Clinical implications of in silico mathematical modeling for glioblastoma: a critical review

Protopapa, Maria; Zygogianni, Anna; Stamatakos, Georgios S.; Antypas, Christos; Armpilia, Christina; Uzunoglu, N.K.; Kouloulias, Vassilis

doi:10.1007/s11060-017-2650-2

Cited by 18 publications

(17 citation statements)

References 61 publications

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“…Further advances in radiogenomics could be of great help in the near future, especially in the follow-up phase of GBM when repeated biopsies or extensive genomic and transcriptomic analysis are not possible. In addition, 3D models that simulate response to radiotherapy have also been developed and validated in small number of patients, based on modern imaging techniques [189].…”

Section: Emerging Novel Technologies and Approaches For Studying Invasive Gbmmentioning

confidence: 99%

Tumor Cell Invasion in Glioblastoma

Vollmann-Zwerenz

Leidgens

Feliciello

et al. 2020

IJMS

171

139

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

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Section: Emerging Novel Technologies and Approaches For Studying Invasive Gbmmentioning

confidence: 99%

Tumor Cell Invasion in Glioblastoma

Vollmann-Zwerenz

Leidgens

Feliciello

et al. 2020

IJMS

171

139

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“…Individual-cell-based models are in general more suitable to describe in vitro experiments, genotype-phenotype relations, local interactions of heterogeneous populations and migration mechanisms. A comprehensive overview of the mathematical models developed for GB progression and therapy response from the clinical perspective and personalized medicine are summarized in 31 . In addition, a thorough review summarizing major studies related to GB invasion can be found in Alfonso et al .…”

Section: Introductionmentioning

confidence: 99%

Integrating in vitro experiments with in silico approaches for Glioblastoma invasion: the role of cell-to-cell adhesion heterogeneity

Oraiopoulou

Tzamali

Tzedakis

et al. 2018

Sci Rep

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Glioblastoma cells adopt migration strategies to invade into the brain parenchyma ranging from individual to collective mechanisms, whose role and dynamics are not yet fully understood. In this work, we explore Glioblastoma heterogeneity and recapitulate its invasive patterns both in vitro, by utilizing primary cells along with the U87MG cell line, and in silico, by adopting discrete, individual cell-based mathematics. Glioblastoma cells are cultured three-dimensionally in an ECM-like substrate. The primary Glioblastoma spheroids adopt a novel cohesive pattern, mimicking perivascular invasion in the brain, while the U87MG adopt a typical, starburst invasive pattern under the same experimental setup. Mathematically, we focus on the role of the intrinsic heterogeneity with respect to cell-to-cell adhesion. Our proposed mathematical approach mimics the invasive morphologies observed in vitro and predicts the dynamics of tumour expansion. The role of the proliferation and migration is also explored showing that their effect on tumour morphology is different per cell type. The proposed model suggests that allowing cell-to-cell adhesive heterogeneity within the tumour population is sufficient for variable invasive morphologies to emerge which remain originally undetectable by conventional imaging, indicating that exploration in pathological samples is needed to improve our understanding and reveal potential patient-specific therapeutic targets.

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“…Importantly, computational models provide a tool to simulate ‘what-if’ scenarios such as up/downregulation of key components that could be targeted. In silico clinical trials, recently baptized phase i trials [162], aid in matching the “right drug to the right patient” [13, 18, 163]. A key idea is the shift from real-world clinical trial testing a single treatment option on many, mostly unselected, patients to first test in silico several treatment options, both approved or repurposed, for each individual patient.…”

Section: Discussionmentioning

confidence: 99%

System-based approaches as prognostic tools for glioblastoma

et al. 2019

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BackgroundThe evasion of apoptosis is a hallmark of cancer. Understanding this process holistically and overcoming apoptosis resistance is a goal of many research teams in order to develop better treatment options for cancer patients. Efforts are also ongoing to personalize the treatment of patients. Strategies to confirm the therapeutic efficacy of current treatments or indeed to identify potential novel additional options would be extremely beneficial to both clinicians and patients. In the past few years, system medicine approaches have been developed that model the biochemical pathways of apoptosis. These systems tools incorporate and analyse the complex biological networks involved. For their successful integration into clinical practice, it is mandatory to integrate systems approaches with routine clinical and histopathological practice to deliver personalized care for patients.ResultsWe review here the development of system medicine approaches that model apoptosis for the treatment of cancer with a specific emphasis on the aggressive brain cancer, glioblastoma.ConclusionsWe discuss the current understanding in the field and present new approaches that highlight the potential of system medicine approaches to influence how glioblastoma is diagnosed and treated in the future.

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Clinical implications of in silico mathematical modeling for glioblastoma: a critical review

Cited by 18 publications

References 61 publications

Tumor Cell Invasion in Glioblastoma

Tumor Cell Invasion in Glioblastoma

Integrating in vitro experiments with in silico approaches for Glioblastoma invasion: the role of cell-to-cell adhesion heterogeneity

System-based approaches as prognostic tools for glioblastoma

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