ReviewOrgan-on-chip models of cancer metastasis for future personalized medicine: From chip to the patient
Introduction
Most cancer deaths result from metastasis. Metastasis is defined as the sequence of events leading to the spread of cancer cells from the site of primary tumor to new locations in the human body. A lot of investigation is being carried out into the molecular basis of tumor growth and dissemination [1]. However, the mechanism of metastasis is still poorly understood [2], [3]. In addition to genetic and external environmental factors, tumor expansion is also determined by the structural properties of the tumor microenvironment [4]. The details on the mechanism of conversion of a physical stimulus in the tumor microenvironment, such as cell-cell/extracellular matrix (ECM) interactions or fluid shear forces, into a biochemical response during tumor progression are not well understood. Thus, the comprehension of the disease and its progression into metastasis is still limited [5], [6], [7], [8]. Metastasis is also related to mechanism of drug resistance which still remains unclear [9], [10], [11]. Multiple efforts are directed toward the development of cancer metastasis models that can help in understanding the disease and in the development of innovative therapeutic strategies. Traditionally, standard in vivo and in vitro models are used to elucidate the mechanisms involved in metastasis [12], [13], [14], [15], [16], [17]. The complexity encountered in humans is reproduced with higher fidelity using in vivo models. However, the individual contribution of interconnected physical and biochemical parameters in an in vivo model cannot be assessed easily. In addition, they fail in predicting the clinical efficacy of new drug candidates [18], [19]. The in vitro, though fully controllable, lack the hierarchical complexity of the tumor niche needed to reproduce the native scenario. This threatens the relevance of the data obtained using in vitro models. Pre-clinical experimentation demands highly sophisticated and physiologically relevant in vitro models capable of recapitulating both the biomolecular and structural properties of the tumor niche along with the dynamic events occurring during the propagation of cancer. In this regard, organ-on-chip technology can be used to design biomimetic microfluidic devices containing human cells to replicate fundamental functional units of human tissues and organs in vitro [20], [21], [22], [23]. Applied to cancer research, organ-on-chip models of cancer metastasis, or metastasis-on-chip (MoC) emerge as a promising methodology for studying the disease under physiological-like conditions [24].
MoC models provide multiple advantages compared to their in vitro and in vivo counterparts, which have many barriers for their clinical applications. During the last decade, MoC models have been used to study the contribution of the mechanical and biochemical cues in tumor dissemination, including the impact of cell-cell/stroma interactions [12], [25], [26], [27], or cytokine gradients [28], among others. Similarly, several events described in the metastasis cascade have been successfully reproduced. This includes cancer cell invasion, angiogenesis, intravasation, extravasation, colonization, and most importantly, the impact of circulating tumor cells (CTCs) in tumor dissemination. Several MoC models have been developed toward their early detection, capturing, analysis and use for exploring their diagnostic and prognostic potential [29]. This is critically important because CTCs are responsible for most cancer-related deaths [30], [31], [32], [33].
This review describes the latest and most relevant advances in MoC models, their main advantages, limitations, and future perspectives for cancer research. We anticipate that this new generation of tumor models will provide new insights into the molecular and mechanical mechanisms of metastasis, which have remained elusive due to the limitations of current models. Further, when combined with advanced imaging, sensing and screening techniques, MoC models may be employed to understand the mechanism of targeted drug delivery in vitro, improving the knowledge on current treatments and potentially developing new therapeutic avenues [34]. Finally, the translation of MoC models into the pharmaceutical and healthcare market will require MoC models to display unprecedented capabilities. This new generation of tumor models will univocally contribute to improve the prognosis of cancer patients reducing the cost in the healthcare system.
Section snippets
Current cancer metastasis models: an overview
A large plethora of cancer metastasis models have been described in the literature during the last years. These standard models include both experimental (in vitro and in vivo) and computational (in silico) approaches, which have provided valuable insights into the mechanistic determinants of the disease. They have been extremely useful for studying tumor dissemination, screening anti-cancerous drugs, or testing novel therapeutic strategies. However, they also display serious limitations. In
Microfluidic models of cancer metastasis: metastasis-on-chip
Cancer metastasis involves a complex cascade of events (Fig. 2a) [3]. Typically, this cascade is first initiated by an uncontrolled growth of the primary malignant tumor followed by the invasion of cancer cells into the surrounding stroma. Next, a deficient oxygen supply serves as a cue for the secretion of cytokines and growth factors which induce the formation of new microvasculature – angiogenesis – that aids in the transmigration of the cancer cells, as well as ctDNA/RNA, exosomes, or
Integration of advanced imaging, screening, and biosensing technologies into organ-on-chip devices: towards precision medicine
The real-time monitoring of tumor growth and progression is challenging and difficult to accomplish with standard methodologies. Genotyping tumor tissue in search of genetic alterations is a routine practice in clinical oncology to provide physicians with highly valuable information. However, the extracted biopsy only represents a single snapshot in time and is subjected to selection bias also due to tumor heterogeneity. Multiple or serial biopsies in time may provide valuable information about
Personalized patient-derived MoC models for clinical applications
Future point-of-care MoC models must fulfill rigid requirements if intended for clinical applications. First, they need to reproduce the complexity of each individual patient to stand for the genetic heterogeneity of tumors and at the same time maintaining this complexity low to keep the model clinically-relevant. This implies the use of engineered biomaterials and cells from patients to develop personalized models of cancer metastasis [142], [143]. Second, they must integrate multi-organ
Conclusions
Standard in vitro and in vivo models of cancer metastasis display certain limitations which limit their applicability in the clinics. The recent progress in bioengineering techniques and microfabrication tools allows the production of a new generation of cancer metastasis models based on organ-on-chip technology. Different events in the metastasis cascade have been successfully reproduced, including organ-specificity and hybrid models. These metastasis-on-chip devices can provide the needed
Acknowledgements
The authors acknowledge the financial support from the European Union Framework Programme for Research and Innovation Horizon 2020 on Forefront Research in 3D Disease Cancer Models as in vitro Screening Technologies (FoReCaST) under grant agreement no 668983. Conflicts of interest: none.
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