A Review of Cell-Based Computational Modeling in Cancer Biology

JCO Clinical Cancer Informatics, Journal Year: 2019, Volume and Issue: 3, P. 1 - 13

Published: Feb. 4, 2019

Cancer biology involves complex, dynamic interactions between cancer cells and their tissue microenvironments. Single-cell effects are critical drivers of clinical progression. Chemical mechanical communication tumor stromal can co-opt normal physiologic processes to promote growth invasion. cell heterogeneity increases cancer's ability test strategies adapt microenvironmental stresses. Hypoxia treatment select for stem drive invasion resistance. Cell-based computational models (also known as discrete models, agent-based or individual-based models) simulate individual they interact in virtual tissues, which allows us explore how single-cell behaviors lead the dynamics we observe work control systems. In this review, introduce broad range techniques available cell-based modeling. The approaches from highly detailed just a few morphologies millions simpler three-dimensional tissues. Modeling directly translate biologic observations into simulation rules. many cases, agents include molecular-scale models. Most also transport oxygen, drugs, factors, allow link development conditions. We illustrate these methods with examples drawn hypoxia, angiogenesis, invasion, cells, immunosurveillance. An ecosystem interoperable tools is emerging at time when cloud computing resources make software easier access supercomputing large-scale studies possible. As field develops, anticipate that high-throughput will rapidly space possibilities, prescreen new therapeutic strategies, even re-engineer bring systems under control.

Language: Английский

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Tumor Cell Invasion in Glioblastoma

International Journal of Molecular Sciences, Journal Year: 2020, Volume and Issue: 21(6), P. 1932 - 1932

Published: March 12, 2020

Glioblastoma (GBM) is a particularly devastating tumor with median survival of about 16 months. Recent research has revealed novel insights into the outstanding heterogeneity this type brain cancer. However, all GBM subtypes share hallmark feature aggressive invasion surrounding tissue. Invasive glioblastoma cells escape surgery and focal therapies thus represent major obstacle for curative therapy. This review aims to provide comprehensive understanding glioma mechanisms respect tumor-cell-intrinsic properties as well cues provided by microenvironment. We discuss genetic programs that may influence dissemination plasticity their different patterns. also how shape microenvironment how, vice versa, components extracellular matrix factors from non-neoplastic cell motility. further platforms modeling invasion. Finally, we highlight importance accounting complex interplay between treatment resistance in when considering new therapeutic approaches.

Language: Английский

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Current and Future Trends on Diagnosis and Prognosis of Glioblastoma: From Molecular Biology to Proteomics

Cells, Journal Year: 2019, Volume and Issue: 8(8), P. 863 - 863

Published: Aug. 9, 2019

Glioblastoma multiforme is the most aggressive malignant tumor of central nervous system. Due to absence effective pharmacological and surgical treatments, identification early diagnostic prognostic biomarkers key importance improve survival rate patients develop new personalized treatments. On these bases, aim this review article summarize current knowledge regarding application molecular biology proteomics techniques for novel through analysis different biological samples obtained from glioblastoma patients, including DNA, microRNAs, proteins, small molecules, circulating cells, extracellular vesicles, etc. Both benefits pitfalls analyses are discussed, mass spectrometry-based analytical techniques, highlighting how investigation strategies powerful tools study glioblastoma, as well advanced methods management pathology.

Language: Английский

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Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment

Processes, Journal Year: 2019, Volume and Issue: 7(1), P. 37 - 37

Published: Jan. 13, 2019

Multiscale systems biology and pharmacology are powerful methodologies that playing increasingly important roles in understanding the fundamental mechanisms of biological phenomena clinical applications. In this review, we summarize state art applications agent-based models (ABM) hybrid modeling to tumor immune microenvironment cancer response, including immunotherapy. Heterogeneity is a hallmark cancer; heterogeneity at molecular, cellular, tissue scales major determinant metastasis, drug resistance, low response rate molecular targeted therapies immunotherapies. Agent-based an effective methodology obtain understand quantitative characteristics these processes propose solutions aimed overcoming current obstacles treatment. We review focusing on intra-tumor heterogeneity, particularly interactions between cells stromal cells, role tumor-associated vasculature immune-related mechanobiology, discuss digital pathology parameterizing validating spatial computational potential therapeutics.

Language: Английский

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Glioblastoma Multiforme: The Latest Diagnostics and Treatment Techniques

Pharmacology, Journal Year: 2023, Volume and Issue: 108(5), P. 423 - 431

Published: Jan. 1, 2023

Background: Glioblastoma multiforme (GBM) is a WHO grade 4 glioma and the most common malignant primary brain tumour. Recently, there has been outstanding progress in treatment of GBM. In addition to newest form GBM removal using fluorescence, three-dimensional (3D) imaging, tomoradiotherapy, moderate electro-hyperthermia, adjuvant temozolomide (post-operative chemotherapy), new developments have made fields immunology, molecular biology, virotherapy. An unusual modern created, especially for stage GBM, latest therapeutic techniques, including immunotherapy Modern oncological medicine producing extraordinary progressive methods. Oncological therapy includes individual analysis properties tumour targeted small-molecule inhibitors. Individualised covers entire patient (tumour host) context immunotherapy. example individualised multimodal (IMI), which relies on immunological tumour-host interactions. addition, IMI based concept oncolytic virus-induced immunogenic cell death. Summary: this review, we outline current knowledge various available options used both traditional strategy therapies, such as tomotherapy, virotherapy, are promising strategies with potential improve prognosis patients Key Messages: This therapy, combined virotherapy (oncolytic viruses cancer vaccines), displaying encouraging signs combating Additionally, 3D imaging compared conventional two-dimensional imaging.

Language: Английский

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Mathematical modeling of tumor-immune cell interactions

Journal of Theoretical Biology, Journal Year: 2019, Volume and Issue: 469, P. 47 - 60

Published: March 2, 2019

Language: Английский

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Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference

IEEE Transactions on Medical Imaging, Journal Year: 2019, Volume and Issue: 38(8), P. 1875 - 1884

Published: Feb. 27, 2019

Glioblastoma (GBM) is a highly invasive brain tumor, whose cells infiltrate surrounding normal tissue beyond the lesion outlines visible in current medical scans. These infiltrative are treated mainly by radiotherapy. Existing radiotherapy plans for tumors derive from population studies and scarcely account patient-specific conditions. Here, we provide Bayesian machine learning framework rational design of improved, personalized using mathematical modeling patient multimodal Our method, first time, integrates complementary information high-resolution MRI scans specific FET-PET metabolic maps to infer tumor cell density GBM patients. The quantifies imaging uncertainties predicts with credible intervals. proposed methodology relies only on data acquired at single time point and, thus, applicable standard clinical settings. An initial study shows that generated inferred infiltration spare more healthy thereby reducing radiation toxicity while yielding comparable accuracy protocols. Moreover, regions high densities coincide radioresistant areas, providing guidance dose-escalation. integration provides robust, non-invasive tool assist design.

Language: Английский

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Non-Coding RNAs in Glioma

Cancers, Journal Year: 2018, Volume and Issue: 11(1), P. 17 - 17

Published: Dec. 22, 2018

Glioma is the most aggressive brain tumor of central nervous system. The ability glioma cells to migrate, rapidly diffuse and invade normal adjacent tissue, their sustained proliferation, heterogeneity contribute an overall survival approximately 15 months for patients with high grade glioma. Numerous studies indicate that non-coding RNA species have critical functions across biological processes regulate initiation progression. Recently, new data emerged, which shows cross-regulation between long RNAs small phenotypic diversity glioblastoma subclasses. In this paper, we review expression, was evaluated in human tissue samples during a five-year period. Thus, summarizes following: (I) role pathogenesis, (II) potential application glioma-grading, (III) crosstalk lncRNAs miRNAs (IV) future perspectives as biomarkers

Language: Английский

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Hybrid Automata Library: A flexible platform for hybrid modeling with real-time visualization

PLoS Computational Biology, Journal Year: 2020, Volume and Issue: 16(3), P. e1007635 - e1007635

Published: March 10, 2020

The Hybrid Automata Library (HAL) is a Java developed for use in mathematical oncology modeling. It made of simple, efficient, generic components that can be used to model complex spatial systems. HAL's broadly classified into: on- and off-lattice agent containers, finite difference diffusion fields, GUI building system, additional tools utilities computation data collection. These are designed operate independently standardized make them easy interface with one another. As demonstration how modeling simplified using our approach, we have included complete example hybrid (a interacting agent-based PDE components). HAL useful asset researchers who wish build performant 1D, 2D 3D models Java, while not starting entirely from scratch. available on GitHub at https://github.com/MathOnco/HAL under the MIT License. requires JDK version 1.8 or later compile run source code.

Language: Английский

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Translating complexity and heterogeneity of pancreatic tumor: 3D in vitro to in vivo models

Advanced Drug Delivery Reviews, Journal Year: 2021, Volume and Issue: 174, P. 265 - 293

Published: April 23, 2021

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive type of cancer with overall survival rate less than 7–8%, emphasizing the need for novel effective therapeutics against PDAC. However only a fraction which seemed promising in laboratory environment will eventually reach clinic. One main reasons behind this low success complex tumor microenvironment (TME) PDAC, highly fibrotic and dense stroma surrounding cells, supports progression as well increases resistance treatment. In particular, growing understanding PDAC TME points out different challenge development efficient – lack biologically relevant vitro vivo models that resemble complexity heterogeneity observed patients. The purpose scope review to provide overview recent developments models, aim recapitulate environment, describe how 3D can be integrated into drug pipelines are already including sophisticated models. Hereby special focus given on challenges face same levels controllable manner. First, brief introduction two dimensional (2D) ex provided. Next, three (3D) described ranging from spheroids, organoids, scaffold bioprinted organ-on-chip discussion advantages limitations each model. Furthermore, we detailed current chemically-induced syngeneic xenogeneic highlighting hetero- orthotopic, patient-derived tissues (PDX) genetically engineered mouse Finally, both, discuss necessary steps overcome these pipeline, possibilities include silico process.

Language: Английский

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