An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.

A common method of three-dimensional (3D) cell cultures is embedding single cells in Matrigel. Separated cells in Matrigel migrate or grow to form spheroids but lack cell-to-cell interaction, which causes difficulty or delay in forming mature spheroids. To address this issue, we proposed a 3D aggregated spheroid model (ASM) to create large single spheroids by aggregating cells in Matrigel attached to the surface of 96-pillar plates. Before gelling the Matrigel, we placed the pillar inserts into blank wells where gravity allowed the cells to gather at the curved end. In a drug screening assay, the ASM with Hepatocellular carcinoma (HCC) cell lines showed higher drug resistance compared to both a conventional spheroid model (CSM) and a two-dimensional (2D) cell culture model. With protein expression, cytokine activation, and penetration analysis, the ASM showed higher expression of cancer markers associated with proliferation (p-AKT, p-Erk), tight junction formation (Fibronectin, ZO-1, Occludin), and epithelial cell identity (E-cadherin) in HCC cells. Furthermore, cytokine factors were increased, which were associated with immune cell recruitment/activation (MIF-3α), extracellular matrix regulation (TIMP-2), cancer interaction (IL-8, TGF-β2), and angiogenesis regulation (VEGF-A). Compared to CSM, the ASM also showed limited drug penetration in doxorubicin, which appears in tissues in vivo. Thus, the proposed ASM better recapitulated the tumor microenvironment and can provide for more instructive data during in vitro drug screening assays of tumor cells and improved prediction of efficacious drugs in HCC patients.

Lung carcinoids are neuroendocrine tumors representing 1 to 2% of lung cancers. This study outlines the case of a patient with a metastatic lung atypical carcinoid who presented with a pleural effusion and progression of liver metastases after developing resistance to conventional treatments. Personalized functional profiling (PFP), i.e. drug screening, was performed in ex-vivo spheroids obtained from the patient’s liver metastasis to identify potential therapeutic options. The drug screening results revealed cediranib, an antiangiogenic drug, as a hit drug for this patient, from a library of 66 Food and Drug Administration (FDA)-approved and investigational drugs. Based on the PFP results and the reported evidence of clinical efficacy of bevacizumab and capecitabine combination in gastro-intestinal neuroendocrine tumors, this combination was given to the patient. Four months later, the pleural effusion and pleura carcinosis regressed and the liver metastasis did not progress. The patient experienced 2 years of a stable disease under the PFP-guided personalized treatment.

Background: Precision medicine aims to optimize therapeutic efficacy and minimize adverse effects by addressing individual biological variability. In radiotherapy, assessing radiation sensitivity is crucial for clinical safety and radiation protection. Recently, patient-derived organoids have emerged as pivotal preclinical models for evaluating personalized radiation responses.Materials and Methods: This study analyzed global patent filings (2005–2025) related to organoid-based radiation sensitivity diagnostics. Patents were systematically classified by country, technology group, and applicant type. After screening and refining 5,097 patents, the final dataset included a total of 1,074 valid patent families. Quantitative analyses were performed to characterize temporal trends, developmental stages, and competitive structures across different regions.Results and Discussion: The global patent landscape has exhibited a robust upward trajectory with a compound annual growth rate of 11.9% from 2005 to 2025. China and South Korea are exhibiting significant recent growth, with the annual filings peaking at 136 in 2023. Technology groups focused on organoid culture/fabrication and radiation sensitivity prediction account for nearly 80% of the total portfolio. A distinct developmental asymmetry was observed: industrial applicants primarily drive culture-related technologies toward commercialization, whereas hospitals and research centers lead sensitivity prediction, reflecting a decisive shift toward clinically oriented, data-driven research.Conclusion: This systematic analysis characterizes the structural and competitive dynamics of organoid-based radiation diagnostics. The findings serve as a strategic baseline for stakeholders to navigate future research trajectories and formulate intellectual property strategies in the field of precision radiation medicine.