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Review
. 2022 May:184:114181.
doi: 10.1016/j.addr.2022.114181. Epub 2022 Mar 9.

Engineering complexity in human tissue models of cancer

Kacey Ronaldson-Bouchard  1 , Ilaria Baldassarri  1 , Daniel Naveed Tavakol  1 , Pamela L Graney  1 , Maria Samaritano  1 , Elisa Cimetta  2 , Gordana Vunjak-Novakovic  3
Affiliations
Review

Engineering complexity in human tissue models of cancer

Kacey Ronaldson-Bouchard et al. Adv Drug Deliv Rev. 2022 May.

Abstract

Major progress in the understanding and treatment of cancer have tremendously improved our knowledge of this complex disease and improved the length and quality of patients' lives. Still, major challenges remain, in particular with respect to cancer metastasis which still escapes effective treatment and remains responsible for 90% of cancer related deaths. In recent years, the advances in cancer cell biology, oncology and tissue engineering converged into the engineered human tissue models of cancer that are increasingly recapitulating many aspects of cancer progression and response to drugs, in a patient-specific context. The complexity and biological fidelity of these models, as well as the specific questions they aim to investigate, vary in a very broad range. When selecting and designing these experimental models, the fundamental question is "how simple is complex enough" to accomplish a specific goal of cancer research. Here we review the state of the art in developing and using the human tissue models in cancer research and developmental drug screening. We describe the main classes of models providing different levels of biological fidelity and complexity, discuss their advantages and limitations, and propose a framework for designing an appropriate model for a given study. We close by outlining some of the current needs, opportunities and challenges in this rapidly evolving field.

Keywords: Cancer; Drug development; Metastasis; Organoids; Organs-on-a-chip; Precision medicine; Tissue engineering.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1 -
Figure 1 -. Complexity driven design of human OOC models.
Complex questions call for complex models, with the goal to select the simplest model enabling investigation of a given question. In all cases, physiological relevance and compatibility with imaging, on-line and end-point assays are a must. Created with BioRender.com.
Figure 2.
Figure 2.. Bioengineering models of human tumors
Our knowledge of the in vivo tissue conditions of human cancers guides the design of in vitro tumor models. Varying levels of complexity can be engineered by incorporating parameter inputs that replicate specific components of the TME. Such inputs include but are not limited to (1) cell-cell interactions, (2) cell-ECM interactions, (3) mechanical stimuli, (4) molecular gradients (chemical, hypoxic, metabolic), (5) vascular integrity, and (6) incorporation of immune components. Created with BioRender.com.
Figure 3.
Figure 3.. Microfluidic models of tumor metastasis
Different models of primary tumors, vasculature and engineered tissues that are common targets for invasion of circulating tumor cells can be utilized alone and in combinations, to model the key steps of metastasis (premetastatic niche, intravasation, dissemination, extravasation, metastatic colonization, formation of secondary tumors). Created with BioRender.com.
Figure 4.
Figure 4.. Incorporation of immune components into organs-on-a-chip models
Overview of the human immune organs that are of interest for in vitro models of cancer, with their patho/physiological roles in the body. Created with BioRender.com.
Figure 5.
Figure 5.. Framework for designing engineered models of cancer
Mechanistic cancer biology, drug development, and precision medicine are three major areas of application of engineered cancer models. The workflow for key studies in each field of research can be summarized identifying the biological question of interest to the investigators and the fundamental elements of the model and strategy adopted to answer it. Created with BioRender.com
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