Diósdi, Ákos and Tóth, Tímea and Harmati, Mária and Grexa, István and Schrettner, Bálint and Hapek, Nóra and Kovács, Ferenc and Kriston, András and Buzás, Krisztina and Pampaloni, Francesco and Piccinini, Filippo and Horváth, Péter (2025) HCS-3DX, a next-generation AI-driven automated 3D-oid high-content screening system. NATURE COMMUNICATIONS, 16 (1). No. -8897. ISSN 2041-1723
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Abstract
Self-organised three-dimensional (3D) cell cultures, collectively called 3D-oids, include spheroids, organoids and other co-culture models. Systematic evaluation of these models forms a critical new generation of high-content screening (HCS) systems for patient-specific drug analysis and cancer research. However, the standardisation of working with 3D-oids remains challenging and lacks convincing implementation. This study develops and tests HCS-3DX, a next-generation system for HCS analysis in 3D imaging and image evaluation. HCS-3DX is based on three main components: an automated Artificial Intelligence (AI)-driven micromanipulator for 3D-oid selection, an HCS foil multiwell plate for optimised imaging, and image-based AI software for single-cell data analysis. We validated HCS-3DX directly on 3D tumour models, including tumour-stroma co-cultures. Our data demonstrate that HCS-3DX achieves a resolution that overcomes the limitations of current systems and reliably and effectively performs 3D HCS at the single-cell level. Its application will enhance the accuracy and efficiency of drug screening processes, support personalised medicine approaches, and facilitate more detailed investigations into cellular behaviour within 3D structures.
| Item Type: | Article |
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| Additional Information: | Funding Agency and Grant Number: Lenduelet BIOMAG [2018-342]; HUNRENTECH [TECH-2024-34]; Horizon-BIALYMPH; Horizon-SYMMETRY; Horizon-SWEEPICS; H2020-Fair-CHARM; HAS-NAP3; TKCS [2024/73]; PerMel-AI [EPPERMED2024-590]; HUNTER-Excellence 2024; OTKA-SNN [139455/ARRS]; NKKP [ADVANCED_24_151202]; FIMM High Content Imaging and Analysis Unit; Finnish Cancer Society; MAECI Science and Technology Cooperation Italy-South Korea by the Italian Ministry of Foreign Affairs and International Cooperation [J53C23000300003]; Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences; [TKP2021-EGA09] Funding text: The authors would like to thank Lilla Pinter (HUN-REN BRC, Szeged, Hungary) for her technical support. A.D., T.T., I.G., B.S., N.H., and P.H. acknowledge generous support from the Lenduelet BIOMAG grant (no. 2018-342), TKP2021-EGA09, HUNRENTECH (TECH-2024-34), Horizon-BIALYMPH, Horizon-SYMMETRY, Horizon-SWEEPICS, H2020-Fair-CHARM, HAS-NAP3, TKCS-2024/73; PerMel-AI (EPPERMED2024-590), the HUNTER-Excellence 2024, and grant from OTKA-SNN no. 139455/ARRS and NKKP (ADVANCED_24_151202). P.H. gratefully acknowledge support from the FIMM High Content Imaging and Analysis Unit (FIMM-HCA; HiLIFE-HELMI), and Finnish Cancer Society. F.Pi. acknowledges support from the MAECI Science and Technology Cooperation Italy-South Korea Grant Years 2023-2025 by the Italian Ministry of Foreign Affairs and International Cooperation (CUP project: J53C23000300003); M.H. from the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences. |
| Subjects: | Q Science / természettudomány > QH Natural history / természetrajz > QH301 Biology / biológia Q Science / természettudomány > QH Natural history / természetrajz > QH301 Biology / biológia > QH3015 Molecular biology / molekuláris biológia Q Science / természettudomány > QR Microbiology / mikrobiológia |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 10 Feb 2026 13:29 |
| Last Modified: | 10 Feb 2026 13:29 |
| URI: | https://real.mtak.hu/id/eprint/233659 |
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