Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2018 Mar 16;11(3):dmm033100.
doi: 10.1242/dmm.033100.

Metastasis in context: modeling the tumor microenvironment with cancer-on-a-chip approaches

Jelle J F Sleeboom  1   2   3 , Hossein Eslami Amirabadi  1   3 , Poornima Nair  1   3 , Cecilia M Sahlgren  2   3   4 , Jaap M J den Toonder  5   3
Affiliations
Review

Metastasis in context: modeling the tumor microenvironment with cancer-on-a-chip approaches

Jelle J F Sleeboom et al. Dis Model Mech. .

Abstract

Most cancer deaths are not caused by the primary tumor, but by secondary tumors formed through metastasis, a complex and poorly understood process. Cues from the tumor microenvironment, such as the biochemical composition, cellular population, extracellular matrix, and tissue (fluid) mechanics, have been indicated to play a pivotal role in the onset of metastasis. Dissecting the role of these cues from the tumor microenvironment in a controlled manner is challenging, but essential to understanding metastasis. Recently, cancer-on-a-chip models have emerged as a tool to study the tumor microenvironment and its role in metastasis. These models are based on microfluidic chips and contain small chambers for cell culture, enabling control over local gradients, fluid flow, tissue mechanics, and composition of the local environment. Here, we review the recent contributions of cancer-on-a-chip models to our understanding of the role of the tumor microenvironment in the onset of metastasis, and provide an outlook for future applications of this emerging technology.

Keywords: Cancer; Cancer-on-a-chip; Metastasis; Microfluidics; Tumor microenvironment.

PubMed Disclaimer

Conflict of interest statement

Competing interestsThe authors declare no competing or financial interests.

Figures

Fig. 1.
Fig. 1.
Metastasis and the TME. (A) The five steps of metastasis. (1) Invasion: cancer cells escape from the primary tumor into the surrounding stroma. (2) Intravasation: cancer cells cross the vessel wall and enter the circulation. (3) Survival: cancer cells survive in the circulation. (4) Extravasation: cancer cells exit the vessel and seed at a distant site after crossing the vessel wall. (5) Secondary tumor development. (B) Biochemical cues. Oxygen and nutrient levels are lower, and acidity and carbon dioxide levels are higher, within the tumor. (C) Cellular cues, from cells such as fibroblasts, immune cells and endothelial cells (ECs). (D) The extracellular matrix (ECM). The structure and biochemical properties of the ECM fibers (green lines) is heterogeneous in the TME. (E) Mechanical cues, including interstitial fluid pressure and flow, and tissue stresses and deformations.
Fig. 2.
Fig. 2.
Cancer-on-a-chip (CoC) designs with different cell culture options. The complete chips are typically a few cm in size: (A) 2D chip. Single- or multi-chamber 2D culture devices with a controlled solute gradient. In this type of chip, cancer cells are typically exposed to a gradient of a solute, such as oxygen, while their viability or migration is measured. (B) Lumen chip. A patterned 3D matrix is used to form lumens or tumor compartments. This design is typically used to model blood vessels in tumors, or to tightly pack cancer cells in a cylindrical compartment. (C) Compartmentalized chip. In this device, pillars are used to separate microchannels in which cell culturing is possible in both 2D and 3D. This type of chip is very versatile, allowing the user to pattern different matrix materials and cells in a controlled manner. (D) Y chip. Parallel matrix compartments patterned by co-flow. This chip type resembles the compartmentalized chip, as it enables matrix patterning, but is slightly less versatile in its patterning possibilities. (E) Membrane chip. A co-culture device with stacked microchannels separated by a porous membrane. One of the interesting features of these devices is that a 3D culture is created only in part of the microchannel, with the rest empty to refresh the media. This multi-layered chip type was originally developed to mimic the endo- and epithelial cell layers found in the lung. In all images, cancer cells are indicated in yellow, additional cell types in red, green or blue, and solute gradient directions as yellow-red gradients.
Fig. 3.
Fig. 3.
CoC in practice. The key input elements of CoC models are: (A) a microfluidic chip, (B) cancer cells, (C) additional cells (optional), (D) matrix materials (optional) and (E) equipment to control fluid flow, such as a syringe pump. Using these elements, the different CoC model types can be built: (F) 2D chips in which chemical gradients can be established (indicated by the arrow) [adapted from Chen et al. (2011) with permission from The Royal Society of Chemistry], (G) lumen chips (adapted from Piotrowski-Daspit et al., 2016, with permission from The Royal Society of Chemistry), (H) compartmentalized chips (Zervantonakis et al., 2012), (I) Y chips (adapted from Sung et al., 2011, with permission from The Royal Society of Chemistry) and (J) membrane chips (adapted from Choi et al., 2015, with permission from The Royal Society of Chemistry). Different experimental read-outs are possible, with some typical examples shown in K-O. The main strength of the CoC approach is that it allows continuous live monitoring of model development. (K) Individual cells (Truong et al., 2016) and (L) invasive lesions (Tien et al., 2012) can be tracked. (M) Solute levels can be tracked (adapted from Wang et al., 2015a, with permission from Springer Nature). These live read-outs can be combined with end-point read-outs, such as tissue staining [N; L, Bischel et al., 2015; R, adapted from Choi et al. (2015), with permission from The Royal Society of Chemistry], and (O) gene expression data (adapted from Piotrowski-Daspit et al., 2016, with permission from The Royal Society of Chemistry). DCIS, ductal carcinoma in situ; HMF, human mammary fibroblasts; Pbase, pressure at cell aggregate base; Ptip, pressure at cell aggregate tip. Scale bars: 50 μm (G), 2 mm (H, left), 300 μm (H, right), 30 μm (I), 100 μm (K,N).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Acosta M. A., Jiang X., Huang P.-K., Cutler K. B., Grant C. S., Walker G. M. and Gamcsik M. P. (2014). A microfluidic device to study cancer metastasis under chronic and intermittent hypoxia. Biomicrofluidics 8, 54117 10.1063/1.4898788 - DOI - PMC - PubMed
    1. Alemany-Ribes M. and Semino C. E. (2014). Bioengineering 3D environments for cancer models. Adv. Drug Deliv. Rev. 79–80, 40-49. 10.1016/j.addr.2014.06.004 - DOI - PubMed
    1. Anguiano M., Castilla C., Maška M., Ederra C., Peláez R., Morales X., Muñoz-Arrieta G., Mujika M., Kozubek M., Muñoz-Barrutia A. et al. (2017). Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis. PLoS ONE 12, e0171417 10.1371/journal.pone.0171417 - DOI - PMC - PubMed
    1. Ayuso J. M., Virumbrales-Muñoz M., Lacueva A., Lanuza P. M., Checa-Chavarria E., Botella P., Fernández E., Doblare M., Allison S. J., Phillips R. M. et al. (2016). Development and characterization of a microfluidic model of the tumour microenvironment. Sci. Rep. 6, 36086 10.1038/srep36086 - DOI - PMC - PubMed
    1. Bai J., Adriani G., Dang T., Tu T., Penny H. L., Wong S., Kamm R. D. and Thiery J.-P. (2015). Contact-dependent carcinoma aggregate dispersion by M2a macrophages via ICAM-1 and β2 integrin interactions. Oncotarget 6, 25295-25307. 10.18632/oncotarget.4716 - DOI - PMC - PubMed