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Review
. 2018 May 24;6:66.
doi: 10.3389/fbioe.2018.00066. eCollection 2018.

Engineering Breast Cancer Microenvironments and 3D Bioprinting

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Free PMC article
Review

Engineering Breast Cancer Microenvironments and 3D Bioprinting

Jorge A Belgodere et al. Front Bioeng Biotechnol. .
Free PMC article

Abstract

The extracellular matrix (ECM) is a critical cue to direct tumorigenesis and metastasis. Although two-dimensional (2D) culture models have been widely employed to understand breast cancer microenvironments over the past several decades, the 2D models still exhibit limited success. Overwhelming evidence supports that three dimensional (3D), physiologically relevant culture models are required to better understand cancer progression and develop more effective treatment. Such platforms should include cancer-specific architectures, relevant physicochemical signals, stromal-cancer cell interactions, immune components, vascular components, and cell-ECM interactions found in patient tumors. This review briefly summarizes how cancer microenvironments (stromal component, cell-ECM interactions, and molecular modulators) are defined and what emerging technologies (perfusable scaffold, tumor stiffness, supporting cells within tumors and complex patterning) can be utilized to better mimic native-like breast cancer microenvironments. Furthermore, this review emphasizes biophysical properties that differ between primary tumor ECM and tissue sites of metastatic lesions with a focus on matrix modulation of cancer stem cells, providing a rationale for investigation of underexplored ECM proteins that could alter patient prognosis. To engineer breast cancer microenvironments, we categorized technologies into two groups: (1) biochemical factors modulating breast cancer cell-ECM interactions and (2) 3D bioprinting methods and its applications to model breast cancer microenvironments. Biochemical factors include matrix-associated proteins, soluble factors, ECMs, and synthetic biomaterials. For the application of 3D bioprinting, we discuss the transition of 2D patterning to 3D scaffolding with various bioprinting technologies to implement biophysical cues to model breast cancer microenvironments.

Keywords: 3D bioprinting; biophysical properties; cancer microenvironments; cell-ECM interactions; extracellular matrix; tumor models.

Figures

Figure 1
Figure 1
Frequency of studies published showing ECM gene influences on specific hallmarks of cancer, patient prognostics and drug resistance. Results of meta-review survey depicting (A) the frequency of publications showing individual ECM-related genes influencing specific hallmarks of cancer and (B) the frequency of publications reporting ECM-related genes as a tool for patient prognostic determinations and specific drug resistance.
Figure 2
Figure 2
Interstitial matrix proteins and the basement membrane proteins are associated in the breast cancer microenvironments (left circle). The signaling from the ECM proteins propagates via multiple signaling pathways either simultaneously or independently (right circle). Possible scenarios of cell-ECM interactions can initiate signaling of breast cancer cells. Upon phosphorylation, β-catenin dissociates from E-cadherin within adherens junction and is degraded by proteasome. ECM proteins can phosphorylate ILK, which in turn inhibits phosphorylation of GSK3β and activate β-catenin (non-phosphorylated). ECM protein initiates phosphorylation of FAK, leading to enhanced translation of pro-survival and pro-proliferation genes associated with MAPK and AKT pathways. FAK also promotes Rho/Rac activity for actin cytoskeleton assembly, mediating cell migration and spreading. MMPs degrade ECM proteins, generating matrikine.
Figure 3
Figure 3
Correlating mechanical properties and ECM reorganization during human breast cancer progression. Stiffness distribution and respective H&E stained sections (A) of normal mammary gland tissue (top), benign lesion (middle) and malignant tumor (bottom). Stiffness distribution of normal breast tissue is unimodal and the histology shows the terminal ductal lobular unit of a normal mammary gland fenced by interstitial connective tissue. A benign lesion reveals a unimodal, but broader stiffness distribution with an increase in stiffness compared with the healthy sample. The histology of benign lesions reveals extensive fibrotic stroma interspersed with fibroblasts typical for fibroadenoma. Invasive cancer shows heterogeneous stiffness distribution with a characteristic soft peak, where the histology shows an invasive breast carcinoma with infiltrating nests of cancer cells that have evoked a dense fibrous tissue response. Scale bar applies to all images, 50 μm. The distinct ECM stiffness and structure of late MMTV-PyMT cancer was probed by atomic force microscopy (B) and immunohistochemistry (C). Gradual stiffening from the core to the periphery was observed. Mechanical heterogeneity increased and is most extensive at the periphery (B). While collagen type I and laminin-111 were virtually absent in soft tissue (the core), the heterogeneous presentation (brown staining) of collagen type I and laminin-111 was increased at the periphery as evidenced in (C). Scale bar applies to all images, 50 μm. (A–C reproduced with permision from Plodinec et al., 2012).
Figure 4
Figure 4
Correlating cell type and ECM architecture after decellularization. (A) Immunofluorescence (IF, scale bars, 50 μm) staining showed sparse distribution of ECM from multiple breast cancer cell lines, while abundant ECM deposition by human neonatal foreskin fibroblast (fFB). (B) To further visualize the deposition of ECM from the breast cancer cell lines, scanning electron microscopy (SEM, bottom row, scale bars 1 μm) was utilized. MCF10A shows organized, interconnected fiber morphology of ECM; MCF7 has a less organized arrangement of ECM fibers; MDA-MB-231 has a thin, sparse fiber morphology; fFB has a copious monolayer of ECM containing both large and thin-diameter fibers. ECM fibers (0.1- to 0.5 μm diameter) indicated by arrows. (A,B reproduced with permission from Hielscher et al., 2012).
Figure 5
Figure 5
An example of 3DBP breast cancer microenvironments. (A) Schematic diagram of direct, 3D bioprinted, cell-laden bone matrix as a biomimetic model for a breast cancer metastasis study. (B) CAD model of the 3D matrix. (C) 3D surface plot of the bioprinted matrix. Scale bar: 200 μm. (D–G) Scanning electron micrographs (cross-sectional view) of porous matrices: (D) 10% GelMA, (E) 10% GelMA + nHA, (F) 15% GelMA, and (G) 15% GelMA+nHA, respectively. Scale bar: 100 μm. The inset images are photographs of the corresponding matrices. (H,I) Fluorescence micrographs of the 3D bioprinted MSC-laden 10% GelMA matrix; 3D bioprinted cells were prelabeled by Cell Tracker Green CMFDA dye. GelMA; gelatin methacrylate (A–I reproduced with permission from Zhou et al., 2016).

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References

    1. Acerbi I., Cassereau L., Dean I., Shi Q., Au A., Park C., et al. . (2015). Human breast cancer invasion and aggression correlates with ECM stiffening and immune cell infiltration. Integr. Biol. (Camb). 7, 1120–1134. 10.1039/C5IB00040H - DOI - PMC - PubMed
    1. Ahmadzadeh H., Webster M. R., Behera R., Jimenez Valencia A. M., Wirtz D., Weeraratna A. T., et al. . (2017). Modeling the two-way feedback between contractility and matrix realignment reveals a nonlinear mode of cancer cell invasion. Proc. Natl. Acad. Sci. U.S.A. 114, E1617–E1626. 10.1073/pnas.1617037114 - DOI - PMC - PubMed
    1. Akthar S., Patel D. F., Beale R. C., Peiro T., Xu X., Gaggar A., et al. . (2015). Matrikines are key regulators in modulating the amplitude of lung inflammation in acute pulmonary infection. Nat. Commun. 6:8423. 10.1038/ncomms9423 - DOI - PMC - PubMed
    1. Almstedt K., Sicking I., Battista M. J., Huangfu S., Heimes A. S., Weyer-Elberich V., et al. . (2017). Prognostic significance of focal adhesion kinase in node-negative breast cancer. Breast Care (Basel). 12, 329–333. 10.1159/000477895 - DOI - PMC - PubMed
    1. Arnold K. M., Opdenaker L. M., Flynn D., Sims-Mourtada J. (2015). Wound healing and cancer stem cells: inflammation as a driver of treatment resistance in breast cancer. Cancer Growth Metastasis 8, 1–13. 10.4137/CGM.S11286 - DOI - PMC - PubMed
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