Tumor-secreted extracellular vesicles (EVs) have been identified as mediators of cancer–host intercellular communication and shown to support pre-metastatic niche formation by modulating stromal cells at future metastatic sites. While osteosarcoma, the most common primary malignant bone tumor in children and adolescents, has a high propensity for pulmonary metastases, the interaction of osteosarcoma cells with resident lung cells remains poorly understood. Here, we deliver foundational in vitro evidence that osteosarcoma cell-derived EVs drive myofibroblast/cancer-associated fibroblast differentiation. Human lung fibroblasts displayed increased invasive competence, in addition to increased α-smooth muscle actin expression and fibronectin production upon EV treatment. Furthermore, we demonstrate, through the use of transforming growth factor beta receptor 1 (TGFBR1) inhibitors and CRISPR-Cas9-mediated knockouts, that TGFβ1 present in osteosarcoma cell-derived EVs is responsible for lung fibroblast differentiation. Overall, our study highlights osteosarcoma-derived EVs as novel regulators of lung fibroblast activation and provides mechanistic insight into how osteosarcoma cells can modulate distant cells to potentially support metastatic progression.

The pre-metastatic niche (PMN) is a tumor-driven microenvironment in distant organs that can foster and support the survival and growth of disseminated tumor cells. This facilitates the establishment of secondary lesions that eventually form overt metastasis, the main cause of cancer-related death. In recent years, tumor-derived extracellular-vesicles (EVs) have emerged as potentially key drivers of the PMN. The role of the PMN in osteosarcoma metastasis is poorly understood and the potential contribution of osteosarcoma cell-derived EVs to PMN formation has not been investigated so far. Here, we characterize pulmonary PMN development using the spontaneously metastasizing 143-B xenograft osteosarcoma mouse model. We demonstrate the accumulation of CD11b⁺ myeloid cells in the pre-metastatic lungs of tumor-bearing mice. We also establish that highly metastatic 143-B and poorly metastatic SAOS-2 osteosarcoma cell-derived EV education in naïve mice can recapitulate the recruitment of myeloid cells to the lungs. Surprisingly, despite EV-induced myeloid cell infiltration in the pre-metastatic lungs, 143-B and SAOS-2 EVs do not contribute towards the 143-B metastatic burden in the context of both spontaneous as well as experimental metastasis in severe-combined immunodeficient (SCID) mice. Taken together, OS-derived EVs alone may not be able to form a functional PMN, and may perhaps require a combination of tumor-secreted factors along with EVs to do so. Additionally, our study gives a valuable insight into the PMN complexity by providing the transcriptomic signature of the premetastatic lungs in an osteosarcoma xenograft model for the first time. In conclusion, identification of regulators of cellular and molecular changes in the pre-metastatic lungs might lead to the development of a combination therapies in the future that interrupt PMN formation and combat osteosarcoma metastasis.

Fascin-1, a prominent actin-bundling protein, is found to be upregulated in several human carcinomas. While it is accepted that Fascin-1 expression correlates with poor clinical outcome and decreased survival in various carcinomas, its role in sarcoma such as osteosarcoma (OS) remains unknown. In the present study, we evaluated the prognostic value and biological relevance of Fascin-1 in OS. The correlation between Fascin-1 expression and the outcome of OS patients was determined by immunohistochemistry analysis of Fascin-1 expression in a tissue microarray of OS tissue specimens collected during primary tumor resection. To examine the effect of Fascin-1, shRNA and overexpression technology to alter Fascin-1 levels in OS cells were used in cellular assays as well as in intratibial xenograft OS models in SCID mice. Kaplan-Meier survival analysis of Fascin-1 expression in OS tumor specimens revealed a direct relationship between Fascin-1 expression and poor patient survival. Furthermore, overexpression of Fascin-1 in OS cells significantly increased their migratory capacity as well as the activity of the matrix metalloprotease MMP-9, known to be critical for the execution of metastasis. Finally, using relevant xenograft mouse models, orthotopic intratibial transplantation of two different OS cell lines overexpressing Fascin-1 promoted tumor growth and lung metastasis. Collectively, our findings demonstrate for the first time that Fascin-1 has considerable potential as a novel prognostic biomarker in OS, and suggest that targeting of Fascin-1 might be a new anti-metastatic strategy in OS patient treatment.

Benchmarking is crucial for healthcare providers to enhance quality and efficiency, notably for complex conditions like sarcomas. Multidisciplinary teams/sarcoma boards (MDT/SBs) are vital in sarcoma management, but differences in their processes can affect patient outcomes and treatment costs, despite adherence to international guidelines. To address this issue, this study aimed to compare two MDT/SBs and establish an interoperable digital platform, Sarconnector^®, for real-time-world data assessment and automated analysis. The study included 983 patients, 46.0% of whom female, with a median age of 58 years, and 4.5% of patients presented with metastasis at diagnosis. Differences were observed in the number of first-time presentations, follow-up presentations, primary sarcomas, biopsies and chemotherapy indications between the two MDT/SB. The results highlight the importance of benchmarking and utilizing a harmonized data approach, such as the RWT approach provided by the Sarconnector^®, to standardize and evaluate quality and cost metrics. By identifying areas of improvement and making data-driven decisions on the meta-level, healthcare providers can optimize resources and improve patient outcomes. In conclusion, benchmarking with the RWT harmonized data approach provided by the Sarconnector^® can help healthcare providers improve the overall effectiveness of the healthcare system and achieve better outcomes for their patients in terms of both outcomes and costs.

The landscape of sarcoma care is on the cusp of a transformative era, spurred by the convergence of digital health and artificial intelligence (AI). This perspectives article explores the multifaceted opportunities and challenges in leveraging these technologies for value-based, precision sarcoma care. We delineate the current state-of-the-art methodologies and technologies in sarcoma care and outline their practical implications for healthcare providers, administrators, and policymakers. The article also addresses the limitations of AI and digital health platforms, emphasizing the need for high-quality data and ethical considerations. We delineate the promise held by the synergy of digital health platforms and AI algorithms in enhancing data-driven decision-making, outcome analytics, and personalized treatment planning. The concept of a sarcoma digital twin serves as an illustrative paradigm for this integration, offering a comprehensive, patient-centric view of the healthcare journey. The paper concludes with proposals for future research aimed at advancing the field, including the need for randomized controlled trials or target trial emulations and studies focusing on ethical and economic aspects. While the road to this transformative care is laden with ethical, regulatory, and practical challenges, we believe that the potential benefits far outweigh the obstacles. We conclude with a call to action for multidisciplinary collaboration and systemic adoption of these technologies, underscoring the urgency to act now for the future betterment of sarcoma care and healthcare at large.

Sarcomas represent a large group of rare to very rare diseases, requiring complex management with a transdisciplinary approach. Overall progress has been hampered because of discipline, institution and network fragmentation, and there is no global data harmonization or quality standards. To report on and improve quality, a common definition of quality indicators (QIs) of sarcoma care as well as the capacity to assess longitudinal real-time data is required. An international advisory board of world-renowned sarcoma experts defined six categories of QIs, totaling more than 80 quality indicators. An interoperable (web-based) digital platform was then created combining the management of the weekly sarcoma board meeting with the sarcoma registry and incorporating patient-reported outcome measures (PROMs) into the routine follow-up care to assess the entire care cycle of the patient. The QIs were then programmed into the digital platform for real-time analysis and visualization. The definition of standardized QIs covering all physician- (diagnostics and therapeutics), patient- (PROMS/PREMS), and cost-based aspects in combination with their real-time assessment over the entire sarcoma care cycle can be realized. Standardized QIs as well as their real-time assessment and data visualization are critical to improving the quality of sarcoma care. By enabling predictive modelling and introducing VBHC, precision health care for a complex disease is on the horizon.