Black, S. et al. CODEX multiplexed tissue imaging with DNA-conjugated antibodies. Nat. Protoc. 16, 3802–3835 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Gerdes, M. J. et al. Highly multiplexed single-cell analysis of formalinfixed, paraffin-embedded cancer tissue. Proc. Natl. Acad. Sci. USA 110, 11982–11987 (2013).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Moses, L. & Pachter, L. Museum of spatial transcriptomics. Nat. Methods 19, 534–546 (2022).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Schapiro, D. et al. MITI minimum information guidelines for highly multiplexed tissue images. Nat. Methods 19, 262–267 (2022).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Ruddle, N. H. High endothelial venules and lymphatic vessels in tertiary lymphoid organs: characteristics, functions, and regulation. Front Immunol. 7, 491 (2016).Sipos, F. & Muzes, G. Isolated lymphoid follicles in colon: Switch points between inflammation and colorectal cancer? World J. Gastroenterol. 17, 1666–1673 (2011).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Hickey, J. W. et al. Organization of the human intestine at single-cell resolution. Nature. 619, 572–584 (2023).McKinley, E. T. et al. MIRIAM: a machine and deep learning single-cell segmentation and quantification pipeline for multi-dimensional tissue images. Cytom. Part A 101, 521–528 (2022).ArticleÂ
Google ScholarÂ
Greenwald, N. F. et al. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat. Biotechnol. 40, 555 (2022).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Liu, C. C. et al. Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering. Nat. Commun. 14, 4618 (2023).Kim, J. et al. Unsupervised discovery of tissue architecture in multiplexed imaging. Nat. Methods. 19, 1653–1661 (2022).Chen, Z., Soifer, I., Hilton, H., Keren, L. & Jojic, V. Modeling multiplexed images with spatial-lda reveals novel tissue microenvironments. J. Comput. Biol. 27, 1204 (2020).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Cable, D. M. et al. Robust decomposition of cell type mixtures in spatial transcriptomics. Nat. Biotechnol. 40, 517–526 (2021).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Andersson, A. et al. Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography. Commun. Biol. 3, 1–8 (2020).ArticleÂ
Google ScholarÂ
Keren, L. et al. A structured tumor-immune microenvironment in triple negative breast cancer revealed by multiplexed ion beam imaging. Cell 174, 1373–1387.e19 (2018).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Schürch, C. M. et al. Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front. Cell 182, 1341–1359.e19 (2020).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Andersson, A. et al. Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions. Nat. Commun. 12, 1–14 (2021).ArticleÂ
Google ScholarÂ
Jackson, H. W. et al. The single-cell pathology landscape of breast cancer. Nature 578, 615–620 (2020).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Lin, J.-R. et al. Multiplexed 3D atlas of state transitions and immune interactions in colorectal cancer. Cell. 186, 363–381 (2023).Piccinini, F. et al. Advanced cell classifier: user-friendly machine-learning-based software for discovering phenotypes in high-content imaging data. Cell Syst. 4, 651–655.e5 (2017).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Amitay, Y. et al. CellSighter: a neural network to classify cells in highly multiplexed images. Nat. Commun.14, 4302 (2022).Wu, Z. et al. Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens. Nat. Biomed. Eng. 6, 1435–1448 (2022).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Alexandrov, T. & Kobarg, J. H. Efficient spatial segmentation of large imaging mass spectrometry datasets with spatially aware clustering. Bioinformatics 27, i230–i238 (2011).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Zhao, E. et al. Spatial transcriptomics at subspot resolution with BayesSpace. Nat. Biotechnol. 39, 1375–1384 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Townes, F. W. & Engelhardt, B. E. Nonnegative spatial factorization. Nat. Methods. https://doi.org/10.48550/arxiv.2110.06122 (2021).Liu, W. et al. Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST. Nat. Commun. 14, 1–18 (2023).
Google ScholarÂ
Long, Y. et al. Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST. Nat. Commun. 14, 1–19 (2023).ArticleÂ
Google ScholarÂ
Li, Z. & Zhou, X. BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies. Genome Biol. 23, 168 (2022).Greenacre, M. J. (eds) Theory and Applications of Correspondence Analysis (Academic Press, 1984). 10.3/JQUERY-UI.JS.Chen, B. et al. Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps. Cell 184, 6262–6280.e26 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
McKinley, E. T. et al. Optimized multiplex immunofluorescence single-cell analysis reveals tuft cell heterogeneity. JCI Insight 2, e93487 (2017).Herring, C. A. et al. Unsupervised trajectory analysis of single-cell RNA-seq and imaging data reveals alternative tuft cell origins in the gut. Cell Syst. 6, 37–51.e9 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Tytgat, K. M. A. J. et al. Biosynthesis of human colonic mucin: Muc2 is the prominent secretory mucin. Gastroenterology 107, 1352–1363 (1994).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Allen, A., Hutton, D. A. & Pearson, J. P. The MUC2 gene product: a human intestinal mucin. Int. J. Biochem. Cell Biol. 30, 797–801 (1998).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Karlsson, N. G. et al. Molecular characterization of the large heavily glycosylated domain glycopeptide from the rat small intestinal Muc2 mucin. Glycoconj. J. 13, 823–831 (1996).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Vega, P. N. et al. Cancer-associated fibroblasts and squamous epithelial cells constitute a unique microenvironment in a mouse model of inflammation-induced colon cancer. Front Oncol. 12, 878920 (2022).Takeuchi, A. et al. A distinct subset of fibroblastic stromal cells constitutes the cortex-medulla boundary subcompartment of the lymph node. Front Immunol. 9, 414794 (2018).ArticleÂ
Google ScholarÂ
Roozendaal, R. & Carroll, M. C. Complement receptors CD21 and CD35 in humoral immunity. Immunol. Rev. 219, 157–166 (2007).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Rodig, S. J., Shahsafaei, A., Li, B. & Dorfman, D. M. The CD45 isoform B220 identifies select subsets of human B cells and B-cell lymphoproliferative disorders. Hum. Pathol. 36, 51–57 (2005).ArticleÂ
PubMedÂ
Google ScholarÂ
Shiota, T. et al. The clinical significance of CD169-positive lymph node macrophage in patients with breast cancer. PLoS One 11, e0166680 (2016).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Schmidt, D. & von Hochstetter, A. R. The use of CD31 and collagen IV as vascular markers a study of 56 vascular lesions. Pathol. Res. Pract. 191, 410–414 (1995).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Willard-Mack, C. L. Normal structure, function, and histology of lymph nodes. Toxicol. Pathol. 34, 409–424 (2006).ArticleÂ
PubMedÂ
Google ScholarÂ
Neumann, E. K. et al. Highly multiplexed immunofluorescence of the human kidney using co-detection by indexing. Kidney Int. 101, 137–143 (2022).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Jain, S. et al. Advances and prospects for the Human Biomolecular Atlas Program (HuBMAP). Nat. Cell Biol. 25, 1089–1100 (2023).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Consortium, H. The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature 574, 187–192 (2019).ArticleÂ
Google ScholarÂ
Gueutin, V., Deray, G. & Isnard-Bagnis, C. [Renal physiology]. Bull. Cancer 99, 237–249 (2012).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Agarwal, S., Sudhini, Y. R., Polat, O. K., Reiser, J. & Altintas, M. M. Renal cell markers: lighthouses for managing renal diseases. Am. J. Physiol. Ren. Physiol. 321, F715–F739 (2021).ArticleÂ
CASÂ
Google ScholarÂ
Aoki, R. et al. Foxl1-expressing mesenchymal cells constitute the intestinal stem cell niche. Cell Mol. Gastroenterol. Hepatol. 2, 175 (2016).ArticleÂ
PubMedÂ
Google ScholarÂ
Shoshkes-Carmel, M. et al. Subepithelial telocytes are an important source of Wnts that supports intestinal crypts. Nature 557, 242 (2018).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Becker, W. R. et al. Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer. Nat. Genet. 54, 985–995 (2022).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Sakamoto, N. et al. BRAFV600E cooperates with CDX2 inactivation to promote serrated colorectal tumorigenesis. Elife 6, e20331 (2017).Leow, C. C., Romero, M. S., Ross, S., Polakis, P. & Gao, W. Q. Hath1, down-regulated in colon adenocarcinomas, inhibits proliferation and tumorigenesis of colon cancer cells. Cancer Res. 64, 6050–6057 (2004).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Yang, K. et al. Interaction of Muc2 and Apc on Wnt signaling and in intestinal tumorigenesis: potential role of chronic inflammation. Cancer Res. 68, 7313 (2008).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Femia, A. P. et al. Frequent mutation of apc gene in rat colon tumors and mucin-depleted foci, preneoplastic lesions in experimental colon carcinogenesis. Cancer Res. 67, 445–449 (2007).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Pretlow, T. P. & Pretlow, T. G. Mutant KRAS in aberrant crypt foci (ACF): Initiation of colorectal cancer? Biochim Biophys. Acta 1756, 83–96 (2005).CASÂ
PubMedÂ
Google ScholarÂ
Femia, A. P., Dolara, P. & Caderni, G. Mucin-depleted foci (MDF) in the colon of rats treated with azoxymethane (AOM) are useful biomakers for colon carcinogenesis. Carcinogenesis 25, 277–281 (2004).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Blache, P. et al. SOX9 is an intestine crypt transcription factor, is regulated by the Wnt pathway, and represses the CDX2 and MUC2 genes. J. Cell Biol. 166, 37–47 (2004).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Mizoshita, T. et al. Loss of MUC2 expression correlates with progression along the adenoma-carcinoma sequence pathway as well as de novo carcinogenesis in the colon. Histol. Histopathol. 22, 251–260 (2007).CASÂ
PubMedÂ
Google ScholarÂ
Sunkin, S. M. et al. Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system. Nucleic Acids Res. 41, D996 (2013).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Ortiz, C. et al. Molecular atlas of the adult mouse brain. Sci. Adv. 6, eabb3446 (2020).Maynard, K. R. et al. Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex. Nat. Neurosci. 24, 425–436 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Warchol, S. et al. Visinity: visual spatial neighborhood analysis for multiplexed tissue imaging data. IEEE Trans. Vis. Comput. Graph. https://doi.org/10.1109/TVCG.2022.3209378 (2022).Hu, J. et al. SpaGCN: integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network. Nat. Methods 18, 1342–1351 (2021).ArticleÂ
PubMedÂ
Google ScholarÂ
Gao, J., Zhang, F., Hu, K. & Cui, X. Hexagonal convolutional neural network for spatial transcriptomics classification. In Proc. 2022 IEEE International Conference on Bioinformatics and Biomedicine, 200–205 (BIBM, 2022) https://doi.org/10.1109/BIBM55620.2022.9995701.Raykov, Y. P., Boukouvalas, A., Baig, F. & Little, M. A. What to do when K-means clustering fails: a simple yet principled alternative algorithm. PLoS One 11, e0162259 (2016).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Harris, C. R. et al. Quantifying and correcting slide-to-slide variation in multiplexed immunofluorescence images. Bioinformatics 38, 1700–1707 (2022).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Graf, J. et al. FLINO: a new method for immunofluorescence bioimage normalization. Bioinformatics 38, 520–526 (2022).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Kotliar, D. et al. Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq. Elife 8, e43803 (2019).Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Palla, G. et al. Squidpy: a scalable framework for spatial omics analysis. Nat. Methods 19, 171–178 (2022).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Rousseeuw, P. J. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53–65 (1987).ArticleÂ
Google ScholarÂ
Gosline, S. J. C. et al. Proteome mapping of the human pancreatic Islet microenvironment reveals endocrine- exocrine signaling sphere of influence. Mol. Cell. Proteomics 22, 100592 (2023).NHPatterson/wsireg: multimodal whole slide image registration in a graph structure. https://github.com/NHPatterson/wsireg.Halekoh, U., Højsgaard, S. & Yan, J. The R package geepack for generalized estimating equations. J. Stat. Softw. 15, 1–11 (2006).ArticleÂ
Google ScholarÂ
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).ArticleÂ
Google ScholarÂ
Vandekar, S., Tao, R. & Blume, J. A robust effect size index. Psychometrika 85, 232 (2020).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 1–5 (2018).ArticleÂ
Google ScholarÂ
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ