Simulation of 3D centimeter-scale continuum tumor growth at sub-millimeter resolution via distributed computing

Goodin, Dylan A.; Frieboes, Hermann B.

doi:10.1016/j.compbiomed.2021.104507

Cited by 6 publications

(3 citation statements)

References 59 publications

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“…drug response, tissue fluidity and tumor invasion [11][12][13]. On the in silico side, tumor growth models of varying degree of coarse-graining are being developed [14][15][16], some of which are also applied to simulate tumor spheroids [17,18]. Thus, both experimentalists and theorists generate data for the same systems, but these studies are often not compared quantitatively.…”

Section: Introductionmentioning

confidence: 99%

Development of a scoring function for comparing simulated and experimental tumor spheroids

et al. 2023

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Progress continues in the field of cancer biology, yet much remains to be unveiled regarding the mechanisms of cancer invasion. In particular, complex biophysical mechanisms enable a tumor to remodel the surrounding extracellular matrix (ECM), allowing cells to invade alone or collectively. Tumor spheroids cultured in collagen represent a simplified, reproducible 3D model system, which is sufficiently complex to recapitulate the evolving organization of cells and interaction with the ECM that occur during invasion. Recent experimental approaches enable high resolution imaging and quantification of the internal structure of invading tumor spheroids. Concurrently, computational modeling enables simulations of complex multicellular aggregates based on first principles. The comparison between real and simulated spheroids represents a way to fully exploit both data sources, but remains a challenge. We hypothesize that comparing any two spheroids requires first the extraction of basic features from the raw data, and second the definition of key metrics to match such features. Here, we present a novel method to compare spatial features of spheroids in 3D. To do so, we define and extract features from spheroid point cloud data, which we simulated using Cells in Silico (CiS), a high-performance framework for large-scale tissue modeling previously developed by us. We then define metrics to compare features between individual spheroids, and combine all metrics into an overall deviation score. Finally, we use our features to compare experimental data on invading spheroids in increasing collagen densities. We propose that our approach represents the basis for defining improved metrics to compare large 3D data sets. Moving forward, this approach will enable the detailed analysis of spheroids of any origin, one application of which is informing in silico spheroids based on their in vitro counterparts. This will enable both basic and applied researchers to close the loop between modeling and experiments in cancer research.

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Section: Introductionmentioning

confidence: 99%

Development of a scoring function for comparing simulated and experimental tumor spheroids

et al. 2023

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“…The model simulates therapeutic response based on the interaction of the delivery vehicle, MSV-nab-PTX, with macrophages in the TME, building upon a 3D continuum mixture model developed in [16] and solved numerically in [17]. To enable the computational feasibility of representing multiple metastases interacting with macrophages, we leverage a novel MPI-CUDA framework [18], in contrast to the CPUbound framework of the 3D mixture model in [16,17] that simulated desmoplastic tumours. Tumour burden is evaluated as a function of treatment regimen and metastases number by simulating multiple BCLM of varying sizes in a liver lobe, calibrated to an experimental mouse model of BCLM.…”

Section: Introductionmentioning

confidence: 99%

Multiple breast cancer liver metastases response to macrophage‐delivered nanotherapy evaluated via a 3D continuum model

et al. 2022

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Breast cancer liver metastases (BCLM) are usually unresectable and difficult to treat with systemic chemotherapy. A major reason for chemotherapy failure is that BCLM are typically small, avascular nodules, with poor transport and fast washout of therapeutics from surrounding capillaries. We have previously shown that nanoalbumin‐bound paclitaxel (nab‐PTX) encapsulated in porous silicon multistage nanovectors (MSV) is preferentially taken up by tumour‐associated macrophages (TAM) in the BCLM microenvironment. The TAM alter therapeutic transport characteristics and retain it in the tumour vicinity, increasing cytotoxicity. Computational modeling has shown that therapeutic regimens could be designed to eliminate single lesions. To evaluate clinically‐relevant scenarios, this study develops a modeling framework to evaluate MSV‐nab‐PTX therapy targeting multiple BCLM. An experimental model of BCLM, splenic injection of breast cancer 4 T1 cells was established in BALB/C mice. Livers were analyzed histologically to determine size and density of BCLM. The data were used to calibrate a 3D continuum mixture model solved via distributed computing to enable simulation of multiple BCLM. Overall tumour burden was analyzed as a function of metastases number and potential therapeutic regimens. The computational model enables realistic 3D representation of metastatic tumour burden in the liver, with the capability to evaluate BCLM growth and therapy response for hundreds of lesions. With the given parameter set, the model projects that repeated MSV‐nab‐PTX treatment in intervals <7 days would control the tumour burden. We conclude that nanotherapy targeting TAM associated with BCLM may be evaluated and fine‐tuned via 3D computational modeling that realistically simulates multiple metastases.

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Section: Introductionmentioning

confidence: 99%

Development of a Scoring Function for Comparing Simulated and Experimental Tumor Spheroids

Herold¹,

Behle

Rosenbauer

et al. 2022

Preprint

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Enormous progress continues in the field of cancer biology, yet much remains to be unveiled regarding the mechanisms of cancer invasion. In particular, complex biophysical mechanisms enable a tumor to remodel the surrounding extracellular matrix (ECM), thus allowing cells to escape and invade alone or as multicellular collectives. Tumor spheroids cultured in collagen represent a simplified, reproducible 3D model system, which is sufficiently complex to recapitulate the evolving internal organization of cells and external interaction with the ECM that occur during invasion. Recent experimental approaches enable high resolution imaging and quantification of the internal structure of invading tumor spheroids. Concurrently, computational modeling enables simulations of complex multicellular aggregates based on first principles. The comparison between real and simulated spheroids represents a way to fully exploit both data sources, but remains a challenging task. We hypothesize that comparing any two spheroids requires first the extraction of basic features from the raw data, and second the definition of key metrics to match such features. Here, we present a novel data-agnostic method to compare spatial features of spheroids in 3D. To do so, we define and extract features from spheroid point cloud data, which we simulated using Cells in Silico (CiS), a high-performance framework for large-scale tissue modeling previously developed by our group. We then define metrics to compare features between individual spheroids, and combine all metrics into an overall deviation score. Finally, we use our features to compare experimental data on invading spheroids in increasing collagen densities. We propose that our approach represents the basis for defining improved metrics to compare large 3D data sets. Moving forward, this approach will enable informing in silico spheroids based on their in vitro counterparts, and vice versa, thus enabling both basic and applied researchers to close the loop between modeling and experiments in cancer research.

show abstract

Simulation of 3D centimeter-scale continuum tumor growth at sub-millimeter resolution via distributed computing

Cited by 6 publications

References 59 publications

Development of a scoring function for comparing simulated and experimental tumor spheroids

Development of a scoring function for comparing simulated and experimental tumor spheroids

Multiple breast cancer liver metastases response to macrophage‐delivered nanotherapy evaluated via a 3D continuum model

Development of a Scoring Function for Comparing Simulated and Experimental Tumor Spheroids

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