Modeling of Tumor Growth with Input from Patient-Specific Metabolomic Data

Miller, Hunter A.; Lowengrub, John; Frieboes, Hermann B.

doi:10.1007/s10439-022-02904-5

Cited by 8 publications

(5 citation statements)

References 85 publications

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“…Despite their model being inherently multi-scale, their in silico experiments were calibrated on macroscopic quantities, i.e., drug dose, injection time and duration, and tumor size. In the same year however, Miller et al 92 presented a multi-level approach that is unique in that it proposes to link tumor metabolomic measurements from patients into the mathematical model for tissue-scale behavior of a carcinoma progression or control, the development of angiogenesis, the effect of chemotherapy, etc. However, an important limitation of the cancer model concerns that its behavior depends mainly on the metabolomic data available, and how they are appropriately weighted and combined to determine the effect on the (mechanistic) model parameters.…”

Section: Agent-based Modeling In Cancer Biomedicinementioning

confidence: 99%

Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation

Cogno,

Axenie,

Bauer

et al. 2024

Cancer Biology & Therapy

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Computational models are not just appealing because they can simulate and predict the development of biological phenomena across multiple spatial and temporal scales, but also because they can integrate information from well-established in vitro and in vivo models and test new hypotheses in cancer biomedicine. Agent-based models and simulations are especially interesting candidates among computational modeling procedures in cancer research due to the capability to, for instance, recapitulate the dynamics of neoplasia and tumor – host interactions. Yet, the absence of methods to validate the consistency of the results across scales can hinder adoption by turning fine-tuned models into black boxes. This review compiles relevant literature that explores strategies to leverage high-fidelity simulations of multi-scale, or multi-level, cancer models with a focus on verification approached as simulation calibration. We consolidate our review with an outline of modern approaches for agent-based models’ validation and provide an ambitious outlook toward rigorous and reliable calibration.

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Section: Agent-based Modeling In Cancer Biomedicinementioning

confidence: 99%

Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation

Cogno,

Axenie,

Bauer

et al. 2024

Cancer Biology & Therapy

View full text Add to dashboard Cite

show abstract

“…Based on biological and biomechanical principles, biomechanical models can explain emerging clinical behaviors and assess the effectiveness of therapeutic strategies. In recent years, mathematical models that combine tumor growth [13][14][15][16][17][18][19][20][21], angiogenesis [22][23][24][25][26][27], blood flow [28,29] and anticancer drugs [30][31][32][33] have been proposed to explore better treatment. Cell-based models directly simulate single cell behaviors and cell-cell interactions at subcellular and cellular scales on the basis of predefined rules [34,35], while most continuum models describe tumor dynamics through partial differential equations (PDEs) and avoid the disadvantages of large computational costs caused by discrete approaches at a large scale [36][37][38][39][40][41][42][43].…”

Section: Biomechanical Models For Tumor Growthmentioning

confidence: 99%

Biomechanical modelling of tumor growth with chemotherapeutic treatment: a review

Xu,

Wang,

Gomez

et al. 2023

Smart Mater. Struct.

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The efficiency of chemotherapy in the treatment of cancer depends on the administration schedule, such as dosage, timing and frequency, and the release control if self-assembled drugs are administered, in addition to the drug transport in the tumor microenvironment. Biomechanical models can help deepen our understanding of drug pharmacokinetics and pharmacodynamics, tumor response and resistance to treatment, as well as enable the use of personalized treatment and optimal therapies. This review aims to provide an overview of computational modeling for vascular tumor growth, drug biotransport, and tumor response with integration of microenvironmental biology phenomena, e.g., angiogensis, blood flow, and mechanical stress. We first review some discrete and continuum models for vascular tumors, highlighting the advantages and challenges of each approach. Then, we discuss mathematical models that include chemotherapeutic treatment and provide potential strategies to promote drug effectiveness through numerical observations. We finalize discussing several aspects that warrant further research including multiscale modeling of cancer, incorporation of patient-specific parameters and coupling of models with emerging medical imaging technologies.

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“…Since tumors are regarded as complex heterogenic tissues with hypoxic areas [ 209 ], the Warburg effect is one of the hallmarks of cancer favoring the suppression of normal oxidative phosphorylation and the adaptation to hypoxia [ 210 ] via upregulating HIF-1 and GLUT expression [ 207 ]. Metabolic products such as lactic acid, originating in tumor cells [ 211 , 212 , 213 ], may promote the spontaneous oxidation of ascorbate to DHA due to pH lowering within the tumor microenvironment [ 32 , 33 ]. Both GLUT-mediated DHA uptake as well as enhanced ascorbate oxidation to DHA may be initiated in the tumor [ 214 ].…”

Section: Dha Transportersmentioning

confidence: 99%

Relevant Membrane Transport Proteins as Possible Gatekeepers for Effective Pharmacological Ascorbate Treatment in Cancer

et al. 2023

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Despite the increasing number of newly diagnosed malignancies worldwide, therapeutic options for some tumor diseases are unfortunately still limited. Interestingly, preclinical but also some clinical data suggest that the administration of pharmacological ascorbate seems to respond well, especially in some aggressively growing tumor entities. The membrane transport and channel proteins are highly relevant for the use of pharmacological ascorbate in cancer therapy and are involved in the transfer of active substances such as ascorbate, hydrogen peroxide, and iron that predominantly must enter malignant cells to induce antiproliferative effects and especially ferroptosis. In this review, the relevant conveying proteins from cellular surfaces are presented as an integral part of the efficacy of pharmacological ascorbate, considering the already known genetic and functional features in tumor tissues. Accordingly, candidates for diagnostic markers and therapeutic targets are mentioned.

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Modeling of Tumor Growth with Input from Patient-Specific Metabolomic Data

Cited by 8 publications

References 85 publications

Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation

Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation

Biomechanical modelling of tumor growth with chemotherapeutic treatment: a review

Relevant Membrane Transport Proteins as Possible Gatekeepers for Effective Pharmacological Ascorbate Treatment in Cancer

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