Skip to main content

Advertisement

Log in

A Hybrid Model of Tumor–Stromal Interactions in Breast Cancer

  • Original Article
  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

Ductal carcinoma in situ (DCIS) is an early stage noninvasive breast cancer that originates in the epithelial lining of the milk ducts, but it can evolve into comedo DCIS and ultimately, into the most common type of breast cancer, invasive ductal carcinoma. Understanding the progression and how to effectively intervene in it presents a major scientific challenge. The extracellular matrix (ECM) surrounding a duct contains several types of cells and several types of growth factors that are known to individually affect tumor growth, but at present the complex biochemical and mechanical interactions of these stromal cells and growth factors with tumor cells is poorly understood. Here we develop a mathematical model that incorporates the cross-talk between stromal and tumor cells, which can predict how perturbations of the local biochemical and mechanical state influence tumor evolution. We focus on the EGF and TGF-β signaling pathways and show how up- or down-regulation of components in these pathways affects cell growth and proliferation. We then study a hybrid model for the interaction of cells with the tumor microenvironment (TME), in which epithelial cells (ECs) are modeled individually while the ECM is treated as a continuum, and show how these interactions affect the early development of tumors. Finally, we incorporate breakdown of the epithelium into the model and predict the early stages of tumor invasion into the stroma. Our results shed light on the interactions between growth factors, mechanical properties of the ECM, and feedback signaling loops between stromal and tumor cells, and suggest how epigenetic changes in transformed cells affect tumor progression.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27

Similar content being viewed by others

References

  • Abdollah, S., Macias-Silva, M., Tsukazaki, T., Hayashi, H., Attisano, L., & Wrana, J. L. (1997). TbetaRI phosphorylation of smad2 on ser465 and ser467 is required for smad2-smad4 complex formation and signaling. J. Biol. Chem., 272(44), 27678–27685.

    Article  Google Scholar 

  • Adams, S., Miller, G. T., Jesson, M. I., Watanabe, T., Jones, B., & Wallner, B. P. (2004). PT-100, a small molecule dipeptidyl peptidase inhibitor, has potent antitumor effects and augments antibody-mediated cytotoxicity via a novel immune mechanism. Cancer Res., 64(15), 5471–5480.

    Article  Google Scholar 

  • Alessi, D. R., Cuenda, A., Cohen, P., Dudley, D. T., & Saltiel, A. R. (1995). PD 098059 is a specific inhibitor of the activation of mitogen-activated protein kinase in vitro and in vivo. J. Biol. Chem., 270(46), 27489–27494.

    Article  Google Scholar 

  • Alexander, S., & Friedl, P. (2012). Cancer invasion and resistance: interconnected processes of disease progression and therapy failure. Trends Mol. Med., 18(1), 13–26.

    Article  Google Scholar 

  • Almholt, K., Green, K., Juncker-Jensen, A., Nielsen, B., Lund, L., & Romer, J. (2007). Extracellular proteolysis in transgenic mouse models of breast cancer. J. Mammary Gland Biol. Neoplasia, 12(1), 83–97.

    Article  Google Scholar 

  • Annabi, B., Bouzeghrane, M., Currie, J. C., Hawkins, R., Dulude, H., Daigneault, L., Ruiz, M., Wisniewski, J., Garde, S., Rabbani, S. A., Panchal, C., Wu, J. J., & Beliveau, R. (2005). A PSP94-derived peptide PCK3145 inhibits MMP-9 secretion and triggers CD44 cell surface shedding: implication in tumor metastasis. Clin. Exp. Metastasis, 22(5), 429–439.

    Article  Google Scholar 

  • Basbaum, C. B., & Werb, Z. (1996). Focalized proteolysis: a spatial and temporal regulation of extracellular matrix degradation at the cell surface. Curr. Opin. Cell Biol., 8, 731–738.

    Article  Google Scholar 

  • Beacham, D. A., & Cukierman, E. (2005). Stromagenesis: the changing face of fibroblastic microenvironments during tumor progression. In Seminars in cancer biology. (Vol. 15, pp. 329–341). Amsterdam: Elsevier.

    Google Scholar 

  • Brown, D. R. (1999). Dependence of neurones on astrocytes in a coculture system renders neurones sensitive to transforming growth factor beta1-induced glutamate toxicity. J. Neurochem., 72(3), 943–953.

    Article  Google Scholar 

  • Burrai, G. P., Mohammed, S. I., Miller, M. A., Marras, V., Pirino, S., Addis, M. F., Uzzau, S., & Antuofermo, E. (2010). Spontaneous feline mammary intraepithelial lesions as a model for human estrogen receptor- and progesterone receptor-negative breast lesions. BMC Cancer, 10, 156.

    Article  Google Scholar 

  • Chen, S. T., Pan, T. L., Juan, H. F., Chen, T. Y., Lin, Y. S., & Huang, C. M. (2008). Breast tumor microenvironment: proteomics highlights the treatments targeting secretome. J. Proteome Res., 7, 1379–1387.

    Article  Google Scholar 

  • Cheng, J. D., & Weiner, L. M. (2003). Tumors and their microenvironments: tilling the soil commentary re: A.M. Scott et al., A phase I dose-escalation study of sibrotuzumab in patients with advanced or metastatic fibroblast activation protein-positive cancer. Clin. Cancer Res., 9(5), 1590–1595.

    Google Scholar 

  • Cheng, G., Tse, J., Jain, R. K., & Minn, L. L. (2009). Micro-environmental mechanical stress controls tumor spheroid size and morphology by suppressing proliferation and inducing aopotosis in cancer cells. PLoS ONE, 4, e4632.

    Article  Google Scholar 

  • Chivukula, M., Bhargava, R., Tseng, G., & Dabbs, D. J. (2009). Clinicopathologic implications of flat epithelial atypia in core needle biopsy specimens of the breast. Am. J. Clin. Pathol., 131, 802–808.

    Article  Google Scholar 

  • Chung, S. W., Miles, F. L., Sikes, R. A., Cooper, C. R., Farach-Carson, M. C., & Ogunnaike, B. A. (2009). Quantitative modeling and analysis of the transforming growth factor beta signaling pathway. Biophys. J., 96(5), 1733–1750.

    Article  Google Scholar 

  • Dallon, J. C., & Othmer, H. G. (1997). A discrete cell model with adaptive signalling for aggregation of Dictyostelium discoideum. Philos. Trans. R. Soc. Lond. B, 352, 391–417.

    Article  Google Scholar 

  • Dallon, J. C., & Othmer, H. G. (2004). How cellular movement determines the collective force generated by the Dictyostelium discoideum slug. J. Theor. Biol., 231, 203–222.

    Article  MathSciNet  Google Scholar 

  • Danielsen, T., & Rofstad, E. K. (1998). VEGF, bFGF and EGF in the angiogenesis of human melanoma xenografts. Int. J. Cancer, 76(6), 836–841.

    Article  Google Scholar 

  • Davis, R. J. (1993). The mitogen-activated protein kinase signal transduction pathway. J. Biol. Chem., 268(20), 14553–14556.

    Google Scholar 

  • Friedl, P., & Alexander, S. (2011). Cancer invasion and the microenvironment: plasticity and reciprocity. Cell, 147(5), 992–1009.

    Article  Google Scholar 

  • Geho, D. H., Bandle, R. W., Clair, T., & Liotta, L. A. (2005). Physiological mechanisms of tumor-cell invasion and migration. Physiology (Bethesda), 20, 194–200.

    Article  Google Scholar 

  • Hanamura, N., Yoshida, T., Matsumoto, E., Kawarada, Y., & Sakakura, T. (1997). Expression of fibronectin and tenascin-c mrna by myofibroblasts, vascular cells and epithelial cells in human colon adenomas and carcinomas. Int. J. Cancer, 73(1), 10–15.

    Article  Google Scholar 

  • Helmlinger, G., Netti, P. A., Lichtenbeld, H. C., Melder, R. J., & Jain, R. K. (1997). Solid stress inhibits the growth of multicellular tumor spheroids. Nat. Biotechnol., 15(8), 778–783.

    Article  Google Scholar 

  • Hendriks, B. S., Orr, G., Wells, A., Wiley, H. S., & Lauffenburger, D. A. (2005). Parsing ERK activation reveals quantitatively equivalent contributions from epidermal growth factor receptor and HER2 in human mammary epithelial cells. J. Biol. Chem., 280(7), 6157–6169.

    Article  Google Scholar 

  • Hillen, T. (2006). M5 mesoscopic and macroscopic models for mesenchymal motion. J. Math. Biol., 53, 585–616.

    Article  MathSciNet  MATH  Google Scholar 

  • Hillen, T., Hinow, P., & Wang, Z. A. (2010). Mathematical analysis of a kinetic model for cell movement in network tissues. Discrete Contin. Dyn. Syst., Ser. B, 14(3), 1055–1080.

    Article  MathSciNet  MATH  Google Scholar 

  • Hinshelwood, R. A., Huschtscha, L. I., Melki, J., Stirzaker, C., Abdipranoto, A., Vissel, B., Ravasi, T., Wells, C. A., Hume, D. A., Reddel, R. R., & Clark, S. J. (2007). Concordant epigenetic silencing of transforming growth factor-signaling pathway genes occurs early in breast carcinogenesis. Cancer Res., 67(24), 11517.

    Article  Google Scholar 

  • Ilina, O., Bakker, G. J., Vasaturo, A., Hofman, R. M., & Friedl, P. (2011). Two-photon laser-generated microtracks in 3D collagen lattices: principles of MMP-dependent and -independent collective cancer cell invasion. Phys Biol., 8(1), 015010.

    Article  Google Scholar 

  • Kaufman, L. J., Brangwynne, C. P., Kasza, K. E., Filippidi, E., Gordon, V. D., Deisboeck, T. S., & Weitz, D. A. (2005). Glioma expansion in collagen I matrices: analyzing collagen concentration-dependent growth and motility patterns. Biophys. J. BioFAST, 89, 635–650.

    Article  Google Scholar 

  • Kim, Y., & Friedman, A. (2010). Interaction of tumor with its microenvironment: a mathematical model. Bull. Math. Biol., 72(5), 1029–1068.

    Article  MathSciNet  MATH  Google Scholar 

  • Kim, Y., Stolarska, M., & Othmer, H. G. (2007). A hybrid model for tumor spheroid growth in vitro I: theoretical development and early results. Math. Models Methods Appl. Sci., 17, 1773–1798.

    Article  MathSciNet  MATH  Google Scholar 

  • Kim, Y., Lawler, S., Nowicki, M., Chiocca, E., & Friedman, A. (2009). A mathematical model of brain tumor: pattern formation of glioma cells outside the tumor spheroid core. J. Theor. Biol., 260, 359–371.

    Article  MathSciNet  Google Scholar 

  • Kim, Y., Stolarska, M. A., & Othmer, H. G. (2011). The role of the microenvironment in tumor growth and invasion. Prog. Biophys. Mol. Biol., 106, 353–379.

    Article  Google Scholar 

  • Kloft, C., Graefe, E., Tanswell, P., Scott, A., Hofheinz, R., Amelsberg, A., & Karlsson, M. (2004). Population pharmacokinetics of sibrotuzumab, a novel therapeutic monoclonal antibody, in cancer patients. Invest. New Drugs, 22(1), 39–52.

    Article  Google Scholar 

  • Koka, S., Vance, J. B., & Maze, G. I. (1995). Bone growth factors: potential for use as an osseointegration enhancement technique (OET). J. West. Soc. Periodontol., Periodontal Abstr., 43(3), 97–104.

    Google Scholar 

  • Kretzschmar, M., Doody, J., & Massagué, J. (1997). Opposing BMP and EGF signalling pathways converge on the TGFb family mediator smad1. Nature, 389(6651), 618–622.

    Article  Google Scholar 

  • Kretzschmar, M., Doody, J., Timokhina, I., & Massagué, J. (1999). A mechanism of repression of TGFbeta/ smad signaling by oncogenic ras. Genes Dev., 13(7), 804–816.

    Article  Google Scholar 

  • Krouskop, T. A., Wheeler, T. M., Kallel, F., Garra, B. S., & Hall, T. (1998). Elastic moduli of breast and prostate tissues under compression. Ultrason. Imag., 20(4), 260–274.

    Article  Google Scholar 

  • Kudlow, J. E., Cheung, C. Y., & Bjorge, J. D. (1986). Epidermal growth factor stimulates the synthesis of its own receptor in a human breast cancer cell line. J. Biol. Chem., 261(9), 4134–4138.

    Google Scholar 

  • Kunz-Schughart, L. A., Wenninger, S., Neumeier, T., Seidl, P., & Knuechel, R. (2003). Three-dimensional tissue structure affects sensitivity of fibroblasts to TGF-beta 1. Am. J. Physiol., Cell Physiol., 284(1), C209–C219.

    Article  Google Scholar 

  • Liu, X., Sun, Y., Constantinescu, S. N., Karam, E., Weinberg, R. A., & Lodish, H. F. (1997). Transforming growth factor beta-induced phosphorylation of smad3 is required for growth inhibition and transcriptional induction in epithelial cells. Proc. Natl. Acad. Sci. USA, 94(20), 10669–10674.

    Article  Google Scholar 

  • Mantzaris, N., Webb, S., & Othmer, H. G. (2004). Mathematical modeling of tumor-induced angiogenesis. J. Math. Biol., 49, 111–187.

    Article  MathSciNet  MATH  Google Scholar 

  • Marino, S., Hogue, I. B., Ray, C. J., & Kirschner, D. E. (2008). A methodology for performing global uncertainty and sensitivity analysis in systems biology. J. Theor. Biol., 254(1), 178–196.

    Article  MathSciNet  Google Scholar 

  • Marshall, C. J. (1995). Specificity of receptor tyrosine kinase signaling: transient versus sustained extracellular signal-regulated kinase activation. Cell, 80(2), 179–185.

    Article  Google Scholar 

  • Massagué, J. (1998). TGF-beta signal transduction. Annu. Rev. Biochem., 67(1), 753.

    Article  Google Scholar 

  • Massagué, J. (2008). TGF [beta] in cancer. Cell, 134(2), 215–230.

    Article  Google Scholar 

  • Mercapide, J., Cicco, R., Castresana, J. S., & Klein-Szanto, A. J. (2003). Stromelysin-1/matrix metalloproteinase-3 (MMP-3) expression accounts for invasive properties of human astrocytoma cell lines. Int. J. Cancer, 106(5), 676–682.

    Article  Google Scholar 

  • Palsson, E., & Othmer, H. G. (2000). A model for individual and collective cell movement in dictyostelium discoideum. Proc. Natl. Acad. Sci., 97, 11448–11453.

    Article  Google Scholar 

  • Paszek, M. J., & Weaver, V. M. (2004). The tension mounts: mechanics meets morphogenesis and malignancy. J. Mammary Gland Biol. Neoplasia, 9(4), 325–342. Review.

    Article  Google Scholar 

  • Preziosi, L., & Vitale, G. (2011). A multiphase model of tumour and tissue growth including cell adhesion and plastic re-organisation. Math. Models Methods Appl. Sci., 21, 1901–1932.

    Article  MathSciNet  MATH  Google Scholar 

  • Provenzano, P., Inman, D., Eliceiri, K., & Keely, P. (2009). Matrix density-induced mechanoregulation of breast cell phenotype, signaling and gene expression through a FAK–ERK linkage. Oncogene, 28, 4326–4343.

    Article  Google Scholar 

  • Renkawitz, J., & Sixt, M. (2010). Mechanisms of force generation and force transmission during interstitial leukocyte migration. EMBO Rep., 11(10), 744–750.

    Article  Google Scholar 

  • Renkawitz, J., Schumann, K., Weber, M., Lämmermann, T., Pflicke, H., Piel, M., Polleux, J., Spatz, J. P., & Sixt, M. (2009). Adaptive force transmission in amoeboid cell migration. Nat. Cell Biol., 11(12), 1438–1443.

    Article  Google Scholar 

  • Saffarian, S., Collier, I. E., Marmer, B. L., Elson, E. L., & Goldberg, G. (2004). Interstitial collagenase is a Brownian ratchet driven by proteolysis of collagen. Science, 306(5693), 108–111.

    Article  Google Scholar 

  • Samoszuk, M., Tan, J., & Chorn, G. (2005). Clonogenic growth of human breast cancer cells co-cultured in direct contact with serum-activated fibroblasts. Breast Cancer Res., 7, R274–R283.

    Article  Google Scholar 

  • Santos, S. D. M., Verveer, P. J., & Bastiaens, P. I. H. (2007). Growth factor-induced MAPK network topology shapes Erk response determining PC-12 cell fate. Nat. Cell Biol., 9(3), 324–330.

    Article  Google Scholar 

  • Sappino, A. P., Skalli, O., Jackson, B., Schurch, W., & Gabbiani, G. (1988). Smooth-muscle differentiation in stromal cells of malignant and non-malignant breast tissues. Int. J. Cancer, 41(5), 707–712.

    Article  Google Scholar 

  • Schmierer, B., Tournier, A. L., Bates, P. A., & Hill, C. S. (2008). Mathematical modeling identifies smad nucleocytoplasmic shuttling as a dynamic signal-interpreting system. Proc. Natl. Acad. Sci. USA, 105(18), 6608–6613.

    Article  Google Scholar 

  • Sherratt, J. A., & Murray, J. D. (1990). Models of epidermal wound healing. Proc. R. Soc. Lond. B, 241, 29–36.

    Article  Google Scholar 

  • Shi, Y., & Massagué, J. (2003). Mechanisms of TGF-β signaling from cell membrane to the nucleus. Cell, 113(6), 685–700.

    Article  Google Scholar 

  • Souchelnytskyi, S., Tamaki, K., Engstrom, U., Wernstedt, C., ten Dijke, P., & Heldin, C. H. (1997). Phosphorylation of ser465 and ser467 in the C terminus of smad2 mediates interaction with smad4 and is required for transforming growth factor-beta signaling. J. Biol. Chem., 272(44), 28107–28115.

    Article  Google Scholar 

  • Stein, A. M., Demuth, T., Mobley, D., Berens, M., & Sander, L. M. (2007). A mathematical model of glioblastoma tumor spheroid invasion in a three-dimensional in vitro experiment. Biophys. J., 92(1), 356–365.

    Article  Google Scholar 

  • Stein, A. M., Vader, D. A., Weitz, D. A., & Sander, L. M. (2011). The micromechanics of three-dimensional collagen-I gels. Complexity, 16(4), 22–28.

    Article  Google Scholar 

  • Thorne, R. G., Hrabetova, S., & Nicholson, C. (2004). Diffusion of epidermal growth factor in rat brain extracellular space measured by integrative optical imaging. J. Neurophysiol., 92(6), 3471–3481.

    Article  Google Scholar 

  • Tlsty, T. D. (2001). Stromal cells can contribute oncogenic signals. Semin. Cancer Biol., 11(2), 97–104.

    Article  Google Scholar 

  • van den Hooff, A. (1988). Stromal involvement in malignant growth. Adv. Cancer Res., 50, 159–196.

    Article  Google Scholar 

  • Wakefield, L. M., Smith, D. M., Masui, T., Harris, C. C., & Sporn, M. B. (1987). Distribution and modulation of the cellular receptor for transforming growth factor-beta. J. Cell Biol., 105(2), 965–975.

    Article  Google Scholar 

  • Wells, C. A., & El-Ayat, G. A. (2007). Non-operative breast pathology: apocrine lesions. J. Clin. Pathol., 60, 1313–1320.

    Article  Google Scholar 

  • Wolf, K., Wu, Y. I., Liu, Y., Geiger, J., Tam, E., Overall, C., Stack, M. S., & Friedl, P. (2007). Multi-step pericellular proteolysis controls the transition from individual to collective cancer cell invasion. Nat. Cell Biol., 9(8), 893–904.

    Article  Google Scholar 

  • Woodcock, E. A., Land, S. L., & Andrews, R. K. (1993). A low affinity, low molecular weight endothelin-A receptor present in neonatal rat heart. Clin. Exp. Pharmacol. Physiol., 20(5), 331–334.

    Article  Google Scholar 

  • Zi, Z., Feng, Z., Chapnick, D. A., Dahl, M., Deng, D., Klipp, E., Moustakas, A., & Liu, X. (2011). Quantitative analysis of transient and sustained transforming growth factor-beta signaling dynamics. Mol. Syst. Biol., 7(492), 1–12.

    Google Scholar 

Download references

Acknowledgements

Y.J.K. was supported by a Faculty research grant from the University of Michigan–Dearborn and the faculty research fund of Konkuk University in 2012. H.G.O. was supported in part by NSF grant DMS-0517884, and NIH grant GM-29123.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hans G. Othmer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, Y., Othmer, H.G. A Hybrid Model of Tumor–Stromal Interactions in Breast Cancer. Bull Math Biol 75, 1304–1350 (2013). https://doi.org/10.1007/s11538-012-9787-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11538-012-9787-0

Keywords

Navigation