AUTHOR=Avnet Sofia , Lemma Silvia , Cortini Margherita , Di Pompo Gemma , Perut Francesca , Baldini Nicola TITLE=Pre-clinical Models for Studying the Interaction Between Mesenchymal Stromal Cells and Cancer Cells and the Induction of Stemness JOURNAL=Frontiers in Oncology VOLUME=9 YEAR=2019 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2019.00305 DOI=10.3389/fonc.2019.00305 ISSN=2234-943X ABSTRACT=

Mesenchymal stromal cells (MSC) have essential functions in building and supporting the tumour microenvironment, providing metastatic niches, and maintaining cancer hallmarks, and it is increasingly evident that the study of the role of MSC in cancer is crucial for paving the way to clinical opportunities for novel anti-cancer therapies. To date, the vast majority of preclinical models that have been used for studying the effect of reactive MSC on cancer growth, metastasis, and response to therapy has been mainly based on in vitro flat biology, including the co-culturing with cell compartmentalization or with cell-to-cell contact, and on in vivo cancer models with different routes of MSC inoculation. More complex in vitro 3D models based on spheroid structures that are formed by intermingled MSC and tumour cells are also capturing the interest in cancer research. These are innovative culture systems tailored on the specific tumour type and that can be combined with a synthetic extracellular matrix, or included in in silico technologies, to more properly mimic the in vivo biological, spatial, biochemical, and biophysical features of tumour tissues. In this review, we summarized the most popular and currently available preclinical models for evaluating the role of MSC in cancer and their specific suitability, for example, in assaying the MSC-driven induction of epithelial-to-mesenchymal transition or of stem-like traits in cancer cells. Finally, we enlightened the need to carefully consider those parameters that might unintentionally strongly affect the secretome in MSC-cancer interplay and introduce confounding variables for the interpretation of results.