Stereo-cell: Advancing spatial single-cell biology towards clinical translation

Abstract

Stereo-cell is a newly developed platform for spatial single-cell sequencing that integrates morphology, transcriptomics, and proteomics in high resolution. By preserving spatial context while enabling multimodal profiling, it bridges the gap between advanced omics and traditional pathology, supporting the detection of rare cells and clinically interpretable diagnoses. This letter highlights the technical innovations of Stereo-cell, its positioning within the spatial omics landscape, and its potential for precision medicine. Important challenges in data integration, regulatory compliance, and digital modelling are discussed as essential steps on the path to clinical implementation.

References

[1] Liao S, Zhou X, Liu C, et al. Stereo-cell: spatial enhanced-resolution single-cell sequencing with high-density DNA nanoball-patterned arrays. Science. 2025; 389(6762): eadr0475.

[2] Wang X, Duan W, Liu X, Fan J. An important step to translate single-cell measurement into clinical practice: stereoscopic cells. Clin Transl Med. 2025; 15(4): e70304.

[3] Ståhl PL, Salmén F, Vickovic S, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016; 353(6294): 78-82.

[4] Stickels RR, Murray E, Kumar P, et al. Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nat Biotechnol. 2021; 39(3): 313-319.

[5] Chen KH, Boettiger AN, Moffitt JR, Wang S, Zhuang X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science. 2015; 348(6233): aaa6090.

[6] Eng CL, Lawson M, Zhu Q, et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH. Nature. 2019; 568(7751): 235-239.

[7] Bressan D, Battistoni G, Hannon GJ. The dawn of spatial omics. Science.2023; 381(6657): eabq4964.

[8] Mund A, Coscia F, Kriston A, et al. Deep visual proteomics defines single-cell identity and heterogeneity. Nat Biotechnol. 2022; 40(8): 1231-1240.

[9] Baumgartner C, Brislinger D. Transforming precision medicine: the potential of the clinical artificial intelligent single-cell framework. Clin Transl Med. 2025; 15(1): e70096.

[10] Germain RN, Meier-Schellersheim M, Nita-Lazar A, Fraser ID. Systems biology in immunology: a computational modeling perspective. Annu Rev Immunol. 2011; 29: 527-585.

[11] Metzcar J, Wang Y, Heiland R, Macklin P. A review of cell-based computational modeling in cancer biology. JCO Clin Cancer Inform. 2019; 3: 1-13.

[12] Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019; 25(1): 44-56.

[13] Regev A, Teichmann SA, Lander ES, et al., Human Cell Atlas Meeting Participants. The Human Cell Atlas. eLife. 2017; 6: e27041.

[14] Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016; 3: 160018.

[15] International Organization for Standardization. ISO/IEC 27001: information security, cybersecurity and privacy protection. Geneva: ISO; 2018. Available from: https://www.iso.org/standard/27001

[16] European Parliament and the Council of the European Union. Regulation (EU) 2017/746 of the European Parliament and of the Council on in vitro diagnostic medical devices (IVDR). Official Journal of the European Union. 2017.

[17] International Medical Device Regulators Forum (IMDRF). Software as a Medical Device (SaMD): Clinical Evaluation (IMDRF/SaMD WG/N41FINAL:2017). 2017. Available from: https://www.imdrf.org/documents/software-medical-device-samd-clinical-evaluation

[18] U.S. Food and Drug Administration (FDA), Health Canada, Medicines and Healthcare products Regulatory Agency (MHRA). Good machine learning practice for medical device development: guiding principles. 2021–2025. Available from: https://www.fda.gov/medical-devices/software-medical-device-samd/good-machine-learning-practice-medical-device-development-guiding-principles

[19] National Medical Products Administration (NMPA). Beijing: NMPA; [cited 2025 Aug 28]. Available from: https://english.nmpa.gov.cn

RIGHTS & PERMISSIONS

2025 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.