An exploratory study of cell stiffness as a mechanical label-free biomarker across multiple musculoskeletal sarcoma cells.

BACKGROUND: Cancer cells are characterized by changes in cell cytoskeletal architecture and stiffness. Despite advances in understanding the molecular mechanisms of musculoskeletal cancers, the corresponding cellular mechanical properties remain largely unexplored. The aim of this study was to investigate the changes in cellular stiffness and the associated cytoskeleton configuration alterations in various musculoskeletal cancer cells. METHODS: Cell lines from five main sarcoma types of the musculoskeletal system (chondrosarcoma, osteosarcoma, Ewing sarcoma, fibrosarcoma and rhabdomyosarcoma) as well as their healthy cell counterparts (chondrocytes, osteoblasts, mesenchymal stem cells, fibroblasts, skeletal muscle cells) were subjected to cell stiffness measurements via atomic force microscopy (AFM). Biochemical and structural changes of the cytoskeleton (F-actin, ß-tubulin and actin-related protein 2/3) were assessed by means of fluorescence labelling, ELISA and qPCR. RESULTS: While AFM stiffness measurements showed that the majority of cancer cells (osteosarcoma, Ewing sarcoma, fibrosarcoma and rhabdomyosarcoma) were significantly less stiff than their corresponding non-malignant counterparts (p < 0.001), the chondrosarcoma cells were significant stiffer than the chondrocytes (p < 0.001). Microscopically, the distribution of F-actin differed between malignant entities and healthy counterparts: the organisation in well aligned stress fibers was disrupted in cancer cell lines and the proteins was mainly concentrated at the periphery of the cell, whereas ß-tubulin had a predominantly perinuclear localization. While the F-actin content was lower in cancer cells, particularly Ewing sarcoma (p = 0.018) and Fibrosarcoma (p = 0.023), this effect was even more pronounced in the case of ß-tubulin for all cancer-healthy cell duos. Interestingly, chondrosarcoma cells were characterized by a significant upregulation of ß-tubulin gene expression (p = 0.005) and protein amount (p = 0.032). CONCLUSION: Modifications in cellular stiffness, along with structural and compositional cytoskeleton rearrangement, constitute typical features of sarcomas cells, when compared to their healthy counterpart. Notably, whereas a decrease in stiffness is typically a feature of malignant entities, chondrosarcoma cells were stiffer than chondrocytes, with chondrosarcoma cells exhibiting a significantly upregulated ß-tubulin expression. Each Sarcoma entity may have his own cellular-stiffness and cytoskeleton organisation/composition fingerprint, which in turn may be exploited for diagnostic or therapeutic purposes.

Addressing Practical Issues in Atomic Force Microscopy-Based Micro-indentation on Human Articular Cartilage Explants.

Without a doubt, atomic force microscopy (AFM) is currently one of the most powerful and useful techniques to assess micro and even nano-cues in the biological field. However, as with any other microscopic approach, methodological challenges can arise. In particular, the characteristics of the sample, sample preparation, type of instrument, and indentation probe can lead to unwanted artifacts. In this protocol, we exemplify these emerging issues on healthy as well as osteoarthritic articular cartilage explants. To this end, we first show via a step-by-step approach how to generate, grade, and visually classify ex vivo articular cartilage discs according to different stages of degeneration by means of large 2D mosaic fluorescence imaging of the whole tissue explants. The major strength of the ex vivo model is that it comprises aged, native, human cartilage that allows the investigation of osteoarthritis-related changes from early onset to progression. In addition, common pitfalls in tissue preparation, as well as the actual AFM procedure together with the subsequent data analysis, are also presented. We show how basic but crucial steps such as sample preparation and processing, topographic sample characteristics caused by advanced degeneration, and sample-tip interaction can impact data acquisition. We also subject to scrutiny the most common problems in AFM and describe, where possible, how to overcome them. Knowledge of these limitations is of the utmost importance for correct data acquisition, interpretation, and, ultimately, the embedding of findings into a broad scientific context.