A technological approach to recapitulate the breast cancer metastatic model in vitro
Abstract: Cancer patients developing a metastatic disease are considered incurable . Breast cancer hits 1 woman in 8, and a major hurdle to overcome breast cancer mortality is the lack of understanding of dynamics leading to the spread of breast cancer cells to metastases. The aim of this work is to generate and validate a first-of-a-kind 3D model of breast cancer metastasis to dissect the complexity of the metastatic process and empower high-throughput drug screening in a physiological context. A novel fluidic multi-chamber device has been adopted to culture tumour organoids of clinically-relevant dimensions in contact with an endothelial barrier for recapitulating spontaneous tumour cells migration, intravasation and circulating metastatic cells survival under flow.
Mechanically tuned alginate and alginate/matrigel hydrogels have been realized as breast cell-laden tumour models. A strict correlation between cell viability and substrate elasticity has been observed, and the highest cellular proliferation rate, associated with the formation of typical cell clusters, has occurred in vitro only in the softest hydrogels (E<200 kPa). Moreover, human breast cancer cells cultured within hydrogels exhibited peculiar cytoskeleton shapes (i.e. invadopodia) and poly-nuclei organization characteristic of their malignancy only in alginate/matrigel hydrogels with the highest concentration of matrigel. Finally, cell-laden hydrogels have been cultured within the fluidic multi-chamber device and the breast cancer cells passage from hydrogel (representing the primary tumor model) to the fluidic circuit, and from the circuit (representing the vascular flow) to the metastatic chamber, was monitored over time and analysis through single cell picking. Analysis of human circulating tumor cells (CTCs) in a 3D model of breast cancer metastasis opens new scenarios in the cancer biology, overcoming the limitations of current in vitro technologies and animal models [2,3], finally providing a breakthrough technology to investigate metastasis, and to lead to the identification of metastasis-suppressing therapies for breast cancer patients.ed on the analogue subset also gave promising results with an r2 value of 0.66 and q2 of 0.47. Initial models based on atom-types alone showed that the models were less predictive than descriptor based models. It was postulated that this was due to an explicit representation of the electronic characteristics of the molecules in those models.