Tissue Eng Part C Methods. 2024 Mar 28. doi: 10.1089/ten.TEC.2023.0374. Online ahead of print.

ABSTRACT

Multiple myeloma (MM) clones reside in the bone marrow (BM), which plays a role in its survival and development. The interactions between MM and their neighboring mesenchymal stromal cells (MSCs) have been shown to promote MM growth and drug resistance. However, those interactions are often missing or misrepresented in traditional two-dimensional (2D) culture models. Application of novel three-dimensional (3D) models might recapitulate the BM niche more precisely, which will offer new insights into MM progression and survival. Here, we aimed to establish two 3D models, based on MSC-spheroids and collagen droplets incorporating both MM cells and MSCs with the goal of replicating the native myeloma context of the BM niche. This approach revealed that although MSCs can spontaneously assemble spheroids with altered metabolic traits, self-assembling MSC spheroid culture does not support the integration of MM cells. On the other hand, collagen-droplet culture supported the growth of both cell types. In collagen, MSC proliferation was reduced, with the correlating decrease in ATP production and Ki-67 expression, which might resemble in vivo conditions, rather than 2D abundance of nutrients and space. MSCs and MMs were distributed homogenously throughout the collagen droplet, with an apparent CXCL12 expression in MSCs. Additionally, the response of MM cells to bortezomib was substantially reduced in collagen, indicating the importance of 3D culture in the investigation of myeloma cell behavior, as drug-resistance is one of the most pertinent issues in cancer therapy. Impact statement: The application of 3D models in the investigation of multiple myeloma will provide better insight into their behaviour and drug resistance, allowing us to develop better treatment strategies. Here, we optimized a collagen-based approach which has shown to be reproducible, cost-effective and already providing an altered feedback in therapy response.

PMID:38545771 | DOI:10.1089/ten.TEC.2023.0374