Three-dimensional in vitro tumor Models as an Alternative for Animal Models in Preclinical Studies.

Pharm Ind.2013 75(3):485-489.

Anna T. Stratmann, Gudrun Dandekar, Sarah L. Nietzer

Chair in Tissue Engineering and Regenerative Medicine, University Wuerzburg/

Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB




Cancer is one of the leading causes of death world-wide. For drug screening and development, appropriate tumor models are needed that reflect the situation in the patient robustly and accurately. Next to the identification of new compounds, cancer research contributes to the understanding of complex tumor biology. This enables targeted and individualized drug development. For these different issues tailored tumor models are required. In this present work we illuminate important research approaches which use various kinds of tumor models. These include animal models, two-dimensionally cultured cancer cell lines and primary cells as well as newly developed more complex three-dimensional cell culture models. We discuss their advantages and disadvantages and give an insight into the actual options for drug testing and development. Furthermore, we present some more sophisticated technologies such as tissue engineering and the use of special bioreactors. These will gain importance in the future.


It has been shown that human cell lines and primary cells cultured under 3D conditions are more chemoresistant (Kimlin et al., 2011), exhibit a more complex histology, and are provided with more natural extracellular stimuli, as compared to 2D culture. These changes go along with altered  gene expression profiles as well as changes in regulation of intracellular signaling (Smalley et al., 2006) and are therefore recognized to be hopeful tools for more accurate results in the pre-clinic (Abbott, 2003; Kimlin et al., 2011).

Three-dimensional in vitro tumor models today

Spheroids are well established 3D tumor models providing an improved platform for high-throughput drug screens over 2D culture, given that the end point is well defined. As a drawback, they lack complex architecture or sensible co-culture conditions for the development of targeted therapies or for studies of complex tumor biology.

A tissue architecture of higher complexity is provided by scaffolds that are generally composed of extracellular matrix components, since these have been shown to support the maintenance of the original cell function in vitro. They include gels (Debnath and Brugge, 2005), membranes (Hicks et al., 1997), artificial matrices (Xu and Burg, 2007) and biological matrices (Kyker et al., 2003).

Advanced tumor models by tissue engineering

Understanding tumor biology is a prerequisite to develop appropriate models. In 2011, Weinberg und Hanahan defined eleven common hallmarks of cancer that should be integrated into more complex models at least in some aspects (Hanahan and Weinberg, 2011). For the development of new effective anti-cancer strategies the resemblance of the tumor model to the in vivo situation is pivotal. Some promising advances are made regarding scaffolds to cultivate cells in 3D conditions, as described above. Tissue engineering in particular offers further enhancements. One is the application of dynamic cell culture conditions to provide the cultured cell with a more accurate environment. Medium supply can be adjusted to natural conditions by the use of bioreactors generating diffusion by flow or even perfusion through the tumor construct (Bancroft et al., 2003; Martin et al., 2004; Ratcliffe and Niklason, 2002; Walles et al., 2007). Furthermore, progress has been made by tissue vascularisation with the BioVaSc® technology that uses decellularised intestinal fragments with preserved vessel structures that can be reseeded with endothelial cells (Schanz et al., 2010). The combination of this technique with tumor cells should generate vascularised tumor models suitable for anti-angiogenic drug testing, drug uptake studies, and investigation of metastatic spread to the blood stream. Furthermore, tissue engineering enables the generation of complex tissues with several cell types on various scaffolds.

Gudrun Dandekar-1

Fig. 1: Standardized method to generate a biological vascularised scaffold (BioVaSc) for the engineering of complex vascularised tissues. A part of the porcine jejunum is isolated including the feeding artery and vein and the connecting capillary bed. After intensive rinsing the cells are removed chemically. The acelluarisation process is finished after a γ-radiation to sterilize the BioVaSc. Figure derived from (Nietzer et al., 2012).

Drug response prediction by in silico models

The combination of the formerly described strategies with bioinformatic tools shows promise for more precise drug development and target identification. Such in silico models can be developed in close association to in vitro or in vivo tumor models and are mainly aligned to detect signaling pathways involved in drug efficacy. The mode of action of the respective tested drug can be simulated and afterwards modulated in silico (Wangorsch et al., 2011). Systems biology is a tool for the analysis of interactomes and multi-drug targets that becomes important to investigate complex diseases such as cancer and its therapy (Schrattenholz et al., 2010). The prediction of a tumor’s sensitivity in a certain patient to a specific anti-cancer compound also enables individualized treatment strategies (Gorelik et al., 2008; Macklin et al., 2012).

Despite the promising strategies of forming complex and more reliable cell-based culture models that are reviewed here, animal models are and stay crucial for drug testing in cancer research today. Nevertheless, every advance that is made raises the hope to reduce or even avoid animal testing in the future.



  1. Abbott, A., 2003. Cell culture: biology’s new dimension. Nature 424, 870-872.
  2. Bancroft, G.N., Sikavitsas, V.I., Mikos, A.G., 2003. Design of a flow perfusion bioreactor system for bone tissue-engineering applications. Tissue Eng 9, 549-554.
  3. Debnath, J., Brugge, J.S., 2005. Modelling glandular epithelial cancers in three-dimensional cultures. Nat Rev Cancer 5, 675-688.
  4. Gorelik, B., Ziv, I., Shohat, R., Wick, M., Hankins, W.D., Sidransky, D., Agur, Z., 2008. Efficacy of weekly docetaxel and bevacizumab in mesenchymal chondrosarcoma: a new theranostic method combining xenografted biopsies with a mathematical model. Cancer Res 68, 9033-9040.
  5. Hanahan, D., Weinberg, R.A., 2011. Hallmarks of cancer: the next generation. Cell 144, 646-674.
  6. Hicks, K.O., Ohms, S.J., van Zijl, P.L., Denny, W.A., Hunter, P.J., Wilson, W.R., 1997. An experimental and mathematical model for the extravascular transport of a DNA intercalator in tumours. Br J Cancer 76, 894-903.
  7. Kimlin, L.C., Casagrande, G., Virador, V.M., 2011. In vitro three-dimensional (3D) models in cancer research: An update. Mol Carcinog.
  8. Kyker, K.D., Culkin, D.J., Hurst, R.E., 2003. A model for 3-dimensional growth of bladder cancers to investigate cell-matrix interactions. Urol Oncol 21, 255-261.
  9. Macklin, P., Edgerton, M.E., Thompson, A.M., Cristini, V., 2012. Patient-calibrated agent-based modelling of ductal carcinoma in situ (DCIS): from microscopic measurements to macroscopic predictions of clinical progression. J Theor Biol 301, 122-140.
  10. Martin, I., Wendt, D., Heberer, M., 2004. The role of bioreactors in tissue engineering. Trends Biotechnol 22, 80-86.
  11. Nietzer, S.L., Dandekar, G., Wasik, M., Walles, H., 2012. Selected Topics in Plastic Reconstructive Surgery, in: Danilla, S. (Ed.), Chapter 9: Three Dimensional Tissue Models for Research in Oncology. InTech.
  12. Ratcliffe, A., Niklason, L.E., 2002. Bioreactors and bioprocessing for tissue engineering. Ann N Y Acad Sci 961, 210-215.
  13. Schanz, J., Pusch, J., Hansmann, J., Walles, H., 2010. Vascularised human tissue models: a new approach for the refinement of biomedical research. J Biotechnol 148, 56-63.
  14. Schrattenholz, A., Groebe, K., Soskic, V., 2010. Systems biology approaches and tools for analysis of interactomes and multi-target drugs. Methods Mol Biol 662, 29-58.
  15. Smalley, K.S., Lioni, M., Herlyn, M., 2006. Life isn’t flat: taking cancer biology to the next dimension. In Vitro Cell Dev Biol Anim 42, 242-247.
  16. Walles, T., Weimer, M., Linke, K., Michaelis, J., Mertsching, H., 2007. The potential of bioartificial tissues in oncology research and treatment. Onkologie 30, 388-394.
  17. Wangorsch, G., Butt, E., Mark, R., Hubertus, K., Geiger, J., Dandekar, T., Dittrich, M., 2011. Time-resolved in silico modeling of fine-tuned cAMP signaling in platelets: feedback loops, titrated phosphorylations and pharmacological modulation. BMC Syst Biol 5, 178.
  18. Xu, F., Burg, K.J., 2007. Three-dimensional polymeric systems for cancer cell studies. Cytotechnology 54, 135-143.



Gudrun Dandekar, Ph.D. , University Hospital Wuerzburg,

Chair of Tissue Engineering and Regenerative Medicine

Roentgenring 11, 97070 Wuerzburg

phone: +49 931/31-82597

fax: +49 931/31-81068


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