Evolution of Metastasis Study Models toward Metastasis-On-A-Chip: The Ultimate Model?

Establishment of highly metastatic sublines and insights into telomerase expression during tumor metastasis using a microfluidic system

Metastasis is an important hallmark of malignant tumors, and telomerase often exhibits high expression in these tumors. Monitoring the real-time dynamics of telomerase will provide valuable insights into its association with tumor metastasis. In this study, we described a microfluidic system for screening highly metastatic sublines based on differential cell invasiveness, investigated telomerase expression in the process of tumor metastasis and explored the genes and signaling pathways involved in tumor metastasis. Cells with different metastasis abilities were efficiently classified into different channels, and the fluorescence imaging visually demonstrates that cells with higher metastasis ability have stronger telomerase activity. In addition, we successfully established the high-metastasis-ability LoVo subline (named as LoVo-H) and low-metastasis-ability LoVo subline (named as LoVo-L) from the human colorectal cancer LoVo cell lines through only one round of selection using the system. The results show that the LoVo-H cells display superior proliferation and invasiveness compared to LoVo-L cells. Furthermore, 6776 differentially expressed genes of LoVo-H compared with LoVo-L were identified by transcriptome sequencing. The genes associated with telomerase activity, cell migration and the epithelial to mesenchymal transition were up-regulated in LoVo-H, and PI3K-Akt signaling pathway, extracellular matrix-receptor interaction and Rap1 signaling pathway were significantly enriched in LoVo-H. This microfluidic system is a highly effective tool for selecting highly metastatic sublines and the LoVo-H subline established through this system presents a promising model for tumor metastasis research. Furthermore, this work preliminarily reveals telomerase expression during tumor metastasis and provides a new strategy for studying tumor metastasis and cancer diagnosis.

Using deep learning for predicting the dynamic evolution of breast cancer migration

BACKGROUND

Breast cancer (BC) remains a prevalent health concern, with metastasis as the main driver of mortality. A detailed understanding of metastatic processes, particularly cell migration, is fundamental to improve therapeutic strategies. The wound healing assay, a traditional two-dimensional (2D) model, offers insights into cell migration but presents scalability issues due to data scarcity, arising from its manual and labor-intensive nature.

METHOD

To overcome these limitations, this study introduces the Prediction Wound Progression Framework (PWPF), an innovative approach utilizing Deep Learning (DL) and artificial data generation. The PWPF comprises a DL model initially trained on artificial data that simulates wound healing in MCF-7 BC cell monolayers and spheres, which is subsequently fine-tuned on real-world data.

RESULTS

Our results underscore the model's effectiveness in analyzing and predicting cell migration dynamics within the wound healing context, thus enhancing the usability of 2D models. The PWPF significantly contributes to a better understanding of cell migration processes in BC and expands the possibilities for research into wound healing mechanisms.

CONCLUSIONS

These advancements in automated cell migration analysis hold the potential for more comprehensive and scalable studies in the future. Our dataset, models, and code are publicly available at https://github.com/frangam/wound-healing.

3D Cell Migration Chip (3DCM-Chip): A New Tool toward the Modeling of 3D Cellular Complex Systems

3D hydrogel-based cell cultures provide models for studying cell behavior and can efficiently replicate the physiologic environment. Hydrogels can be tailored to mimic mechanical and biochemical properties of specific tissues and allow to produce gel-in-gel models. In this system, microspheres encapsulating cells are embedded in an outer hydrogel matrix, where cells are able to migrate. To enhance the efficiency of such studies, a lab-on-a-chip named 3D cell migration-chip (3DCM-chip) is designed, which offers substantial advantages over traditional methods. 3DCM-chip facilitates the analysis of biochemical and physical stimuli effects on cell migration/invasion in different cell types, including stem, normal, and tumor cells. 3DCM-chip provides a smart platform for developing more complex cell co-cultures systems. Herein the impact of human fibroblasts on MDA-MB 231 breast cancer cells' invasiveness is investigated. Moreover, how the presence of different cellular lines, including mesenchymal stem cells, normal human dermal fibroblasts, and human umbilical vein endothelial cells, affects the invasive behavior of cancer cells is investigated using 3DCM-chip. Therefore, predictive tumoroid models with a more complex network of interactions between cells and microenvironment are here produced. 3DCM-chip moves closer to the creation of in vitro systems that can potentially replicate key aspects of the physiological tumor microenvironment.

Collagen-alginate 3D microscaffolds for studying cellular migration

Metastasis is one of the major causes for cancer mortality. Its early steps comprise of invasion of basement membrane and migration. Thus, it is hypothesized that a platform, that allows quantification and grading of migration capability of cells can potentially be used for predicting metastatic potential. Two-dimensional (2D) models have been rendered inadequate for modelling in-vivo microenvironment due to various reasons. To attenuate homogeneity observed in 2D, three-dimensional (3D) platforms supplemented with bioinspired components have been designed. Unfortunately, till date there are no simple models to capture the migration of cells in 3D along with quantification of the process. In this study, we report an alginate-collagen based 3D model system, which can predict the migratory property of the cells within 72 h. The micron size of the scaffold enabled faster readout and the optimum pore-size provided conducive cellular growth environment. The platform's ability to allow observation of cellular migration was validated by encapsulating cells with transiently upregulated matrix metalloprotease 9 (MMP9), which has been reported to play a significant role in migration of cells during metastasis. The readout for migration was clustering of cells in the microscaffolds detected in a short span of 48 h. The observed clustering in MMP9 upregulated cells was validated by observing changes in the epithelial-mesenchymal transition (EMT) markers. Thus, this simple 3D platform can be used to study migration and predict the metastatic potential of cells.

Optimization of Neferine Purification Based on Response Surface Methodology and Its Anti-Metastasis Mechanism on HepG2 Cells

Liver cancer continues to be a focus of scientific research due to its low five-year survival rate. One of its main core issues is the high metastasis of cells, for which there is no effective treatment. Neferine was originally isolated from Plumula nelumbinis and demonstrated to have a good antitumor effect. In order to extract high-purity Neferine in a more efficient and environmentally friendly manner, response surface methodology (RSM) was used to optimize the isolation and purification procedures in this study. The extract conditions of a 7:3 ratio for the eluent of dichloromethane: methanol, 1:60 for the mass ratio of the extract amount: silica gel, and 3 mL/min of the elution flow rate were shown to be the optimal conditions. These conditions resulted in the highest yield of 6.13 mg per 66.60 mg of starting material, with productivity of 8.76% and purity of 87.04%. Compared with the previous methods, this method can prepare Neferine in large quantities more quickly. We subsequently evaluated the antitumor activity of the purified Neferine against HepG2 hepatic cancer cells. The purified Neferine was found to inhibit the proliferation of HepG2 cells through the CCK-8 assay, with an IC₅₀ of 33.80 μM in 24 h, 29.47 μM in 48 h, 24.35 μM in 72 h and 2.78 μM in 96 h of treatment. Neferine at a concentration of 3 μM could significantly inhibit the migration and invasion abilities of the HepG2 cells in vitro. We also explored the mechanism of action of Neferine via Western blot. We showed that Neferine could reduce RhoA expression by effectively inhibiting the phosphorylation of MYPT1, thereby effectively exerting anti-metastasis activity against HepG2 cells. Thus, we have optimized the isolation procedures for highly pure Neferine by response surface methodology (RSM) in this study, and purified Neferine is shown to play an essential role in the anti-metastasis process of liver cancer cells. The Neferine purification procedure may make a wide contribution to the follow-up development of other anti-metastasis lead compounds.

Recent Advances of Organ-on-a-Chip in Cancer Modeling Research

Although many studies have focused on oncology and therapeutics in cancer, cancer remains one of the leading causes of death worldwide. Due to the unclear molecular mechanism and complex in vivo microenvironment of tumors, it is challenging to reveal the nature of cancer and develop effective therapeutics. Therefore, the development of new methods to explore the role of heterogeneous TME in individual patients' cancer drug response is urgently needed and critical for the effective therapeutic management of cancer. The organ-on-chip (OoC) platform, which integrates the technology of 3D cell culture, tissue engineering, and microfluidics, is emerging as a new method to simulate the critical structures of the in vivo tumor microenvironment and functional characteristics. It overcomes the failure of traditional 2D/3D cell culture models and preclinical animal models to completely replicate the complex TME of human tumors. As a brand-new technology, OoC is of great significance for the realization of personalized treatment and the development of new drugs. This review discusses the recent advances of OoC in cancer biology studies. It focuses on the design principles of OoC devices and associated applications in cancer modeling. The challenges for the future development of this field are also summarized in this review. This review displays the broad applications of OoC technique and has reference value for oncology development.

Biofabrication approaches and regulatory framework of metastatic tumor-on-a-chip models for precision oncology

The complexity of the tumor microenvironment (TME) together with the development of the metastatic process are the main reasons for the failure of conventional anticancer treatment. In recent years, there is an increasing need to advance toward advanced in vitro models of cancer mimicking TME and simulating metastasis to understand the associated mechanisms that are still unknown, and to be able to develop personalized therapy. In this review, the commonly used alternatives and latest advances in biofabrication of tumor‐on‐chips, which allow the generation of the most sophisticated and optimized models for recapitulating the tumor process, are presented. In addition, the advances that have allowed these new models in the area of metastasis, cancer stem cells, and angiogenesis are summarized, as well as the recent integration of multiorgan‐on‐a‐chip systems to recapitulate natural metastasis and pharmacological screening against it. We also analyze, for the first time in the literature, the normative and regulatory framework in which these models could potentially be found, as well as the requirements and processes that must be fulfilled to be commercially implemented as in vitro study model. Moreover, we are focused on the possible regulatory pathways for their clinical application in precision medicine and decision making through the generation of personalized models with patient samples. In conclusion, this review highlights the synergistic combination of three‐dimensional bioprinting systems with the novel tumor/metastasis/multiorgan‐on‐a‐chip systems to generate models for both basic research and clinical applications to have devices useful for personalized oncology.

Organ on Chip Technology to Model Cancer Growth and Metastasis

Organ on chip (OOC) has emerged as a major technological breakthrough and distinct model system revolutionizing biomedical research and drug discovery by recapitulating the crucial structural and functional complexity of human organs in vitro. OOC are rapidly emerging as powerful tools for oncology research. Indeed, Cancer on chip (COC) can ideally reproduce certain key aspects of the tumor microenvironment (TME), such as biochemical gradients and niche factors, dynamic cell-cell and cell-matrix interactions, and complex tissue structures composed of tumor and stromal cells. Here, we review the state of the art in COC models with a focus on the microphysiological systems that host multicellular 3D tissue engineering models and can help elucidate the complex biology of TME and cancer growth and progression. Finally, some examples of microengineered tumor models integrated with multi-organ microdevices to study disease progression in different tissues will be presented.