Page 35 - TD-3-1

Tumor Discovery AI uncovers tumor spatial organization

semi-supervised methods, generative adversarial neural References
networks, and graph-based deep learning have shown 1. Wang X, Fan J. Spatiotemporal molecular medicine: A new
promise for improving the accuracy and effectiveness of era of clinical and translational medicine. Clin Transl Med.
spatial clustering in organizational analysis. 2021;11(1):e294.
Acknowledgments doi: 10.1002/ctm2.294

We thank BioRender (biorender.com) for providing 2. Wang X. Clinical trans-omics: An integration of clinical
technical support in drawing the figures. phenomes with molecular multiomics. Cell Biol. Toxicol.
2018;34:163-166.
Funding doi: 10.1007/s10565-018-9431-3
This work was supported in part by the National Key R&D 3. Rao A, Barkley D, França GS, et al. Exploring tissue
Programs (NKPs) of China (Grant No. 2022YFC3601800) architecture using spatial transcriptomics. Nature.
[M.Y.]; the Science and Technology Research Program of 2021;596:211-220.
Chongqing Municipal Education Commission (Grant No. doi: 10.1038/s41586-021-03634-9
KJZD-K202300105) [T.L.]; Chongqing medical scientific
research project (Joint project of Chongqing Health 4. Eng CHL, Lawson M, Zhu Q, et al. Transcriptome-scale
super-resolved imaging in tissues by RNA seqFISH+.
Commission and Science and Technology Bureau) (Grant Nature. 2019;568:235-239.
No. 2024QNXM004) [T.L.].
doi: 10.1038/s41586-019-1049-y
Conflict of interest 5. Chen KH, Boettiger AN, Moffitt JR, et al. RNA imaging.

The authors declare that they have no competing interests. Spatially resolved, highly multiplexed RNA profiling in
single cells. Science. 2015;348:aaa6090.
Author contributions doi: 10.1016/B978-0-12-822824-1.00002-X

Conceptualization: Mingzhu Yin 6. Codeluppi S, Borm LE, Zeisel A, et al. Spatial organization
Formal analysis: Jiangnan Liao of the somatosensory cortex revealed by osmFISH. Nat
Investigation: Jinxin Ye, Chunlan Hu Methods. 2018;15:932-935.
Methodology: Teng Liu, Zongbo Zhang doi: 10.1038/s41592-018-0175-z
Writing – original draft: Teng Liu, Zhuomiao Ye
Writing – review & editing: Jinxin Ye, Mingzhu Yin 7. Ghorbani S, Jelinek E, Jain R, et al. Versican promotes T helper
17 cytotoxic inflammation and impedes oligodendrocyte
Ethics approval and consent to participate precursor cell remyelination. Nat Commun. 2022;13:2445.
doi: 10.1038/s41467-022-30032-0
Not applicable.
8. Stickels RR, Murray E, Kumar P, et al. Highly sensitive
Consent for publication spatial transcriptomics at near-cellular resolution with
Slide-seqV2. Nat Biotechnol. 2021;39:313-319.
Not applicable.
doi: 10.1038/s41587-020-0739-1
Availability of data 9. Janesick A, Shelansky R, Gottscho AD, et al. High resolution
The data can be downloaded from the provided links. mapping of the tumor microenvironment using integrated
Human DLPFC: the primary source: https://www.nature. single-cell, spatial and in situ analysis. Nat Commun.
com/articles/s41593-020-00787-0; the pre-processed 2023;14:8353.
source: https://github.com/LieberInstitute/spatialLIBD); doi: 10.1038/s41467-023-43458-x
Human breast cancer: the primary source: https:// 10. Chen A, Liao S, Cheng M, et al. Spatiotemporal
www.10xgenomics.com/resources/datasets/human-breast- transcriptomic atlas of mouse organogenesis using DNA
cancer-block-a-section-1-1-standard-1-1-0; the pre- nanoball-patterned arrays. Cell. 2022;185:1777-1792.e21.
processed source: https://github.com/JinmiaoChenLab/ doi: 10.1016/j.cell.2022.04.003
SEDR_analyses/); and Human breast cancer from 10x
Xenium: the primary source: https://www.10xgenomics. 11. Williams CG, Lee HJ, Asatsuma T, et al. An introduction
com/products/xenium-in-situ/preview-dataset-human- to spatial transcriptomics for biomedical research. Genome
breast; https://squidpy.readthedocs.io/en/stable/notebooks/ Med. 2022;14:68.
tutorials/tutorial_xenium.html doi: 10.1186/s13073-022-01075-1

Volume 3 Issue 1 (2024) 9 https://doi.org/10.36922/td.2049