tumor growth. Unlike previous reports, this is the first study reporting that MSCs may exert opposite roles on tumor growth in the same animal model by modulating the host immune system, which may shed light on the potential application of MSCs as vehicles for tumor therapy and other clinical applications. Mesenchymal stem cells (MSCs) have been widely investigated for their potential roles in tissue engineering, autoimmune diseases, and tumor therapeutics. This study explored the impact of coinjection and distant injection of allogeneic bone marrow-derived MSCs on mouse 4T1 breast cancer cells. The results showed that the coinjection of MSCs and 4T1 cells promoted tumor growth. MSCs might act as the tumor stromal precursors and cause immunosuppression to protect tumor cells from immunosurveillance, which subsequently facilitated tumor metastasis. Interestingly, the distant injection of MSCs and 4T1 cells suppressed tumor growth. Together, the results of this study revealed the dual functions of MSCs in immunoregulation. ©AlphaMed Press.

TumorML: Concept and requirements of an in silico cancer modelling markup language.

PubMed

Johnson, David; Cooper, Jonathan; McKeever, Steve

2011-01-01

This paper describes the initial groundwork carried out as part of the European Commission funded Transatlantic Tumor Model Repositories project, to develop a new markup language for computational cancer modelling, TumorML. In this paper we describe the motivations for such a language, arguing that current state-of-the-art biomodelling languages are not suited to the cancer modelling domain. We go on to describe the work that needs to be done to develop TumorML, the conceptual design, and a description of what existing markup languages will be used to compose the language specification.

A novel canine model for prostate cancer.

PubMed

Keller, Jill M; Schade, George R; Ives, Kimberly; Cheng, Xu; Rosol, Thomas J; Piert, Morand; Siddiqui, Javed; Roberts, William W; Keller, Evan T

2013-06-01

No existing animal model fully recapitulates all features of human prostate cancer. The dog is the only large mammal, besides humans, that commonly develops spontaneous prostate cancer. Canine prostate cancer features many similarities with its human counterpart. We sought to develop a canine model of prostate cancer that would more fully represent the features of human prostate cancer than existing models. The Ace-1 canine prostate cancer cell line was injected transabdominally under transrectal ultrasound (TRUS) guidance into the prostates of immunosuppressed, intact, adult male dogs. Tumor progression was monitored by TRUS imaging. Some dogs were subjected to positron emission tomography (PET) for tumor detection. Time of euthanasia was determined based on tumor size, impingement on urethra, and general well-being. Euthanasia was followed by necropsy and histopathology. Ace-1 tumor cells grew robustly in every dog injected. Tumors grew in subcapsular and parenchymal regions of the prostate. Tumor tissue could be identified using PET. Histological findings were similar to those observed in human prostate cancer. Metastases to lungs and lymph nodes were detected, predominantly in dogs with intraprostatic tumors. We have established a minimally invasive dog model of prostate cancer. This model may be valuable for studying prostate cancer progression and distant metastasis. Copyright © 2013 Wiley Periodicals, Inc.

Neuropathology of genetically engineered mice: consensus report and recommendations from an international forum.

PubMed

Weiss, William A; Israel, Mark; Cobbs, Charles; Holland, Eric; James, C David; Louis, David N; Marks, Cheryl; McClatchey, Andrea I; Roberts, Tim; Van Dyke, Terry; Wetmore, Cynthia; Chiu, Ing-Ming; Giovannini, Marco; Guha, Abhijit; Higgins, Robert J; Marino, Silvia; Radovanovic, Ivan; Reilly, Karlyne; Aldape, Ken

2002-10-24

The Mouse Models of Cancer Consortium of the NCI sponsored a meeting of neuropathologists and veterinary pathologists in New York City in November of 2000. A rapidly growing number of genetically engineered mice (GEM) predisposed to tumors of the nervous system have led to a concomitant need for neuropathological evaluation and validation of these models. A panel of 13 pathologists reviewed material representing most of the available published and unpublished GEM models of medulloblastoma, primitive neuroectodermal tumor, astrocytoma, oligodendroglioma, mixed glioma, and tumors of the peripheral nerve. The GEM tumors were found to have many similarities and some distinct differences with respect to human disease. After review of the biology and pathology for all models presented, participants were split into groups reflective of clinical expertise in human pathology, tumor biology, neuroimaging, or treatment/intervention. Recommendations were made detailing an extensive and complete neuropathological characterization of animals. Importance was placed on including information on strains, tumor clonality, and examination for genetic mutation or altered gene expression characteristics of the corresponding human malignancy. Specific proposals were made to incorporate GEM models in emerging neuroradiological modalities. Recommendations were also made for preclinical validation of these models in cancer therapeutics, and for incorporation of surrogate markers of tumor burden to facilitate preclinical evaluation of new therapies.

Fractal dimension and universality in avascular tumor growth

NASA Astrophysics Data System (ADS)

Ribeiro, Fabiano L.; dos Santos, Renato Vieira; Mata, Angélica S.

2017-04-01

For years, the comprehension of the tumor growth process has been intriguing scientists. New research has been constantly required to better understand the complexity of this phenomenon. In this paper, we propose a mathematical model that describes the properties, already known empirically, of avascular tumor growth. We present, from an individual-level (microscopic) framework, an explanation of some phenomenological (macroscopic) aspects of tumors, such as their spatial form and the way they develop. Our approach is based on competitive interaction between the cells. This simple rule makes the model able to reproduce evidence observed in real tumors, such as exponential growth in their early stage followed by power-law growth. The model also reproduces (i) the fractal-space distribution of tumor cells and (ii) the universal growth behavior observed in both animals and tumors. Our analyses suggest that the universal similarity between tumor and animal growth comes from the fact that both can be described by the same dynamic equation—the Bertalanffy-Richards model—even if they do not necessarily share the same biological properties.

Synthesis and evaluation of Tc-99m-labeled RRL-containing peptide as a non-invasive tumor imaging agent in a mouse fibrosarcoma model.

PubMed

Kim, Dae-Weung; Kim, Woo Hyoung; Kim, Myoung Hyoun; Kim, Chang Guhn

2015-11-01

Arginine-arginine-leucine (RRL) is considered a tumor endothelial cell-specific binding sequence. RRL-containing peptide targeting tumor vessels is an excellent candidate for tumor imaging. In this study, we developed RRL-containing hexapeptides and evaluated their feasibility as a tumor imaging agent in a HT-1080 fibrosarcoma-bearing murine model. The hexapeptide, glutamic acid-cysteine-glycine (ECG)-RRL was synthesized using Fmoc solid-phase peptide synthesis. Radiolabeling efficiency was evaluated using instant thin-layer chromatography. Uptake of Tc-99m ECG-RRL within HT-1080 cells was evaluated in vitro by confocal microscopy and cellular binding affinity was calculated. Gamma images were acquired In HT-1080 fibrosarcoma tumor-bearing mice, and the tumor-to-muscle uptake ratio was calculated. The inflammatory-to-normal muscle uptake ratio was also calculated in an inflammation mouse model. A biodistribution study was performed to calculate %ID/g. A high yield of Tc-99m ECG-RRL complexes was prepared after Tc-99m radiolabeling. Binding of Tc-99m ECG-RRL to tumor cells had was confirmed by in vitro studies. Gamma camera imaging in the murine model showed that Tc-99m ECG-RRL accumulated substantially in the subcutaneously engrafted tumor and that tumoral uptake was blocked by co-injecting excess RRL. Moreover, Tc-99m ECG-RRL accumulated minimally in inflammatory lesions. We successfully developed Tc-99m ECG-RRL as a new tumor imaging candidate. Specific tumoral uptake of Tc-99m ECG-RRL was evaluated both in vitro and in vivo, and it was determined to be a good tumor imaging candidate. Additionally, Tc-99m ECG-RRL effectively distinguished between cancerous tissue and inflammatory lesions.

EFFECTS OF IRRADIATION ON BRAIN VASCULATURE USING AN IN SITU TUMOR MODEL

PubMed Central

Zawaski, Janice A.; Gaber, M. Waleed; Sabek, Omaima M.; Wilson, Christy M.; Duntsch, Christopher D.; Merchant, Thomas E.

2013-01-01

Purpose Damage to normal tissue is a limiting factor in clinical radiotherapy (RT). We tested the hypothesis that the presence of tumor alters the response of normal tissues to irradiation using a rat in situ brain tumor model. Methods and Materials Intravital microscopy was used with a rat cranial window to assess the in situ effect of rat C6 glioma on peritumoral tissue with and without RT. The RT regimen included 40 Gy at 8 Gy/day starting Day 5 after tumor implant. Endpoints included blood–brain barrier permeability, clearance index, leukocyte-endothelial interactions and staining for vascular endothelial growth factor (VEGF) glial fibrillary acidic protein, and apoptosis. To characterize the system response to RT, animal survival and tumor surface area and volume were measured. Sham experiments were performed on similar animals implanted with basement membrane matrix absent of tumor cells. Results The presence of tumor alone increases permeability but has little effect on leukocyte–endothelial interactions and astrogliosis. Radiation alone increases tissue permeability, leukocyte-endothelial interactions, and astrogliosis. The highest levels of permeability and cell adhesion were seen in the model that combined tumor and irradiation; however, the presence of tumor appeared to reduce the volume of rolling leukocytes. Unirradiated tumor and peritumoral tissue had poor clearance. Irradiated tumor and peritumoral tissue had a similar clearance index to irradiated and unirradiated sham-implanted animals. Radiation reduces the presence of VEGF in peritumoral normal tissues but did not affect the amount of apoptosis in the normal tissue. Apoptosis was identified in the tumor tissue with and without radiation. Conclusions We developed a novel approach to demonstrate that the presence of the tumor in a rat intracranial model alters the response of normal tissues to irradiation. PMID:22197233

Tumor growth model for atlas based registration of pathological brain MR images

NASA Astrophysics Data System (ADS)

Moualhi, Wafa; Ezzeddine, Zagrouba

2015-02-01

The motivation of this work is to register a tumor brain magnetic resonance (MR) image with a normal brain atlas. A normal brain atlas is deformed in order to take account of the presence of a large space occupying tumor. The method use a priori model of tumor growth assuming that the tumor grows in a radial way from a starting point. First, an affine transformation is used in order to bring the patient image and the brain atlas in a global correspondence. Second, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed combining a method derived from optical flow principles and a model for tumor growth (MTG). Results show that an automatic segmentation method of brain structures in the presence of large deformation can be provided.

A deterministic and stochastic model for the system dynamics of tumor-immune responses to chemotherapy

NASA Astrophysics Data System (ADS)

Liu, Xiangdong; Li, Qingze; Pan, Jianxin

2018-06-01

Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.

Immunosuppression Enhances Oncolytic Adenovirus Replication and Antitumor Efficacy in the Syrian Hamster Model

PubMed Central

Thomas, Maria A; Spencer, Jacqueline F; Toth, Karoly; Sagartz, John E; Phillips, Nancy J; Wold, William SM

2012-01-01

We recently described an immunocompetent Syrian hamster model for oncolytic adenoviruses (Ads) that permits virus replication in tumor cells as well as some normal tissues. This model allows exploration of interactions between the virus, tumor, normal organs, and host immune system that could not be examined in the immunodeficient or nonpermissive animal models previously used in the oncolytic Ad field. Here we asked whether the immune response to oncolytic Ad enhances or limits antitumor efficacy. We first determined that cyclophosphamide (CP) is a potent immunosuppressive agent in the Syrian hamster and that CP alone had no effect on tumor growth. Importantly, we found that the antitumor efficacy of oncolytic Ads was significantly enhanced in immunosuppressed animals. In animals that received virus therapy plus immunosuppression, significant differences were observed in tumor histology, and in many cases little viable tumor remained. Notably, we also determined that immunosuppression allowed intratumoral virus levels to remain elevated for prolonged periods. Although favorable tumor responses can be achieved in immunocompetent animals, the rate of virus clearance from the tumor may lead to varied antitumor efficacy. Immunosuppression, therefore, allows sustained Ad replication and oncolysis, which leads to substantially improved suppression of tumor growth. PMID:18665155

Characterization of patient-derived tumor xenografts (PDXs) as models for estrogen receptor positive (ER+HER2- and ER+HER2+) breast cancers.

PubMed

Kanaya, Noriko; Somlo, George; Wu, Jun; Frankel, Paul; Kai, Masaya; Liu, Xueli; Wu, Shang Victoria; Nguyen, Duc; Chan, Nymph; Hsieh, Meng-Yin; Kirschenbaum, Michele; Kruper, Laura; Vito, Courtney; Badie, Behnam; Yim, John H; Yuan, Yuan; Hurria, Arti; Peiguo, Chu; Mortimer, Joanne; Chen, Shiuan

2017-06-01

The research was to appraise the utility of the patient-derived tumor xenografts (PDXs) as models of estrogen receptor positive (ER+HER2- and ER+HER2+) breast cancers. We compared protein expression profiles by Reverse Phase Protein Array (RPPA) in tumors that resulted in PDXs compared to those that did not. Our overall PDX intake rate for ER+ breast cancer was 9% (9/97). The intake rate for ER+HER2+ tumors (3/16, 19%) was higher than for ER+HER2- tumors (6/81, 7%). Heat map analyses of RPPA data showed that ER+HER2- tumors were divided into 2 groups by luminal A/B signature [protein expression of ER, AR, Bcl-2, Bim (BCL2L11), GATA3 and INPP4b], and this expression signature was also associated with the rate of PDX intake. Cell survival pathways such as the PI3K/AKT signaling and RAS/ERK pathways were more activated in the specimens that could be established as PDX in both classes. Expression of the ER protein itself may have a bearing on the potential success of an ER+ PDX model. In addition, HER2 and its downstream protein expressions were up-regulated in the ER+HER2+ patient tumors that were successfully established as PDX models. Moreover, the comparison of RPPA data between original and PDX tumors suggested that the selection/adaptation process required to grow the tumors in mice is unavoidable for generation of ER+ PDX models, and we identified differences between patient tumor samples and paired PDX tumors. A better understanding of the biological characteristics of ER+PDX would be the key to using PDX models in assessing treatment strategies in a preclinical setting. Copyright © 2016 Elsevier Ltd. All rights reserved.

WE-AB-204-07: Spatiotemporal Distribution of the FDG PET Tracer in Solid Tumors: Contributions of Diffusion and Convection Mechanisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soltani, M; Sefidgar, M; Bazmara, H

2015-06-15

Purpose: In this study, a mathematical model is utilized to simulate FDG distribution in tumor tissue. In contrast to conventional compartmental modeling, tracer distributions across space and time are directly linked together (i.e. moving beyond ordinary differential equations (ODEs) to utilizing partial differential equations (PDEs) coupling space and time). The diffusion and convection transport mechanisms are both incorporated to model tracer distribution. We aimed to investigate the contributions of these two mechanisms on FDG distribution for various tumor geometries obtained from PET/CT images. Methods: FDG transport was simulated via a spatiotemporal distribution model (SDM). The model is based on amore » 5K compartmental model. We model the fact that tracer concentration in the second compartment (extracellular space) is modulated via convection and diffusion. Data from n=45 patients with pancreatic tumors as imaged using clinical FDG PET/CT imaging were analyzed, and geometrical information from the tumors including size, shape, and aspect ratios were classified. Tumors with varying shapes and sizes were assessed in order to investigate the effects of convection and diffusion mechanisms on FDG transport. Numerical methods simulating interstitial flow and solute transport in tissue were utilized. Results: We have shown the convection mechanism to depend on the shape and size of tumors whereas diffusion mechanism is seen to exhibit low dependency on shape and size. Results show that concentration distribution of FDG is relatively similar for the considered tumors; and that the diffusion mechanism of FDG transport significantly dominates the convection mechanism. The Peclet number which shows the ratio of convection to diffusion rates was shown to be of the order of 10−{sup 3} for all considered tumors. Conclusion: We have demonstrated that even though convection leads to varying tracer distribution profiles depending on tumor shape and size, the domination of the diffusion phenomenon prevents these factors from modulating FDG distribution.« less

Deriving Therapies for Children with Primary CNS Tumors Using Pharmacokinetic Modeling and Simulation of Cerebral Microdialysis Data

PubMed Central

Jacus, M.O.; Throm, S.L.; Turner, D.C.; Patel, Y.T.; Freeman, B.B.; Morfouace, M.; Boulos, N.; Stewart, C. F.

2014-01-01

The treatment of children with primary central nervous system (CNS) tumors continues to be a challenge despite recent advances in technology and diagnostics. In this overview, we describe our approach for identifying and evaluating active anticancer drugs through a process that enables rational translation from the lab to the clinic. The preclinical approach we discuss uses tumor subgroup-specific models of pediatric CNS tumors, cerebral microdialysis sampling of tumor extracellular fluid (tECF), and pharmacokinetic modeling and simulation to overcome challenges that currently hinder researchers in this field. This approach involves performing extensive systemic (plasma) and target site (CNS tumor) pharmacokinetic studies. Pharmacokinetic modeling and simulation of the data derived from these studies are then used to inform future decisions regarding drug administration, including dosage and schedule. Here, we also present how our approach was used to examine two FDA approved drugs, simvastatin and pemetrexed, as candidates for new therapies for pediatric CNS tumors. We determined that due to unfavorable pharmacokinetic characteristics and insufficient concentrations in tumor tissue in a mouse model of ependymoma, simvastatin would not be efficacious in further preclinical trials. In contrast to simvastatin, pemetrexed was advanced to preclinical efficacy studies after our studies determined that plasma exposures were similar to those in humans treated at similar tolerable dosages and adequate unbound concentrations were found in tumor tissue of medulloblastoma-bearing mice. Generally speaking, the high clinical failure rates for CNS drug candidates can be partially explained by the fact that therapies are often moved into clinical trials without extensive and rational preclinical studies to optimize the transition. Our approach addresses this limitation by using pharmacokinetic and pharmacodynamic modeling of data generated from appropriate in vivo models to support the rational testing and usage of innovative therapies in children with CNS tumors. PMID:24269626

Role of Smac in Lung Carcinogenesis and Therapy

DTIC Science & Technology

2017-07-01

tumor regression mediated by TNF-α as shown below. Debio 1143 enhances the efficacy of anti-PD1and increases tumor- infiltrating lymphocytes...agents in both tumor models, as measured by tumor volumes. Tumor infiltrating lymphocytes (TILs) were significantly increased in tumors treated with

Cancer-specific health-related quality of life in children with brain tumors.

PubMed

Sato, Iori; Higuchi, Akiko; Yanagisawa, Takaaki; Mukasa, Akitake; Ida, Kohmei; Sawamura, Yutaka; Sugiyama, Kazuhiko; Saito, Nobuhito; Kumabe, Toshihiro; Terasaki, Mizuhiko; Nishikawa, Ryo; Ishida, Yasushi; Kamibeppu, Kiyoko

2014-05-01

To understand the influence of disease and treatment on the health-related quality of life (HRQOL) of children with brain tumors, compared to the HRQOL of children with other cancers, from the viewpoints of children and parents. A total of 133 children aged 5-18 years and 165 parents of children aged 2-18 completed questionnaires of the Pediatric Quality of Life Inventory Cancer Module (Pain and Hurt, Nausea, Procedural Anxiety, Treatment Anxiety, Worry, Cognitive Problems, Perceived Physical Appearance, and Communication scales); higher scores indicate a better HRQOL. The Cancer Module scores, weighted by age and treatment status, were compared to those obtained in a previous study of children with other cancers (mostly leukemia). The weighted mean scores for Pain and Hurt (effect size d = 0.26) and Nausea (d = 0.23) from child reports and the scores for Nausea (d = 0.28) from parent reports were higher for children with brain tumors than scores for children with other cancers. The scores for Procedural Anxiety (d = -0.22) and Treatment Anxiety (d = -0.32) from parent reports were lower for parents of children with brain tumors than the scores for parents of children with other cancers. The child-reported Pain and Hurt score of the Cancer Module was higher (d = 0.29) and in less agreement (intraclass correlation coefficient = 0.43) with scores from the Brain Tumor Module, indicating that assessments completed with the Cancer Module misesteem pain and hurt problems in children with brain tumors. The profiles of cancer-specific HRQOL in children with brain tumors differ from those of children with other cancers; we therefore suggest that these children receive specific psychological support.

Quantum Dots for Molecular Diagnostics of Tumors

PubMed Central

Zdobnova, T.A.; Lebedenko, E.N.; Deyev, S.М.

2011-01-01

Semiconductor quantum dots (QDs) are a new class of fluorophores with unique physical and chemical properties, which allow to appreciably expand the possibilities for the current methods of fluorescent imaging and optical diagnostics. Here we discuss the prospects of QD application for molecular diagnostics of tumors ranging from cancer-specific marker detection on microplates to non-invasive tumor imagingin vivo. We also point out the essential problems that require resolution in order to clinically promote QD, and we indicate innovative approaches to oncology which are implementable using QD. PMID:22649672

How I Manage Breast Problems in Athletes.

PubMed

Haycock, C E

1987-03-01

In brief: Although breast problems usually are associated with women, men have them also. This paper reviews the anatomy of the breast and describes injuries and disorders that occur in both men and women, including runner's nipples, tumors, and trauma (common in contact and racket sports). The author also discusses management of these problems and describes various types of sports bras.

Optical time-of-flight and absorbance imaging of biologic media.

PubMed

Benaron, D A; Stevenson, D K

1993-03-05

Imaging the interior of living bodies with light may assist in the diagnosis and treatment of a number of clinical problems, which include the early detection of tumors and hypoxic cerebral injury. An existing picosecond time-of-flight and absorbance (TOFA) optical system has been used to image a model biologic system and a rat. Model measurements confirmed TOFA principles in systems with a high degree of photon scattering; rat images, which were constructed from the variable time delays experienced by a fixed fraction of early-arriving transmitted photons, revealed identifiable internal structure. A combination of light-based quantitative measurement and TOFA localization may have applications in continuous, noninvasive monitoring for structural imaging and spatial chemometric analysis in humans.

Optical Time-of-Flight and Absorbance Imaging of Biologic Media

NASA Astrophysics Data System (ADS)

Benaron, David A.; Stevenson, David K.

1993-03-01

Imaging the interior of living bodies with light may assist in the diagnosis and treatment of a number of clinical problems, which include the early detection of tumors and hypoxic cerebral injury. An existing picosecond time-of-flight and absorbance (TOFA) optical system has been used to image a model biologic system and a rat. Model measurements confirmed TOFA principles in systems with a high degree of photon scattering; rat images, which were constructed from the variable time delays experienced by a fixed fraction of early-arriving transmitted photons, revealed identifiable internal structure. A combination of light-based quantitative measurement and TOFA localization may have applications in continuous, noninvasive monitoring for structural imaging and spatial chemometric analysis in humans.

Investigation of Tumor Cell Behaviors on a Vascular Microenvironment-Mimicking Microfluidic Chip

PubMed Central

Huang, Rong; Zheng, Wenfu; Liu, Wenwen; Zhang, Wei; Long, Yunze; Jiang, Xingyu

2015-01-01

The extravasation of tumor cells is a key event in tumor metastasis. However, the mechanism underlying tumor cell extravasation remains unknown, mainly hindered by obstacles from the lack of complexity of biological tissues in conventional cell culture, and the costliness and ethical issues of in vivo experiments. Thus, a cheap, time and labor saving, and most of all, vascular microenvironment-mimicking research model is desirable. Herein, we report a microfluidic chip-based tumor extravasation research model which is capable of simultaneously simulating both mechanical and biochemical microenvironments of human vascular systems and analyzing their synergistic effects on the tumor extravasation. Under different mechanical conditions of the vascular system, the tumor cells (HeLa cells) had the highest viability and adhesion activity in the microenvironment of the capillary. The integrity of endothelial cells (ECs) monolayer was destroyed by tumor necrosis factor-α (TNF-α) in a hemodynamic background, which facilitated the tumor cell adhesion, this situation was recovered by the administration of platinum nanoparticles (Pt-NPs). This model bridges the gap between cell culture and animal experiments and is a promising platform for studying tumor behaviors in the vascular system. PMID:26631692

Molecular Characterization of Growth Hormone-producing Tumors in the GC Rat Model of Acromegaly.

PubMed

Martín-Rodríguez, Juan F; Muñoz-Bravo, Jose L; Ibañez-Costa, Alejandro; Fernandez-Maza, Laura; Balcerzyk, Marcin; Leal-Campanario, Rocío; Luque, Raúl M; Castaño, Justo P; Venegas-Moreno, Eva; Soto-Moreno, Alfonso; Leal-Cerro, Alfonso; Cano, David A

2015-11-09

Acromegaly is a disorder resulting from excessive production of growth hormone (GH) and consequent increase of insulin-like growth factor 1 (IGF-I), most frequently caused by pituitary adenomas. Elevated GH and IGF-I levels results in wide range of somatic, cardiovascular, endocrine, metabolic, and gastrointestinal morbidities. Subcutaneous implantation of the GH-secreting GC cell line in rats leads to the formation of tumors. GC tumor-bearing rats develop characteristics that resemble human acromegaly including gigantism and visceromegaly. However, GC tumors remain poorly characterized at a molecular level. In the present work, we report a detailed histological and molecular characterization of GC tumors using immunohistochemistry, molecular biology and imaging techniques. GC tumors display histopathological and molecular features of human GH-producing tumors, including hormone production, cell architecture, senescence activation and alterations in cell cycle gene expression. Furthermore, GC tumors cells displayed sensitivity to somatostatin analogues, drugs that are currently used in the treatment of human GH-producing adenomas, thus supporting the GC tumor model as a translational tool to evaluate therapeutic agents. The information obtained would help to maximize the usefulness of the GC rat model for research and preclinical studies in GH-secreting tumors.

Molecular Characterization of Growth Hormone-producing Tumors in the GC Rat Model of Acromegaly

PubMed Central

Martín-Rodríguez, Juan F.; Muñoz-Bravo, Jose L.; Ibañez-Costa, Alejandro; Fernandez-Maza, Laura; Balcerzyk, Marcin; Leal-Campanario, Rocío; Luque, Raúl M.; Castaño, Justo P.; Venegas-Moreno, Eva; Soto-Moreno, Alfonso; Leal-Cerro, Alfonso; Cano, David A.

2015-01-01

Acromegaly is a disorder resulting from excessive production of growth hormone (GH) and consequent increase of insulin-like growth factor 1 (IGF-I), most frequently caused by pituitary adenomas. Elevated GH and IGF-I levels results in wide range of somatic, cardiovascular, endocrine, metabolic, and gastrointestinal morbidities. Subcutaneous implantation of the GH-secreting GC cell line in rats leads to the formation of tumors. GC tumor-bearing rats develop characteristics that resemble human acromegaly including gigantism and visceromegaly. However, GC tumors remain poorly characterized at a molecular level. In the present work, we report a detailed histological and molecular characterization of GC tumors using immunohistochemistry, molecular biology and imaging techniques. GC tumors display histopathological and molecular features of human GH-producing tumors, including hormone production, cell architecture, senescence activation and alterations in cell cycle gene expression. Furthermore, GC tumors cells displayed sensitivity to somatostatin analogues, drugs that are currently used in the treatment of human GH-producing adenomas, thus supporting the GC tumor model as a translational tool to evaluate therapeutic agents. The information obtained would help to maximize the usefulness of the GC rat model for research and preclinical studies in GH-secreting tumors. PMID:26549306

Multifractal modeling, segmentation, prediction, and statistical validation of posterior fossa tumors

NASA Astrophysics Data System (ADS)

Islam, Atiq; Iftekharuddin, Khan M.; Ogg, Robert J.; Laningham, Fred H.; Sivakumar, Bhuvaneswari

2008-03-01

In this paper, we characterize the tumor texture in pediatric brain magnetic resonance images (MRIs) and exploit these features for automatic segmentation of posterior fossa (PF) tumors. We focus on PF tumor because of the prevalence of such tumor in pediatric patients. Due to varying appearance in MRI, we propose to model the tumor texture with a multi-fractal process, such as a multi-fractional Brownian motion (mBm). In mBm, the time-varying Holder exponent provides flexibility in modeling irregular tumor texture. We develop a detailed mathematical framework for mBm in two-dimension and propose a novel algorithm to estimate the multi-fractal structure of tissue texture in brain MRI based on wavelet coefficients. This wavelet based multi-fractal feature along with MR image intensity and a regular fractal feature obtained using our existing piecewise-triangular-prism-surface-area (PTPSA) method, are fused in segmenting PF tumor and non-tumor regions in brain T1, T2, and FLAIR MR images respectively. We also demonstrate a non-patient-specific automated tumor prediction scheme based on these image features. We experimentally show the tumor discriminating power of our novel multi-fractal texture along with intensity and fractal features in automated tumor segmentation and statistical prediction. To evaluate the performance of our tumor prediction scheme, we obtain ROCs and demonstrate how sharply the curves reach the specificity of 1.0 sacrificing minimal sensitivity. Experimental results show the effectiveness of our proposed techniques in automatic detection of PF tumors in pediatric MRIs.

Monitoring the development of xenograft triple-negative breast cancer models using diffusion-weighted magnetic resonance imaging.

PubMed

Stephen, Renu M; Pagel, Mark D; Brown, Kathy; Baker, Amanda F; Meuillet, Emmanuelle J; Gillies, Robert J

2012-11-01

Evaluations of tumor growth rates and molecular biomarkers are traditionally used to assess new mouse models of human breast cancers. This study investigated the utility of diffusion weighted (DW)-magnetic resonance imaging (MRI) for evaluating cellular proliferation of new tumor models of triple-negative breast cancer, which may augment traditional analysis methods. Eleven human breast cancer cell lines were used to develop xenograft tumors in severe combined immunodeficient mice, with two of these cell lines exhibiting sufficient growth to be serially passaged. DW-MRI was performed to measure the distributions of the apparent diffusion coefficient (ADC) in these two tumor xenograft models, which showed a correlation with tumor growth rates and doubling times during each passage. The distributions of the ADC values were also correlated with expression of Ki67, a biomarker of cell proliferation, and hypoxia inducible factor (HIF)-1α and vascular endothelial growth factor receptor-2 (VEGFR2), which are essential proteins involved in regulating aerobic glycolysis and angiogenesis that support tumor cell proliferation. Although phosphatase and tensin homolog (PTEN) levels were different between the two xenograft models, AKT levels did not differ nor did they correlate with tumor growth. This last result demonstrates the complexity of signaling protein pathways and the difficulty in interpreting the effects of protein expression on tumor cell proliferation. In contrast, DW-MRI may be a more direct assessment of tumor growth and cancer cell proliferation.

Olaratumab Exerts Antitumor Activity in Preclinical Models of Pediatric Bone and Soft Tissue Tumors through Inhibition of Platelet-Derived Growth Factor Receptor α.

PubMed

Lowery, Caitlin D; Blosser, Wayne; Dowless, Michele; Knoche, Shelby; Stephens, Jennifer; Li, Huiling; Surguladze, David; Loizos, Nick; Luffer-Atlas, Debra; Oakley, Gerard J; Guo, Qianxu; Iyer, Seema; Rubin, Brian P; Stancato, Louis

2018-02-15

Purpose: Platelet-derived growth factor receptor α (PDGFRα) is implicated in several adult and pediatric malignancies, where activated signaling in tumor cells and/or cells within the microenvironment drive tumorigenesis and disease progression. Olaratumab (LY3012207/IMC-3G3) is a human mAb that exclusively binds to PDGFRα and recently received accelerated FDA approval and conditional EMA approval for treatment of advanced adult sarcoma patients in combination with doxorubicin. In this study, we investigated olaratumab in preclinical models of pediatric bone and soft tissue tumors. Experimental Design: PDGFRα expression was evaluated by qPCR and Western blot analysis. Olaratumab was investigated in in vitro cell proliferation and invasion assays using pediatric osteosarcoma and rhabdoid tumor cell lines. In vivo activity of olaratumab was assessed in preclinical mouse models of pediatric osteosarcoma and malignant rhabdoid tumor. Results: In vitro olaratumab treatment of osteosarcoma and rhabdoid tumor cell lines reduced proliferation and inhibited invasion driven by individual platelet-derived growth factors (PDGFs) or serum. Furthermore, olaratumab delayed primary tumor growth in mouse models of pediatric osteosarcoma and malignant rhabdoid tumor, and this activity was enhanced by combination with either doxorubicin or cisplatin. Conclusions: Overall, these data indicate that olaratumab, alone and in combination with standard of care, blocks the growth of some preclinical PDGFRα-expressing pediatric bone and soft tissue tumor models. Clin Cancer Res; 24(4); 847-57. ©2017 AACR . ©2017 American Association for Cancer Research.

A switching control law approach for cancer immunotherapy of an evolutionary tumor growth model.

PubMed

Doban, Alina I; Lazar, Mircea

2017-02-01

We propose a new approach for tumor immunotherapy which is based on a switching control strategy defined on domains of attraction of equilibria of interest. For this, we consider a recently derived model which captures the effects of the tumor cells on the immune system and viceversa, through predator-prey competition terms. Additionally, it incorporates the immune system's mechanism for producing hunting immune cells, which makes the model suitable for immunotherapy strategies analysis and design. For computing domains of attraction for the tumor nonlinear dynamics, and thus, for deriving immunotherapeutic strategies we employ rational Lyapunov functions. Finally, we apply the switching control strategy to destabilize an invasive tumor equilibrium and steer the system trajectories to tumor dormancy. Copyright © 2016 Elsevier Inc. All rights reserved.

Combination Therapy with NHS-muIL12 and Avelumab (anti-PD-L1) Enhances Antitumor Efficacy in Preclinical Cancer Models.

PubMed

Xu, Chunxiao; Zhang, Yanping; Rolfe, P Alexander; Hernández, Vivian M; Guzman, Wilson; Kradjian, Giorgio; Marelli, Bo; Qin, Guozhong; Qi, Jin; Wang, Hong; Yu, Huakui; Tighe, Robert; Lo, Kin-Ming; English, Jessie M; Radvanyi, Laszlo; Lan, Yan

2017-10-01

Purpose: To determine whether combination therapy with NHS-muIL12 and the anti-programmed death ligand 1 (PD-L1) antibody avelumab can enhance antitumor efficacy in preclinical models relative to monotherapies. Experimental Design: BALB/c mice bearing orthotopic EMT-6 mammary tumors and μMt - mice bearing subcutaneous MC38 tumors were treated with NHS-muIL12, avelumab, or combination therapy; tumor growth and survival were assessed. Tumor recurrence following remission and rechallenge was evaluated in EMT-6 tumor-bearing mice. Immune cell populations within spleen and tumors were evaluated by FACS and IHC. Immune gene expression in tumor tissue was profiled by NanoString® assay and plasma cytokine levels were determined by multiplex cytokine assay. The frequency of tumor antigen-reactive IFNγ-producing CD8 + T cells was evaluated by ELISpot assay. Results: NHS-muIL12 and avelumab combination therapy enhanced antitumor efficacy relative to either monotherapy in both tumor models. Most EMT-6 tumor-bearing mice treated with combination therapy had complete tumor regression. Combination therapy also induced the generation of tumor-specific immune memory, as demonstrated by protection against tumor rechallenge and induction of effector and memory T cells. Combination therapy enhanced cytotoxic NK and CD8 + T-cell proliferation and T-bet expression, whereas NHS-muIL12 monotherapy induced CD8 + T-cell infiltration into the tumor. Combination therapy also enhanced plasma cytokine levels and stimulated expression of a greater number of innate and adaptive immune genes compared with either monotherapy. Conclusions: These data indicate that combination therapy with NHS-muIL12 and avelumab increased antitumor efficacy in preclinical models, and suggest that combining NHS-IL12 and avelumab may be a promising approach to treating patients with solid tumors. Clin Cancer Res; 23(19); 5869-80. ©2017 AACR . ©2017 American Association for Cancer Research.

Potent Antitumor Effects of Combination Therapy With IFNs and Monocytes in Mouse Models of Established Human Ovarian and Melanoma Tumors

PubMed Central

Nakashima, Hideyuki; Miyake, Kotaro; Clark, Christopher R; Bekisz, Joseph; Finbloom, Joel; Husain, Syed R.; Baron, Samuel; Puri, Raj K.; Zoon, Kathryn C.

2012-01-01

Interferon-activated monocytes are known to exert cytocidal activity against tumor cells in vitro. Here, we have examined whether a combination of IFN-α2a and IFN-γ and human monocytes mediate significant antitumor effects against human ovarian and melanoma tumor xenografts in mouse models. OVCAR-3 tumors were treated i.t. with monocytes alone, IFN-α2a and IFN-γ alone or combination of all three on day 0, 15 or 30 post-tumor implantation. Mice receiving combination therapy beginning day 15 showed significantly reduced tumor growth and prolonged survival including complete regression in 40% mice., Tumor volumes measured on day 80 in mice receiving combination therapy (206 mm3) were significantly smaller than those of mice receiving the IFNs alone (1041 mm3), monocytes alone (1111 mm3) or untreated controls (1728 mm3). Similarly, combination therapy with monocytes and IFNs of much larger tumor also inhibited OVCAR-3 tumor growth. Immunohistochemistry studies showed a large number of activated macrophages (CD31+/CD68+) infiltrating into OVCAR-3 tumors and higher densities of IL-12, IP10 and NOS2, markers of M1 (classical) macrophages in tumors treated with combination therapy compared to the controls. Interestingly, IFNs activated macrophages induced apoptosis of OVCAR-3 tumor cells as monocytes alone or IFNs alone did not mediate significant apoptosis. Similar antitumor activity was observed in the LOX melanoma mouse model, but not as profound as seen with the OVCAR-3 tumors. Administration of either mixture of monocytes and IFN-α2a or monocytes and IFN-γ did not inhibit Lox melanoma growth; however a significant inhibition was observed when tumors were treated with a mixture of monocytes, IFN-α2a and IFN-γ. These results indicate that monocytes and both IFN-α2a and IFN-γ may be required to mediate profound antitumor effect against human ovarian and melanoma tumors in mouse models. PMID:22159517

A multiphase model for three-dimensional tumor growth

NASA Astrophysics Data System (ADS)

Sciumè, G.; Shelton, S.; Gray, W. G.; Miller, C. T.; Hussain, F.; Ferrari, M.; Decuzzi, P.; Schrefler, B. A.

2013-01-01

Several mathematical formulations have analyzed the time-dependent behavior of a tumor mass. However, most of these propose simplifications that compromise the physical soundness of the model. Here, multiphase porous media mechanics is extended to model tumor evolution, using governing equations obtained via the thermodynamically constrained averaging theory. A tumor mass is treated as a multiphase medium composed of an extracellular matrix (ECM); tumor cells (TCs), which may become necrotic depending on the nutrient concentration and tumor phase pressure; healthy cells (HCs); and an interstitial fluid for the transport of nutrients. The equations are solved by a finite element method to predict the growth rate of the tumor mass as a function of the initial tumor-to-healthy cell density ratio, nutrient concentration, mechanical strain, cell adhesion and geometry. Results are shown for three cases of practical biological interest such as multicellular tumor spheroids (MTSs) and tumor cords. First, the model is validated by experimental data for time-dependent growth of an MTS in a culture medium. The tumor growth pattern follows a biphasic behavior: initially, the rapidly growing TCs tend to saturate the volume available without any significant increase in overall tumor size; then, a classical Gompertzian pattern is observed for the MTS radius variation with time. A core with necrotic cells appears for tumor sizes larger than 150 μm, surrounded by a shell of viable TCs whose thickness stays almost constant with time. A formula to estimate the size of the necrotic core is proposed. In the second case, the MTS is confined within a healthy tissue. The growth rate is reduced, as compared to the first case—mostly due to the relative adhesion of the TCs and HCs to the ECM, and the less favorable transport of nutrients. In particular, for HCs adhering less avidly to the ECM, the healthy tissue is progressively displaced as the malignant mass grows, whereas TC infiltration is predicted for the opposite condition. Interestingly, the infiltration potential of the tumor mass is mostly driven by the relative cell adhesion to the ECM. In the third case, a tumor cord model is analyzed where the malignant cells grow around microvessels in a three-dimensional geometry. It is shown that TCs tend to migrate among adjacent vessels seeking new oxygen and nutrients. This model can predict and optimize the efficacy of anticancer therapeutic strategies. It can be further developed to answer questions on tumor biophysics, related to the effects of ECM stiffness and cell adhesion on TC proliferation.

Establishment of a patient-derived orthotopic osteosarcoma mouse model.

PubMed

Blattmann, Claudia; Thiemann, Markus; Stenzinger, Albrecht; Roth, Eva K; Dittmar, Anne; Witt, Hendrik; Lehner, Burkhard; Renker, Eva; Jugold, Manfred; Eichwald, Viktoria; Weichert, Wilko; Huber, Peter E; Kulozik, Andreas E

2015-04-30

Osteosarcoma (OS) is the most common pediatric primary malignant bone tumor. As the prognosis for patients following standard treatment did not improve for almost three decades, functional preclinical models that closely reflect important clinical cancer characteristics are urgently needed to develop and evaluate new treatment strategies. The objective of this study was to establish an orthotopic xenotransplanted mouse model using patient-derived tumor tissue. Fresh tumor tissue from an adolescent female patient with osteosarcoma after relapse was surgically xenografted into the right tibia of 6 immunodeficient BALB/c Nu/Nu mice as well as cultured into medium. Tumor growth was serially assessed by palpation and with magnetic resonance imaging (MRI). In parallel, a primary cell line of the same tumor was established. Histology and high-resolution array-based comparative genomic hybridization (aCGH) were used to investigate both phenotypic and genotypic characteristics of different passages of human xenografts and the cell line compared to the tissue of origin. A primary OS cell line and a primary patient-derived orthotopic xenotranplanted mouse model were established. MRI analyses and histopathology demonstrated an identical architecture in the primary tumor and in the xenografts. Array-CGH analyses of the cell line and all xenografts showed highly comparable patterns of genomic progression. So far, three further primary patient-derived orthotopic xenotranplanted mouse models could be established. We report the first orthotopic OS mouse model generated by transplantation of tumor fragments directly harvested from the patient. This model represents the morphologic and genomic identity of the primary tumor and provides a preclinical platform to evaluate new treatment strategies in OS.

Modeling and predicting tumor response in radioligand therapy.

PubMed

Kletting, Peter; Thieme, Anne; Eberhardt, Nina; Rinscheid, Andreas; D'Alessandria, Calogero; Allmann, Jakob; Wester, Hans-Jürgen; Tauber, Robert; Beer, Ambros J; Glatting, Gerhard; Eiber, Matthias

2018-05-10

The aim of this work was to develop a theranostic method that allows predicting PSMA-positive tumor volume after radioligand therapy (RLT) based on a pre-therapeutic PET/CT measurement and physiologically based pharmacokinetic/dynamic (PBPK/PD) modeling at the example of RLT using 177 Lu-labeled PSMA for imaging and therapy (PSMA I&T). Methods: A recently developed PBPK model for 177 Lu PSMA I&T RLT was extended to account for tumor (exponential) growth and reduction due to irradiation (linear quadratic model). Data of 13 patients with metastatic castration-resistant prostate cancer (mCRPC) were retrospectively analyzed. Pharmacokinetic/dynamic parameters were simultaneously fitted in a Bayesian framework to PET/CT activity concentrations, planar scintigraphy data and tumor volumes prior and post (6 weeks) therapy. The method was validated using the leave-one-out Jackknife method. The tumor volume post therapy was predicted based on pre-therapy PET/CT imaging and PBPK/PD modeling. Results: The relative deviation of the predicted and measured tumor volume for PSMA-positive tumor cells (6 weeks post therapy) was 1±40% excluding one patient (PSA negative) from the population. The radiosensitivity for the PSA positive patients was determined to be 0.0172±0.0084 Gy-1. Conclusion: The proposed method is the first attempt to solely use PET/CT and modeling methods to predict the PSMA-positive tumor volume after radioligand therapy. Internal validation shows that this is feasible with an acceptable accuracy. Improvement of the method and external validation of the model is ongoing. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

A 3-dimensional DTI MRI-based model of GBM growth and response to radiation therapy.

PubMed

Hathout, Leith; Patel, Vishal; Wen, Patrick

2016-09-01

Glioblastoma (GBM) is both the most common and the most aggressive intra-axial brain tumor, with a notoriously poor prognosis. To improve this prognosis, it is necessary to understand the dynamics of GBM growth, response to treatment and recurrence. The present study presents a mathematical diffusion-proliferation model of GBM growth and response to radiation therapy based on diffusion tensor (DTI) MRI imaging. This represents an important advance because it allows 3-dimensional tumor modeling in the anatomical context of the brain. Specifically, tumor infiltration is guided by the direction of the white matter tracts along which glioma cells infiltrate. This provides the potential to model different tumor growth patterns based on location within the brain, and to simulate the tumor's response to different radiation therapy regimens. Tumor infiltration across the corpus callosum is simulated in biologically accurate time frames. The response to radiation therapy, including changes in cell density gradients and how these compare across different radiation fractionation protocols, can be rendered. Also, the model can estimate the amount of subthreshold tumor which has extended beyond the visible MR imaging margins. When combined with the ability of being able to estimate the biological parameters of invasiveness and proliferation of a particular GBM from serial MRI scans, it is shown that the model has potential to simulate realistic tumor growth, response and recurrence patterns in individual patients. To the best of our knowledge, this is the first presentation of a DTI-based GBM growth and radiation therapy treatment model.

Therapeutic targeting of tumors with imageable GFP-expressing Salmonella typhimurium auxotrophic mutants

NASA Astrophysics Data System (ADS)

Hoffman, Robert M.; Hayashi, Katsuhiro; Zhao, Ming

2008-02-01

Tumor targeting Salmonella typhimurium has been developed. These bacteria were mutagenized and a strain auxotrophic for leucine and arguine was selected. This strain was also engineered to express GFP. This train, termed A1, could target prostate tumors in nude mouse models and inhibit their growth. A1 was passaged through a tumor and re-isolated and termed A1-R. A1-R had greater antitumor efficacy and could cure breast, prostate, pancreatic, and lung tumors in nude mouse models.

Immunocompetent syngeneic cotton rat tumor models for the assessment of replication-competent oncolytic adenovirus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steel, Jason C.; Morrison, Brian J.; Mannan, Poonam

Oncolytic adenoviruses as a treatment for cancer have demonstrated limited clinical activity. Contributing to this may be the relevance of preclinical animal models used to study these agents. Syngeneic mouse tumor models are generally non-permissive for adenoviral replication, whereas human tumor xenograft models exhibit attenuated immune responses to the vector. The cotton rat (Sigmodon hispidus) is susceptible to human adenovirus infection, permissive for viral replication and exhibits similar inflammatory pathology to humans with adenovirus replicating in the lungs, respiratory passages and cornea. We evaluated three transplantable tumorigenic cotton rat cell lines, CCRT, LCRT and VCRT as models for the studymore » of oncolytic adenoviruses. All three cells lines were readily infected with adenovirus type-5-based vectors and exhibited high levels of transgene expression. The cell lines supported viral replication demonstrated by the induction of cytopathogenic effect (CPE) in tissue culture, increase in virus particle numbers and assembly of virions seen on transmission electron microscopy. In vivo, LCRT and VCRT tumors demonstrated delayed growth after injection with replicating adenovirus. No in vivo antitumor activity was seen in CCRT tumors despite in vitro oncolysis. Adenovirus was also rapidly cleared from the CCRT tumors compared to LCRT and VCRT tumors. The effect observed with the different cotton rat tumor cell lines mimics the variable results of human clinical trials highlighting the potential relevance of this model for assessing the activity and toxicity of oncolytic adenoviruses.« less

Spectral imaging based in vivo model system for characterization of tumor microvessel response to vascular targeting agents

NASA Astrophysics Data System (ADS)

Wankhede, Mamta

Functional vasculature is vital for tumor growth, proliferation, and metastasis. Many tumor-specific vascular targeting agents (VTAs) aim to destroy this essential tumor vasculature to induce indirect tumor cell death via oxygen and nutrition deprivation. The tumor angiogenesis-inhibiting anti-angiogenics (AIs) and the established tumor vessel targeting vascular disrupting agents (VDAs) are the two major players in the vascular targeting field. Combination of VTAs with conventional therapies or with each other, have been shown to have additive or supra-additive effects on tumor control and treatment. Pathophysiological changes post-VTA treatment in terms of structural and vessel function changes are important parameters to characterize the treatment efficacy. Despite the abundance of information regarding these parameters acquired using various techniques, there remains a need for a quantitative, real-time, and direct observation of these phenomenon in live animals. Through this research we aspired to develop a spectral imaging based mouse tumor system for real-time in vivo microvessel structure and functional measurements for VTA characterization. A model tumor system for window chamber studies was identified, and then combinatorial effects of VDA and AI were characterized in model tumor system. (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html)

Interleukin-10 production by tumor infiltrating macrophages plays a role in Human Papillomavirus 16 tumor growth.

PubMed

Bolpetti, Aline; Silva, João S; Villa, Luisa L; Lepique, Ana Paula

2010-06-07

Human Papillomavirus, HPV, is the main etiological factor for cervical cancer. Different studies show that in women infected with HPV there is a positive correlation between lesion grade and number of infiltrating macrophages, as well as with IL-10 higher expression. Using a HPV16 associated tumor model in mice, TC-1, our laboratory has demonstrated that tumor infiltrating macrophages are M2-like, induce T cell regulatory phenotype and play an important role in tumor growth. M2 macrophages secrete several cytokines, among them IL-10, which has been shown to play a role in T cell suppression by tumor macrophages in other tumor models. In this work, we sought to establish if IL-10 is part of the mechanism by which HPV tumor associated macrophages induce T cell regulatory phenotype, inhibiting anti-tumor activity and facilitating tumor growth. TC-1 tumor cells do not express or respond to IL-10, but recruit leukocytes which, within the tumor environment, produce this cytokine. Using IL-10 deficient mice or blocking IL-10 signaling with neutralizing antibodies, we observed a significant reduction in tumor growth, an increase in tumor infiltration by HPV16 E7 specific CD8 lymphocytes, including a population positive for Granzyme B and Perforin expression, and a decrease in the percentage of HPV specific regulatory T cells in the lymph nodes. Our data shows that in the HPV16 TC-1 tumor mouse model, IL-10 produced by tumor macrophages induce regulatory phenotype on T cells, an immune escape mechanism that facilitates tumor growth. Our results point to a possible mechanism behind the epidemiologic data that correlates higher IL-10 expression with risk of cervical cancer development in HPV infected women.

Information dynamics in carcinogenesis and tumor growth.

PubMed

Gatenby, Robert A; Frieden, B Roy

2004-12-21

The storage and transmission of information is vital to the function of normal and transformed cells. We use methods from information theory and Monte Carlo theory to analyze the role of information in carcinogenesis. Our analysis demonstrates that, during somatic evolution of the malignant phenotype, the accumulation of genomic mutations degrades intracellular information. However, the degradation is constrained by the Darwinian somatic ecology in which mutant clones proliferate only when the mutation confers a selective growth advantage. In that environment, genes that normally decrease cellular proliferation, such as tumor suppressor or differentiation genes, suffer maximum information degradation. Conversely, those that increase proliferation, such as oncogenes, are conserved or exhibit only gain of function mutations. These constraints shield most cellular populations from catastrophic mutator-induced loss of the transmembrane entropy gradient and, therefore, cell death. The dynamics of constrained information degradation during carcinogenesis cause the tumor genome to asymptotically approach a minimum information state that is manifested clinically as dedifferentiation and unconstrained proliferation. Extreme physical information (EPI) theory demonstrates that altered information flow from cancer cells to their environment will manifest in-vivo as power law tumor growth with an exponent of size 1.62. This prediction is based only on the assumption that tumor cells are at an absolute information minimum and are capable of "free field" growth that is, they are unconstrained by external biological parameters. The prediction agrees remarkably well with several studies demonstrating power law growth in small human breast cancers with an exponent of 1.72+/-0.24. This successful derivation of an analytic expression for cancer growth from EPI alone supports the conceptual model that carcinogenesis is a process of constrained information degradation and that malignant cells are minimum information systems. EPI theory also predicts that the estimated age of a clinically observed tumor is subject to a root-mean square error of about 30%. This is due to information loss and tissue disorganization and probably manifests as a randomly variable lag phase in the growth pattern that has been observed experimentally. This difference between tumor size and age may impose a fundamental limit on the efficacy of screening based on early detection of small tumors. Independent of the EPI analysis, Monte Carlo methods are applied to predict statistical tumor growth due to perturbed information flow from the environment into transformed cells. A "simplest" Monte Carlo model is suggested by the findings in the EPI approach that tumor growth arises out of a minimally complex mechanism. The outputs of large numbers of simulations show that (a) about 40% of the populations do not survive the first two-generations due to mutations in critical gene segments; but (b) those that do survive will experience power law growth identical to the predicted rate obtained from the independent EPI approach. The agreement between these two very different approaches to the problem strongly supports the idea that tumor cells regress to a state of minimum information during carcinogenesis, and that information dynamics are integrally related to tumor development and growth.

Clinical problems of colorectal cancer and endometrial cancer cases with unknown cause of tumor mismatch repair deficiency (suspected Lynch syndrome).

PubMed

Buchanan, Daniel D; Rosty, Christophe; Clendenning, Mark; Spurdle, Amanda B; Win, Aung Ko

2014-01-01

Carriers of a germline mutation in one of the DNA mismatch repair (MMR) genes have a high risk of developing numerous different cancers, predominantly colorectal cancer and endometrial cancer (known as Lynch syndrome). MMR gene mutation carriers develop tumors with MMR deficiency identified by tumor microsatellite instability or immunohistochemical loss of MMR protein expression. Tumor MMR deficiency is used to identify individuals most likely to carry an MMR gene mutation. However, MMR deficiency can also result from somatic inactivation, most commonly methylation of the MLH1 gene promoter. As tumor MMR testing of all incident colorectal and endometrial cancers (universal screening) is becoming increasingly adopted, a growing clinical problem is emerging for individuals who have tumors that show MMR deficiency who are subsequently found not to carry an MMR gene mutation after genetic testing using the current diagnostic approaches (Sanger sequencing and multiplex ligation-dependent probe amplification) and who also show no evidence of MLH1 methylation. The inability to determine the underlying cause of tumor MMR deficiency in these "Lynch-like" or "suspected Lynch syndrome" cases has significant implications on the clinical management of these individuals and their relatives. When the data from published studies are combined, 59% (95% confidence interval [CI]: 55% to 64%) of colorectal cancers and 52% (95% CI: 41% to 62%) of endometrial cancers with MMR deficiency were identified as suspected Lynch syndrome. Recent studies estimated that colorectal cancer risk for relatives of suspected Lynch syndrome cases is lower than for relatives of those with MMR gene mutations, but higher than for relatives of those with tumor MMR deficiency resulting from methylation of the MLH1 gene promoter. The cause of tumor MMR deficiency in suspected Lynch syndrome cases is likely due to either unidentified germline MMR gene mutations, somatic cell mosaicism, or biallelic somatic inactivation. Determining the underlying cause of tumor MMR deficiency in suspected Lynch syndrome cases is likely to reshape the current triaging schemes used to identify germline MMR gene mutations in cancer-affected individuals and their relatives.

Fine-needle aspiration biopsy of the salivary gland: problem cases.

PubMed

MacLeod, C B; Frable, W J

1993-01-01

Among 582 fine-needle aspiration (FNA) biopsies of major and minor salivary glands performed between 1974 and 1990, lack of cytological histologic correlation was noted in 21 cases. Of these, the cause in 10 FNAs was inadequate cytological sampling of the lesion. [One case of malignant hemangiopericytoma was tentatively diagnosed as a monomorphic adenoma on FNA, a polymorphic T-cell lymphoma was diagnosed as granulomatous inflammation on aspiration biopsy, a benign lymphoepithelial lesion was diagnosed as a reactive lymph node, a branchial cleft cyst was called benign mixed tumor (BMT), one case of chronic sialoadenitis was called BMT by FNA, two cases of benign lymphoepithelial lesion (BLEL) were diagnosed as cystic Warthin's tumor, two low-grade mucoepidermoid carcinomas were called BMT, and a BMT was cytologically diagnosed as a Warthin's tumor with squamous metaplasia versus low-grade mucoepidermoid carcinoma. One case of low-grade mucoepidermoid carcinoma was diagnosed only as a "cyst."] Review of these cases identifies constant features that permit differentiation between Warthin's tumor and BLEL, and among BMT, mucoepidermoid carcinoma, and chronic sialoadenitis. Despite a few problem cases, FNA of the salivary gland is accurate in the preoperative diagnosis and classification of salivary gland neoplasms.

Clinical study and numerical simulation of brain cancer dynamics under radiotherapy

NASA Astrophysics Data System (ADS)

Nawrocki, S.; Zubik-Kowal, B.

2015-05-01

We perform a clinical and numerical study of the progression of brain cancer tumor growth dynamics coupled with the effects of radiotherapy. We obtained clinical data from a sample of brain cancer patients undergoing radiotherapy and compare it to our numerical simulations to a mathematical model of brain tumor cell population growth influenced by radiation treatment. We model how the body biologically receives a physically delivered dose of radiation to the affected tumorous area in the form of a generalized LQ model, modified to account for the conversion process of sublethal lesions into lethal lesions at high radiation doses. We obtain good agreement between our clinical data and our numerical simulations of brain cancer progression given by the mathematical model, which couples tumor growth dynamics and the effect of irradiation. The correlation, spanning a wide dataset, demonstrates the potential of the mathematical model to describe the dynamics of brain tumor growth influenced by radiotherapy.

WE-E-17A-01: Characterization of An Imaging-Based Model of Tumor Angiogenesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adhikarla, V; Jeraj, R

2014-06-15

Purpose: Understanding the transient dynamics of tumor oxygenation is important when evaluating tumor-vasculature response to anti-angiogenic therapies. An imaging-based tumor-vasculature model was used to elucidate factors that affect these dynamics. Methods: Tumor growth depends on its doubling time (Td). Hypoxia increases pro-angiogenic factor (VEGF) concentration which is modeled to reduce vessel perfusion, attributing to its effect of increasing vascular permeability. Perfused vessel recruitment depends on the existing perfused vasculature, VEGF concentration and maximum VEGF concentration (VEGFmax) for vessel dysfunction. A convolution-based algorithm couples the tumor to the normal tissue vessel density (VD-nt). The parameters are benchmarked to published pre-clinical datamore » and a sensitivity study evaluating the changes in the peak and time to peak tumor oxygenation characterizes them. The model is used to simulate changes in hypoxia and proliferation PET imaging data obtained using [Cu- 61]Cu-ATSM and [F-18]FLT respectively. Results: Td and VD-nt were found to be the most influential on peak tumor pO2 while VEGFmax was marginally influential. A +20 % change in Td, VD-nt and VEGFmax resulted in +50%, +25% and +5% increase in peak pO2. In contrast, Td was the most influential on the time to peak oxygenation with VD-nt and VEGFmax playing marginal roles. A +20% change in Td, VD-nt and VEGFmax increased the time to peak pO2 by +50%, +5% and +0%. A −20% change in the above parameters resulted in comparable decreases in the peak and time to peak pO2. Model application to the PET data was able to demonstrate the voxel-specific changes in hypoxia of the imaged tumor. Conclusion: Tumor-specific doubling time and vessel density are important parameters to be considered when evaluating hypoxia transients. While the current model simulates the oxygen dynamics of an untreated tumor, incorporation of therapeutic effects can make the model a potent tool for analyzing anti-angiogenic therapies.« less

Biodegradable polymeric micelle-encapsulated doxorubicin suppresses tumor metastasis by killing circulating tumor cells

NASA Astrophysics Data System (ADS)

Deng, Senyi; Wu, Qinjie; Zhao, Yuwei; Zheng, Xin; Wu, Ni; Pang, Jing; Li, Xuejing; Bi, Cheng; Liu, Xinyu; Yang, Li; Liu, Lei; Su, Weijun; Wei, Yuquan; Gong, Changyang

2015-03-01

Circulating tumor cells (CTCs) play a crucial role in tumor metastasis, but it is rare for any chemotherapy regimen to focus on killing CTCs. Herein, we describe doxorubicin (Dox) micelles that showed anti-metastatic activity by killing CTCs. Dox micelles with a small particle size and high encapsulation efficiency were obtained using a pH-induced self-assembly method. Compared with free Dox, Dox micelles exhibited improved cytotoxicity, apoptosis induction, and cellular uptake. In addition, Dox micelles showed a sustained release behavior in vitro, and in a transgenic zebrafish model, Dox micelles exhibited a longer circulation time and lower extravasation from blood vessels into surrounding tissues. Anti-tumor and anti-metastatic activities of Dox micelles were investigated in transgenic zebrafish and mouse models. In transgenic zebrafish, Dox micelles inhibited tumor growth and prolonged the survival of tumor-bearing zebrafish. Furthermore, Dox micelles suppressed tumor metastasis by killing CTCs. In addition, improved anti-tumor and anti-metastatic activities were also confirmed in mouse tumor models, where immunofluorescent staining of tumors indicated that Dox micelles induced more apoptosis and showed fewer proliferation-positive cells. There were decreased side effects in transgenic zebrafish and mice after administration of Dox micelles. In conclusion, Dox micelles showed stronger anti-tumor and anti-metastatic activities and decreased side effects both in vitro and in vivo, which may have potential applications in cancer therapy.

Improving Tumor Treating Fields Treatment Efficacy in Patients With Glioblastoma Using Personalized Array Layouts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenger, Cornelia, E-mail: cwenger@fc.ul.pt; Salvador, Ricardo; Basser, Peter J.

Purpose: To investigate tumors of different size, shape, and location and the effect of varying transducer layouts on Tumor Treating Fields (TTFields) distribution in an anisotropic model. Methods and Materials: A realistic human head model was generated from MR images of 1 healthy subject. Four different virtual tumors were placed at separate locations. The transducer arrays were modeled to mimic the TTFields-delivering commercial device. For each tumor location, varying array layouts were tested. The finite element method was used to calculate the electric field distribution, taking into account tissue heterogeneity and anisotropy. Results: In all tumors, the average electric field inducedmore » by either of the 2 perpendicular array layouts exceeded the 1-V/cm therapeutic threshold value for TTFields effectiveness. Field strength within a tumor did not correlate with its size and shape but was higher in more superficial tumors. Additionally, it always increased when the array was adapted to the tumor's location. Compared with a default layout, the largest increase in field strength was 184%, and the highest average field strength induced in a tumor was 2.21 V/cm. Conclusions: These results suggest that adapting array layouts to specific tumor locations can significantly increase field strength within the tumor. Our findings support the idea of personalized treatment planning to increase TTFields efficacy for patients with GBM.« less

Protective Effect of Perindopril on Tumor Progression and Angiogenesis in Animal Model of Breast Cancer.

PubMed

Patel, Snehal S; Nakka, Surender

2017-01-01

Studies have shown that the renin angiotensin system via angiogenesis is involved in tumor development. Therefore, objective of the present study was to examine the effect of perindopril on tumor growth and angiogenesis in animal models of breast cancer. In the present study, the effect of perindopril on tumor development of mammary gland cancer induced by 7,12-dimethylbenz[a]anthracene, mouse tumor xenograft and corneal micropocket model has been investigated. Anti-angiogenic effect by chick yolk sac membrane assay has also been studied. In the present study, it has been found that perindopril produced a significant inhibition of tumor growth, in DMBA induced breast cancer. Treatment also produced significant suppression of cancer biomarkers such as lactate dehydrogenase, gamma glutamyl transferase and inflammatory markers such as C-reactive protein, erythrocyte sedimentation rate. Histopathological analysis also showed that perindopril was able to inhibit tumor development by the inhibition of hyperplastic lesions. Perindopril produced significant inhibition of tumor growth, in a mouse xenograft model and caused inhibition of neovascularization in the corneal micropocket model. In chick yolk sac membrane assay, perindopril showed inhibition of vascular growth and reduced blood vessel formation. Therefore, perindopril is widely used in clinical practice, may represent a neo-adjuvant therapy for treatment of breast cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Gamma-Ray Imaging Probes.

NASA Astrophysics Data System (ADS)

Wild, Walter James

1988-12-01

External nuclear medicine diagnostic imaging of early primary and metastatic lung cancer tumors is difficult due to the poor sensitivity and resolution of existing gamma cameras. Nonimaging counting detectors used for internal tumor detection give ambiguous results because distant background variations are difficult to discriminate from neighboring tumor sites. This suggests that an internal imaging nuclear medicine probe, particularly an esophageal probe, may be advantageously used to detect small tumors because of the ability to discriminate against background variations and the capability to get close to sites neighboring the esophagus. The design, theory of operation, preliminary bench tests, characterization of noise behavior and optimization of such an imaging probe is the central theme of this work. The central concept lies in the representation of the aperture shell by a sequence of binary digits. This, coupled with the mode of operation which is data encoding within an axial slice of space, leads to the fundamental imaging equation in which the coding operation is conveniently described by a circulant matrix operator. The coding/decoding process is a classic coded-aperture problem, and various estimators to achieve decoding are discussed. Some estimators require a priori information about the object (or object class) being imaged; the only unbiased estimator that does not impose this requirement is the simple inverse-matrix operator. The effects of noise on the estimate (or reconstruction) is discussed for general noise models and various codes/decoding operators. The choice of an optimal aperture for detector count times of clinical relevance is examined using a statistical class-separability formalism.

Real-time temperature feedback for nanoparticles based tumor thermal treatment (Conference Presentation)

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Tamir, Gil; Gannot, Israel

2017-02-01

Systemic hyperthermia therapy exploits the fact that cancer cells are more sensitive to elevated temperatures than healthy tissue. Systemic application of hyperthermia externally usually leads to low efficiency treatment. Recently, our group and others have proposed an antibody conjugated magnetic nanoparticles (MNPs) approach to overcome the limitation of systemic hyperthermia. MNPs can bind specifically to the tumor sites, thus delivering internal highly effective targeted hyperthermia. However, such internal mechanism requires more complicated controls and monitoring. This current work presents a deep tissue temperature monitoring method to control hyperthermia effectiveness and minimize collateral damage to surrounding tissues. A low-frequency narrowband modulation of the RF field used for MNP heating leads to the generation of diffused thermal waves which propagate to the tissue surface and captured by a thermal camera. A Fourier domain, analytical heat transfer model is used for temperature monitoring algorithm. The ill-posed thermal inverse problem is solved efficiently by iterating over the source power until both the amplitude and phase match the recorded thermal image sequence. The narrow bandwidth thermal stimulation enables acquiring deep signals with high SNR. We show that thermal transverse resolution improves as the stimulation frequency increases even slightly above DC, enabling better heat source transverse separation and margin identification in the case of distributed tumors. These results can be used as a part of an overall image and treat system for efficient detection of tumors, manipulation of MNPs and monitoring MNP based hyperthermia.

Multiple-Tumor Analysis with MS_Combo Model (Use with BMDS Wizard)

EPA Pesticide Factsheets

Exercises and procedures on setting up and using the MS_Combo Wizard. The MS_Combo model provides BMD and BMDL estimates for the risk of getting one or more tumors for any combination of tumors observed in a single bioassay.

MSW Time to Tumor Model and Supporting Documentation

EPA Science Inventory

The multistage Weibull (MSW) time-to-tumor model and related documentation were developed principally (but not exclusively) for conducting time-to-tumor analyses to support risk assessments under the IRIS program. These programs and related docum...

Cross-visit tumor sub-segmentation and registration with outlier rejection for dynamic contrast-enhanced MRI time series data.

PubMed

Buonaccorsi, G A; Rose, C J; O'Connor, J P B; Roberts, C; Watson, Y; Jackson, A; Jayson, G C; Parker, G J M

2010-01-01

Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers.

In Vitro Model of Tumor Cell Extravasation

PubMed Central

Jeon, Jessie S.; Zervantonakis, Ioannis K.; Chung, Seok; Kamm, Roger D.; Charest, Joseph L.

2013-01-01

Tumor cells that disseminate from the primary tumor and survive the vascular system can eventually extravasate across the endothelium to metastasize at a secondary site. In this study, we developed a microfluidic system to mimic tumor cell extravasation where cancer cells can transmigrate across an endothelial monolayer into a hydrogel that models the extracellular space. The experimental protocol is optimized to ensure the formation of an intact endothelium prior to the introduction of tumor cells and also to observe tumor cell extravasation by having a suitable tumor seeding density. Extravasation is observed for 38.8% of the tumor cells in contact with the endothelium within 1 day after their introduction. Permeability of the EC monolayer as measured by the diffusion of fluorescently-labeled dextran across the monolayer increased 3.8 fold 24 hours after introducing tumor cells, suggesting that the presence of tumor cells increases endothelial permeability. The percent of tumor cells extravasated remained nearly constant from1 to 3 days after tumor seeding, indicating extravasation in our system generally occurs within the first 24 hours of tumor cell contact with the endothelium. PMID:23437268

Numerical modeling of nanodrug distribution in tumors with heterogeneous vasculature.

PubMed

Chou, Cheng-Ying; Chang, Wan-I; Horng, Tzyy-Leng; Lin, Win-Li

2017-01-01

The distribution and accumulation of nanoparticle dosage in a tumor are important in evaluating the effectiveness of cancer treatment. The cell survival rate can quantify the therapeutic effect, and the survival rates after multiple treatments are helpful to evaluate the efficacy of a chemotherapy plan. We developed a mathematical tumor model based on the governing equations describing the fluid flow and particle transport to investigate the drug transportation in a tumor and computed the resulting cumulative concentrations. The cell survival rate was calculated based on the cumulative concentration. The model was applied to a subcutaneous tumor with heterogeneous vascular distributions. Various sized dextrans and doxorubicin were respectively chosen as the nanodrug carrier and the traditional chemotherapeutic agent for comparison. The results showed that: 1) the largest nanoparticle drug in the current simulations yielded the highest cumulative concentration in the well vascular region, but second lowest in the surrounding normal tissues, which implies it has the best therapeutic effect to tumor and at the same time little harmful to normal tissue; 2) on the contrary, molecular chemotherapeutic agent produced the second lowest cumulative concentration in the well vascular tumor region, but highest in the surrounding normal tissue; 3) all drugs have very small cumulative concentrations in the tumor necrotic region, where drug transport is solely through diffusion. This might mean that it is hard to kill tumor stem cells hiding in it. The current model indicated that the effectiveness of the anti-tumor drug delivery was determined by the interplay of the vascular density and nanoparticle size, which governs the drug transport properties. The use of nanoparticles as anti-tumor drug carriers is generally a better choice than molecular chemotherapeutic agent because of its high treatment efficiency on tumor cells and less damage to normal tissues.

Patient-specific model-based segmentation of brain tumors in 3D intraoperative ultrasound images.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Lindner, Dirk; Arlt, Felix; Ituna-Yudonago, Jean Fulbert; Chalopin, Claire

2018-03-01

Intraoperative ultrasound (iUS) imaging is commonly used to support brain tumor operation. The tumor segmentation in the iUS images is a difficult task and still under improvement because of the low signal-to-noise ratio. The success of automatic methods is also limited due to the high noise sensibility. Therefore, an alternative brain tumor segmentation method in 3D-iUS data using a tumor model obtained from magnetic resonance (MR) data for local MR-iUS registration is presented in this paper. The aim is to enhance the visualization of the brain tumor contours in iUS. A multistep approach is proposed. First, a region of interest (ROI) based on the specific patient tumor model is defined. Second, hyperechogenic structures, mainly tumor tissues, are extracted from the ROI of both modalities by using automatic thresholding techniques. Third, the registration is performed over the extracted binary sub-volumes using a similarity measure based on gradient values, and rigid and affine transformations. Finally, the tumor model is aligned with the 3D-iUS data, and its contours are represented. Experiments were successfully conducted on a dataset of 33 patients. The method was evaluated by comparing the tumor segmentation with expert manual delineations using two binary metrics: contour mean distance and Dice index. The proposed segmentation method using local and binary registration was compared with two grayscale-based approaches. The outcomes showed that our approach reached better results in terms of computational time and accuracy than the comparative methods. The proposed approach requires limited interaction and reduced computation time, making it relevant for intraoperative use. Experimental results and evaluations were performed offline. The developed tool could be useful for brain tumor resection supporting neurosurgeons to improve tumor border visualization in the iUS volumes.

PlGF/VEGFR-1 Signaling Promotes Macrophage Polarization and Accelerated Tumor Progression in Obesity.

PubMed

Incio, Joao; Tam, Josh; Rahbari, Nuh N; Suboj, Priya; McManus, Dan T; Chin, Shan M; Vardam, Trupti D; Batista, Ana; Babykutty, Suboj; Jung, Keehoon; Khachatryan, Anna; Hato, Tai; Ligibel, Jennifer A; Krop, Ian E; Puchner, Stefan B; Schlett, Christopher L; Hoffmman, Udo; Ancukiewicz, Marek; Shibuya, Masabumi; Carmeliet, Peter; Soares, Raquel; Duda, Dan G; Jain, Rakesh K; Fukumura, Dai

2016-06-15

Obesity promotes pancreatic and breast cancer progression via mechanisms that are poorly understood. Although obesity is associated with increased systemic levels of placental growth factor (PlGF), the role of PlGF in obesity-induced tumor progression is not known. PlGF and its receptor VEGFR-1 have been shown to modulate tumor angiogenesis and promote tumor-associated macrophage (TAM) recruitment and activity. Here, we hypothesized that increased activity of PlGF/VEGFR-1 signaling mediates obesity-induced tumor progression by augmenting tumor angiogenesis and TAM recruitment/activity. We established diet-induced obese mouse models of wild-type C57BL/6, VEGFR-1 tyrosine kinase (TK)-null, or PlGF-null mice, and evaluated the role of PlGF/VEGFR-1 signaling in pancreatic and breast cancer mouse models and in human samples. We found that obesity increased TAM infiltration, tumor growth, and metastasis in pancreatic cancers, without affecting vessel density. Ablation of VEGFR-1 signaling prevented obesity-induced tumor progression and shifted the tumor immune environment toward an antitumor phenotype. Similar findings were observed in a breast cancer model. Obesity was associated with increased systemic PlGF, but not VEGF-A or VEGF-B, in pancreatic and breast cancer patients and in various mouse models of these cancers. Ablation of PlGF phenocopied the effects of VEGFR-1-TK deletion on tumors in obese mice. PlGF/VEGFR-1-TK deletion prevented weight gain in mice fed a high-fat diet, but exacerbated hyperinsulinemia. Addition of metformin not only normalized insulin levels but also enhanced antitumor immunity. Targeting PlGF/VEGFR-1 signaling reprograms the tumor immune microenvironment and inhibits obesity-induced acceleration of tumor progression. Clin Cancer Res; 22(12); 2993-3004. ©2016 AACR. ©2016 American Association for Cancer Research.

The impact of ranitidine on monocyte responses in the context of solid tumors

PubMed Central

Vila-Leahey, Ava; Rogers, Dakota; Marshall, Jean S.

2016-01-01

Monocytes and myeloid derived suppressor cells (MDSC) have been implicated on the regulation of tumor growth. Histamine is also important for regulating MDSC responses. Oral administration of the H2 receptor antagonist ranitidine can inhibit breast tumor growth and metastasis. In the current study, we examined the impact of oral ranitidine treatment, at a clinically relevant dose, on multiple murine tumor models. The impact of ranitidine on monocyte responses and the role of CCR2 in ranitidine-induced tumor growth inhibition were also investigated. Oral ranitidine treatment did not reduce tumor growth in the B16-F10 melanoma, LLC1 lung cancer and EL4 thymoma models. However, it consistently reduced E0771 primary tumor growth and metastasis in the 4T1 model. Ranitidine had no impact on E0771 tumor growth in mice deficient in CCR2, where monocyte recruitment to tumors was limited. Analysis of splenic monocytes also revealed an elevated ratio of H2 versus H1 expression from tumor-bearing compared with naïve mice. More detailed examination of the role of ranitidine on monocyte development demonstrated a decrease in monocyte progenitor cells following ranitidine treatment. Taken together, these results reveal that H2 signaling may be a novel target to alter the monocyte population in breast tumor models, and that targeting H2 on monocytes via oral ranitidine treatment impacts effective tumor immunity. Ranitidine is widely used for control of gastrointestinal disorders. The potential role of ranitidine as an adjunct to immunotherapies for breast cancer and the potential impact of H2 antagonists on breast cancer outcomes should be considered. PMID:26863636

The impact of ranitidine on monocyte responses in the context of solid tumors.

PubMed

Vila-Leahey, Ava; Rogers, Dakota; Marshall, Jean S

2016-03-08

Monocytes and myeloid derived suppressor cells (MDSC) have been implicated on the regulation of tumor growth. Histamine is also important for regulating MDSC responses. Oral administration of the H2 receptor antagonist ranitidine can inhibit breast tumor growth and metastasis. In the current study, we examined the impact of oral ranitidine treatment, at a clinically relevant dose, on multiple murine tumor models. The impact of ranitidine on monocyte responses and the role of CCR2 in ranitidine-induced tumor growth inhibition were also investigated. Oral ranitidine treatment did not reduce tumor growth in the B16-F10 melanoma, LLC1 lung cancer and EL4 thymoma models. However, it consistently reduced E0771 primary tumor growth and metastasis in the 4T1 model. Ranitidine had no impact on E0771 tumor growth in mice deficient in CCR2, where monocyte recruitment to tumors was limited. Analysis of splenic monocytes also revealed an elevated ratio of H2 versus H1 expression from tumor-bearing compared with naïve mice. More detailed examination of the role of ranitidine on monocyte development demonstrated a decrease in monocyte progenitor cells following ranitidine treatment. Taken together, these results reveal that H2 signaling may be a novel target to alter the monocyte population in breast tumor models, and that targeting H2 on monocytes via oral ranitidine treatment impacts effective tumor immunity. Ranitidine is widely used for control of gastrointestinal disorders. The potential role of ranitidine as an adjunct to immunotherapies for breast cancer and the potential impact of H2 antagonists on breast cancer outcomes should be considered.

3-D individual cell based computational modeling of tumor cell–macrophage paracrine signaling mediated by EGF and CSF-1 gradients†

PubMed Central

Knutsdottir, Hildur; Condeelis, John S.; Palsson, Eirikur

2016-01-01

High density of macrophages in mammary tumors has been associated with a higher risk of metastasis and thus increased mortality in women. The EGF/CSF-1 paracrine signaling increases the number of invasive tumor cells by both recruiting tumor cells further away and manipulating the macrophages’ innate ability to open up a passage into blood vessels thus promoting intravasation and finally metastasis. A 3-D individual-cell-based model is introduced, to better understand the tumor cell–macrophage interactions, and to explore how changing parameters of the paracrine signaling system affects the number of invasive tumor cells. The simulation data and videos of the cell movements correlated well with findings from both in vitro and in vivo experimental results. The model demonstrated how paracrine signaling is necessary to achieve co-migration of tumor cells and macrophages towards a specific signaling source. We showed how the paracrine signaling enhances the number of both invasive tumor cells and macrophages. The simulations revealed that for the in vitro experiments the imposed no-flux boundary condition might be affecting the results, and that changing the setup might lead to different experimental findings. In our simulations, the 3 : 1 tumor cell/macrophage ratio, observed in vivo, was robust for many parameters but sensitive to EGF signal strength and fraction of macrophages in the tumor. The model can be used to identify new agents for targeted therapy and we suggest that a successful strategy to prevent or limit invasion of tumor cells would be to block the tumor cell–macrophage paracrine signaling. This can be achieved by either blocking the EGF or CSF-1 receptors or supressing the EGF or CSF-1 signal. PMID:26686751

Near infrared photoimmunotherapy in the treatment of disseminated peritoneal ovarian cancer

PubMed Central

Sato, Kazuhide; Hanaoka, Hirofumi; Watanabe, Rira; Nakajima, Takahito; Choyke, Peter L.; Kobayashi, Hisataka

2014-01-01

Near infrared photoimmunotherapy (NIR-PIT) is a new cancer treatment that combines the specificity of intravenously injected antibodies for targeting tumors with the toxicity induced by photosensitizers after exposure to near infrared (NIR) light. Herein, we evaluate the efficacy of NIR-PIT in a mouse model of disseminated peritoneal ovarian cancer. In vitro and in vivo experiments were conducted with a HER2-expressing, luciferase expressing, ovarian cancer cell line (SKOV-luc). An antibody-photosensitizer conjugate (APC) consisting of trastuzumab and a phthalocyanine dye, IRDye-700DX, was synthesized (tra-IR700) and cells or tumors were exposed to near infrared (NIR) light. In vitro PIT cytotoxicity was assessed with dead staining and luciferase activity in freely growing cells and in a 3D spheroid model. In vivo NIR-PIT was performed in mice with tumors implanted in the peritoneum and in the flank and these assessed by tumor volume and/or bioluminescence. In vitro NIR-PIT-induced cytotoxicity was light dose dependent. Repeated light exposures induced complete tumor cell killing in the 3D spheroid model. In vivo the anti-tumor effects of NIR-PIT were confirmed by significant reductions in both tumor volume and luciferase activity in the flank model (NIR-PIT vs control in tumor volume changes at day 10; p=0.0001, NIR-PIT vs control in luciferase activity at day 4; p=0.0237), and the peritoneal model (NIR-PIT vs control in luciferase activity at day 7; p=0.0037). NIR-PIT provided effective cell killing in this HER2 positive model of disseminated peritoneal ovarian cancer. Thus, NIR-PIT is a promising new therapy for the treatment of disseminated peritoneal tumors. PMID:25416790

Perfusion kinetics in human brain tumor with DCE-MRI derived model and CFD analysis.

PubMed

Bhandari, A; Bansal, A; Singh, A; Sinha, N

2017-07-05

Cancer is one of the leading causes of death all over the world. Among the strategies that are used for cancer treatment, the effectiveness of chemotherapy is often hindered by factors such as irregular and non-uniform uptake of drugs inside tumor. Thus, accurate prediction of drug transport and deposition inside tumor is crucial for increasing the effectiveness of chemotherapeutic treatment. In this study, a computational model of human brain tumor is developed that incorporates dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data into a voxelized porous media model. The model takes into account realistic transport and perfusion kinetics parameters together with realistic heterogeneous tumor vasculature and accurate arterial input function (AIF), which makes it patient specific. The computational results for interstitial fluid pressure (IFP), interstitial fluid velocity (IFV) and tracer concentration show good agreement with the experimental results. The computational model can be extended further for predicting the deposition of chemotherapeutic drugs in tumor environment as well as selection of the best chemotherapeutic drug for a specific patient. Copyright © 2017 Elsevier Ltd. All rights reserved.

Threshold for extinction and survival in stochastic tumor immune system

NASA Astrophysics Data System (ADS)

Li, Dongxi; Cheng, Fangjuan

2017-10-01

This paper mainly investigates the stochastic character of tumor growth and extinction in the presence of immune response of a host organism. Firstly, the mathematical model describing the interaction and competition between the tumor cells and immune system is established based on the Michaelis-Menten enzyme kinetics. Then, the threshold conditions for extinction, weak persistence and stochastic persistence of tumor cells are derived by the rigorous theoretical proofs. Finally, stochastic simulation are taken to substantiate and illustrate the conclusion we have derived. The modeling results will be beneficial to understand to concept of immunoediting, and develop the cancer immunotherapy. Besides, our simple theoretical model can help to obtain new insight into the complexity of tumor growth.

Learning oncogenetic networks by reducing to mixed integer linear programming.

PubMed

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results

NASA Astrophysics Data System (ADS)

Jarrett, Angela M.; Hormuth, David A.; Barnes, Stephanie L.; Feng, Xinzeng; Huang, Wei; Yankeelov, Thomas E.

2018-05-01

Clinical methods for assessing tumor response to therapy are largely rudimentary, monitoring only temporal changes in tumor size. Our goal is to predict the response of breast tumors to therapy using a mathematical model that utilizes magnetic resonance imaging (MRI) data obtained non-invasively from individual patients. We extended a previously established, mechanically coupled, reaction-diffusion model for predicting tumor response initialized with patient-specific diffusion weighted MRI (DW-MRI) data by including the effects of chemotherapy drug delivery, which is estimated using dynamic contrast-enhanced (DCE-) MRI data. The extended, drug incorporated, model is initialized using patient-specific DW-MRI and DCE-MRI data. Data sets from five breast cancer patients were used—obtained before, after one cycle, and at mid-point of neoadjuvant chemotherapy. The DCE-MRI data was used to estimate spatiotemporal variations in tumor perfusion with the extended Kety–Tofts model. The physiological parameters derived from DCE-MRI were used to model changes in delivery of therapy drugs within the tumor for incorporation in the extended model. We simulated the original model and the extended model in both 2D and 3D and compare the results for this five-patient cohort. Preliminary results show reductions in the error of model predicted tumor cellularity and size compared to the experimentally-measured results for the third MRI scan when therapy was incorporated. Comparing the two models for agreement between the predicted total cellularity and the calculated total cellularity (from the DW-MRI data) reveals an increased concordance correlation coefficient from 0.81 to 0.98 for the 2D analysis and 0.85 to 0.99 for the 3D analysis (p  <  0.01 for each) when the extended model was used in place of the original model. This study demonstrates the plausibility of using DCE-MRI data as a means to estimate drug delivery on a patient-specific basis in predictive models and represents a step toward the goal of achieving individualized prediction of tumor response to therapy.

Establishment of a neuroblastoma mouse model by subcutaneous xenograft transplantation and its use to study metastatic neuroblastoma.

PubMed

Gao, Q; Chen, C F; Dong, Q; Hou, L; Chen, X; Zhi, Y L; Li, X; Lu, H T; Zhang, H Y

2015-12-08

The aim of this study was to establish a metastatic human neuroblastoma (NB) mouse model by xenograft in order to study the metastatic mechanisms of NB. A human NB cell line was obtained from a 5-year-old patient and cultured in vitro. A suspension of these cells was subcutaneously inoculated into nude mice at the right flank next to the forelimb. The biological characteristics of the developed subcutaneous and metastatic tumors were analyzed by hematoxylin and eosin staining. The expression of the tumor marker neuron-specific enolase was determined by immunohistochemistry, and the invasive ability of metastatic tumors was examined by a Matrigel invasion assay. DNA microarray analyses were performed to examine the metastasis-related gene expression. Our results showed that tumors grew in 75% of the mice injected with NB cells and the rate of metastasis was 21%. The xenograft tumors retained the morphological and biological characteristics of the NB specimen from the pediatric patient. Neuron-specific enolase was highly expressed in both subcutaneous and metastatic tumors. The metastatic tumor cells possessed a higher invasive capability than the primary NB cells. The expression of 25 metastasis-related genes was found to be significantly altered in metastatic tumors compared to primary tumors, including RECK, MMP2, VEGF, MMP3, and CXCL12. In conclusion, we successfully established a human NB xenograft model with high tumor-bearing and metastatic rates in nude mice, providing an ideal animal model for the in vivo study of NB.

Patient-derived xenograft in zebrafish embryos: a new platform for translational research in neuroendocrine tumors.

PubMed

Gaudenzi, Germano; Albertelli, Manuela; Dicitore, Alessandra; Würth, Roberto; Gatto, Federico; Barbieri, Federica; Cotelli, Franco; Florio, Tullio; Ferone, Diego; Persani, Luca; Vitale, Giovanni

2017-08-01

Preclinical research on neuroendocrine tumors usually involves immortalized cell lines and few animal models. In the present study we described an in vivo model based on patient-derived xenografts of neuroendocrine tumor cells in zebrafish (Danio rerio) embryos, allowing a rapid analysis of the angiogenic and invasive potential. Patient-derived neuroendocrine tumor cells were transplanted in 48 hours post-fertilization Tg(fli1a:EGFP) y1 zebrafish embryos that express enhanced green fluorescent protein in the entire vasculature. Neuroendocrine tumor cells, stained with CM-Dil, were injected into the subperidermal (perivitelline) space, close to the developing subintestinal venous plexus. A proper control group, represented by zebrafish injected with only D-PBS, was included in this study. Angiogenic and invasive potentials of each patient-derived xenograft were evaluated by both epifluorescence and confocal microscopes. Six out of eight neuroendocrine tumor samples were successfully transplanted in zebrafish embryos. Although the implanted tumor mass had a limited size (about 100 cells for embryos), patient-derived xenografts showed pro-angiogenic (5 cases) and invasive (6 cases) behaviors within 48 hours post injection. Patient-derived xenograft in zebrafish embryos appears to be a reliable in vivo preclinical model for neuroendocrine tumors, tumors with often limited cell availability. The rapidity of this procedure makes our model a promising platform to perform preclinical drug screening and opens a new scenario for personalized treatment in patients with neuroendocrine tumors.

3D Porous Chitosan-Alginate Scaffolds as an In Vitro Model for Evaluating Nanoparticle-Mediated Tumor Targeting and Gene Delivery to Prostate Cancer.

PubMed

Wang, Kui; Kievit, Forrest M; Florczyk, Stephen J; Stephen, Zachary R; Zhang, Miqin

2015-10-12

Cationic nanoparticles (NPs) for targeted gene delivery are conventionally evaluated using 2D in vitro cultures. However, this does not translate well to corresponding in vivo studies because of the marked difference in NP behavior in the presence of the tumor microenvironment. In this study, we investigated whether prostate cancer (PCa) cells cultured in three-dimensional (3D) chitosan-alginate (CA) porous scaffolds could model cationic NP-mediated gene targeted delivery to tumors in vitro. We assessed in vitro tumor cell proliferation, formation of tumor spheroids, and expression of marker genes that promote tumor malignancy in CA scaffolds. The efficacy of NP-targeted gene delivery was evaluated in PCa cells in 2D cultures, PCa tumor spheroids grown in CA scaffolds, and PCa tumors in a mouse TRAMP-C2 flank tumor model. PCa cells cultured in CA scaffolds grew into tumor spheroids and displayed characteristics of higher malignancy as compared to those in 2D cultures. Significantly, targeted gene delivery was only observed in cells cultured in CA scaffolds, whereas cells cultured on 2D plates showed no difference in gene delivery between targeted and nontarget control NPs. In vivo NP evaluation confirmed targeted gene delivery, indicating that only CA scaffolds correctly modeled NP-mediated targeted delivery in vivo. These findings suggest that CA scaffolds serve as a better in vitro platform than 2D cultures for evaluation of NP-mediated targeted gene delivery to PCa.

[Effect of depsides salts from Salvia miltiorrhiza on human hepatoma cell line SMMC-7721 subcutaneous xenografts in nude mice].

PubMed

Li, Xiangping; Song, Zhouye; Zhong, Haiying; Gong, Zhicheng; Yin, Tao; Zhang, Zanling; Zhou, Boting

2015-02-01

To exlpore the eff ect of depsides salts from Salvia miltiorrhiza on human hepatoma cell line SMMC-7721 xenograft tumors and the possible mechanisms. A total of 36 nude mice were divided into 6 groups: A model group, a negative control group, a positive control group, and 3 treatment groups at low, middle or high dose (n=6). The tumor model of nude mice was given depsides salts at a dose of 10, 20 or 50 mg/kg every 3 day for 16 days. Then samples of subcutaneous tumors in nude mice were collected. The morphological changes of tumor samples were observed by HE staining and the expression of vascular endothelial growth factor (VEGF) and the tumor antigen Ki67 was detected by immunohistochemical method. The tumor growth was inhibited by all doses of depsides salts. The morphology of tumors was shrinkage, broken and irregularly arranged compared with the tumors in the model group and the negative control group. Morphological changes were more obvious in tumors with treatment at high dose. Expression of VEGF and Ki67 in treatment groups and the positive control group were lower than that in the model group and the negative control group, with a significant difference (P<0.05). Depsides salts from Salvia miltiorrhiza can inhibit the growth of human hepatoma cell line SMMC-7721 tumor in nude mice, which is related to the inhibition of Ki67 and VEGF.

Fluorescence imaging of angiogenesis in green fluorescent protein-expressing tumors

NASA Astrophysics Data System (ADS)

Yang, Meng; Baranov, Eugene; Jiang, Ping; Li, Xiao-Ming; Wang, Jin W.; Li, Lingna; Yagi, Shigeo; Moossa, A. R.; Hoffman, Robert M.

2002-05-01

The development of therapeutics for the control of tumor angiogenesis requires a simple, reliable in vivo assay for tumor-induced vascularization. For this purpose, we have adapted the orthotopic implantation model of angiogenesis by using human and rodent tumors genetically tagged with Aequorea victoria green fluorescent protein (GFP) for grafting into nude mice. Genetically-fluorescent tumors can be readily imaged in vivo. The non-luminous induced capillaries are clearly visible against the bright tumor fluorescence examined either intravitally or by whole-body luminance in real time. Fluorescence shadowing replaces the laborious histological techniques for determining blood vessel density. High-level GFP-expressing tumor cell lines made it possible to acquire the high-resolution real-time fluorescent optical images of angiogenesis in both primary tumors and their metastatic lesions in various human and rodent tumor models by means of a light-based imaging system. Intravital images of angiogenesis onset and development were acquired and quantified from a GFP- expressing orthotopically-growing human prostate tumor over a 19-day period. Whole-body optical imaging visualized vessel density increasing linearly over a 20-week period in orthotopically-growing, GFP-expressing human breast tumor MDA-MB-435. Vessels in an orthotopically-growing GFP- expressing Lewis lung carcinoma tumor were visualized through the chest wall via a reversible skin flap. These clinically-relevant angiogenesis mouse models can be used for real-time in vivo evaluation of agents inhibiting or promoting tumor angiogenesis in physiological micro- environments.

Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy Using Spatial-Temporal {sup 18}F-FDG PET Features, Clinical Parameters, and Demographics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Hao; Tan, Shan; Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan

2014-01-01

Purpose: To construct predictive models using comprehensive tumor features for the evaluation of tumor response to neoadjuvant chemoradiation therapy (CRT) in patients with esophageal cancer. Methods and Materials: This study included 20 patients who underwent trimodality therapy (CRT + surgery) and underwent {sup 18}F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) both before and after CRT. Four groups of tumor features were examined: (1) conventional PET/CT response measures (eg, standardized uptake value [SUV]{sub max}, tumor diameter); (2) clinical parameters (eg, TNM stage, histology) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associated changesmore » resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, cross-validations being used to avoid model overfitting. Prediction accuracy was assessed by area under the receiver operating characteristic curve (AUC), and precision was evaluated by confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). With the use of spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications)—results that were significantly better than when conventional PET/CT measures or clinical parameters and demographics alone were used. For groups with many tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than did the LR model. Conclusions: The SVM model that used all features including spatial-temporal PET features accurately and precisely predicted pathologic tumor response to CRT in esophageal cancer.« less

Selection, calibration, and validation of models of tumor growth.

PubMed

Lima, E A B F; Oden, J T; Hormuth, D A; Yankeelov, T E; Almeida, R C

2016-11-01

This paper presents general approaches for addressing some of the most important issues in predictive computational oncology concerned with developing classes of predictive models of tumor growth. First, the process of developing mathematical models of vascular tumors evolving in the complex, heterogeneous, macroenvironment of living tissue; second, the selection of the most plausible models among these classes, given relevant observational data; third, the statistical calibration and validation of models in these classes, and finally, the prediction of key Quantities of Interest (QOIs) relevant to patient survival and the effect of various therapies. The most challenging aspects of this endeavor is that all of these issues often involve confounding uncertainties: in observational data, in model parameters, in model selection, and in the features targeted in the prediction. Our approach can be referred to as "model agnostic" in that no single model is advocated; rather, a general approach that explores powerful mixture-theory representations of tissue behavior while accounting for a range of relevant biological factors is presented, which leads to many potentially predictive models. Then representative classes are identified which provide a starting point for the implementation of OPAL, the Occam Plausibility Algorithm (OPAL) which enables the modeler to select the most plausible models (for given data) and to determine if the model is a valid tool for predicting tumor growth and morphology ( in vivo ). All of these approaches account for uncertainties in the model, the observational data, the model parameters, and the target QOI. We demonstrate these processes by comparing a list of models for tumor growth, including reaction-diffusion models, phase-fields models, and models with and without mechanical deformation effects, for glioma growth measured in murine experiments. Examples are provided that exhibit quite acceptable predictions of tumor growth in laboratory animals while demonstrating successful implementations of OPAL.

Front Instabilities and Invasiveness of Simulated Avascular Tumors

PubMed Central

Popławski, Nikodem J.; Agero, Ubirajara; Gens, J. Scott; Swat, Maciej; Glazier, James A.; Anderson, Alexander R. A.

2009-01-01

We study the interface morphology of a 2D simulation of an avascular tumor composed of identical cells growing in an homogeneous healthy tissue matrix (TM), in order to understand the origin of the morphological changes often observed during real tumor growth. We use the GlazierGraner-Hogeweg model, which treats tumor cells as extended, deformable objects, to study the effects of two parameters: a dimensionless diffusion-limitation parameter defined as the ratio of the tumor consumption rate to the substrate transport rate, and the tumor-TM surface tension. We model TM as a nondiffusing field, neglecting the TM pressure and haptotactic repulsion acting on a real growing tumor; thus our model is appropriate for studying tumors with highly motile cells, e.g., gliomas. We show that the diffusion-limitation parameter determines whether the growing tumor develops a smooth (noninvasive) or fingered (invasive) interface, and that the sensitivity of tumor morphology to tumor-TM surface tension increases with the size of the dimensionless diffusion-limitation parameter. For large diffusion-limitation parameters we find a transition (missed in previous work) between dendritic structures, produced when tumor-TM surface tension is high, and seaweed-like structures, produced when tumor-TM surface tension is low. This observation leads to a direct analogy between the mathematics and dynamics of tumors and those observed in nonbiological directional solidification. Our results are also consistent with biological observation that hypoxia promotes invasive growth of tumor cells by inducing higher levels of receptors for scatter factors that weaken cell-cell adhesion and increase cell motility. These findings suggest that tumor morphology may have value in predicting the efficiency of antiangiogenic therapy in individual patients. PMID:19234746

Human Xenografts Are Not Rejected in a Naturally Occurring Immunodeficient Porcine Line: A Human Tumor Model in Pigs

PubMed Central

Basel, Matthew T.; Balivada, Sivasai; Beck, Amanda P.; Kerrigan, Maureen A.; Pyle, Marla M.; Dekkers, Jack C.M.; Wyatt, Carol R.; Rowland, Robert R.R.; Anderson, David E.; Bossmann, Stefan H.

2012-01-01

Abstract Animal models for cancer therapy are invaluable for preclinical testing of potential cancer treatments; however, therapies tested in such models often fail to translate into clinical settings. Therefore, a better preclinical model for cancer treatment testing is needed. Here we demonstrate that an immunodeficient line of pigs can host and support the growth of xenografted human tumors and has the potential to be an effective animal model for cancer therapy. Wild-type and immunodeficient pigs were injected subcutaneously in the left ear with human melanoma cells (A375SM cells) and in the right ear with human pancreatic carcinoma cells (PANC-1). All immunodeficient pigs developed tumors that were verified by histology and immunohistochemistry. Nonaffected littermates did not develop tumors. Immunodeficient pigs, which do not reject xenografted human tumors, have the potential to become an extremely useful animal model for cancer therapy because of their similarity in size, anatomy, and physiology to humans. PMID:23514746

Advanced Cell Culture Techniques for Cancer Drug Discovery

PubMed Central

Lovitt, Carrie J.; Shelper, Todd B.; Avery, Vicky M.

2014-01-01

Human cancer cell lines are an integral part of drug discovery practices. However, modeling the complexity of cancer utilizing these cell lines on standard plastic substrata, does not accurately represent the tumor microenvironment. Research into developing advanced tumor cell culture models in a three-dimensional (3D) architecture that more prescisely characterizes the disease state have been undertaken by a number of laboratories around the world. These 3D cell culture models are particularly beneficial for investigating mechanistic processes and drug resistance in tumor cells. In addition, a range of molecular mechanisms deconstructed by studying cancer cells in 3D models suggest that tumor cells cultured in two-dimensional monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner. Recent studies have demonstrated the potential of utilizing 3D cell culture models in drug discovery programs; however, it is evident that further research is required for the development of more complex models that incorporate the majority of the cellular and physical properties of a tumor. PMID:24887773

Advanced cell culture techniques for cancer drug discovery.

PubMed

Lovitt, Carrie J; Shelper, Todd B; Avery, Vicky M

2014-05-30

Human cancer cell lines are an integral part of drug discovery practices. However, modeling the complexity of cancer utilizing these cell lines on standard plastic substrata, does not accurately represent the tumor microenvironment. Research into developing advanced tumor cell culture models in a three-dimensional (3D) architecture that more prescisely characterizes the disease state have been undertaken by a number of laboratories around the world. These 3D cell culture models are particularly beneficial for investigating mechanistic processes and drug resistance in tumor cells. In addition, a range of molecular mechanisms deconstructed by studying cancer cells in 3D models suggest that tumor cells cultured in two-dimensional monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner. Recent studies have demonstrated the potential of utilizing 3D cell culture models in drug discovery programs; however, it is evident that further research is required for the development of more complex models that incorporate the majority of the cellular and physical properties of a tumor.

Oral Mucosa Model for Electrochemotherapy Treatment of Dog Mouth Cancer: Ex Vivo, In Silico, and In Vivo Experiments.

PubMed

Suzuki, Daniela O H; Berkenbrock, José A; Frederico, Marisa J S; Silva, Fátima R M B; Rangel, Marcelo M M

2018-03-01

Electrochemotherapy (EQT) is a local cancer treatment well established to cutaneous and subcutaneous tumors. Electric fields are applied to biological tissue in order to improve membrane permeability for cytotoxic drugs. This phenomenon is called electroporation or electropermeabilization. Studies have reported that tissue conductivity is electric field dependent. Electroporation numerical models of biological tissues are essential in treatment planning. Tumors of the mouth are very common in dogs. Inadequate EQT treatment of oral tumor may be caused by significant anatomic variations between dogs and tumor position. Numerical models of oral mucosa and tumor allow the treatment planning and optimization of electrodes for each patient. In this work, oral mucosa conductivity during electroporation was characterized by measuring applied voltage and current of ex vivo rats. This electroporation model was used with a spontaneous canine oral melanoma. The model outcomes of oral tumor EQT is applied in different parts of the oral cavity including near bones and the hard palate. The numerical modeling for treatment planning will help the development of new electrodes and increase the EQT effectiveness. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Levels of Murine, but Not Human, CXCL13 Are Greatly Elevated in NOD-SCID Mice Bearing the AIDS-Associated Burkitt Lymphoma Cell Line, 2F7

PubMed Central

Widney, Daniel P.; Olafsen, Tove; Wu, Anna M.; Kitchen, Christina M. R.; Said, Jonathan W.; Smith, Jeffrey B.; Peña, Guadalupe; Magpantay, Larry I.; Penichet, Manuel L.; Martinez-Maza, Otoniel

2013-01-01

Currently, few rodent models of AIDS-associated non-Hodgkin’s lymphoma (AIDS-NHL) exist. In these studies, a novel mouse/human xenograft model of AIDS-associated Burkitt lymphoma (AIDS-BL) was created by injecting cells of the human AIDS-BL cell line, 2F7, intraperitoneally into NOD-SCID mice. Mice developed tumors in the peritoneal cavity, with metastases to the spleen, thymus, and mesenteric lymph nodes. Expression of the chemokine receptor, CXCR5, was greatly elevated in vivo on BL tumor cells in this model, as shown by flow cytometry. CXCL13 is the ligand for CXCR5, and serum and ascites levels of murine, but not human, CXCL13 showed a striking elevation in tumor-bearing mice, with levels as high as 200,000 pg/ml in ascites, as measured by ELISA. As shown by immunohistochemistry, murine CXCL13 was associated with macrophage-like tumor-infiltrating cells that appeared to be histiocytes. Blocking CXCR5 on 2F7 cells with neutralizing antibodies prior to injection into the mice substantially delayed tumor formation. The marked elevations in tumor cell CXCR5 expression and in murine CXCL13 levels seen in the model may potentially identify an important link between tumor-interacting histiocytes and tumor cells in AIDS-BL. These results also identify CXCL13 as a potential biomarker for this disease, which is consistent with previous studies showing that serum levels of CXCL13 were elevated in human subjects who developed AIDS-lymphoma. This mouse model may be useful for future studies on the interactions of the innate immune system and AIDS-BL tumor cells, as well as for the assessment of potential tumor biomarkers for this disease. PMID:23936541

Preconditioning methods influence tumor property in an orthotopic bladder urothelial carcinoma rat model

PubMed Central

MIYAZAKI, KOZO; MORIMOTO, YUJI; NISHIYAMA, NOBUHIRO; SATOH, HIROYUKI; TANAKA, MASAMITSU; SHINOMIYA, NARIYOSHI; ITO, KEIICHI

2014-01-01

Urothelial carcinoma (UC) is an extremely common type of cancer that occurs in the bladder. It has a particularly high rate of recurrence. Therefore, preclinical studies using animal models are essential to determine effective forms of treatment. In the present study, in order to establish an orthotopic bladder UC animal model with clinical relevance, the effects of preconditioning methods on properties of the developed tumor were evaluated. The bladder cavity was pretreated with phosphate-buffered saline (PBS), acid-base, trypsin (TRY) or poly (L-lysine) (PLL) and then rat UC cells (AY-27) (4×106 cells) were inoculated. The results demonstrated that, two weeks later, the tumorigenic rate (88%) and tumor count (2.3 per rat) were not significantly different among the preconditioning methods, whereas tumor volume and invasion depth into bladder tissue were significantly different. Average tumor volumes were >50 mm3 in the PBS and acid-base-treated groups and <10 mm3 in the TRY- and PLL-treated groups. The percentage of invasive tumors (T2 or more advanced stage) was ∼75% of total tumors in the PBS- and acid-base-treated groups, whereas the percentages were reduced in the TRY- and PLL-treated groups (58 and 32%, respectively). Non-invasive tumors (Ta or T1) accounted for 54% of tumors in the PLL-treated group, which was 2-5-fold higher than the percentages in the remaining groups. Properties of the developed tumor in the rat orthotopic UC model were different depending on preconditioning methods. Therefore, different animal models suitable for a discrete preclinical examination may be established by using the appropriate preconditioning condition. PMID:24649309

Levels of murine, but not human, CXCL13 are greatly elevated in NOD-SCID mice bearing the AIDS-associated Burkitt lymphoma cell line, 2F7.

PubMed

Widney, Daniel P; Olafsen, Tove; Wu, Anna M; Kitchen, Christina M R; Said, Jonathan W; Smith, Jeffrey B; Peña, Guadalupe; Magpantay, Larry I; Penichet, Manuel L; Martinez-Maza, Otoniel

2013-01-01

Currently, few rodent models of AIDS-associated non-Hodgkin's lymphoma (AIDS-NHL) exist. In these studies, a novel mouse/human xenograft model of AIDS-associated Burkitt lymphoma (AIDS-BL) was created by injecting cells of the human AIDS-BL cell line, 2F7, intraperitoneally into NOD-SCID mice. Mice developed tumors in the peritoneal cavity, with metastases to the spleen, thymus, and mesenteric lymph nodes. Expression of the chemokine receptor, CXCR5, was greatly elevated in vivo on BL tumor cells in this model, as shown by flow cytometry. CXCL13 is the ligand for CXCR5, and serum and ascites levels of murine, but not human, CXCL13 showed a striking elevation in tumor-bearing mice, with levels as high as 200,000 pg/ml in ascites, as measured by ELISA. As shown by immunohistochemistry, murine CXCL13 was associated with macrophage-like tumor-infiltrating cells that appeared to be histiocytes. Blocking CXCR5 on 2F7 cells with neutralizing antibodies prior to injection into the mice substantially delayed tumor formation. The marked elevations in tumor cell CXCR5 expression and in murine CXCL13 levels seen in the model may potentially identify an important link between tumor-interacting histiocytes and tumor cells in AIDS-BL. These results also identify CXCL13 as a potential biomarker for this disease, which is consistent with previous studies showing that serum levels of CXCL13 were elevated in human subjects who developed AIDS-lymphoma. This mouse model may be useful for future studies on the interactions of the innate immune system and AIDS-BL tumor cells, as well as for the assessment of potential tumor biomarkers for this disease.

A quantitative systems approach to identify paracrine mechanisms that locally suppress immune response to Interleukin-12 in the B16 melanoma model

PubMed Central

Kulkarni, Yogesh M.; Chambers, Emily; McGray, A. J. Robert; Ware, Jason S.; Bramson, Jonathan L.

2012-01-01

Interleukin-12 (IL12) enhances anti-tumor immunity when delivered to the tumor microenvironment. However, local immunoregulatory elements dampen the efficacy of IL12. The identity of these local mechanisms used by tumors to suppress immunosurveillance represents a key knowledge gap for improving tumor immunotherapy. From a systems perspective, local suppression of anti-tumor immunity is a closed-loop system - where system response is determined by an unknown combination of external inputs and local cellular cross-talk. Here, we recreated this closed-loop system in vitro and combined quantitative high content assays, in silico model-based inference, and a proteomic workflow to identify the biochemical cues responsible for immunosuppression. Following an induction period, the B16 melanoma cell model, a transplantable model for spontaneous malignant melanoma, inhibited the response of a T helper cell model to IL12. This paracrine effect was not explained by induction of apoptosis or creation of a cytokine sink, despite both mechanisms present within the co-culture assay. Tumor-derived Wnt-inducible signaling protein-1 (WISP-1) was identified to exert paracrine action on immune cells by inhibiting their response to IL12. Moreover, WISP-1 was expressed in vivo following intradermal challenge with B16F10 cells and was inferred to be expressed at the tumor periphery. Collectively, the data suggest that (1) biochemical cues associated with epithelial-to-mesenchymal transition can shape anti-tumor immunity through paracrine action and (2) remnants of the immunoselective pressure associated with evolution in cancer include both sculpting of tumor antigens and expression of proteins that proactively shape anti-tumor immunity. PMID:22777646

A fractional motion diffusion model for grading pediatric brain tumors.

PubMed

Karaman, M Muge; Wang, He; Sui, Yi; Engelhard, Herbert H; Li, Yuhua; Zhou, Xiaohong Joe

2016-01-01

To demonstrate the feasibility of a novel fractional motion (FM) diffusion model for distinguishing low- versus high-grade pediatric brain tumors; and to investigate its possible advantage over apparent diffusion coefficient (ADC) and/or a previously reported continuous-time random-walk (CTRW) diffusion model. With approval from the institutional review board and written informed consents from the legal guardians of all participating patients, this study involved 70 children with histopathologically-proven brain tumors (30 low-grade and 40 high-grade). Multi- b -value diffusion images were acquired and analyzed using the FM, CTRW, and mono-exponential diffusion models. The FM parameters, D fm , φ , ψ (non-Gaussian diffusion statistical measures), and the CTRW parameters, D m , α , β (non-Gaussian temporal and spatial diffusion heterogeneity measures) were compared between the low- and high-grade tumor groups by using a Mann-Whitney-Wilcoxon U test. The performance of the FM model for differentiating between low- and high-grade tumors was evaluated and compared with that of the CTRW and the mono-exponential models using a receiver operating characteristic (ROC) analysis. The FM parameters were significantly lower ( p  < 0.0001) in the high-grade ( D fm : 0.81 ± 0.26, φ : 1.40 ± 0.10, ψ : 0.42 ± 0.11) than in the low-grade ( D fm : 1.52 ± 0.52, φ : 1.64 ± 0.13, ψ : 0.67 ± 0.13) tumor groups. The ROC analysis showed that the FM parameters offered better specificity (88% versus 73%), sensitivity (90% versus 82%), accuracy (88% versus 78%), and area under the curve (AUC, 93% versus 80%) in discriminating tumor malignancy compared to the conventional ADC. The performance of the FM model was similar to that of the CTRW model. Similar to the CTRW model, the FM model can improve differentiation between low- and high-grade pediatric brain tumors over ADC.

Radiation Response of Cancer Stem-Like Cells From Established Human Cell Lines After Sorting for Surface Markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Al-Assar, Osama; Muschel, Ruth J.; Mantoni, Tine S.

2009-11-15

Purpose: A subpopulation of cancer stem-like cells (CSLC) is hypothesized to exist in different cancer cell lines and to mediate radioresistance in solid tumors. Methods and Materials: Cells were stained for CSLC markers and sorted (fluorescence-activated cell sorter/magnetic beads) to compare foci and radiosensitivity of phosphorylated histone H2AX at Ser 139 (gamma-H2AX) in sorted vs. unsorted populations in eight cell lines from different organs. CSLC properties were examined using anchorage-independent growth and levels of activated Notch1. Validation consisted of testing tumorigenicity and postirradiation enrichment of CSLC in xenograft tumors. Results: The quantity of CSLC was generally in good agreement withmore » primary tumors. CSLC from MDA-MB-231 (breast) and Panc-1 and PSN-1 (both pancreatic) cells had fewer residual gamma-H2AX foci than unsorted cells, pointing to radioresistance of CSLC. However, only MDA-MB-231 CSLC were more radioresistant than unsorted cells. Furthermore, MDA-MB-231 CSLC showed enhanced anchorage-independent growth and overexpression of activated Notch1 protein. The expression of cancer stem cell surface markers in the MDA-MB-231 xenograft model was increased after exposure to fractionated radiation. In contrast to PSN-1 cells, a growth advantage for MDA-MB-231 CSLC xenograft tumors was found compared to tumors arising from unsorted cells. Conclusions: CSLC subpopulations showed no general radioresistant phenotype, despite the quantities of CSLC subpopulations shown to correspond relatively well in other reports. Likewise, CSLC characteristics were found in some but not all of the tested cell lines. The reported problems in testing for CSLC in cell lines may be overcome by additional techniques, beyond sorting for markers.« less

Dual inhibition of Met kinase and angiogenesis to overcome HGF-induced EGFR-TKI resistance in EGFR mutant lung cancer.

PubMed

Takeuchi, Shinji; Wang, Wei; Li, Qi; Yamada, Tadaaki; Kita, Kenji; Donev, Ivan S; Nakamura, Takahiro; Matsumoto, Kunio; Shimizu, Eiji; Nishioka, Yasuhiko; Sone, Saburo; Nakagawa, Takayuki; Uenaka, Toshimitsu; Yano, Seiji

2012-09-01

Acquired resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) is a serious problem in the management of EGFR mutant lung cancer. We recently reported that hepatocyte growth factor (HGF) induces resistance to EGFR-TKIs by activating the Met/PI3K pathway. HGF is also known to induce angiogenesis in cooperation with vascular endothelial growth factor (VEGF), which is an important therapeutic target in lung cancer. Therefore, we hypothesized that dual inhibition of HGF and VEGF may be therapeutically useful for controlling HGF-induced EGFR-TKI-resistant lung cancer. We found that a dual Met/VEGF receptor 2 kinase inhibitor, E7050, circumvented HGF-induced EGFR-TKI resistance in EGFR mutant lung cancer cell lines by inhibiting the Met/Gab1/PI3K/Akt pathway in vitro. HGF stimulated VEGF production by activation of the Met/Gab1 signaling pathway in EGFR mutant lung cancer cell lines, and E7050 showed an inhibitory effect. In a xenograft model, tumors produced by HGF-transfected Ma-1 (Ma-1/HGF) cells were more angiogenic than vector control tumors and showed resistance to gefitinib. E7050 alone inhibited angiogenesis and retarded growth of Ma-1/HGF tumors. E7050 combined with gefitinib induced marked regression of tumor growth. Moreover, dual inhibition of HGF and VEGF by neutralizing antibodies combined with gefitinib also markedly regressed tumor growth. These results indicate the therapeutic rationale of dual targeting of HGF-Met and VEGF-VEGF receptor 2 for overcoming HGF-induced EGFR-TKI resistance in EGFR mutant lung cancer. Copyright © 2012 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

A naive Bayes algorithm for tissue origin diagnosis (TOD-Bayes) of synchronous multifocal tumors in the hepatobiliary and pancreatic system.

PubMed

Jiang, Weiqin; Shen, Yifei; Ding, Yongfeng; Ye, Chuyu; Zheng, Yi; Zhao, Peng; Liu, Lulu; Tong, Zhou; Zhou, Linfu; Sun, Shuo; Zhang, Xingchen; Teng, Lisong; Timko, Michael P; Fan, Longjiang; Fang, Weijia

2018-01-15

Synchronous multifocal tumors are common in the hepatobiliary and pancreatic system but because of similarities in their histological features, oncologists have difficulty in identifying their precise tissue clonal origin through routine histopathological methods. To address this problem and assist in more precise diagnosis, we developed a computational approach for tissue origin diagnosis based on naive Bayes algorithm (TOD-Bayes) using ubiquitous RNA-Seq data. Massive tissue-specific RNA-Seq data sets were first obtained from The Cancer Genome Atlas (TCGA) and ∼1,000 feature genes were used to train and validate the TOD-Bayes algorithm. The accuracy of the model was >95% based on tenfold cross validation by the data from TCGA. A total of 18 clinical cancer samples (including six negative controls) with definitive tissue origin were subsequently used for external validation and 17 of the 18 samples were classified correctly in our study (94.4%). Furthermore, we included as cases studies seven tumor samples, taken from two individuals who suffered from synchronous multifocal tumors across tissues, where the efforts to make a definitive primary cancer diagnosis by traditional diagnostic methods had failed. Using our TOD-Bayes analysis, the two clinical test cases were successfully diagnosed as pancreatic cancer (PC) and cholangiocarcinoma (CC), respectively, in agreement with their clinical outcomes. Based on our findings, we believe that the TOD-Bayes algorithm is a powerful novel methodology to accurately identify the tissue origin of synchronous multifocal tumors of unknown primary cancers using RNA-Seq data and an important step toward more precision-based medicine in cancer diagnosis and treatment. © 2017 UICC.

Mimicking Metastases Including Tumor Stroma: A New Technique to Generate a Three-Dimensional Colorectal Cancer Model Based on a Biological Decellularized Intestinal Scaffold.

PubMed

Nietzer, Sarah; Baur, Florentin; Sieber, Stefan; Hansmann, Jan; Schwarz, Thomas; Stoffer, Carolin; Häfner, Heide; Gasser, Martin; Waaga-Gasser, Ana Maria; Walles, Heike; Dandekar, Gudrun

2016-07-01

Tumor models based on cancer cell lines cultured two-dimensionally (2D) on plastic lack histological complexity and functionality compared to the native microenvironment. Xenogenic mouse tumor models display higher complexity but often do not predict human drug responses accurately due to species-specific differences. We present here a three-dimensional (3D) in vitro colon cancer model based on a biological scaffold derived from decellularized porcine jejunum (small intestine submucosa+mucosa, SISmuc). Two different cell lines were used in monoculture or in coculture with primary fibroblasts. After 14 days of culture, we demonstrated a close contact of human Caco2 colon cancer cells with the preserved basement membrane on an ultrastructural level as well as morphological characteristics of a well-differentiated epithelium. To generate a tissue-engineered tumor model, we chose human SW480 colon cancer cells, a reportedly malignant cell line. Malignant characteristics were confirmed in 2D cell culture: SW480 cells showed higher vimentin and lower E-cadherin expression than Caco2 cells. In contrast to Caco2, SW480 cells displayed cancerous characteristics such as delocalized E-cadherin and nuclear location of β-catenin in a subset of cells. One central drawback of 2D cultures-especially in consideration of drug testing-is their artificially high proliferation. In our 3D tissue-engineered tumor model, both cell lines showed decreased numbers of proliferating cells, thus correlating more precisely with observations of primary colon cancer in all stages (UICC I-IV). Moreover, vimentin decreased in SW480 colon cancer cells, indicating a mesenchymal to epithelial transition process, attributed to metastasis formation. Only SW480 cells cocultured with fibroblasts induced the formation of tumor-like aggregates surrounded by fibroblasts, whereas in Caco2 cocultures, a separate Caco2 cell layer was formed separated from the fibroblast compartment beneath. To foster tissue generation, a bioreactor was constructed for dynamic culture approaches. This induced a close tissue-like association of cultured tumor cells with fibroblasts reflecting tumor biopsies. Therapy with 5-fluorouracil (5-FU) was effective only in 3D coculture. In conclusion, our 3D tumor model reflects human tissue-related tumor characteristics, including lower tumor cell proliferation. It is now available for drug testing in metastatic context-especially for substances targeting tumor-stroma interactions.

An optoacoustic guide with augmented reality system towards precision breast conserving surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lan, Lu; Liu, Kaiming; Xia, Yan; Wu, Jiayingzi; Li, Rui; Wang, Pu; Han, Linda K.; Cheng, Ji-Xin

2017-02-01

Breast-conserving surgery is a well-accepted breast cancer treatment. However, it is still challenging for the surgeon to accurately localize the tumor during the surgery. Also, the guidance provided by current methods is 1 dimensional distance information, which is indirect and not intuitive. Therefore, it creates problems on a large re-excision rate, and a prolonged surgical time. To solve these problems, we have developed a fiber-delivered optoacoustic guide (OG), which mimics the traditional localization guide wire and is preoperatively placed into tumor mass, and an augmented reality (AR) system to provide real-time visualization on the location of the tumor with sub-millimeter variance. By a nano-composite light diffusion sphere and light absorbing layer formed on the tip of an optical fiber, the OG creates an omnidirectional acoustic source inside tumor mass under pulsed laser excitation. The optoacoustic signal generated has a high dynamic range ( 58dB) and spreads in a large apex angle of 320 degrees. Then, an acoustic radar with three ultrasound transducers is attached to the breast skin, and triangulates the location of the OG tip. With an AR system to sense the location of the acoustic radar, the relative position of the OG tip inside the tumor to the AR display is calculated and rendered. This provides direct visual feedback of the tumor location to surgeons, which will greatly ease the surgical planning during the operation and save surgical time. A proof-of-concept experiment using a tablet and a stereo-vision camera is demonstrated and 0.25 mm tracking variance is achieved.

Maintaining tumor targeting accuracy in real-time motion compensation systems for respiration-induced tumor motion.

PubMed

Malinowski, Kathleen; McAvoy, Thomas J; George, Rohini; Dieterich, Sonja; D'Souza, Warren D

2013-07-01

To determine how best to time respiratory surrogate-based tumor motion model updates by comparing a novel technique based on external measurements alone to three direct measurement methods. Concurrently measured tumor and respiratory surrogate positions from 166 treatment fractions for lung or pancreas lesions were analyzed. Partial-least-squares regression models of tumor position from marker motion were created from the first six measurements in each dataset. Successive tumor localizations were obtained at a rate of once per minute on average. Model updates were timed according to four methods: never, respiratory surrogate-based (when metrics based on respiratory surrogate measurements exceeded confidence limits), error-based (when localization error ≥ 3 mm), and always (approximately once per minute). Radial tumor displacement prediction errors (mean ± standard deviation) for the four schema described above were 2.4 ± 1.2, 1.9 ± 0.9, 1.9 ± 0.8, and 1.7 ± 0.8 mm, respectively. The never-update error was significantly larger than errors of the other methods. Mean update counts over 20 min were 0, 4, 9, and 24, respectively. The same improvement in tumor localization accuracy could be achieved through any of the three update methods, but significantly fewer updates were required when the respiratory surrogate method was utilized. This study establishes the feasibility of timing image acquisitions for updating respiratory surrogate models without direct tumor localization.

Preclinical Kinetic Analysis of the Caspase-3/7 PET Tracer 18F-C-SNAT: Quantifying the Changes in Blood Flow and Tumor Retention After Chemotherapy.

PubMed

Palner, Mikael; Shen, Bin; Jeon, Jongho; Lin, Jianguo; Chin, Frederick T; Rao, Jianghong

2015-09-01

Early detection of tumor response to therapy is crucial to the timely identification of the most efficacious treatments. We recently developed a novel apoptosis imaging tracer, (18)F-C-SNAT (C-SNAT is caspase-sensitive nanoaggregation tracer), that undergoes an intramolecular cyclization reaction after cleavage by caspase-3/7, a biomarker of apoptosis. This caspase-3/7-dependent reaction leads to an enhanced accumulation and retention of (18)F activity in apoptotic tumors. This study aimed to fully examine in vivo pharmacokinetics of the tracer through PET imaging and kinetic modeling in a preclinical mouse model of tumor response to systemic anticancer chemotherapy. Tumor-bearing nude mice were treated 3 times with intravenous injections of doxorubicin before undergoing a 120-min dynamic (18)F-C-SNAT PET/CT scan. Time-activity curves were extracted from the tumor and selected organs. A 2-tissue-compartment model was fitted to the time-activity curves from tumor and muscle, using the left ventricle of the heart as input function, and the pharmacokinetic rate constants were calculated. Both tumor uptake (percentage injected dose per gram) and the tumor-to-muscle activity ratio were significantly higher in the treated mice than untreated mice. Pharmacokinetic rate constants calculated by the 2-tissue-compartment model showed a significant increase in delivery and accumulation of the tracer after the systemic chemotherapeutic treatment. Delivery of (18)F-C-SNAT to the tumor tissue, quantified as K1, increased from 0.31 g⋅(mL⋅min)(-1) in untreated mice to 1.03 g⋅(mL⋅min)(-1) in treated mice, a measurement closely related to changes in blood flow. Accumulation of (18)F-C-SNAT, quantified as k3, increased from 0.03 to 0.12 min(-1), proving a higher retention of (18)F-C-SNAT in treated tumors independent from changes in blood flow. An increase in delivery was also found in the muscular tissue of treated mice without increasing accumulation. (18)F-C-SNAT has significantly increased tumor uptake and significantly increased tumor-to-muscle ratio in a preclinical mouse model of tumor therapy. Furthermore, our kinetic modeling of (18)F-C-SNAT shows that chemotherapeutic treatment increased accumulation (k3) in the treated tumors, independent of increased delivery (K1). © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Primary benign brachial plexus tumors: an experience of 115 operated cases.

PubMed

Desai, Ketan I

2012-01-01

Primary benign brachial plexus tumors are rare. They pose a great challenge to the neurosurgeon, because the majority of patients present with minimal or no neurological deficits. Radical to complete excision of the tumor with preservation of neurological function of the involved nerve is an ideal surgical treatment option with benign primary brachial plexus tumor surgery. We present a review article of our 10-year experience with primary benign brachial plexus tumors surgically treated at King Edward Memorial Hospital and P.D. Hinduja National Hospital from 2000 to 2009. The clinical presentations, radiological features, surgical strategies, and the eventual outcome following surgery are analyzed, discussed, and compared with available series in the world literature. Various difficulties and problems faced in the management of primary benign brachial plexus tumors are analyzed. Irrespective of the tumor size, the indications for surgical intervention are also discussed. The goal of our study was to optimize the treatment of patients with benign brachial plexus tumors with minimal neurological deficits. It is of paramount importance that brachial plexus tumors be managed by a peripheral nerve surgeon with expertise and experience in this field to minimize the neurological insult following surgery.

[Bronchopulmonary ACTH-producing tumors].

PubMed

Pikunov, M Iu; Kuznetsov, N S; Latkina, N V; Dobreva, E A; Remizov, O V

2014-01-01

Neuroendocrine tumors have the ability to produce the hormones and vasoactive peptides. Excess of these hormones leads to different symptoms and syndromes because of organs' injuries. Detection of ACTH origin by using of modern diagnostic methods is not always possible. Lungs and bronchi are one of the most frequent localization of ACTH-producing tumors. It is considered that carcinoids with bronchopulmonary localization like a benign tumors in the clinical course. But at the same time carcinoid tends to metastasize, so timely diagnostics and treatment improve quality of life significant and increase the life expectancy of patients. The modern state of diagnostics and surgical treatment problem of ACTH-producing tumors with bronchopulmonary localization is presented in the article. It was described the brief historical background, clinical symptoms, instrumental and biochemical methods of diagnosis. The principles of surgical treatment are presented in the article.

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.

PubMed

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing

2015-11-21

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.

Sensitivity of Tumor Motion Simulation Accuracy to Lung Biomechanical Modeling Approaches and Parameters

PubMed Central

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu

2015-01-01

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the Neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation. PMID:26531324

Oncogenetic tree model of somatic mutations and DNA methylation in colon tumors.

PubMed

Sweeney, Carol; Boucher, Kenneth M; Samowitz, Wade S; Wolff, Roger K; Albertsen, Hans; Curtin, Karen; Caan, Bette J; Slattery, Martha L

2009-01-01

Our understanding of somatic alterations in colon cancer has evolved from a concept of a series of events taking place in a single sequence to a recognition of multiple pathways. An oncogenetic tree is a model intended to describe the pathways and sequence of somatic alterations in carcinogenesis without assuming that tumors will fall in mutually exclusive categories. We applied this model to data on colon tumor somatic alterations. An oncogenetic tree model was built using data on mutations of TP53, KRAS2, APC, and BRAF genes, methylation at CpG sites of MLH1 and TP16 genes, methylation in tumor (MINT) markers, and microsatellite instability (MSI) for 971 colon tumors from a population-based series. Oncogenetic tree analysis resulted in a reproducible tree with three branches. The model represents methylation of MINT markers as initiating a branch and predisposing to MSI, methylation of MHL1 and TP16, and BRAF mutation. APC mutation is the first alteration in an independent branch and is followed by TP53 mutation. KRAS2 mutation was placed a third independent branch, implying that it neither depends on, nor predisposes to, the other alterations. Individual tumors were observed to have alteration patterns representing every combination of one, two, or all three branches. The oncogenetic tree model assumptions are appropriate for the observed heterogeneity of colon tumors, and the model produces a useful visual schematic of the sequence of events in pathways of colon carcinogenesis.

Early experiences of planning stereotactic radiosurgery using 3D printed models of eyes with uveal melanomas

PubMed Central

Furdová, Alena; Sramka, Miron; Thurzo, Andrej; Furdová, Adriana

2017-01-01

Objective The objective of this study was to determine the use of 3D printed model of an eye with intraocular tumor for linear accelerator-based stereotactic radiosurgery. Methods The software for segmentation (3D Slicer) created virtual 3D model of eye globe with tumorous mass based on tissue density from computed tomography and magnetic resonance imaging data. A virtual model was then processed in the slicing software (Simplify3D®) and printed on 3D printer using fused deposition modeling technology. The material that was used for printing was polylactic acid. Results In 2015, stereotactic planning scheme was optimized with the help of 3D printed model of the patient’s eye with intraocular tumor. In the period 2001–2015, a group of 150 patients with uveal melanoma (139 choroidal melanoma and 11 ciliary body melanoma) were treated. The median tumor volume was 0.5 cm3 (0.2–1.6 cm3). The radiation dose was 35.0 Gy by 99% of dose volume histogram. Conclusion The 3D printed model of eye with tumor was helpful in planning the process to achieve the optimal scheme for irradiation which requires high accuracy of defining the targeted tumor mass and critical structures. PMID:28203052

Pharmacokinetic optimization of class-selective histone deacetylase inhibitors and identification of associated candidate predictive biomarkers of hepatocellular carcinoma tumor response.

PubMed

Wong, Jason C; Tang, Guozhi; Wu, Xihan; Liang, Chungen; Zhang, Zhenshan; Guo, Lei; Peng, Zhenghong; Zhang, Weixing; Lin, Xianfeng; Wang, Zhanguo; Mei, Jianghua; Chen, Junli; Pan, Song; Zhang, Nan; Liu, Yongfu; Zhou, Mingwei; Feng, Lichun; Zhao, Weili; Li, Shijie; Zhang, Chao; Zhang, Meifang; Rong, Yiping; Jin, Tai-Guang; Zhang, Xiongwen; Ren, Shuang; Ji, Ying; Zhao, Rong; She, Jin; Ren, Yi; Xu, Chunping; Chen, Dawei; Cai, Jie; Shan, Song; Pan, Desi; Ning, Zhiqiang; Lu, Xianping; Chen, Taiping; He, Yun; Chen, Li

2012-10-25

Herein, we describe the pharmacokinetic optimization of a series of class-selective histone deacetylase (HDAC) inhibitors and the subsequent identification of candidate predictive biomarkers of hepatocellular carcinoma (HCC) tumor response for our clinical lead using patient-derived HCC tumor xenograft models. Through a combination of conformational constraint and scaffold hopping, we lowered the in vivo clearance (CL) and significantly improved the bioavailability (F) and exposure (AUC) of our HDAC inhibitors while maintaining selectivity toward the class I HDAC family with particular potency against HDAC1, resulting in clinical lead 5 (HDAC1 IC₅₀ = 60 nM, mouse CL = 39 mL/min/kg, mouse F = 100%, mouse AUC after single oral dose at 10 mg/kg = 6316 h·ng/mL). We then evaluated 5 in a biomarker discovery pilot study using patient-derived tumor xenograft models, wherein two out of the three models responded to treatment. By comparing tumor response status to compound tumor exposure, induction of acetylated histone H3, candidate gene expression changes, and promoter DNA methylation status from all three models at various time points, we identified preliminary candidate response prediction biomarkers that warrant further validation in a larger cohort of patient-derived tumor models and through confirmatory functional studies.

Science to practice: Can we expand focal interventional oncologic ablation treatments into an effective systemic therapy?

PubMed

Goldberg, S Nahum

2013-05-01

Hamamoto et al (1) were able to demonstrate that combination therapy of a lung tumor by using radiofrequency ablation (RFA) with local injection of an immunostimulant, OK-432, resulted in improved survival when compared with other therapies tested in a VX2 rabbit model. In addition, not only was greater tumor regression seen in a second distant ear tumor implanted prior to the therapy, but also reduced tumor growth was seen when a second tumor implantation (ie, rechallenge) was attempted. These factors strongly suggest the successful activation of systemic antitumor immunity using this approach in this specific tumor model.

A novel pre-clinical in vivo mouse model for malignant brain tumor growth and invasion.

PubMed

Shelton, Laura M; Mukherjee, Purna; Huysentruyt, Leanne C; Urits, Ivan; Rosenberg, Joshua A; Seyfried, Thomas N

2010-09-01

Glioblastoma multiforme (GBM) is a rapidly progressive disease of morbidity and mortality and is the most common form of primary brain cancer in adults. Lack of appropriate in vivo models has been a major roadblock to developing effective therapies for GBM. A new highly invasive in vivo GBM model is described that was derived from a spontaneous brain tumor (VM-M3) in the VM mouse strain. Highly invasive tumor cells could be identified histologically on the hemisphere contralateral to the hemisphere implanted with tumor cells or tissue. Tumor cells were highly expressive for the chemokine receptor CXCR4 and the proliferation marker Ki-67 and could be identified invading through the pia mater, the vascular system, the ventricular system, around neurons, and over white matter tracts including the corpus callosum. In addition, the brain tumor cells were labeled with the firefly luciferase gene, allowing for non-invasive detection and quantitation through bioluminescent imaging. The VM-M3 tumor has a short incubation time with mortality occurring in 100% of the animals within approximately 15 days. The VM-M3 brain tumor model therefore can be used in a pre-clinical setting for the rapid evaluation of novel anti-invasive therapies.

Sponge-supported cultures of primary head and neck tumors for an optimized preclinical model.

PubMed

Dohmen, Amy J C; Sanders, Joyce; Canisius, Sander; Jordanova, Ekaterina S; Aalbersberg, Else A; van den Brekel, Michiel W M; Neefjes, Jacques; Zuur, Charlotte L

2018-05-18

Treatment of advanced head and neck cancer is associated with low survival, high toxicity and a widely divergent individual response. The sponge-gel-supported histoculture model was previously developed to serve as a preclinical model for predicting individual treatment responses. We aimed to optimize the sponge-gel-supported histoculture model and provide more insight in cell specific behaviour by evaluating the tumor and its microenvironment using immunohistochemistry. We collected fresh tumor biopsies from 72 untreated patients and cultured them for 7 days. Biopsies from 57 patients (79%) were successfully cultured and 1451 tumor fragments (95.4%) were evaluated. Fragments were scored for percentage of tumor, tumor viability and proliferation, EGF-receptor expression and presence of T-cells and macrophages. Median tumor percentage increased from 53% at day 0 to 80% at day 7. Viability and proliferation decreased after 7 days, from 90% to 30% and from 30% to 10%, respectively. Addition of EGF, folic acid and hydrocortisone can lead to improved viability and proliferation, however this was not systematically observed. No patient subgroup could be identified with higher culture success rates. Immune cells were still present at day 7, illustrating that the tumor microenvironment is sustained. EGF supplementation did not increase viability and proliferation in patients overexpressing EGF-Receptor.

Tetrahedral node for Transmission-Line Modeling (TLM) applied to Bio-heat Transfer.

PubMed

Milan, Hugo F M; Gebremedhin, Kifle G

2016-12-01

Transmission-Line Modeling (TLM) is a numerical method used to solve complex and time-domain bio-heat transfer problems. In TLM, parallelepipeds are used to discretize three-dimensional problems. The drawback in using parallelepiped shapes is that instead of refining only the domain of interest, a large additional domain would also have to be refined, which results in increased computational time and memory space. In this paper, we developed a tetrahedral node for TLM applied to bio-heat transfer that does not have the drawback associated with the parallelepiped node. The model includes heat source, blood perfusion, boundary conditions and initial conditions. The boundary conditions could be adiabatic, temperature, heat flux, or convection. The predicted temperature and heat flux were compared against results from an analytical solution and the results agreed within 2% for a mesh size of 69,941 nodes and a time step of 5ms. The method was further validated against published results of maximum skin-surface temperature difference in a breast with and without tumor and the results agreed within 6%. The published results were obtained from a model that used parallelepiped TLM node. An open source software, TLMBHT, was written using the theory developed herein and is available for download free-of-charge. Copyright © 2016 Elsevier Ltd. All rights reserved.

A drug-delivery strategy for overcoming drug resistance in breast cancer through targeting of oncofetal fibronectin.

PubMed

Saw, Phei Er; Park, Jinho; Jon, Sangyong; Farokhzad, Omid C

2017-02-01

A major problem with cancer chemotherapy begins when cells acquire resistance. Drug-resistant cancer cells typically upregulate multi-drug resistance proteins such as P-glycoprotein (P-gp). However, the lack of overexpressed surface biomarkers has limited the targeted therapy of drug-resistant cancers. Here we report a drug-delivery carrier decorated with a targeting ligand for a surface marker protein extra-domain B(EDB) specific to drug-resistant breast cancer cells as a new therapeutic option for the aggressive cancers. We constructed EDB-specific aptide (APT EDB )-conjugated liposome to simultaneously deliver siRNA(siMDR1) and Dox to drug-resistant breast cancer cells. APT EDB -LS(Dox,siMDR1) led to enhanced delivery of payloads into MCF7/ADR cells and showed significantly higher accumulation and retention in the tumors. While either APT EDB -LS(Dox) or APT EDB -LS(siMDR1) did not lead to appreciable tumor retardation in MCF7/ADR orthotropic model, APT EDB -LS(Dox,siMDR1) treatment resulted in significant reduction of the drug-resistant breast tumor. Taken together, this study provides a new strategy of drug delivery for drug-resistant cancer therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Distant failure prediction for early stage NSCLC by analyzing PET with sparse representation

NASA Astrophysics Data System (ADS)

Hao, Hongxia; Zhou, Zhiguo; Wang, Jing

2017-03-01

Positron emission tomography (PET) imaging has been widely explored for treatment outcome prediction. Radiomicsdriven methods provide a new insight to quantitatively explore underlying information from PET images. However, it is still a challenging problem to automatically extract clinically meaningful features for prognosis. In this work, we develop a PET-guided distant failure predictive model for early stage non-small cell lung cancer (NSCLC) patients after stereotactic ablative radiotherapy (SABR) by using sparse representation. The proposed method does not need precalculated features and can learn intrinsically distinctive features contributing to classification of patients with distant failure. The proposed framework includes two main parts: 1) intra-tumor heterogeneity description; and 2) dictionary pair learning based sparse representation. Tumor heterogeneity is initially captured through anisotropic kernel and represented as a set of concatenated vectors, which forms the sample gallery. Then, given a test tumor image, its identity (i.e., distant failure or not) is classified by applying the dictionary pair learning based sparse representation. We evaluate the proposed approach on 48 NSCLC patients treated by SABR at our institute. Experimental results show that the proposed approach can achieve an area under the characteristic curve (AUC) of 0.70 with a sensitivity of 69.87% and a specificity of 69.51% using a five-fold cross validation.

A true orthotopic gastric cancer murine model using electrocoagulation.

PubMed

Bhullar, Jasneet Singh; Makarawo, Tafadzwa; Subhas, Gokulakkrishna; Alomari, Ahmed; Silberberg, Boris; Tilak, Jacqueline; Decker, Milessa; Mittal, Vijay K

2013-07-01

Orthotopic mouse models of human gastric cancer represent an important in vivo tool for testing chemotherapeutic agents and for studying intraluminal factors. Currently, orthotopic mouse models of gastric cancer require an operative procedure involving either injection or implantation of tumor cells in stomach layers. The resultant tumor does not grow from the stomach's mucosal surface, so it does not mimic the human disease process. A low-dose gastric mucosal coagulation was done transorally in the body of stomach using a specially designed polyethylene catheter in 16 female severe combined immunodeficient mice. This was followed by the instillation of SNU-16 human gastric cancer tumor cells (1 × 10(6) cells). Five mice each were euthanized at 1 and 2 months, and 6 mice were euthanized at 3 months. Three control mice underwent electrocoagulation alone and 3 mice underwent cell line instillation alone. Tumors were detected in 11 of 16 experimental mice, but not in the control mice. Tumors were noted in mice at 1 month. Over time, there was an increase in tumor growth and metastasis to lymph nodes and surrounding organs. Histopathologic evaluation showed that the tumors grew from the gastric mucosa. Our model is easy to create and overcomes the limitations of the existing models, as the tumor arises from the stomach's mucosal layer and mimics the human disease in terms of morphology and biologic behavior. This is the first report of a true orthotopic gastric cancer murine model. This model opens new doors for additional studies that were not possible earlier. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Traction patterns of tumor cells.

PubMed

Ambrosi, D; Duperray, A; Peschetola, V; Verdier, C

2009-01-01

The traction exerted by a cell on a planar deformable substrate can be indirectly obtained on the basis of the displacement field of the underlying layer. The usual methodology used to address this inverse problem is based on the exploitation of the Green tensor of the linear elasticity problem in a half space (Boussinesq problem), coupled with a minimization algorithm under force penalization. A possible alternative strategy is to exploit an adjoint equation, obtained on the basis of a suitable minimization requirement. The resulting system of coupled elliptic partial differential equations is applied here to determine the force field per unit surface generated by T24 tumor cells on a polyacrylamide substrate. The shear stress obtained by numerical integration provides quantitative insight of the traction field and is a promising tool to investigate the spatial pattern of force per unit surface generated in cell motion, particularly in the case of such cancer cells.

3D tumor microtissues as an in vitro testing platform for microenvironmentally-triggered drug delivery systems.

PubMed

Brancato, Virginia; Gioiella, Filomena; Profeta, Martina; Imparato, Giorgia; Guarnieri, Daniela; Urciuolo, Francesco; Melone, Pietro; Netti, Paolo A

2017-07-15

Therapeutic approaches based on nanomedicine have garnered great attention in cancer research. In vitro biological models that better mimic in vivo conditions are crucial tools to more accurately predict their therapeutic efficacy in vivo. In this work, a new 3D breast cancer microtissue has been developed to recapitulate the complexity of the tumor microenvironment and to test its efficacy as screening platform for drug delivery systems. The proposed 3D cancer model presents human breast adenocarcinoma cells and cancer-associated fibroblasts embedded in their own ECM, thus showing several features of an in vivo tumor, such as overexpression of metallo-proteinases (MMPs). After demonstrating at molecular and protein level the MMP2 overexpression in such tumor microtissues, we used them to test a recently validated formulation of endogenous MMP2-responsive nanoparticles (NP). The presence of the MMP2-sensitive linker allows doxorubicin release from NP only upon specific enzymatic cleavage of the peptide. The same NP without the MMP-sensitive linker and healthy breast microtissues were also produced to demonstrate NP specificity and selectivity. Cell viability after NP treatment confirmed that controlled drug delivery is achieved only in 3D tumor microtissues suggesting that the validation of therapeutic strategies in such 3D tumor model could predict human response. A major issue of modern cancer research is the development of accurate and predictive experimental models of human tumors consistent with tumor microenvironment and applicable as screening platforms for novel therapeutic strategies. In this work, we developed and validated a new 3D microtissue model of human breast tumor as a testing platform of anti-cancer drug delivery systems. To this aim, biodegradable nanoparticles responsive to physiological changes specifically occurring in tumor microenvironment were used. Our findings clearly demonstrate that the breast tumor microtissue well recapitulates in vivo physiological features of tumor tissue and elicits a specific response to microenvironmentally-responsive nanoparticles compared to healthy tissue. We believe this study is of particular interest for cancer research and paves the way to exploit tumor microtissues for several testing purposes. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Development and Preclinical Application of an Immunocompetent Transplant Model of Basal Breast Cancer with Lung, Liver and Brain Metastases

PubMed Central

Hoenerhoff, Mark; Hixon, Julie A.; Durum, Scott K.; Qiu, Ting-hu; He, Siping; Burkett, Sandra; Liu, Zi-Yao; Swanson, Steven M.; Green, Jeffrey E.

2016-01-01

Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer that is associated with a poor prognosis and for which no targeted therapies currently exist. In order to improve preclinical testing for TNBC that relies primarily on using human xenografts in immunodeficient mice, we have developed a novel immunocompetent syngeneic murine tumor transplant model for basal-like triple-negative breast cancer. The C3(1)/SV40-T/t-antigen (C3(1)/Tag) mouse mammary tumor model in the FVB/N background shares important similarities with human basal-like TNBC. However, these tumors or derived cell lines are rejected when transplanted into wt FVB/N mice, likely due to the expression of SV40 T-antigen. We have developed a sub-line of mice (designated REAR mice) that carry only one copy of the C3(1)/Tag-antigen transgene resulting from a spontaneous transgene rearrangement in the original founder line. Unlike the original C3(1)/Tag mice, REAR mice do not develop mammary tumors or other phenotypes observed in the original C3(1)/Tag transgenic mice. REAR mice are more immunologically tolerant to SV40 T-antigen driven tumors and cell lines in an FVB/N background (including prostate tumors from TRAMP mice), but are otherwise immunologically intact. This transplant model system offers the ability to synchronously implant the C3(1)/Tag tumor-derived M6 cell line or individual C3(1)/Tag tumors from various stages of tumor development into the mammary fat pads or tail veins of REAR mice. C3(1)/Tag tumors or M6 cells implanted into the mammary fat pads spontaneously metastasize at a high frequency to the lung and liver. M6 cells injected by tail vein can form brain metastases. We demonstrate that irradiated M6 tumor cells or the same cells expressing GM-CSF can act as a vaccine to retard tumor growth of implanted tumor cells in the REAR model. Preclinical studies performed in animals with an intact immune system should more authentically replicate treatment responses in human patients. PMID:27171183

Identifying tumor vascular permeability heterogeneity using reduced encoding techniques

NASA Astrophysics Data System (ADS)

Aref, Michael

We test the hypothesis that the loss of spatial resolution to gain temporal resolution in clinical dynamic contrast enhanced (DCE) magnetic resonance mammography (MRM) causes partial volume effects that yield inaccurate permeability-surface area products (PS = Kp↔t) which results in erroneous diagnostic information and we offer a potential solution using reduced encoding techniques to solve this problem. We compared the PS obtained from DCE MRI at clinical MRI resolutions (2500 x 2500 mum resolution), to that obtained from resolutions analogous to histopathological in plane resolutions (938 x 938 mum and 469 x 469 mum resolution). Secondly, we determined the accuracy of PS obtained from Keyhole, Ṟeduced-encoding I&barbelow;maging by G&barbelow;eneralized-series Ṟeconstruction (RIGR), and Ṯwo-reference RIGR (TRIGR) using high-resolution baseline data (469 x 469 mum resolution) and clinical resolution dynamic data (2500 x 2500 mum resolution). Lastly, we statistically correlated two-compartment model fitting parameters (tumor EES volume fraction, ve, tumor plasma volume fraction, vp, and PS) obtained from DCE MRI at all three resolutions to histopathologically determined tumor diagnosis. In our model, female Sprague Dawley rats with N-ethyl-N-nitrosourea (ENU) induced mammary tumors imaged with fast T1-weighted gradient echo DCE MRI following a Gd-DTPA injection, there is a window of resolutions that detects similar PS "hot spots" compared to those obtained from the clinical imager resolution. The top five PS "hot spots" obtained from 469 mum resolution FFT are statistically different from those at 938 mum resolution FFT, p = 0.0014, and 2500 mum resolution FFT, p < 0.0001. Keyhole when compared with a FFT of similar resolution does not detect PS "hot spots" of similar value, p = 0.0002. PS "hot spots" obtained from RIGR compared to those from FFT are statistically the same value, p = 0.2734, but do not statistically agree on the location of mapped values. The top five Kp↔t/VT "hot spots" and their corresponding ve can statistically differentiate invasive ductal carcinoma from non-invasive papillary carcinoma for the 469 mum and 938 mum resolution, p = 0.0017 and p = 0.0047, respectively, but not for 2500 mum resolution, p = 0.9008.

A model of tumor architecture and spatial interactions with tumor microenvironment in breast carcinoma

NASA Astrophysics Data System (ADS)

Ben Cheikh, Bassem; Bor-Angelier, Catherine; Racoceanu, Daniel

2017-03-01

Breast carcinomas are cancers that arise from the epithelial cells of the breast, which are the cells that line the lobules and the lactiferous ducts. Breast carcinoma is the most common type of breast cancer and can be divided into different subtypes based on architectural features and growth patterns, recognized during a histopathological examination. Tumor microenvironment (TME) is the cellular environment in which tumor cells develop. Being composed of various cell types having different biological roles, TME is recognized as playing an important role in the progression of the disease. The architectural heterogeneity in breast carcinomas and the spatial interactions with TME are, to date, not well understood. Developing a spatial model of tumor architecture and spatial interactions with TME can advance our understanding of tumor heterogeneity. Furthermore, generating histological synthetic datasets can contribute to validating, and comparing analytical methods that are used in digital pathology. In this work, we propose a modeling method that applies to different breast carcinoma subtypes and TME spatial distributions based on mathematical morphology. The model is based on a few morphological parameters that give access to a large spectrum of breast tumor architectures and are able to differentiate in-situ ductal carcinomas (DCIS) and histological subtypes of invasive carcinomas such as ductal (IDC) and lobular carcinoma (ILC). In addition, a part of the parameters of the model controls the spatial distribution of TME relative to the tumor. The validation of the model has been performed by comparing morphological features between real and simulated images.

[Inhibitory effect of Xiaotan Sanjie Recipe on the microsatellite instability of orthotopic transplantation tumor in MKN-45 human gastric cancer nude mice].

PubMed

Ye, Min; Sun, Da-Zhi; Wei, Pin-kang

2014-05-01

To study the inhibitory effect of Xiaotan Sanjie Recipe (XSR) on the microsatellite instability of orthotopic transplantation tumor in MKN-45 human gastric cancer nude mice. The 3rd passage subcutaneous transplantation tumor was taken as the origin of the model by using MKN-45 human gastric cancer cell lines. MKN-45 human gastric cancer nude mouse model was established using OB glue adhesive method. Then 30 nude mice were divided into the model group, the XSR group, and the chemotherapy group. Mice in the XSR group were intragastrically given XSR at the daily dose of 0.4 mL. Mice in the chemotherapy group were intragastrically given Fluorouracil at the daily dose of 0.4 mL. No intervention was given to mice in the model group. After 6 weeks of medication, the tumor weight was measured, and the tumor inhibition rate calculated. The size, the peak height, and the peak area of 5 microsatellite instability sites were detected. The tumor inhibition rate was 40. 84% in the XSR group. The tumor weight was significantly lower in the XSR group than in the model group (P < 0.01), showing no statistical difference when compared with the chemotherapy group (P >0.05). The incidence of high microsatellite instability (MSI-H) in the model group was 70%, and the incidence of low microsatellite instability (MSI-L) was 30%. Microsatellite stable site tended be stable after 6 weeks of XSR treatment. XSR showed inhibition on microsatellite instable orthotopic transplantation tumor in MKN-45 human gastric cancer nude mice.

Comparison of Allogeneic and Syngeneic Rat Glioma Models by Using MRI and Histopathologic Evaluation.

PubMed

Biasibetti, Elena; Valazza, Alberto; Capucchio, Maria T; Annovazzi, Laura; Battaglia, Luigi; Chirio, Daniela; Gallarate, Marina; Mellai, Marta; Muntoni, Elisabetta; Peira, Elena; Riganti, Chiara; Schiffer, Davide; Panciani, Pierpaolo; Lanotte, Michele

2017-03-01

Research in neurooncology traditionally requires appropriate in vivo animal models, on which therapeutic strategies are tested before human trials are designed and proceed. Several reproducible animal experimental models, in which human physiologic conditions can be mimicked, are available for studying glioblastoma multiforme. In an ideal rat model, the tumor is of glial origin, grows in predictable and reproducible patterns, closely resembles human gliomas histopathologically, and is weakly or nonimmunogenic. In the current study, we used MRI and histopathologic evaluation to compare the most widely used allogeneic rat glioma model, C6-Wistar, with the F98-Fischer syngeneic rat glioma model in terms of percentage tumor growth or regression and growth rate. In vivo MRI demonstrated considerable variation in tumor volume and frequency between the 2 rat models despite the same stereotactic implantation technique. Faster and more reproducible glioma growth occurred in the immunoresponsive environment of the F98-Fischer model, because the immune response is minimized toward syngeneic cells. The marked inability of the C6-Wistar allogeneic system to generate a reproducible model and the episodes of spontaneous tumor regression with this system may have been due to the increased humoral and cellular immune responses after tumor implantation.

Polyphenols in brewed green tea inhibit prostate tumor xenograft growth by localizing to the tumor and decreasing oxidative stress and angiogenesis

PubMed Central

Henning, Susanne M.; Wang, Piwen; Said, Jonathan; Magyar, Clara; Castor, Brandon; Doan, Ngan; Tosity, Carmen; Moro, Aune; Gao, Kun; Li, Luyi; Heber, David

2011-01-01

It has been demonstrated in various animal models that the oral administration of green tea (GT) extracts in drinking water can inhibit tumor growth, but the effects of brewed GT on factors promoting tumor growth, including oxidant damage of DNA and protein, angiogenesis, and DNA methylation, have not been tested in an animal model. To explore these potential mechanisms, brewed GT was administered instead of drinking water to male severe combined immunodeficiency (SCID) mice with androgen-dependent human LAPC4 prostate cancer cell subcutaneous xenografts. Tumor volume was decreased significantly in mice consuming GT, and tumor size was significantly correlated with GT polyphenol (GTP) content in tumor tissue. There was a significant reduction in hypoxia-inducible factor 1-alpha and vascular endothelial growth factor protein expression. GT consumption significantly reduced oxidative DNA and protein damage in tumor tissue as determined by 8-hydroxydeoxyguanosine/deoxyguanosine ratio and protein carbonyl assay, respectively. Methylation is known to inhibit antioxidative enzymes such as glutathione S-transferase pi (GSTp1) to permit reactive oxygen species promotion of tumor growth. GT inhibited tumor 5-cytosine DNA methyltransferase 1 (DNMT1) mRNA and protein expression significantly, which may contribute to the inhibition of tumor growth by reactivation of antioxidative enzymes. This study advances our understanding of tumor growth inhibition by brewed GT in an animal model by demonstrating tissue localization of GTPs in correlation with inhibition of tumor growth. Our results suggest that the inhibition of tumor growth is due to GTP-mediated inhibition of oxidative stress and angiogenesis in the LAPC4 xenograft prostate tumor in SCID mice. PMID:22405694

Direct Extraction of Tumor Response Based on Ensemble Empirical Mode Decomposition for Image Reconstruction of Early Breast Cancer Detection by UWB.

PubMed

Li, Qinwei; Xiao, Xia; Wang, Liang; Song, Hang; Kono, Hayato; Liu, Peifang; Lu, Hong; Kikkawa, Takamaro

2015-10-01

A direct extraction method of tumor response based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by ultra-wide band (UWB) microwave imaging. With this approach, the image reconstruction for the tumor detection can be realized with only extracted signals from as-detected waveforms. The calibration process executed in the previous research for obtaining reference waveforms which stand for signals detected from the tumor-free model is not required. The correctness of the method is testified by successfully detecting a 4 mm tumor located inside the glandular region in one breast model and by the model located at the interface between the gland and the fat, respectively. The reliability of the method is checked by distinguishing a tumor buried in the glandular tissue whose dielectric constant is 35. The feasibility of the method is confirmed by showing the correct tumor information in both simulation results and experimental results for the realistic 3-D printed breast phantom.

Longitudinal Assessment of Lung Cancer Progression in Mice Using the Sodium Iodide Symporter Reporter Gene and SPECT/CT Imaging.

PubMed

Price, Dominique N; McBride, Amber A; Anton, Martina; Kusewitt, Donna F; Norenberg, Jeffrey P; MacKenzie, Debra A; Thompson, Todd A; Muttil, Pavan

2016-01-01

Lung cancer has the highest mortality rate of any tissue-specific cancer in both men and women. Research continues to investigate novel drugs and therapies to mitigate poor treatment efficacy, but the lack of a good descriptive lung cancer animal model for preclinical drug evaluation remains an obstacle. Here we describe the development of an orthotopic lung cancer animal model which utilizes the human sodium iodide symporter gene (hNIS; SLC5A5) as an imaging reporter gene for the purpose of non-invasive, longitudinal tumor quantification. hNIS is a glycoprotein that naturally transports iodide (I-) into thyroid cells and has the ability to symport the radiotracer 99mTc-pertechnetate (99mTcO4-). A549 lung adenocarcinoma cells were genetically modified with plasmid or lentiviral vectors to express hNIS. Modified cells were implanted into athymic nude mice to develop two tumor models: a subcutaneous and an orthotopic xenograft tumor model. Tumor progression was longitudinally imaged using SPECT/CT and quantified by SPECT voxel analysis. hNIS expression in lung tumors was analyzed by quantitative real-time PCR. Additionally, hematoxylin and eosin staining and visual inspection of pulmonary tumors was performed. We observed that lentiviral transduction provided enhanced and stable hNIS expression in A549 cells. Furthermore, 99mTcO4- uptake and accumulation was observed within lung tumors allowing for imaging and quantification of tumor mass at two-time points. This study illustrates the development of an orthotopic lung cancer model that can be longitudinally imaged throughout the experimental timeline thus avoiding inter-animal variability and leading to a reduction in total animal numbers. Furthermore, our orthotopic lung cancer animal model is clinically relevant and the genetic modification of cells for SPECT/CT imaging can be translated to other tissue-specific tumor animal models.

Longitudinal Assessment of Lung Cancer Progression in Mice Using the Sodium Iodide Symporter Reporter Gene and SPECT/CT Imaging

PubMed Central

Anton, Martina; Kusewitt, Donna F.; Norenberg, Jeffrey P.; MacKenzie, Debra A.; Thompson, Todd A.; Muttil, Pavan

2016-01-01

Lung cancer has the highest mortality rate of any tissue-specific cancer in both men and women. Research continues to investigate novel drugs and therapies to mitigate poor treatment efficacy, but the lack of a good descriptive lung cancer animal model for preclinical drug evaluation remains an obstacle. Here we describe the development of an orthotopic lung cancer animal model which utilizes the human sodium iodide symporter gene (hNIS; SLC5A5) as an imaging reporter gene for the purpose of non-invasive, longitudinal tumor quantification. hNIS is a glycoprotein that naturally transports iodide (I-) into thyroid cells and has the ability to symport the radiotracer 99mTc-pertechnetate (99mTcO4-). A549 lung adenocarcinoma cells were genetically modified with plasmid or lentiviral vectors to express hNIS. Modified cells were implanted into athymic nude mice to develop two tumor models: a subcutaneous and an orthotopic xenograft tumor model. Tumor progression was longitudinally imaged using SPECT/CT and quantified by SPECT voxel analysis. hNIS expression in lung tumors was analyzed by quantitative real-time PCR. Additionally, hematoxylin and eosin staining and visual inspection of pulmonary tumors was performed. We observed that lentiviral transduction provided enhanced and stable hNIS expression in A549 cells. Furthermore, 99mTcO4- uptake and accumulation was observed within lung tumors allowing for imaging and quantification of tumor mass at two-time points. This study illustrates the development of an orthotopic lung cancer model that can be longitudinally imaged throughout the experimental timeline thus avoiding inter-animal variability and leading to a reduction in total animal numbers. Furthermore, our orthotopic lung cancer animal model is clinically relevant and the genetic modification of cells for SPECT/CT imaging can be translated to other tissue-specific tumor animal models. PMID:28036366

Quantitative Primary Tumor Indocyanine Green Measurements Predict Osteosarcoma Metastatic Lung Burden in a Mouse Model.

PubMed

Fourman, Mitchell S; Mahjoub, Adel; Mandell, Jon B; Yu, Shibing; Tebbets, Jessica C; Crasto, Jared A; Alexander, Peter E; Weiss, Kurt R

2018-03-01

Current preclinical osteosarcoma (OS) models largely focus on quantifying primary tumor burden. However, most fatalities from OS are caused by metastatic disease. The quantification of metastatic OS currently relies on CT, which is limited by motion artifact, requires intravenous contrast, and can be technically demanding in the preclinical setting. We describe the ability for indocyanine green (ICG) fluorescence angiography to quantify primary and metastatic OS in a previously validated orthotopic, immunocompetent mouse model. (1) Can near-infrared ICG fluorescence be used to attach a comparable, quantitative value to the primary OS tumor in our experimental mouse model? (2) Will primary tumor fluorescence differ in mice that go on to develop metastatic lung disease? (3) Does primary tumor fluorescence correlate with tumor volume measured with CT? Six groups of 4- to 6-week-old immunocompetent Balb/c mice (n = 6 per group) received paraphyseal injections into their left hindlimb proximal tibia consisting of variable numbers of K7M2 mouse OS cells. A hindlimb transfemoral amputation was performed 4 weeks after injection with euthanasia and lung extraction performed 10 weeks after injection. Histologic examination of lung and primary tumor specimens confirmed ICG localization only within the tumor bed. Mice with visible or palpable tumor growth had greater hindlimb fluorescence (3.5 ± 2.3 arbitrary perfusion units [APU], defined as the fluorescence pixel return normalized by the detector) compared with those with a negative examination (0.71 ± 0.38 APU, -2.7 ± 0.5 mean difference, 95% confidence interval -3.7 to -1.8, p < 0.001). A strong linear trend (r = 0.81, p < 0.01) was observed between primary tumor and lung fluorescence, suggesting that quantitative ICG tumor fluorescence is directly related to eventual metastatic burden. We did not find a correlation (r = 0.04, p = 0.45) between normalized primary tumor fluorescence and CT volumetric measurements. We demonstrate a novel methodology for quantifying primary and metastatic OS in a previously validated, immunocompetent, orthotopic mouse model. Quantitative fluorescence of the primary tumor with ICG angiography is linearly related to metastatic burden, a relationship that does not exist with respect to clinical tumor size. This highlights the potential utility of ICG near-infrared fluorescence imaging as a valuable preclinical proof-of-concept modality. Future experimental work will use this model to evaluate the efficacy of novel OS small molecule inhibitors. Given the histologic localization of ICG to only the tumor bed, we envision the clinical use of ICG angiography as an intraoperative margin and tumor detector. Such a tool may be used as an alternative to intraoperative histology to confirm negative primary tumor margins or as a valuable tool for debulking surgeries in vulnerable anatomic locations. Because we have demonstrated the successful preservation of ICG in frozen tumor samples, future work will focus on blinded validation of this modality in observational human trials, comparing the ICG fluorescence of harvested tissue samples with fresh frozen pathology.

Measurement of telomerase activity in dog tumors.

PubMed

Yazawa, M; Okuda, M; Setoguchi, A; Nishimura, R; Sasaki, N; Hasegawa, A; Watari, T; Tsujimoto, H

1999-10-01

Telomeres are specific structures present at the end of liner chromosomes. DNA polymerase can not synthesize the end of liner DNA and, as a result, the telomeres become progressively shortened by successive cell divisions. To overcome the end replication problem, telomerase adds new telomeric sequences to the end of chromosomal DNA. The enzyme activity is undetectable in most normal human adult somatic cells, in which shortening of the telomere is thought to limit the somatic-cell life span. In contrast to normal somatic cells, many human tumors possess telomerase activity. The present study looked at whether telomerase activity might serve as a marker for canine tumors. Telomerase activity was measured using the telomeric repeat amplification protocol assay. Normal dog somatic tissues showed little or no telomerase activity, while normal testis exhibited a high level of telomerase activity. We measured telomerase activity in tumor samples from 45 dogs; 21 mammary gland tumors, 16 tumors developed in the skin and oral cavity, 7 vascular tumors and 1 Sertoli cell tumor. Greater than 95% of the tumor samples contained telomerase activity (3-924 U/2 micrograms protein). The results obtained in this study indicated that telomerase should be a useful diagnostic marker for a variety of dog tumors, and it may serve as a target for antitumor chemotherapy.

Theoretic criteria for antibody penetration into solid tumors and micrometastases.

PubMed

Thurber, Greg M; Zajic, Stefan C; Wittrup, K Dane

2007-06-01

Targeting tumors with antibody-based therapeutics is a complex task presenting multiple kinetic barriers. Antibody internalization and clearance inhibit uptake both in solid tumors, limited by tumor vascular permeability, and in micrometastases, limited by diffusion. A modeling exercise is used to introduce 2 simple criteria that must be less than unity for saturation of both tumors and micrometastases. The clearance modulus and the Thiele modulus are ratios of the plasma clearance rate and antibody catabolism, respectively, to the tumor tissue penetration rate. Even low rates of antigen internalization from constitutive membrane turnover can significantly retard antibody penetration. Rapid clearance of single-chain variable fragments also hinders uptake, often more than counterbalancing their more rapid extravasation and diffusion. The model illustrates that with the large resistance from the tumor capillary, antibodies may be more suitable for targeting micrometastases than vascularized tumors.

Biochemomechanical poroelastic theory of avascular tumor growth

NASA Astrophysics Data System (ADS)

Xue, Shi-Lei; Li, Bo; Feng, Xi-Qiao; Gao, Huajian

2016-09-01

Tumor growth is a complex process involving genetic mutations, biochemical regulations, and mechanical deformations. In this paper, a thermodynamics-based nonlinear poroelastic theory is established to model the coupling among the mechanical, chemical, and biological mechanisms governing avascular tumor growth. A volumetric growth law accounting for mechano-chemo-biological coupled effects is proposed to describe the development of solid tumors. The regulating roles of stresses and nutrient transport in the tumor growth are revealed under different environmental constraints. We show that the mechano-chemo-biological coupling triggers anisotropic and heterogeneous growth, leading to the formation of layered structures in a growing tumor. There exists a steady state in which tumor growth is balanced by resorption. The influence of external confinements on tumor growth is also examined. A phase diagram is constructed to illustrate how the elastic modulus and thickness of the confinements jointly dictate the steady state of tumor volume. Qualitative and quantitative agreements with experimental observations indicate the developed model is capable of capturing the essential features of avascular tumor growth in various environments.

Comparative expression analysis reveals lineage relationships between human and murine gliomas and a dominance of glial signatures during tumor propagation in vitro.

PubMed

Henriquez, Nico V; Forshew, Tim; Tatevossian, Ruth; Ellis, Matthew; Richard-Loendt, Angela; Rogers, Hazel; Jacques, Thomas S; Reitboeck, Pablo Garcia; Pearce, Kerra; Sheer, Denise; Grundy, Richard G; Brandner, Sebastian

2013-09-15

Brain tumors are thought to originate from stem/progenitor cell populations that acquire specific genetic mutations. Although current preclinical models have relevance to human pathogenesis, most do not recapitulate the histogenesis of the human disease. Recently, a large series of human gliomas and medulloblastomas were analyzed for genetic signatures of prognosis and therapeutic response. Using a mouse model system that generates three distinct types of intrinsic brain tumors, we correlated RNA and protein expression levels with human brain tumors. A combination of genetic mutations and cellular environment during tumor propagation defined the incidence and phenotype of intrinsic murine tumors. Importantly, in vitro passage of cancer stem cells uniformly promoted a glial expression profile in culture and in brain tumors. Gene expression profiling revealed that experimental gliomas corresponded to distinct subclasses of human glioblastoma, whereas experimental supratentorial primitive neuroectodermal tumors (sPNET) correspond to atypical teratoid/rhabdoid tumor (AT/RT), a rare childhood tumor. ©2013 AACR.

Nanoparticle-mediated combination chemotherapy and photodynamic therapy overcomes tumor drug resistance.

PubMed

Khdair, Ayman; Chen, Di; Patil, Yogesh; Ma, Linan; Dou, Q Ping; Shekhar, Malathy P V; Panyam, Jayanth

2010-01-25

Tumor drug resistance significantly limits the success of chemotherapy in the clinic. Tumor cells utilize multiple mechanisms to prevent the accumulation of anticancer drugs at their intracellular site of action. In this study, we investigated the anticancer efficacy of doxorubicin in combination with photodynamic therapy using methylene blue in a drug-resistant mouse tumor model. Surfactant-polymer hybrid nanoparticles formulated using an anionic surfactant, Aerosol-OT (AOT), and a naturally occurring polysaccharide polymer, sodium alginate, were used for synchronized delivery of the two drugs. Balb/c mice bearing syngeneic JC tumors (mammary adenocarcinoma) were used as a drug-resistant tumor model. Nanoparticle-mediated combination therapy significantly inhibited tumor growth and improved animal survival. Nanoparticle-mediated combination treatment resulted in enhanced tumor accumulation of both doxorubicin and methylene blue, significant inhibition of tumor cell proliferation, and increased induction of apoptosis. These data suggest that nanoparticle-mediated combination chemotherapy and photodynamic therapy using doxorubicin and methylene blue has significant therapeutic potential against drug-resistant tumors. Copyright 2009 Elsevier B.V. All rights reserved.

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations

PubMed Central

Li, Laquan; Wang, Jian; Lu, Wei; Tan, Shan

2016-01-01

Accurate tumor segmentation from PET images is crucial in many radiation oncology applications. Among others, partial volume effect (PVE) is recognized as one of the most important factors degrading imaging quality and segmentation accuracy in PET. Taking into account that image restoration and tumor segmentation are tightly coupled and can promote each other, we proposed a variational method to solve both problems simultaneously in this study. The proposed method integrated total variation (TV) semi-blind de-convolution and Mumford-Shah segmentation with multiple regularizations. Unlike many existing energy minimization methods using either TV or L2 regularization, the proposed method employed TV regularization over tumor edges to preserve edge information, and L2 regularization inside tumor regions to preserve the smooth change of the metabolic uptake in a PET image. The blur kernel was modeled as anisotropic Gaussian to address the resolution difference in transverse and axial directions commonly seen in a clinic PET scanner. The energy functional was rephrased using the Γ-convergence approximation and was iteratively optimized using the alternating minimization (AM) algorithm. The performance of the proposed method was validated on a physical phantom and two clinic datasets with non-Hodgkin’s lymphoma and esophageal cancer, respectively. Experimental results demonstrated that the proposed method had high performance for simultaneous image restoration, tumor segmentation and scanner blur kernel estimation. Particularly, the recovery coefficients (RC) of the restored images of the proposed method in the phantom study were close to 1, indicating an efficient recovery of the original blurred images; for segmentation the proposed method achieved average dice similarity indexes (DSIs) of 0.79 and 0.80 for two clinic datasets, respectively; and the relative errors of the estimated blur kernel widths were less than 19% in the transversal direction and 7% in the axial direction. PMID:28603407

Dosimetry study of PHOTOFRIN-mediated photodynamic therapy in a mouse tumor model

NASA Astrophysics Data System (ADS)

Qiu, Haixia; Kim, Michele M.; Penjweini, Rozhin; Zhu, Timothy C.

2016-03-01

It is well known in photodynamic therapy (PDT) that there is a large variability between PDT light dose and therapeutic outcomes. An explicit dosimetry model using apparent reacted 1O2 concentration [1O2]rx has been developed as a PDT dosimetric quantity to improve the accuracy of the predicted ability of therapeutic efficacy. In this study, this explicit macroscopic singlet oxygen model was adopted to establish the correlation between calculated reacted [1O2]rx and the tumor growth using Photofrin-mediated PDT in a mouse tumor model. Mice with radiation-induced fibrosarcoma (RIF) tumors were injected with Photofrin at a dose of 5 mg/kg. PDT was performed 24h later with different fluence rates (50, 75 and 150 mW/cm2) and different fluences (50 and 135 J/cm2) using a collimated light applicator coupled to a 630nm laser. The tumor volume was monitored daily after PDT and correlated with the total light fluence and [1O2]rx. Photophysical parameters as well as the singlet oxygen threshold dose for this sensitizer and the RIF tumor model were determined previously. The result showed that tumor growth rate varied greatly with light fluence for different fluence rates while [1O2]rx had a good correlation with the PDT-induced tumor growth rate. This preliminary study indicated that [1O2]rx could serve as a better dosimetric predictor for predicting PDT outcome than PDT light dose.

Chimeric Mouse model to track the migration of bone marrow derived cells in glioblastoma following anti-angiogenic treatments.

PubMed

Achyut, B R; Shankar, Adarsh; Iskander, A S M; Ara, Roxan; Knight, Robert A; Scicli, Alfonso G; Arbab, Ali S

2016-01-01

Bone marrow derived cells (BMDCs) have been shown to contribute in the tumor development. In vivo animal models to investigate the role of BMDCs in tumor development are poorly explored. We established a novel chimeric mouse model using as low as 5 × 10(6) GFP+ BM cells in athymic nude mice, which resulted in >70% engraftment within 14 d. In addition, chimera was established in NOD-SCID mice, which displayed >70% with in 28 d. Since anti-angiogenic therapies (AAT) were used as an adjuvant against VEGF-VEGFR pathway to normalize blood vessels in glioblastoma (GBM), which resulted into marked hypoxia and recruited BMDCs to the tumor microenvironment (TME). We exploited chimeric mice in athymic nude background to develop orthotopic U251 tumor and tested receptor tyrosine kinase inhibitors and CXCR4 antagonist against GBM. We were able to track GFP+ BMDCs in the tumor brain using highly sensitive multispectral optical imaging instrument. Increased tumor growth associated with the infiltration of GFP+ BMDCs acquiring suppressive myeloid and endothelial phenotypes was seen in TME following treatments. Immunofluorescence study showed GFP+ cells accumulated at the site of VEGF, SDF1 and PDGF expression, and at the periphery of the tumors following treatments. In conclusion, we developed a preclinical chimeric model of GBM and phenotypes of tumor infiltrated BMDCs were investigated in context of AATs. Chimeric mouse model could be used to study detailed cellular and molecular mechanisms of interaction of BMDCs and TME in cancer.

Suppression of Metastasis by Primary Tumor and Acceleration of Metastasis Following Primary Tumor Resection: A Natural Law?

PubMed

Hanin, Leonid; Rose, Jason

2018-03-01

We study metastatic cancer progression through an extremely general individual-patient mathematical model that is rooted in the contemporary understanding of the underlying biomedical processes yet is essentially free of specific biological assumptions of mechanistic nature. The model accounts for primary tumor growth and resection, shedding of metastases off the primary tumor and their selection, dormancy and growth in a given secondary site. However, functional parameters descriptive of these processes are assumed to be essentially arbitrary. In spite of such generality, the model allows for computing the distribution of site-specific sizes of detectable metastases in closed form. Under the assumption of exponential growth of metastases before and after primary tumor resection, we showed that, regardless of other model parameters and for every set of site-specific volumes of detected metastases, the model-based likelihood-maximizing scenario is always the same: complete suppression of metastatic growth before primary tumor resection followed by an abrupt growth acceleration after surgery. This scenario is commonly observed in clinical practice and is supported by a wealth of experimental and clinical studies conducted over the last 110 years. Furthermore, several biological mechanisms have been identified that could bring about suppression of metastasis by the primary tumor and accelerated vascularization and growth of metastases after primary tumor resection. To the best of our knowledge, the methodology for uncovering general biomedical principles developed in this work is new.

Colonoscopy-based colorectal cancer modeling in mice with CRISPR-Cas9 genome editing and organoid transplantation.

PubMed

Roper, Jatin; Tammela, Tuomas; Akkad, Adam; Almeqdadi, Mohammad; Santos, Sebastian B; Jacks, Tyler; Yilmaz, Ömer H

2018-02-01

Most genetically engineered mouse models (GEMMs) of colorectal cancer are limited by tumor formation in the small intestine, a high tumor burden that limits metastasis, and the need to generate and cross mutant mice. Cell line or organoid transplantation models generally produce tumors in ectopic locations-such as the subcutaneous space, kidney capsule, or cecal wall-that do not reflect the native stromal environment of the colon mucosa. Here, we describe detailed protocols to rapidly and efficiently induce site-directed tumors in the distal colon of mice that are based on colonoscopy-guided mucosal injection. These techniques can be adapted to deliver viral vectors carrying Cre recombinase, CRISPR-Cas9 components, CRISPR-engineered mouse tumor organoids, or human cancer organoids to mice to model the adenoma-carcinoma-metastasis sequence of tumor progression. The colonoscopy injection procedure takes ∼15 min, including preparation. In our experience, anyone with reasonable hand-eye coordination can become proficient with mouse colonoscopy and mucosal injection with a few hours of practice. These approaches are ideal for a wide range of applications, including assessment of gene function in tumorigenesis, examination of tumor-stroma interactions, studies of cancer metastasis, and translational research with patient-derived cancers.

Orthotopic lung cancer murine model by nonoperative transbronchial approach.

PubMed

Nakajima, Takahiro; Anayama, Takashi; Matsuda, Yasushi; Hwang, David M; McVeigh, Patrick Z; Wilson, Brian C; Zheng, Gang; Keshavjee, Shaf; Yasufuku, Kazuhiro

2014-05-01

The aim of this work was to establish a novel orthotopic human non-small cell lung cancer (NSCLC) murine xenograft model by a nonsurgical, transbronchial approach. Male athymic nude mice and human NSCLC cell lines, including A549, H460, and H520 were used. Under direct visualization of the vocal cords, a 23-gauge blunt-tip slightly curved metal catheter was introduced into the trachea to the bronchus, and 2.5×10(5) tumor cells mixed with Matrigel (BD Biosciences, Mississauga, Ontario, Canada) were administered into the lung. Mice were monitored using weekly microcomputed tomography scans for tumor formation. When the tumor size reached more than 4 mm in diameter, the animals were euthanized, and the tumor tissue was evaluated histopathologically. Of 37 mice studied, 34 were confirmed to have tumor formation: 29 developed solitary tumors and 5 had multifocal lesions. There was no evidence of extrapleural dissemination or effusion. Transbronchial delivery of tumor cells enabled the establishment of a novel orthotopic human NSCLC murine xenograft model. This clinically relevant preclinical model bearing a solitary nodule is of value for a variety of in vivo research studies. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

New insights into the earliest stages of colorectal tumorigenesis.

PubMed

Sievers, Chelsie K; Grady, William M; Halberg, Richard B; Pickhardt, Perry J

2017-08-01

Tumors in the large intestine have been postulated to arise via a stepwise accumulation of mutations, a process that takes up to 20 years. Recent advances in lineage tracing and DNA sequencing, however, are revealing new evolutionary models that better explain the vast amount of heterogeneity observed within and across colorectal tumors. Areas covered: A review of the literature supporting a novel model of colorectal tumor evolution was conducted. The following commentary examines the basic science and clinical evidence supporting a modified view of tumor initiation and progression in the colon. Expert commentary: The proposed 'cancer punctuated equilibrium' model of tumor evolution better explains the variability seen within and across polyps of the colon and rectum. Small colorectal polyps (6-9mm) followed longitudinally by interval imaging with CT colonography have been reported to have multiple fates: some growing, some remaining static in size, and others regressing in size over time. This new model allows for this variability in growth behavior and supports the hypothesis that some tumors can be 'born to be bad' as originally postulated by Sottoriva and colleagues, with very early molecular events impacting tumor fitness and growth behavior in the later stages of the disease process.

Zoledronic acid has differential antitumor activity in the pre- and postmenopausal bone microenvironment in vivo.

PubMed

Ottewell, Penelope D; Wang, Ning; Brown, Hannah K; Reeves, Kimberly J; Fowles, C Anne; Croucher, Peter I; Eaton, Colby L; Holen, Ingunn

2014-06-01

Clinical trials in early breast cancer have suggested that benefits of adjuvant bone-targeted treatments are restricted to women with established menopause. We developed models that mimic pre- and postmenopausal status to investigate effects of altered bone turnover on growth of disseminated breast tumor cells. Here, we report a differential antitumor effect of zoledronic acid (ZOL) in these two settings. Twleve-week-old female Balb/c-nude mice with disseminated MDA-MB-231 breast tumor cells in bone underwent sham operation or ovariectomy (OVX), mimicking the pre- and postmenopausal bone microenvironment, respectively. To determine the effects of bone-targeted therapy, sham/OVX animals received saline or 100 μg/kg ZOL weekly. Tumor growth was assessed by in vivo imaging and effects on bone by real-time PCR, micro-CT, histomorphometry, and measurements of bone markers. Disseminated tumor cells were detected by two-photon microscopy. OVX increased bone resorption and induced growth of disseminated tumor cells in bone. Tumors were detected in 83% of animals following OVX (postmenopausal model) compared with 17% following sham operation (premenopausal model). OVX had no effect on tumors outside of bone. OVX-induced tumor growth was completely prevented by ZOL, despite the presence of disseminated tumor cells. ZOL did not affect tumor growth in bone in the sham-operated animals. ZOL increased bone volume in both groups. This is the first demonstration that tumor growth is driven by osteoclast-mediated mechanisms in models that mimic post- but not premenopausal bone, providing a biologic rationale for the differential antitumor effects of ZOL reported in these settings. Clin Cancer Res; 20(11); 2922-32. ©2014 AACR. ©2014 American Association for Cancer Research.