Cancer death is attributed mainly to the dissemination of metastatic cells to distant locations. Many efforts in cancer treatment focus on targeting or preventing the formation of metastatic colonies and progression of systemic metastatic disease1. Cancer cell migration is a crucial step in the tumor metastasis process, thus, the research of the cancer invasion cascade is very important and a prerequisite to finding anti-metastatic therapeutics.
The use of animal models as tools for studying metastatic disease has been found to be very expensive and not always representative of the tumor in humans. Moreover, the extracellular microenvironment topology, mechanics and composition strongly affect cancer cell behavior2. Since in vivo models inherently lack the ability to separate and control such specific parameters which contribute to cancer invasion and metastasis, there is a need for controllable biomimetic in vitro models.
In order to metastasize to distant organs, cancer cells must exhibit migratory and invasive phenotypic traits which can be targeted for therapy. However, since most in vitro cancer models do not mimic the actual features of solid tumors3, it is very challenging to detect physiologically relevant phenotypes. In addition, the phenotypic heterogeneity that exists within the tumor, dictates the need for analyzing tumor migration at single-element resolution in order to discover phenotype-directed therapies, for instance, by targeting the metastasis-initiating cell population within heterogeneous tumors4.
The study of cell motility and collective migration is primarily conducted in monolayer cultures of epithelial cells on homogeneous planar surfaces. These conventional cellular models for cancer cell migration are based on the population analysis of individual cells invading through the membranes and ECM components5, but in such systems, the intrinsic differences between individual cells cannot be studied. Generating 3D spheroids either via scaffolds or in scaffold-free micro-structures is considered as a superior means to study the tumor cell growth and cancer invasion6,7,8. However, most 3D systems are not suitable to high throughput formats, and inter-spheroid interaction cannot usually be achieved since isolated individual spheroids are generated in each micro-well9. Recent studies involving the cancer migration are based on microfluidic devices3,10,11,12, however, these sophisticated microfluidic tools are difficult to produce and cannot be used for high throughput screening (HTS) of anti-invasive drugs.
Two main phenotypes, collective and individual cell migration, which play a role in tumor cells overcoming the ECM barrier and invading neighboring tissue, have been demonstrated13,14, each displaying distinct morphological characteristics, biochemical, molecular and genetic mechanisms. In addition, two forms of migrating tumor cells, fibroblast-like and amoeboid, are observed in each phenotype. Since both, invasion phenotypes and migration modes, are mainly defined by morphological properties, there is a need for cellular models that enable imaging-based detection and examination of all forms of tumor invasion and migrating cells.
The overall goal of the current method is to provide a simple and reproducible biomimetic 3D in vitro cell-based system for the analysis of invasion capacity in large populations of tumor spheroids. Here, we introduce the HMCA-based 6-well imaging plate for the research of tumor invasion and anti-metastatic therapy. The technology enables the formation of large numbers of uniform 3D tumor spheroids (450 per well) in a hydrogel micro-chambers (MC) structure. Various ECM components are added to the spheroid array to enable the invasion of the cells into the surrounding environment. Invasion process is continuously monitored by short- and long-term observation of the same individual spheroids/invading cells and facilitates morphological characterization, fluorescent staining and retrieval of specific spheroids at any point. Since numerous spheroids share space and medium, interaction via soluble molecules between individual spheroids and their impact on one another is possible. Semi-automatic image analysis is performed by using in-house MATLAB code which enables faster and more efficient collection of large amount of data. The platform facilitates accurate, simultaneous measurement of numerous spheroids/invading cells in a time-efficient manner, allowing medium throughput screening of anti-invasion drugs.