شبیه‌سازی نقش درمان ضدرگ‌زایی در رفتار جریان سیال و رسانش ماکرومولکول در تومور جامد غیرهمگن

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکترا، گروه تبدیل انرژی، دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

2 استاد، گروه تبدیل انرژی، دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

3 دانشیار، گروه تبدیل انرژی، دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

چکیده

مطالعه حاضر مدل عددی مبتنی بر مدل‌های ریاضی حاکم بر رفتار جریان سیال و انتقال دارو در تومورها را توسعه می‌دهد تا به بررسی رسانش ماکرومولکول به یک تومور غیریکنواخت، شامل بخش‌های مختلف موجود در تومور جامد واقعی، تحت تأثیر هنجارسازی عروقی بپردازد. در این پژوهش اندازه تومور در بازه متفاوتی (شعاع معادل از 0/23 تا 2/79 سانتی‌متر) در نظر گرفته می‌شود. مساحت زیر نمودارهای توزیع غلظت میانگین دارو و انحراف از آن بر حسب زمان در ناحیه توموری به عنوان مقدار داروی تحویلی و یکنواختی توزیع داروی تحویلی برای بررسی کیفیت دارورسانی مطالعه می‌شوند. نتایج نشان می‌دهند که رفتار جریان سیال میان‌بافتی و توزیع غلظت عامل درمانی، قبل و بعد از هنجارسازی، به اندازه تومور وابسته می‌باشند. هنجارسازی در تمام اندازه‌ها سبب کاهش فشار سیال میان‌بافتی می‌شود که با کم شدن اندازه تومور، افت فشار ناشی از هنجارسازی افزایش می‌یابد. هنجارسازی در زمان‌های متفاوتی که وابسته به اندازه تومور است، سبب بهبود توزیع غلظت آنتی‌بادی می‌شود. با این‌حال از منظر معیارهای میانگین مکانی-زمانی، هنجارسازی عروقی در شعاع معادل از 0/46 تا 0/93 سانتی‌متر با افزایش یکنواختی توزیع، سبب بهبود رسانش ماکرومولکول به ناحیه توموری می‌شود. این پژوهش با بحث راجع به سازوکار‌های اثرگذار در کارکرد هنجارسازی می‌تواند چشم‌اندازی برای مطالعات درون‌تنی و برون‌تنی فراهم کند که از درمان ترکیبی ضدرگ‌زایی و شیمی‌درمانی بهره می‌برند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Simulation of the Role of the Anti-Angiogenic Therapy in Fluid Flow Behavior and Macromolecule Transport into a Heterogeneous Solid Tumor

نویسندگان [English]

  • Mahya Mohammadi 1
  • Cyrus Aghanajafi 2
  • Majid Soltani 3
1 Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
3 Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
چکیده [English]

The present study develops a numerical approach based on the mathematical models governing the behavior of fluid flow and drug transport in tumors to investigate the delivery of a macromolecule under the effect of the vascular normalization into a non-uniform tumor, including different parts of a real solid tumor. In this study, different tumor sizes in the range of  are considered. The area under the curves of the drug average distribution and its deviation in the tumor site over time is studied as the amount of drug delivered and the uniformity of delivered drug to assess the quality of drug delivery. Results show that before and after normalization, the behaviors of interstitial fluid flow and the distribution of therapeutic agent concentration depend on tumor size. Normalization in all sizes reduces the interstitial fluid pressure, which this pressure drop increases as the tumor size reduces. Normalization improves antibody concentration distribution at different times depending on tumor size. However, from the point of view of the average spatiotemporal criterion, vascular normalization improves macromolecule delivery into the tumor site in  by increasing the distribution uniformity. This research, by discussing the mechanisms affecting normalization efficiency, can provide insights for in vivo and in vitro studies that address the combination of anti-angiogenic therapy and chemotherapy.

کلیدواژه‌ها [English]

  • Fluid flow
  • Drug transport
  • Non-uniform tumor
  • Vascular normalization
  • Combo-therapy
[1] M. Enayatrad, M. Mirzaei, H. Salehiniya, M.R. Karimirad, S. Vaziri, F. Mansouri, A. Moudi, Trends in Incidence of Common Cancers in Iran, Asian Pacific Journal of Cancer Prevention, 17 (2016) 39-42.
[2] R.K. Jain, Normalization of Tumor Vasculature: An Emerging Concept in Antiangiogenic Therapy, Science, 307 (2005) 58-62.
[3] F. Moradi Kashkooli, M. Soltani, M.H. Hamedi, Image-Based Numerical Model for Drug Delivery to Solid Tumors, Amirkabir Journal of Mechanical Engineering, 53 (2021) 5-5 (in Persian).
[4] M. Rezaeian, M. Soltani, Computational Modeling of Intraperitoneal Drug Delivery for the Treatment of Peritoneal Carcinomatosis, Amirkabir Journal of Mechanical Engineering, 54 (2022) 11-11 (in Persian).
[5] F. Moradi Kashkooli, M. Rezaeian, M. Soltani, Drug Delivery through Nanoparticles in Solid Tumors: A Mechanistic Understanding, Nanomedicine, Article in Press (2022).
[6] M. Hadjicharalambous, P.A. Wijeratne, V. Vavourakis, From Tumour Perfusion to Drug Delivery and Clinical Translation of in Silico Cancer Models, Methods, 185 (2021) 82-93.
[7] R.K. Jain, L.T. Baxter, Mechanisms of Heterogeneous Distribution of Monoclonal Antibodies and other Macromolecules in Tumors: Significance of Elevated Interstitial Pressure, Cancer Research, 48 (1988) 7022-7032.
[8] L.T. Baxter, R.K. Jain, Transport of Fluid and Macromolecules in Tumors I. Role of Interstitial Pressure and Convection, Microvascular Research, 37 (1989) 77-104.
[9] L.T. Baxter, R.K. Jain, Transport of Fluid and Macromolecules in Tumors II. Role of Heterogeneous Perfusion and Lymphatics, Microvascular Research, 40 (1990) 246-263.
[10] L.T. Baxter, R.K. Jain, Transport of Fluid and Macromolecules in Tumors III Role of Binding and Metabolism, Microvascular Research, 41 (1991) 5-23.
[11] M. Soltani, P. Chen, Numerical Modeling of Fluid Flow in Solid Tumors, PLoS ONE, 6 (2011) e20344.
[12] M. Soltani, P. Chen, Effect of Tumor Shape and Size on Drug Delivery to Solid Tumors, Journal of Biological Engineering, 6 (2012) 4.
[13] M.F. Flessner, R.L. Dedrick, J.S. Schultz, A Distributed Model of Peritoneal-Plasma Transport: Theoretical Considerations, American Journal of Physiology, 246 (1984) 597-607.
[14] M.F. Flessner, J.D. Fenstermacher, R.L. Dedrick, R.G. Blasberg, A Distributed Model of Peritoneal-Plasma Transport: Tissue Concentration Gradients, American Journal of Physiology, 248 (1985) 425-435.
[15] M. Sefidgar, M. Soltani, K. Raahemifar, H. Bazmara, S.M. Mousavi Nayinian, M. Bazargan, Effect of Tumor Shape, Size, and Tissue Transport Properties on Drug Delivery to Solid Tumors, Journal of Biological Engineering, 8 (2014) 12.
[16] M. Steuperaert, G.F. D’Urso Labate, C. Debbaut, O. De Wever, C. Vanhove, Mathematical Modeling of Intraperitoneal Drug Delivery: Simulation of Drug Distribution in a Single Tumor Nodule, Drug Delivery, 24 (2017) 491-501.
[17] M. Sefidgar, M. Soltani, K. Raahemifar, M. Sadeghi, H. Bazmara, M. Bazargan, S.M. Mousavi Nayinian, Numerical Modeling of Drug Delivery in a Dynamic Solid Tumor Microvasculature, Microvascular Research, 99 (2015) 43-56.
[18] F. Moradi Kashkooli, M. Soltani, M. Rezaeian, E. Taatizadeh, M.H. Hamedi, Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor-Computational Approach, Microvascular Research, 123 (2019) 111-124.
[19] F. Moradi Kashkooli, M. Soltani, Evaluation of Solid Tumor Response to Sequential Treatment Cycles via a New Computational Hybrid Approach, Scientific Reports, 11 (2021) 21475.
[20] M. Mohammadi, M. Sefidgar, Modeling of Drug Delivery to Solid Tumor with a Remodeled Dynamic Capillary Network Induced by Two Parent Vessels, Modares Mechanical Engineering, 19 (2019) 2877-2886 (in Persian).
[21] G.M. Tozer, Measuring Tumour Vascular Response to Antivascular and Antiangiogenic Drugs, The British Journal of Radiology, 76 (2003) 23-35.
[22] R.K. Jain, Normalizing Tumor Vasculature with Anti-angiogenic Therapy: A New paradigm for Combination Therapy, Nature Medicine 7(2001) 987–989.
[23] D. Fukumura, R.K. Jain, Tumor Microvasculature and Microenvironment: Targets for Anti-Angiogenesis and Normalization, Microvascular Research, 74 (2007) 72-84.
[24] L. Pian, Z. Chen, C. Jing, Z. Ruiguang, R. Jinghua, H. Yuhui, Z. Fang, L. Zhenyu, W. Gang, Combinational Therapy of Interferon-α and Chemotherapy Normalizes Tumor Vasculature by Regulating Pericytes Including the Novel Marker RGS5 in Melanoma, Journal of Immunotherapy, 34 (2011) 320-326.
[25] R. Grossman, H. Brastianos, J.O. Blakeley, A. Mangraviti, B. Lal, P. Zadnik, L. Hwang, R.T. Wicks, R.C. Goodwin, H. Brem, B. Tyler, Combination of Anti-VEGF Therapy and Temozolomide in Two Experimental Human Glioma Models, Journal of Neuro-Oncology, 116 (2014) 59-65.
[26] R.K. Jain, R.T. Tong, L.L. Munn, Effect of Vascular Normalization by Antiangiogenic Therapy on Interstitial Hypertension, Peritumor Edema, and Lymphatic Metastasis: Insights from a Mathematical Model, Cancer Research, 67 (2007) 2729-2735.
[27] M. Mohammadi, C. Aghanajafi, M. Soltani, (2021) Numerical Modelling of Drug Delivery in an Isolated Solid Tumor under the Influence of Vascular Normalization. In: Kilgour, D. M., Kunze, H., Makarov, R., Melnik, R. & Wang, X. Recent Developments in Mathematical, Statistical, and Computational Sciences. AMMCS 2019, Springer Proceedings in Mathematics & Statistics, vol 343. Springer, Cham.
[28] T. Stylianopoulos, R.K. Jain, Combining Two Strategies to Improve Perfusion and Drug Delivery in Solid Tumors, Proceedings of the National Academy of Science, 110 (2013) 18632-18637.
[29] A. Moath, Y.X. Xiao, The Influence of Tumour Vasculature on Fluid Flow in Solid Tumours: A Mathematical Modelling Study., Biophysics Reports, 7 (2021) 35-54.
[30] E.P. Salathe, K.-N. An, A Mathematical Analysis of Fluid Movement across Capillary Walls, Microvascular Research, 11 (1976) 1-23.
[31] E.A. Swabb, J. Wei, P.M. Gullino, Diffusion and Convection in Normal and Neoplastic Tissues, Cancer Research, 34 (1974) 2814–2822.
[32] C.S. Patlak, D.A. Goldstein, J.F. Hoffman, The Flow of Solute and Solvent across a Two-Membrane System, Journal of Theoretical Biology, 5 (1963) 426-442.
[33] L.I. Kolitsi, S.G. Yiantsios, Transport of Nanoparticles in Magnetic Targeting: Comparison of Magnetic, Diffusive and Convective Forces and Fluxes in the Microvasculature, through Vascular Pores and across the Interstitium, Microvascular Research, 130 (2020) 104007.
[34] J. Lyu, J. Cao, P. Zhang, Y. Liu, H. Cheng, Coupled Hybrid Continuum-Discrete Model of Tumor Angiogenesis and Growth, PLoS ONE, 11 (2016) e0163173.
[35] F. Moradi Kashkooli, M. Soltani, M.M. Momeni, Computational Modeling of Drug Delivery to Solid Tumors: A Pilot Study Based on a Real Image, Journal of Drug Delivery Science and Technology, 62 (2021) 102347.
[36] B. Rippe, B. Haraldsson, Capillary Permeability in Rat Hindquarters as Determined by Estimations of Capillary Reflection Coefficients, Acta Physiologica Scandinavica, 127 (1986) 289-303.
[37] C.G. Willett, Y. Boucher, E.d. Tomaso, D.G. Duda, L.L. Munn, R.T. Tong, D.C. Chung, D.V. Sahani, S.P. Kalva, S.V. Kozin, M. Mino, K.S. Cohen, D.T. Scadden, A.C. Hartford, A.J. Fischman, J.W. Clark, D.P. Ryan, A.X. Zhu, L.S. Blaszkowsky, H.X. Chen, P.C. Shellito, G.Y. Lauwers, R.K. Jain, Direct Evidence that the VEGF-Specific Antibody Bevacizumab Has Antivascular Effects in Human Rectal Cancer, Nature Medicine, 10 (2004) 145–147.
[38] K. Ballard, W. Perl, Osmotic Reflection Coefficients of Canine Subcutaneous Adipose Tissue Endothelium, Microvascular Research, 16 (1978) 224-236.
[39] J.L. Anderson, D.M. Malone, Mechanism of Osmotic Flow in Porous Membranes, Biophysical Journal, 14 (1974) 957-982.
[40] M. Mohammadi, C. Aghanajafi, M. Soltani, K. Raahemifar, Numerical Investigation on the Anti-Angiogenic Therapy-Induced Normalization in Solid Tumors, Pharmaceutics, 14 (2022) 363.
[41] D.G. Covell, J. Barbet, O.D. Holton, C.D.V. Black, R.J. Parker, J.N. Weinstein, Pharmacokinetics of Monoclonal Immunoglobulin , , and , Cancer Research, 46 (1986) 3969-3978.
[42] S.R. Plotkin, A.O. Stemmer-Rachamimov, F.G. Barker, C. Halpin, T.P. Padera, A. Tyrrell, A.G. Sorensen, R.K. Jain, E.d. Tomaso, Hearing Improvement after Bevacizumab in Patients with Neurofibromatosis Type 2, The New England Journal of Medicine, 361 (2009) 358-367.
[43] Y. Boucher, L.T. Baxter, R.K. Jain, Interstitial Pressure Gradients in Tissue-Isolated and Subcutaneous Tumors: Implications for Therapy, Cancer Research, 50 (1990) 4478-4484.
[44] R.K. Jain, Transport of Molecules in the Tumor Interstitium: A Review, Cancer Research, 47 (1987) 3039-3051.
[45] H. Wiig, E. Tveit, R. Hultborn, R.K. Reed, L. Weiss, Interstitial Fluid Pressure in DMBA-Induced rat Mammary Tumours, Scandinavian Journal of Clinical and Laboratory Investigation, 42 (1982) 159-164.
[46] Y. Boucher, R.K. Jain, Microvascular Pressure is the Principal Driving Force for Interstitial Hypertension in Solid Tumors: Implications for Vascular Collapse, Cancer Research, 52 (1992) 5110–5114.
[47] L. Eikenes, Ø.S. Bruland, C. Brekken, C.d. Lange Davies, Collagenase Increases the Transcapillary Pressure Gradient and Improves the Uptake and Distribution of Monoclonal Antibodies in Human Osteosarcoma Xenografts, Cancer Research, 64 (2004) 4768-4773.
[48] Y. Fan, W. Du, B. He, F. Fu, L. Yuan, H. Wu, W. Dai, H. Zhang, X. Wang, J. Wang, X. Zhang, Q. Zhang, The Reduction of Tumor Interstitial Fluid Pressure by Liposomal Imatinib and its Effect on Combination Therapy with Liposomal Doxorubicin, Biomaterials, 34 (2013) 2277-2288.
[49] C.-G. Lee, M. Heijn, E.d. Tomaso, G. Griffon-Etienne, M. Ancukiewicz, C. Koike, K.R. Park, N. Ferrara, R.K. Jain, H.D. Suit, Y. Boucher, Anti-Vascular Endothelial Growth Factor Treatment Augments Tumor Radiation Response under Normoxic or Hypoxic Conditions, Cancer Research, 60 (2000) 5565-5570.
[50] J.R. Bourne, Mixing in Single-Phase Chemical Reactors, in: Mixing in the Process Industries, Butterworth-Heinemann, 1992.
[51] T. Webb, Vascular Normalization: Study Examines How Antiangiogenesis Therapies Work, Journal of the National Cancer Institute, 97 (2005) 336-337.
[52] Y.-J. Ho, C.-K. Yeh, Combination of Anti-Angiogenesis Treatment and Chemotherapy in Solid Tumors by Using Drug-Loaded Nanodroplets Vaporization, in: IEEE International Ultrasonics Symposium (IUS), 2016, pp. 1-4.