An organ-on-a-chip model of the how mechanical stimulation of osteocytes affects the phenotype of breast and prostate cancer cells, published in the journal Cancers 2021 and available here.
Breast and prostate cancers preferentially metastasise to bone tissue, with metastatic lesions forming in the skeletons of most patients. On arriving in bone tissue, disseminated tumour cells enter a mechanical microenvironment that is substantially different to that of the primary tumour and is largely regulated by bone cells. Osteocytes, the most ubiquitous bone cell type, orchestrate healthy bone remodelling in response to physical exercise. However, the effects of mechanical loading of osteocytes on cancer cell behaviour is still poorly understood. The aim of this study was to characterise the effects of osteocyte mechanical stimulation on the behaviour of breast and prostate cancer cells. To replicate an osteocyte-controlled environment, this study treated breast (MDA-MB-231 and MCF-7) and prostate (PC-3 and LNCaP) cancer cell lines with conditioned media from MLO-Y4 osteocyte-like cells exposed to mechanical stimulation in the form of fluid shear stress. We found that osteocyte paracrine signalling acted to inhibit metastatic breast and prostate tumour growth, characterised by reduced proliferation and invasion and increased migration. In breast cancer cells, these effects were largely reversed by mechanical stimulation of osteocytes. In contrast, conditioned media from mechanically stimulated osteocytes had no effect on prostate cancer cells. To further investigate these interactions, we developed a microfluidic organ-chip model using the Emulate platform. This new organ-chip model enabled analysis of cancer cell migration, proliferation and invasion in the presence of mechanical stimulation of osteocytes by fluid shear stress, resulting in increased invasion of breast and prostate cancer cells. These findings demonstrate the importance of osteocytes and mechanical loading in regulating cancer cell behaviour and the need to incorporate these factors into predictive in vitro models of bone metastasis.