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A numerical study on the effect of osmotic pressure on stress and strain in intercellular structures of tumor tissue in the poro-elastic model

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Abstract

Understanding the biomechanical phenomena governing the intercellular space can be considered as an effective tool for the treatment of tumors and cancerous tissues. One of the factors that plays a significant role in the quality and efficiency of the drug delivery process to tumors and cancerous tissues as one of the influential biomechanical factors is the osmotic pressure in the interstitial fluid in the intercellular space of tumors. In this study, the effect of osmotic pressure on the distribution of stress and strain in a tumor tissue is investigated in two modes using a poro-elastic and two-dimensional model. The results of this study show that the effect of osmotic pressure and change in the circumference of tumor tissue causes a decrease or increase in mechanical stress and strain, which can be used to control the tumor growth for treatment. In fact, according to the results, by isolating the tumor tissue (This refers to a condition in which tumor cells have grown in rigid containers) and considering the osmotic pressure, the stress created in the tissue is reduced, but if the tumor tissue is surrounded by healthy tissue and osmotic pressure is applied to it, the stress to increase by about 30 Pa compared to when these two assumptions are not considered.

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References

  1. Roh HD, Boucher Y, Kalnicki S, Buchsbaum R, Bloomer WD, Jain RK (1991) Interstitial hypertension in carcinoma of uterine cervix in patients: possible correlation with tumor oxygenation and radiation response. Cancer Res 51(24):6695–6698

    Google Scholar 

  2. Grantab RH, Tannock IF (2012) Penetration of anticancer drugs through tumour tissue as a function of cellular packing density and interstitial fluid pressure and its modification by bortezomib. BMC Cancer 12(1):214

    Article  Google Scholar 

  3. Sen A, Capitano ML, Spernyak JA, Schueckler JT, Thomas S, Singh AK, Evans SS, Hylander BL, Repasky EA (2011) Mild elevation of body temperature reduces tumor interstitial fluid pressure and hypoxia and enhances efficacy of radiotherapy in murine tumor models. Can Res 71(11):3872–3880

    Article  Google Scholar 

  4. Rofstad EK, Galappathi K, Mathiesen BS (2014) Tumor interstitial fluid pressure—a link between tumor hypoxia, microvascular density, and lymph node metastasis. Neoplasia 16(7):586–594

    Article  Google Scholar 

  5. Lee I, Boucher Y, Demhartner TJ, Jain RK (1994) Changes in tumour blood flow, oxygenation and interstitial fluid pressure induced by pentoxifylline. Br J Cancer 69(3):492

    Article  Google Scholar 

  6. Ferretti S, Allegrini PR, Becquet MM, McSheehy PM (2009) Tumor interstitial fluid pressure as an early-response marker for anticancer therapeutics. Neoplasia 11(9):874–881

    Article  Google Scholar 

  7. Tong RT, Boucher Y, Kozin SV, Winkler F, Hicklin DJ, Jain RK (2004) Vascular normalization by vascular endothelial growth factor receptor 2 blockade induces a pressure gradient across the vasculature and improves drug penetration in tumors. Can Res 64(11):3731–3736

    Article  Google Scholar 

  8. Ariffin AB et al (2014) Releasing pressure in tumors: what do we know so far and where do we go from here? A review. Cancer Res 74(10):2655–2662

    Article  Google Scholar 

  9. Heldin C-H, Rubin K, Pietras K, Östman A (2004) High interstitial fluid pressure—an obstacle in cancer therapy. Nat Rev Cancer 4(10):806

    Article  Google Scholar 

  10. Gao X, Zhang J, Huang Z, Zuo T, Qing Lu, Guangyu Wu, Shen Qi (2017) Reducing interstitial fluid pressure and inhibiting pulmonary metastasis of breast cancer by gelatin modified cationic lipid nanoparticles. ACS Appl Mater Interfaces 9(35):29457–29468

    Article  Google Scholar 

  11. Northcott JM et al (2018) Feeling stress: the mechanics of cancer progression and aggression. Front Cell Dev Biol 6:17

    Article  Google Scholar 

  12. Shieh AC (2011) Biomechanical forces shape the tumor microenvironment. Ann Biomed Eng 39(5):1379–1389

    Article  Google Scholar 

  13. Jain RK, Martin JD, Stylianopoulos T (2014) The role of mechanical forces in tumor growth and therapy. Ann Rev Biomed Eng 16:321–346

    Article  Google Scholar 

  14. Iranmanesh F, Nazari MA (2017) Finite element modeling of avascular tumor growth using a stress-driven model. J Biomech Eng 139(8):081009

    Article  Google Scholar 

  15. Helmlinger G, Netti PA, Lichtenbeld HC, Melder RJ, Jain RK (1997) Solid stress inhibits the growth of multicellular tumor spheroids. Nat Biotechnol 15(8):778

    Article  Google Scholar 

  16. Cheng G, Tse J, Jain RK, Munn LL (2009) Micro-environmental mechanical stress controls tumor spheroid size and morphology by suppressing proliferation and inducing apoptosis in cancer cells. PLoS one 4(2):e4632

    Article  Google Scholar 

  17. Mascheroni P, Stigliano C, Carfagna M, Boso DP, Preziosi L, Decuzzi P, Schrefler BA (2016) Predicting the growth of glioblastoma multiforme spheroids using a multiphase porous media model. Biomech Model Mechanobiol 15(5):1215–1228

    Article  Google Scholar 

  18. Delarue M, Montel F, Vignjevic D, Prost J, Joanny J-F, Cappello G (2014) Compressive stress inhibits proliferation in tumor spheroids through a volume limitation. Biophys J 107(8):1821–1828

    Article  Google Scholar 

  19. Mascheroni P, Boso D, Preziosi L, Schrefler BA (2017) Evaluating the influence of mechanical stress on anticancer treatments through a multiphase porous media model. J Theor Biol 421:179–188

    Article  MathSciNet  MATH  Google Scholar 

  20. Pozzi G, Marchesi S, Scita G, Ambrosi D, Ciarletta P (2019) Mechano-biological model of glioblastoma cells in response to osmotic stress. Math Biosci Eng MBE 16(4):2795–2810

    Article  MathSciNet  Google Scholar 

  21. Zhang F, Jiang R, Zhang C (2020) Uncontrolled intracellular osmotic pressure leads to cancer. Preprints 2020:2020060270. https://doi.org/10.20944/preprints202006.0270.v1

  22. Bhattacharyya A, O’Bryan C, Ni Y et al (2020) Hydrogel compression and polymer osmotic pressure. Biotribology 22:100125. https://doi.org/10.1016/j.biotri.2020.100125

  23. Shirole PU, Patil PB, Bachhav RS (2020) REVIEW ON OSMOTIC DRUG DELIVERY SYSTEM. IJRAR Int J Res Anal Rev (IJRAR) 7(2):7–22

    Google Scholar 

  24. Soltani M, Chen P (2011) Numerical modeling of fluid flow in solid tumors. PloS one 6(6):e20344

    Article  Google Scholar 

  25. Soltani M, Chen P (2013) Numerical modeling of interstitial fluid flow coupled with blood flow through a remodeled solid tumor microvascular network. PloS one 8(6):e67025

    Article  Google Scholar 

  26. Sefidgar M, Soltani M, Raahemifar K, Sadeghi M, Bazmara H, Bazargan M, Naeenian MM (2015) Numerical modeling of drug delivery in a dynamic solid tumor microvasculature. Microvasc Res 99:43–56

    Article  Google Scholar 

  27. Kashkooli FM, Soltani M, Hamedi MH (2020) Drug delivery to solid tumors with heterogeneous microvascular networks: novel insights from image-based numerical modeling. Eur J Pharm Sci 151:105399

    Article  Google Scholar 

  28. LoCastro E, Paudyal R, Mazaheri Y, Hatzoglou V, Oh JH, Lu Y, Konar AS et al (2020) Computational modeling of interstitial fluid pressure and velocity in head and neck cancer based on dynamic contrast-enhanced magnetic resonance imaging: feasibility analysis. Tomography 6(2):129

    Article  Google Scholar 

  29. Steuperaert M, Debbaut C, Carlier C, De Wever O, Descamps B, Vanhove C, Ceelen W, Segers P (2019) A 3D CFD model of the interstitial fluid pressure and drug distribution in heterogeneous tumor nodules during intraperitoneal chemotherapy. Drug Deliv 26(1):404–415

    Article  Google Scholar 

  30. Stylianopoulos T, Martin JD, Snuderl M, Mpekris F, Jain SR, Jain RK (2013) Coevolution of solid stress and interstitial fluid pressure in tumors during progression: implications for vascular collapse. Can Res 73(13):3833–3841

    Article  Google Scholar 

  31. Jain RK, Martin JD, Stylianopoulos T (2014) The role of mechanical forces in tumor growth and therapy. Annu Rev Biomed Eng 16:321–346

    Article  Google Scholar 

  32. Mpekris F, Angeli S, Pirentis AP, Stylianopoulos T (2015) Stress-mediated progression of solid tumors: effect of mechanical stress on tissue oxygenation, cancer cell proliferation, and drug delivery. Biomech Model Mechanobiol 14(6):1391–1402

    Article  Google Scholar 

  33. Voutouri C, Polydorou C, Papageorgis P, Gkretsi V, Stylianopoulos T (2016) Hyaluronan-derived swelling of solid tumors, the contribution of collagen and cancer cells, and implications for cancer therapy. Neoplasia 18(12):732–741

    Article  Google Scholar 

  34. Mpekris F, Voutouri C, Papageorgis P, Stylianopoulos T (2018) Stress alleviation strategy in cancer treatment: insights from a mathematical model. ZAMM J Appl Math Mech/Z Angew Math Mech 98(12):2295–2306

    Article  MathSciNet  Google Scholar 

  35. Katsamba I, Evangelidis P, Voutouri C, Tsamis A, Vavourakis V, Stylianopoulos T (2020) Biomechanical modelling of spinal tumour anisotropic growth. Proc R Soc A 476(2238):20190364

    Article  MathSciNet  Google Scholar 

  36. Netti PA, Baxter LT, Boucher Y, Skalak R, Jain RK (1995) Time-dependent behavior of interstitial fluid pressure in solid tumors: implications for drug delivery. Can Res 55(22):5451–5458

    Google Scholar 

  37. Netti PA, Baxter LT, Boucher Y, Skalak R, Jain RK (1997) Macro-and microscopic fluid transport in living tissues: application to solid tumors. AIChE J 43(3):818–834

    Article  Google Scholar 

  38. Andreozzi A, Iasiello M, Netti PA (2019) A thermoporoelastic model for fluid transport in tumour tissues. J R Soc Interface 16(154):20190030

    Article  Google Scholar 

  39. Carotenuto AR, Cutolo A, Palumbo S, Fraldi M (2019) Growth and remodeling in highly stressed solid tumors. Meccanica 54(13):1941–1957

    Article  MathSciNet  Google Scholar 

  40. Yin S-F, Xue S-L, Li Bo, Feng X-Q (2019) Bio–chemo–mechanical modeling of growing biological tissues: finite element method. Int J Non Linear Mech 108:46–54

    Article  Google Scholar 

  41. Cui F, Liu J (2019) Prostate deformable registration through geometric transformation by finite element method. Meccanica 55:1–12

    Google Scholar 

  42. Penta R, Merodio J (2017) Homogenized modeling for vascularized poroelastic materials. Meccanica 52(14):3321–3343

    Article  MathSciNet  MATH  Google Scholar 

  43. Stylianopoulos T (2017) The solid mechanics of cancer and strategies for improved therapy. J Biomech Eng 139(2): 021004. https://doi.org/10.1115/1.4034991

  44. Talebizadeh Sardari P, Walker GS, Gillott M, Grant D, Giddings D (2020) Numerical modelling of phase change material melting process embedded in porous media: effect of heat storage size. Proc Inst Mech Eng Part A J Power Energy 234(3):365–383

    Article  Google Scholar 

  45. Reddy KE, Reddy M, Reddy R (2011) Mathematical model governing magnetic field effect on bio magnetic fluid flow and orientation of red blood cells. Pac Asian J Math 5:344–356

    Google Scholar 

  46. Zablotskii V, Polyakova T, Lunov O, Dejneka A (2016) How a high-gradient magnetic field could affect cell life. Sci Rep 6(1):1–13

    Article  Google Scholar 

  47. Nguyen N-T (2012) Micro-magnetofluidics: interactions between magnetism and fluid flow on the microscale. Microfluid Nanofluid 12(1–4):1–16

    Article  Google Scholar 

  48. Cyron CJ, Humphrey JD (2017) Growth and remodeling of load-bearing biological soft tissues. Meccanica 52(3):645–664

    Article  MathSciNet  Google Scholar 

  49. Intaglietta M (1990) Vasomotion and flowmotion: physiological mechanisms and clinical evidence. Vasc Med Rev 2:101–112

    Article  Google Scholar 

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Appendix

Appendix

We start the solution from Eq. (6):

$$ \mathop \sigma \limits^{ = } _{{total}} = \mathop \sigma \limits^{ = } _{t} + \mathop \sigma \limits^{ = } _{i} $$
(13)

Using Eqs. (7) and (8) we will have:

(14)

Using Eq. (9) and assuming that the porosity value is constant, we will have:

(15)

Assuming the theory of infinitesimal strain, Eq. (11), we will have:

(16)

Now we take divergence from Eq. (16) and so we will have:

(17)

Considering the constant and equal volumetric values in both fluid and solid spaces for porous media, i.e.

$$ \left\{ {\begin{array}{*{20}c} {\varepsilon _{i} = \varepsilon _{t} = \varepsilon } \\ {\varepsilon _{i} + \varepsilon _{t} = 1} \\ \end{array} } \right.~~ \to 2\varepsilon = 1~~ \to \varepsilon = \frac{1}{2} $$
(18)

and assuming the process of tissue production and conversion is ignored, i.e.

$$ S = 0 $$
(19)

and also, by taking divergence from Eq. (4) and then using Eq. (10), we have:

$$ \begin{gathered} \nabla \cdot \left( { - \nabla P_{i} - \left( {\frac{{\mu _{i} }}{k}} \right)\varepsilon _{i} \left( {\overrightarrow {{V_{i} }} - \overrightarrow {{V_{t} }} } \right)} \right) = - \nabla ^{2} P_{i} - \left( {\frac{{\mu _{i} }}{k}} \right)\nabla \cdot \left( {\varepsilon _{i} \overrightarrow {{V_{i} }} - \varepsilon _{i} \overrightarrow {{V_{t} }} } \right) \hfill \\ \;\;\;\;\;\;\;\,\,\,\,\;\;\,\,\,\;\;\,\,\,\,\;\,\,\;\,\,\,\;\,\,\;\;\,\,\,\,\;\,\;\;\,\,\;\,\,\,\,\;\, = - \nabla ^{2} P_{i} - \left( {\frac{{\mu _{i} }}{k}} \right)\left( {\nabla \cdot \left( {\varepsilon _{i} \overrightarrow {{V_{i} }} } \right) - \nabla \cdot \left( {\varepsilon _{t} \overrightarrow {{V_{t} }} } \right)} \right) \hfill \\ \,\,\,\,\,\,\;\,\,\,\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; = - \nabla ^{2} P_{i} - \left( {\frac{{\mu _{i} }}{k}} \right)\left( {\left( {\left( {\varphi _{B} - \varphi _{L} } \right) - \nabla \cdot \left( {\varepsilon _{t} \overrightarrow {{V_{t} }} } \right)} \right) - \nabla \cdot \left( {\varepsilon _{t} \overrightarrow {{V_{t} }} } \right)} \right) = 0~~~ \hfill \\ \end{gathered} $$
(20)

According to:

$$ \varepsilon _{i} = \varepsilon _{t} = \varepsilon = \frac{1}{2} $$
(21)

we will have:

$$ - \nabla ^{2} P_{i} - \left( {\frac{{\mu _{i} }}{k}} \right)\left( {\varphi _{B} - \varphi _{L} } \right) + \left( {\frac{{\mu _{i} }}{k}} \right)\nabla \cdot \left( {\overrightarrow {{V_{t} }} } \right) = 0~ $$
(22)

Now considering Eq. (12) and using two Eqs. (17) and (22) we will have:

(23)

Now, using Eqs. (2) and (3), we rewrite Eq. (23):

(24)

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Halabian, M., Beigzadeh, B. & Siavashi, M. A numerical study on the effect of osmotic pressure on stress and strain in intercellular structures of tumor tissue in the poro-elastic model. Meccanica 56, 2471–2486 (2021). https://doi.org/10.1007/s11012-021-01395-3

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