1
|
Mascheroni P, Penta R, Merodio J. The impact of vascular volume fraction and compressibility of the interstitial matrix on vascularised poroelastic tissues. Biomech Model Mechanobiol 2023; 22:1901-1917. [PMID: 37587330 PMCID: PMC10613172 DOI: 10.1007/s10237-023-01742-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/05/2023] [Indexed: 08/18/2023]
Abstract
In this work we address the role of the microstructural properties of a vascularised poroelastic material, characterised by the coupling between a poroelastic matrix and a viscous fluid vessels network, on its overall response in terms of pressures, velocities and stress maps. We embrace the recently developed model (Penta and Merodio in Meccanica 52(14):3321-3343, 2017) as a theoretical starting point and present the results obtained by solving the full interplay between the microscale, represented by the intervessels' distance, and the macroscale, representing the size of the overall tissue. We encode the influence of the vessels' density and the poroelastic matrix compressibility in the poroelastic coefficients of the model, which are obtained by solving appropriate periodic cell problem at the microscale. The double-poroelastic model (Penta and Merodio 2017) is then solved at the macroscale in the context of vascular tumours, for different values of vessels' walls permeability. The results clearly indicate that improving the compressibility of the matrix and decreasing the vessels' density enhances the transvascular pressure difference and hence transport of fluid and drug within a tumour mass after a transient time. Our results suggest to combine vessel and interstitial normalization in tumours to allow for better drug delivery into the lesions.
Collapse
Affiliation(s)
- Pietro Mascheroni
- Laboratoire Interdisciplinaire de Physique, Université Grenoble Alpes, 140, Rue de la Physique, 38402, Saint Martin d'Héres, France
| | - Raimondo Penta
- School of Mathematics and Statistics, University of Glasgow, University Place, Glasgow, G12 8QQ, UK.
| | - José Merodio
- Departamento de Matemática Aplicada a las TIC ETS de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, 28031, Madrid, Spain
| |
Collapse
|
2
|
Mascheroni P, Savvopoulos S, Alfonso JCL, Meyer-Hermann M, Hatzikirou H. Improving personalized tumor growth predictions using a Bayesian combination of mechanistic modeling and machine learning. Commun Med (Lond) 2021; 1:19. [PMID: 35602187 PMCID: PMC9053281 DOI: 10.1038/s43856-021-00020-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 07/08/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND In clinical practice, a plethora of medical examinations are conducted to assess the state of a patient's pathology producing a variety of clinical data. However, investigation of these data faces two major challenges. Firstly, we lack the knowledge of the mechanisms involved in regulating these data variables, and secondly, data collection is sparse in time since it relies on patient's clinical presentation. The former limits the predictive accuracy of clinical outcomes for any mechanistic model. The latter restrains any machine learning algorithm to accurately infer the corresponding disease dynamics. METHODS Here, we propose a novel method, based on the Bayesian coupling of mathematical modeling and machine learning, aiming at improving individualized predictions by addressing the aforementioned challenges. RESULTS We evaluate the proposed method on a synthetic dataset for brain tumor growth and analyze its performance in predicting two relevant clinical outputs. The method results in improved predictions in almost all simulated patients, especially for those with a late clinical presentation (>95% patients show improvements compared to standard mathematical modeling). In addition, we test the methodology in two additional settings dealing with real patient cohorts. In both cases, namely cancer growth in chronic lymphocytic leukemia and ovarian cancer, predictions show excellent agreement with reported clinical outcomes (around 60% reduction of mean squared error). CONCLUSIONS We show that the combination of machine learning and mathematical modeling approaches can lead to accurate predictions of clinical outputs in the context of data sparsity and limited knowledge of disease mechanisms.
Collapse
Affiliation(s)
- Pietro Mascheroni
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Centre for Infectious Research, Braunschweig, Germany
| | - Symeon Savvopoulos
- grid.5596.f0000 0001 0668 7884KU Leuven, Department of Chemical Engineering, Leuven, Belgium
| | - Juan Carlos López Alfonso
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Centre for Infectious Research, Braunschweig, Germany
| | - Michael Meyer-Hermann
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Centre for Infectious Research, Braunschweig, Germany ,Centre for Individualized Infection Medicine, Hannover, Germany ,grid.6738.a0000 0001 1090 0254Institute for Biochemistry, Biotechnology and Bioinformatics, Technische Universität Braunschweig, Braunschweig, Germany
| | - Haralampos Hatzikirou
- grid.440568.b0000 0004 1762 9729Mathematics Department, Khalifa University, Abu Dhabi, UAE ,grid.4488.00000 0001 2111 7257Centre for Information Services and High Performance Computing, TU Dresden, Dresden, Germany
| |
Collapse
|
3
|
Khailaie S, Mitra T, Bandyopadhyay A, Schips M, Mascheroni P, Vanella P, Lange B, Binder SC, Meyer-Hermann M. Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures. BMC Med 2021; 19:32. [PMID: 33504336 PMCID: PMC7840427 DOI: 10.1186/s12916-020-01884-4] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 12/09/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. METHODS We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. RESULTS The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2-3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. CONCLUSIONS The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.
Collapse
Affiliation(s)
- Sahamoddin Khailaie
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, Braunschweig, 38106 Germany
| | - Tanmay Mitra
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, Braunschweig, 38106 Germany
| | - Arnab Bandyopadhyay
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, Braunschweig, 38106 Germany
| | - Marta Schips
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, Braunschweig, 38106 Germany
| | - Pietro Mascheroni
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, Braunschweig, 38106 Germany
| | - Patrizio Vanella
- Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, Braunschweig, 38124 Germany
- Hannover Biomedical Research School (HBRS), Carl-Neuberg-Str. 1, Hannover, 30625 Germany
- Chair of Empirical Methods in Social Science and Demography, University of Rostock, Ulmenstr. 69, Rostock, 18057 Germany
| | - Berit Lange
- Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, Braunschweig, 38124 Germany
- German Center for Infection Research (DZIF), Inhoffenstraße 7, Braunschweig, 38124 Germany
| | - Sebastian C. Binder
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, Braunschweig, 38106 Germany
| | - Michael Meyer-Hermann
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, Braunschweig, 38106 Germany
- Institute for Biochemistry, Biotechnology and Bioinformatics, Technische Universität Braunschweig, Braunschweig, Germany
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Carl-Neuberg-Straße 1, Hannover, 30625 Germany
| |
Collapse
|
4
|
Rizzuti IF, Mascheroni P, Arcucci S, Ben-Mériem Z, Prunet A, Barentin C, Rivière C, Delanoë-Ayari H, Hatzikirou H, Guillermet-Guibert J, Delarue M. Mechanical Control of Cell Proliferation Increases Resistance to Chemotherapeutic Agents. Phys Rev Lett 2020; 125:128103. [PMID: 33016731 DOI: 10.1103/physrevlett.125.128103] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 08/07/2020] [Indexed: 06/11/2023]
Abstract
While many cellular mechanisms leading to chemotherapeutic resistance have been identified, there is an increasing realization that tumor-stroma interactions also play an important role. In particular, mechanical alterations are inherent to solid cancer progression and profoundly impact cell physiology. Here, we explore the influence of compressive stress on the efficacy of chemotherapeutics in pancreatic cancer spheroids. We find that increased compressive stress leads to decreased drug efficacy. Theoretical modeling and experiments suggest that mechanical stress decreases cell proliferation which in turn reduces the efficacy of chemotherapeutics that target proliferating cells. Our work highlights a mechanical form of drug resistance and suggests new strategies for therapy.
Collapse
Affiliation(s)
- Ilaria Francesca Rizzuti
- CNRS, UPR8001, LAAS-CNRS, 7 Avenue du Colonel Roche, F-31400 Toulouse, France
- Laboratory of Nanotechnology for Precision Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30, 16163 Genoa, Italy
- Computer Science and Technology, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, Via All'Opera Pia, 13, 16145 Genoa, Italy
| | - Pietro Mascheroni
- Department of Systems Immunology and Braunschweig Integrated Center of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, 38106 Braunschweig, Germany
| | - Silvia Arcucci
- INSERM U1037, CRCT, Universite Paul Sabatier, F-31037 Toulouse, France
- Laboratoire d'Excellence TouCAN, F-31037 Toulouse, France
| | - Zacchari Ben-Mériem
- CNRS, UPR8001, LAAS-CNRS, 7 Avenue du Colonel Roche, F-31400 Toulouse, France
| | - Audrey Prunet
- Univ Lyon, Univ Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, F-69622 Villeurbanne, France
| | - Catherine Barentin
- Univ Lyon, Univ Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, F-69622 Villeurbanne, France
| | - Charlotte Rivière
- Univ Lyon, Univ Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, F-69622 Villeurbanne, France
| | - Hélène Delanoë-Ayari
- Univ Lyon, Univ Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, F-69622 Villeurbanne, France
| | - Haralampos Hatzikirou
- Department of Systems Immunology and Braunschweig Integrated Center of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Rebenring 56, 38106 Braunschweig, Germany
| | - Julie Guillermet-Guibert
- INSERM U1037, CRCT, Universite Paul Sabatier, F-31037 Toulouse, France
- Laboratoire d'Excellence TouCAN, F-31037 Toulouse, France
| | - Morgan Delarue
- CNRS, UPR8001, LAAS-CNRS, 7 Avenue du Colonel Roche, F-31400 Toulouse, France
| |
Collapse
|
5
|
Mascheroni P, Meyer-Hermann M, Hatzikirou H. Investigating the Physical Effects in Bacterial Therapies for Avascular Tumors. Front Microbiol 2020; 11:1083. [PMID: 32582070 PMCID: PMC7287150 DOI: 10.3389/fmicb.2020.01083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 04/30/2020] [Indexed: 11/13/2022] Open
Abstract
Tumor-targeting bacteria elicit anticancer effects by infiltrating hypoxic regions, releasing toxic agents and inducing immune responses. Although current research has largely focused on the influence of chemical and immunological aspects on the mechanisms of bacterial therapy, the impact of physical effects is still elusive. Here, we propose a mathematical model for the anti-tumor activity of bacteria in avascular tumors that takes into account the relevant chemo-mechanical effects. We consider a time-dependent administration of bacteria and analyze the impact of bacterial chemotaxis and killing rate. We show that active bacterial migration toward tumor hypoxic regions provides optimal infiltration and that high killing rates combined with high chemotactic values provide the smallest tumor volumes at the end of the treatment. We highlight the emergence of steady states in which a small population of bacteria is able to constrain tumor growth. Finally, we show that bacteria treatment works best in the case of tumors with high cellular proliferation and low oxygen consumption.
Collapse
Affiliation(s)
- Pietro Mascheroni
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Michael Meyer-Hermann
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Centre for Infection Research, Braunschweig, Germany.,Centre for Individualized Infection Medicine, Hannover, Germany.,Institute for Biochemistry, Biotechnology and Bioinformatics, Technische Universität Braunschweig, Braunschweig, Germany
| | - Haralampos Hatzikirou
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Centre for Infection Research, Braunschweig, Germany
| |
Collapse
|
6
|
Alfonso JCL, Papaxenopoulou LA, Mascheroni P, Meyer-Hermann M, Hatzikirou H. On the Immunological Consequences of Conventionally Fractionated Radiotherapy. iScience 2020; 23:100897. [PMID: 32092699 PMCID: PMC7038527 DOI: 10.1016/j.isci.2020.100897] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 01/25/2020] [Accepted: 02/04/2020] [Indexed: 12/17/2022] Open
Abstract
Emerging evidence demonstrates that radiotherapy induces immunogenic death on tumor cells that emit immunostimulating signals resulting in tumor-specific immune responses. However, the impact of tumor features and microenvironmental factors on the efficacy of radiation-induced immunity remains to be elucidated. Herein, we use a calibrated model of tumor-effector cell interactions to investigate the potential benefits and immunological consequences of radiotherapy. Simulations analysis suggests that radiotherapy success depends on the functional tumor vascularity extent and reveals that the pre-treatment tumor size is not a consistent determinant of treatment outcomes. The one-size-fits-all approach of conventionally fractionated radiotherapy is predicted to result in some overtreated patients. In addition, model simulations also suggest that an arbitrary increase in treatment duration does not necessarily result in better tumor control. This study highlights the potential benefits of tumor-immune ecosystem profiling during treatment planning to better harness the immunogenic potential of radiotherapy. Radiotherapy success depends on radiation-induced tumor-specific immune responses Pre-treatment tumor size is not a consistent determinant of radiotherapy outcomes Increase in treatment duration does not necessarily result in better tumor control Tumor vascularity impacts antitumor efficacy of radiation-induced immune responses
Collapse
Affiliation(s)
- Juan Carlos L Alfonso
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Rebenring 56, 38106 Braunschweig, Germany
| | - Lito A Papaxenopoulou
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Rebenring 56, 38106 Braunschweig, Germany
| | - Pietro Mascheroni
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Rebenring 56, 38106 Braunschweig, Germany
| | - Michael Meyer-Hermann
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Rebenring 56, 38106 Braunschweig, Germany; Centre for Individualised Infection Medicine (CIIM), Feodor-Lynen-Straße 15, 30625 Hannover, Germany; Institute of Biochemistry, Biotechnology and Bioinformatics, Technische Universität Braunschweig, Spielmannstraße 7, 38106 Braunschweig, Germany.
| | - Haralampos Hatzikirou
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Rebenring 56, 38106 Braunschweig, Germany.
| |
Collapse
|
7
|
Mascheroni P, López Alfonso JC, Kalli M, Stylianopoulos T, Meyer-Hermann M, Hatzikirou H. On the Impact of Chemo-Mechanically Induced Phenotypic Transitions in Gliomas. Cancers (Basel) 2019; 11:cancers11050716. [PMID: 31137643 PMCID: PMC6562768 DOI: 10.3390/cancers11050716] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 05/07/2019] [Accepted: 05/17/2019] [Indexed: 11/16/2022] Open
Abstract
Tumor microenvironment is a critical player in glioma progression, and novel therapies for its targeting have been recently proposed. In particular, stress-alleviation strategies act on the tumor by reducing its stiffness, decreasing solid stresses and improving blood perfusion. However, these microenvironmental changes trigger chemo-mechanically induced cellular phenotypic transitions whose impact on therapy outcomes is not completely understood. In this work we analyze the effects of mechanical compression on migration and proliferation of glioma cells. We derive a mathematical model of glioma progression focusing on cellular phenotypic plasticity. Our results reveal a trade-off between tumor infiltration and cellular content as a consequence of stress-alleviation approaches. We discuss how these novel findings increase the current understanding of glioma/microenvironment interactions and can contribute to new strategies for improved therapeutic outcomes.
Collapse
Affiliation(s)
- Pietro Mascheroni
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Center for Infectious Research, 38106 Braunschweig, Germany.
| | - Juan Carlos López Alfonso
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Center for Infectious Research, 38106 Braunschweig, Germany.
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, 30625 Hannover, Germany.
| | - Maria Kalli
- Cancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678 Nicosia, Cyprus.
| | - Triantafyllos Stylianopoulos
- Cancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678 Nicosia, Cyprus.
| | - Michael Meyer-Hermann
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Center for Infectious Research, 38106 Braunschweig, Germany.
- Centre for Individualized Infection Medicine, 30625 Hannover, Germany.
- Institute for Biochemistry, Biotechnology and Bioinformatics, Technische Universität Braunschweig, 38106 Braunschweig, Germany.
| | - Haralampos Hatzikirou
- Braunschweig Integrated Centre of Systems Biology and Helmholtz Center for Infectious Research, 38106 Braunschweig, Germany.
| |
Collapse
|
8
|
Mascheroni P, Schrefler BA. In Silico Models for Nanomedicine: Recent Developments. Curr Med Chem 2019; 25:4192-4207. [PMID: 28911299 DOI: 10.2174/0929867324666170417120725] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Revised: 01/11/2017] [Accepted: 03/02/2017] [Indexed: 11/22/2022]
Abstract
Nanomedicine is a recent promising setting for the advancement of current medical therapies, in particular for cancer. Nanoparticle-mediated therapies are aimed to tackle extremely complex phenomena, involving different biochemical, mechanical and biophysical factors. Computational models can contribute to medical research by helping the understanding of biological mechanisms and by providing quantitative analyses. In this work, we report on computational models that address four main issues related to the use of nanoparticles in anti-cancer therapies, namely the delivery of nanoparticles, their uptake by cells, the release of drugs from nano-platforms and nanoparticle-based therapeutics. In silico approaches constitute a valuable tool to aid clinical studies, to guide the rational design of new nanoparticle formulations and to identify the optimal strategies for existing treatments.
Collapse
Affiliation(s)
- Pietro Mascheroni
- Department of Civil, Environmental and Architectural Engineering, Universita di Padova, Via Marzolo 9, 35131, Padova, Italy
| | - Bernhard Aribo Schrefler
- Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX 77030, United States.,Institute for Advanced Study (IAS), Technische Universität München, Lichtenbergstraße 2a, 85748, Garching bei München, Germany
| |
Collapse
|
9
|
Mascheroni P, Penta R. The role of the microvascular network structure on diffusion and consumption of anticancer drugs. Int J Numer Method Biomed Eng 2017; 33:e2857. [PMID: 27921393 DOI: 10.1002/cnm.2857] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2016] [Revised: 10/19/2016] [Accepted: 11/26/2016] [Indexed: 06/06/2023]
Abstract
We investigate the impact of microvascular geometry on the transport of drugs in solid tumors, focusing on the diffusion and consumption phenomena. We embrace recent advances in the asymptotic homogenization literature starting from a double Darcy-double advection-diffusion-reaction system of partial differential equations that is obtained exploiting the sharp length separation between the intercapillary distance and the average tumor size. The geometric information on the microvascular network is encoded into effective hydraulic conductivities and diffusivities, which are numerically computed by solving periodic cell problems on appropriate microscale representative cells. The coefficients are then injected into the macroscale equations, and these are solved for an isolated, vascularized spherical tumor. We consider the effect of vascular tortuosity on the transport of anticancer molecules, focusing on Vinblastine and Doxorubicin dynamics, which are considered as a tracer and as a highly interacting molecule, respectively. The computational model is able to quantify the treatment performance through the analysis of the interstitial drug concentration and the quantity of drug metabolized in the tumor. Our results show that both drug advection and diffusion are dramatically impaired by increasing geometrical complexity of the microvasculature, leading to nonoptimal absorption and delivery of therapeutic agents. However, this effect apparently has a minor role whenever the dynamics are mostly driven by metabolic reactions in the tumor interstitium, eg, for highly interacting molecules. In the latter case, anticancer therapies that aim at regularizing the microvasculature might not play a major role, and different strategies are to be developed.
Collapse
Affiliation(s)
- Pietro Mascheroni
- Dipartimento di Ingegneria Civile, Edile ed Ambientale, Università di Padova, Via Marzolo 9, 35131, Padua, Italy
| | - Raimondo Penta
- Departamento de Mecanica de los Medios Continuos y T. Estructuras, E.T.S. de caminos, canales y puertos, Universidad Politecnica de Madrid, Calle Profesor Aranguren S/N, 28040, Madrid, Spain
| |
Collapse
|
10
|
Mascheroni P, Boso D, Preziosi L, Schrefler BA. Evaluating the influence of mechanical stress on anticancer treatments through a multiphase porous media model. J Theor Biol 2017; 421:179-188. [PMID: 28392183 DOI: 10.1016/j.jtbi.2017.03.027] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2016] [Revised: 03/27/2017] [Accepted: 03/28/2017] [Indexed: 01/16/2023]
Abstract
Drug resistance is one of the leading causes of poor therapy outcomes in cancer. As several chemotherapeutics are designed to target rapidly dividing cells, the presence of a low-proliferating cell population contributes significantly to treatment resistance. Interestingly, recent studies have shown that compressive stresses acting on tumor spheroids are able to hinder cell proliferation, through a mechanism of growth inhibition. However, studies analyzing the influence of mechanical compression on therapeutic treatment efficacy have still to be performed. In this work, we start from an existing mathematical model for avascular tumors, including the description of mechanical compression. We introduce governing equations for transport and uptake of a chemotherapeutic agent, acting on cell proliferation. Then, model equations are adapted for tumor spheroids and the combined effect of compressive stresses and drug action is investigated. Interestingly, we find that the variation in tumor spheroid volume, due to the presence of a drug targeting cell proliferation, considerably depends on the compressive stress level of the cell aggregate. Our results suggest that mechanical compression of tumors may compromise the efficacy of chemotherapeutic agents. In particular, a drug dose that is effective in reducing tumor volume for stress-free conditions may not perform equally well in a mechanically compressed environment.
Collapse
Affiliation(s)
- Pietro Mascheroni
- Dipartimento di Ingegneria Civile, Edile ed Ambientale, Università di Padova, Via Marzolo 9, 35131 Padova, Italy
| | - Daniela Boso
- Dipartimento di Ingegneria Civile, Edile ed Ambientale, Università di Padova, Via Marzolo 9, 35131 Padova, Italy
| | - Luigi Preziosi
- Dipartimento di Scienze Matematiche, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10124 Torino, Italy
| | - Bernhard A Schrefler
- Institute for Advanced Study, Technische Universität München, Lichtenbergstraße 2, 85748 Garching bei München, Germany and Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX 77030, USA.
| |
Collapse
|
11
|
Cappello L, Demma F, Ermolli P, Mascheroni P, Moalli S. [Surgical treatment of arthrosis]. Minerva Med 1979; 70:1105-19. [PMID: 440581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
|