Background: Personalised medicine is a medical model that aims to provide tailor-made prevention and treatment strategies for defined groups of individuals. The concept brings new challenges to the translational step, both in clinical relevance and validity of models. We have developed a set of recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. Methods: These recommendations have been developed following four main steps: (1) a scoping review of the literature with a gap analysis, (2) working sessions with a wide range of experts in the field, (3) a consensus workshop, and (4) preparation of the final set of recommendations. Results: Despite the progress in developing innovative and complex preclinical model systems, to date there are fundamental deficits in translational methods that prevent the further development of personalised medicine. The literature review highlighted five main gaps, relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. We identified five points of focus for the recommendations, based on the consensus reached during the consultation meetings: (1) clinically relevant translational research, (2) robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research and patient engagement. Here, we present a set of 15 recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. Conclusions: Appropriate preclinical models should be an integral contributor to interventional clinical trial success rates, and predictive translational models are a fundamental requirement to realise the dream of personalised medicine. The implementation of these guidelines is ambitious, and it is only through the active involvement of all relevant stakeholders in this field that we will be able to make an impact and effectuate a change which will facilitate improved translation of personalised medicine in the future.

Complete cytoreductive surgery is the cornerstone of the treatment of epithelial ovarian cancer (EOC). The application of fluorescence image-guided surgery (FIGS) allows for the increased intraoperative visualization and delineation of malignant lesions by using fluorescently labeled targeting biomarkers, thereby improving intraoperative guidance. CD24, a small glycophosphatidylinositol-anchored cell surface receptor, is overexpressed in approximately 70% of solid cancers, and has been proposed as a prognostic and therapeutic tumor-specific biomarker for EOC. Recently, preclinical studies have demonstrated the benefit of CD24-targeted contrast agents for non-invasive fluorescence imaging, as well as improved tumor resection by employing CD24-targeted FIGS in orthotopic patient-derived xenograft models of EOC. The successful detection of miniscule metastases denotes CD24 as a promising biomarker for the application of fluorescence-guided surgery in EOC patients. The aim of this review is to present the clinical and preclinically evaluated biomarkers for ovarian cancer FIGS, highlight the strengths of CD24, and propose a future bimodal approach combining CD24-targeted fluorescence imaging with radionuclide detection and targeted therapy.

Osteosarcoma (OSA) is a naturally occurring malignant bone tumor in both humans and canines that is characterized by aggressive local behavior and a high propensity for metastasis. Despite advances in diagnostic methods and therapies, long-term survival rates have remained stagnant, underscoring the great need for the development of biomarkers serving in the prognosis and diagnosis of OSA across species. Biomarkers, molecular indicators of disease presence or progression, are pivotal tools in oncology, offering the potential to determine risk stratification, guide targeted therapies, and monitor treatment response. This review provides an in-depth analysis of the current landscape of OSA biomarkers, highlighting diagnostic and prognostic markers identified across species. We highlighted the role of biomarkers, including protein, cellular, metabolic, imaging, genetic, and epigenetic markers, in osteosarcoma diagnosis and prognosis and categorized them across multiple domains. Furthermore, this review explores the utility of the canine model in osteosarcoma research, emphasizing its relevance to human OSA due to comparable diagnostic approaches, prognostic indicators, and clinical manifestations. With this review, we aim to demonstrate that integrating biomarker research across species can deepen the understanding of osteosarcoma pathogenesis and advance knowledge of its underlying biology, ultimately paving the way for precision medicine strategies that benefit both human and veterinary oncology.

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.

Osteosarcoma is an aggressive primary bone malignancy affecting both humans and dogs, and canine osteosarcoma represents a valuable comparative model for investigating novel therapeutic strategies. Targeting tumour metabolism may enhance the efficacy of existing anticancer treatments. This study investigated whether the mitochondrial uncoupler BAM15 modifies the response of canine D17 osteosarcoma cells to regorafenib. Cells were treated with BAM15 (20 µM) or regorafenib (REG; IC₂₅, 8 µM; IC₅₀, 16 µM) alone or pretreated with BAM15 before regorafenib exposure. Treatment effects were assessed using viability assays, Annexin V/propidium iodide staining, cell-cycle analysis, Seahorse XF bioenergetic profiling, quantitative PCR, and Western blotting. BAM15 alone did not significantly affect cell metabolic activity. Combined treatment with BAM15 and regorafenib produced a significantly greater reduction in cell metabolic activity than regorafenib alone at IC₅₀, whereas no significant difference between treatments was observed at IC₂₅. Combined treatment at IC₅₀ increased late apoptotic and necrotic populations and disrupted cell-cycle distribution. BAM15 reduced oxidative phosphorylation-derived ATP production without detectable glycolytic compensation but did not further suppress mitochondrial ATP production beyond regorafenib effect alone. Combined treatment also induced transcriptional changes in stress-adaptation-related genes, while protein analysis revealed reduced BAX and BAX/BCL-2 ratio. These exploratory findings provide preliminary evidence that mitochondrial uncoupling by BAM15 may modify the response to regorafenib and support further mechanistic investigation and validation in additional tumour and non-malignant canine models.