{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T09:22:20Z","timestamp":1789118540840,"version":"build-2803163510"},"reference-count":120,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Research Project of Anhui Educational Committee","award":["2023AH051201"],"award-info":[{"award-number":["2023AH051201"]}]},{"name":"Natural Science Research Project of Anhui Educational Committee","award":["2023AH051200"],"award-info":[{"award-number":["2023AH051200"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62502005"],"award-info":[{"award-number":["62502005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62501014"],"award-info":[{"award-number":["62501014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["62502005"],"award-info":[{"award-number":["62502005"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"award":["62501014"],"award-info":[{"award-number":["62501014"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biology"],"abstract":"<jats:p>Background\/Objectives: Tumor heterogeneity is reflected in cell composition, molecular states, spatial distribution, and microenvironment interactions. Spatial transcriptomics can map in situ expression and cell states but cannot fully explain upstream regulation, while spatial epigenomics provides complementary evidence such as chromatin accessibility, histone modifications, and deoxyribonucleic acid (DNA) methylation. This review summarizes the applications of spatial multi-omics and deep learning in prioritizing candidate drug targets in tumors. Methods: We reviewed spatial transcriptomics, spatial epigenomics, and combined sequencing technologies, with a focus on how deep learning supports the analysis and integration of spatial multi-omics data for candidate-target prioritization. Results: Deep learning facilitates the detection of abnormal regions, deciphering of cell origins, integration across samples, inference of cell\u2013cell communication, and combination of imaging with omics data. Spatial multi-omics studies provide therapeutic insights into malignant cells, immunosuppression, stromal and vascular remodeling, and invasion and metastasis niches. Based on these applications, candidate targets can be evaluated in a layered manner according to spatial specificity, cell origin, regulatory consistency, reproducibility across patients, functional dependency, disease relevance, and druggability. Conclusions: Spatial multi-omics and deep learning can enhance the systematic and interpretable selection of candidate targets. However, computational associations cannot replace functional validation. Candidate targets still require verification through gene perturbation, drug sensitivity assays, organoids, animal models, and clinical cohorts to confirm their therapeutic potential.<\/jats:p>","DOI":"10.3390\/biology15181601","type":"journal-article","created":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T08:17:42Z","timestamp":1789114662000},"page":"1601","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning-Assisted Prioritization of Candidate Drug Targets in Tumors Using Spatial Multi-Omics"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1458-9648","authenticated-orcid":false,"given":"Yuxian","family":"Liu","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Anhui University of Science & Technology, Huainan 232001, China"},{"name":"State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, Anhui University of Science & Technology, Huainan 232001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueyan","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Anhui University of Science & Technology, Huainan 232001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Anhui University of Science & Technology, Huainan 232001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guochao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Anhui University of Science & Technology, Huainan 232001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1508-4131","authenticated-orcid":false,"given":"Yanni","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Anhui University of Science & Technology, Huainan 232001, China"},{"name":"State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, Anhui University of Science & Technology, Huainan 232001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4774","DOI":"10.1039\/D2LC00633B","article-title":"Recent advances in high-throughput single-cell transcriptomics and spatial transcriptomics","volume":"22","author":"Shen","year":"2022","journal-title":"Lab Chip"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1186\/s13046-022-02385-3","article-title":"Spatially resolved transcriptomics provide a new method for cancer research","volume":"41","author":"Zheng","year":"2022","journal-title":"J. Exp. Clin. Cancer Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.ccell.2025.12.009","article-title":"Spatial omics at the forefront: Emerging technologies, analytical innovations, and clinical applications","volume":"44","author":"Liu","year":"2026","journal-title":"Cancer Cell"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.trecan.2025.09.002","article-title":"Spatially resolving cancer: From cell states to therapy","volume":"12","author":"Pei","year":"2026","journal-title":"Trends Cancer"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s10555-025-10304-z","article-title":"Spatial omics: Applications and utility in profiling the tumor microenvironment","volume":"44","author":"See","year":"2025","journal-title":"Cancer Metastasis Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"101740","DOI":"10.1016\/j.xcrm.2024.101740","article-title":"The spatial multi-omics revolution in cancer therapy: Precision redefined","volume":"5","author":"Du","year":"2024","journal-title":"Cell Rep. Med."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e70031","DOI":"10.1002\/ctm2.70031","article-title":"Spatially resolved metabolomics: From metabolite mapping to function visualising","volume":"14","author":"Min","year":"2024","journal-title":"Clin. Transl. Med."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1016\/j.jpha.2023.07.003","article-title":"Promise of spatially resolved omics for tumor research","volume":"13","author":"Zhou","year":"2023","journal-title":"J. Pharm. Anal."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1038\/s41698-025-00857-1","article-title":"Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments","volume":"9","author":"Jing","year":"2025","journal-title":"npj Precis. Oncol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1146\/annurev-pathmechdis-111523-023520","article-title":"Roles of Cellular Neighborhoods in Hepatocellular Carcinoma Pathogenesis","volume":"20","author":"Ma","year":"2025","journal-title":"Annu. Rev. Pathol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1038\/s41586-022-05094-1","article-title":"Spatial profiling of chromatin accessibility in mouse and human tissues","volume":"609","author":"Deng","year":"2022","journal-title":"Nature"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2383","DOI":"10.1038\/s41596-025-01145-9","article-title":"Spatially resolved genome-wide joint profiling of epigenome and transcriptome with spatial-ATAC-RNA-seq and spatial-CUT&Tag-RNA-seq","volume":"20","author":"Li","year":"2025","journal-title":"Nat. Protoc."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1038\/s41586-023-05795-1","article-title":"Spatial epigenome-transcriptome co-profiling of mammalian tissues","volume":"616","author":"Zhang","year":"2023","journal-title":"Nature"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1038\/s41586-025-09478-x","article-title":"Spatial joint profiling of DNA methylome and transcriptome in tissues","volume":"646","author":"Lee","year":"2025","journal-title":"Nature"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"103889","DOI":"10.1016\/j.drudis.2024.103889","article-title":"Spatial transcriptomics data and analytical methods: An updated perspective","volume":"29","author":"Danishuddin","year":"2024","journal-title":"Drug Discov. Today"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1016\/j.scib.2026.01.034","article-title":"Mapping biology in space: From spatial transcriptomics platforms to analytical tools and databases","volume":"71","author":"Guo","year":"2026","journal-title":"Sci. Bull."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1146\/annurev-pathmechdis-111523-023417","article-title":"Challenges and Opportunities in the Clinical Translation of High-Resolution Spatial Transcriptomics","volume":"20","author":"Pentimalli","year":"2025","journal-title":"Annu. Rev. Pathol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"giaf128","DOI":"10.1093\/gigascience\/giaf128","article-title":"Emerging AI approaches for cancer spatial omics","volume":"14","author":"Noorbakhsh","year":"2025","journal-title":"GigaScience"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1158\/2159-8290.CD-24-0101","article-title":"Accelerating Drug Development Using Spatial Multi-omics","volume":"14","author":"Goodwin","year":"2024","journal-title":"Cancer Discov."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1568","DOI":"10.1038\/s41592-025-02707-1","article-title":"A visual-omics foundation model to bridge histopathology with spatial transcriptomics","volume":"22","author":"Chen","year":"2025","journal-title":"Nat. Methods"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1186\/s13073-022-01075-1","article-title":"An introduction to spatial transcriptomics for biomedical research","volume":"14","author":"Williams","year":"2022","journal-title":"Genome Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1038\/s41587-022-01448-2","article-title":"The expanding vistas of spatial transcriptomics","volume":"41","author":"Tian","year":"2023","journal-title":"Nat. Biotechnol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s43556-023-00144-0","article-title":"Spatial transcriptomics in development and disease","volume":"4","author":"Zhou","year":"2023","journal-title":"Mol. Biomed."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Chen, T.-Y., You, L., Hardillo, J.A.U., and Chien, M.-P. (2023). Spatial Transcriptomic Technologies. Cells, 12.","DOI":"10.3390\/cells12162042"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3737","DOI":"10.1016\/j.molcel.2024.08.002","article-title":"Spatial omics advances for in situ RNA biology","volume":"84","author":"Ren","year":"2024","journal-title":"Mol. Cell"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"110671","DOI":"10.1016\/j.ygeno.2023.110671","article-title":"Spatial transcriptomics: Technologies, applications and experimental considerations","volume":"115","author":"Wang","year":"2023","journal-title":"Genomics"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1038\/nmeth.2563","article-title":"In situ sequencing for RNA analysis in preserved tissue and cells","volume":"10","author":"Ke","year":"2013","journal-title":"Nat. Methods"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1038\/s41698-023-00488-4","article-title":"Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics","volume":"8","author":"Valdeolivas","year":"2024","journal-title":"npj Precis. Oncol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"R921","DOI":"10.1016\/j.cub.2020.06.081","article-title":"The tumor microenvironment","volume":"30","author":"Anderson","year":"2020","journal-title":"Curr. Biol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1038\/s41592-021-01203-6","article-title":"Spatial omics and multiplexed imaging to explore cancer biology","volume":"18","author":"Lewis","year":"2021","journal-title":"Nat. Methods"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1186\/s12967-023-04150-2","article-title":"Advances in spatial transcriptomics and related data analysis strategies","volume":"21","author":"Du","year":"2023","journal-title":"J. Transl. Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1126\/science.aaf2403","article-title":"Visualization and analysis of gene expression in tissue sections by spatial transcriptomics","volume":"353","author":"Vickovic","year":"2016","journal-title":"Science"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"6278","DOI":"10.1038\/s41467-021-26614-z","article-title":"Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface","volume":"12","author":"Hunter","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1126\/science.aaw1219","article-title":"Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution","volume":"363","author":"Rodriques","year":"2019","journal-title":"Science"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1016\/j.cell.2022.04.003","article-title":"Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays","volume":"185","author":"Chen","year":"2022","journal-title":"Cell"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1016\/j.cell.2020.10.026","article-title":"High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue","volume":"183","author":"Liu","year":"2020","journal-title":"Cell"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"8353","DOI":"10.1038\/s41467-023-43458-x","article-title":"High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis","volume":"14","author":"Janesick","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"aaa6090","DOI":"10.1126\/science.aaa6090","article-title":"RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells","volume":"348","author":"Chen","year":"2015","journal-title":"Science"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1038\/s41586-019-1049-y","article-title":"Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH","volume":"568","author":"Eng","year":"2019","journal-title":"Nature"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1794","DOI":"10.1038\/s41587-022-01483-z","article-title":"High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging","volume":"40","author":"He","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"eaat5691","DOI":"10.1126\/science.aat5691","article-title":"Three-dimensional intact-tissue sequencing of single-cell transcriptional states","volume":"361","author":"Wang","year":"2018","journal-title":"Science"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1360","DOI":"10.1126\/science.1250212","article-title":"Highly multiplexed subcellular RNA sequencing in situ","volume":"343","author":"Lee","year":"2014","journal-title":"Science"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"e22","DOI":"10.1093\/nar\/gkx1206","article-title":"Efficient in situ barcode sequencing using padlock probe-based BaristaSeq","volume":"46","author":"Chen","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1038\/s41392-023-01507-3","article-title":"Harnessing the potential of spatial multiomics: A timely opportunity","volume":"8","author":"Li","year":"2023","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"4448","DOI":"10.1016\/j.cell.2022.09.035","article-title":"Spatially resolved epigenomic profiling of single cells in complex tissues","volume":"185","author":"Lu","year":"2022","journal-title":"Cell"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1038\/s41580-019-0132-4","article-title":"The role of 3D genome organization in development and cell differentiation","volume":"20","author":"Zheng","year":"2019","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3389","DOI":"10.1038\/s41596-024-01013-y","article-title":"Spatially resolved epigenome sequencing via Tn5 transposition and deterministic DNA barcoding in tissue","volume":"19","author":"Farzad","year":"2024","journal-title":"Nat. Protoc."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1126\/science.abg7216","article-title":"Spatial-CUT&Tag: Spatially resolved chromatin modification profiling at the cellular level","volume":"375","author":"Deng","year":"2022","journal-title":"Science"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4253","DOI":"10.1016\/j.cell.2022.10.014","article-title":"Omics goes spatial epigenomics","volume":"185","author":"Schueder","year":"2022","journal-title":"Cell"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2667","DOI":"10.1038\/s41596-021-00518-0","article-title":"Chromatin tracing and multiplexed imaging of nucleome architectures (MINA) and RNAs in single mammalian cells and tissue","volume":"16","author":"Liu","year":"2021","journal-title":"Nat. Protoc."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.tcb.2020.10.006","article-title":"Chromatin Tracing: Imaging 3D Genome and Nucleome","volume":"31","author":"Hu","year":"2021","journal-title":"Trends Cell Biol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.molcel.2019.01.011","article-title":"Microscopy-Based Chromosome Conformation Capture Enables Simultaneous Visualization of Genome Organization and Transcription in Intact Organisms","volume":"74","author":"Cattoni","year":"2019","journal-title":"Mol. Cell"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.ymeth.2012.05.001","article-title":"Hi-C: A comprehensive technique to capture the conformation of genomes","volume":"58","author":"Belton","year":"2012","journal-title":"Methods"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1038\/s41587-021-01139-4","article-title":"Cell2location maps fine-grained cell types in spatial transcriptomics","volume":"40","author":"Kleshchevnikov","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1038\/s41587-022-01273-7","article-title":"Spatially informed cell-type deconvolution for spatial transcriptomics","volume":"40","author":"Ma","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"101479","DOI":"10.1016\/j.cels.2025.101479","article-title":"Interpretable data integration for single-cell and spatial multi-omics","volume":"17","author":"Yang","year":"2026","journal-title":"Cell Syst."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"9403","DOI":"10.1038\/s41467-025-63418-x","article-title":"MultiGATE: Integrative analysis and regulatory inference in spatial multi-omics data via graph representation learning","volume":"16","author":"Miao","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1342","DOI":"10.1038\/s41592-021-01255-8","article-title":"SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network","volume":"18","author":"Hu","year":"2021","journal-title":"Nat. Methods"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"e18949","DOI":"10.1002\/advs.202518949","article-title":"Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases","volume":"13","author":"Li","year":"2026","journal-title":"Adv. Sci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"11674","DOI":"10.1038\/s41467-025-66691-y","article-title":"A deep learning-based multiscale integration of spatial omics with tumor morphology","volume":"16","author":"Schmauch","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1038\/s41467-022-29439-6","article-title":"Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder","volume":"13","author":"Dong","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Liu, W., Zhang, X., Chai, X., Fan, Z., Lin, H., Chen, J., Sun, L., Yu, T., Yeong, J., and Liu, J. (2026). FAST: Scalable Factor Analysis for Spatial Dimension Reduction of Multi-section Spatial Transcriptomics. Genom. Proteom. Bioinform., qzag006.","DOI":"10.1093\/gpbjnl\/qzag006"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1186\/s13073-024-01283-x","article-title":"Unsupervised spatially embedded deep representation of spatial transcriptomics","volume":"16","author":"Xu","year":"2024","journal-title":"Genome Med."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1155","DOI":"10.1038\/s41467-023-36796-3","article-title":"Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST","volume":"14","author":"Long","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Wang, Z., Dai, R., Wang, M., Zhang, Z., Lei, L., Li, Z., Han, K., Wang, Z., and Guo, Q. (2026). SpatioFreq: A Deep Learning Framework for Decoding Cellular and Tissue Landscapes Across Organisms Using Spatial Transcriptomics. Interdiscip. Sci.","DOI":"10.1007\/s12539-025-00811-6"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"8276","DOI":"10.1038\/s41467-023-44017-0","article-title":"GNTD: Reconstructing spatial transcriptomes with graph-guided neural tensor decomposition informed by spatial and functional relations","volume":"14","author":"Song","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"bbaf528","DOI":"10.1093\/bib\/bbaf528","article-title":"Denoising spatially resolved transcriptomics with consistency of heterogeneous spatial coordinates, transcription, and morphology","volume":"26","author":"Wang","year":"2025","journal-title":"Brief. Bioinform."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"giae042","DOI":"10.1093\/gigascience\/giae042","article-title":"spatiAlign: An unsupervised contrastive learning model for data integration of spatially resolved transcriptomics","volume":"13","author":"Zhang","year":"2024","journal-title":"GigaScience"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"btae747","DOI":"10.1093\/bioinformatics\/btae747","article-title":"NLSDeconv: An efficient cell-type deconvolution method for spatial transcriptomics data","volume":"41","author":"Chen","year":"2025","journal-title":"Bioinformatics"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1360","DOI":"10.1038\/s41587-022-01272-8","article-title":"DestVI identifies continuums of cell types in spatial transcriptomics data","volume":"40","author":"Lopez","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"eadp4942","DOI":"10.1126\/sciadv.adp4942","article-title":"SpaTopic: A statistical learning framework for exploring tumor spatial architecture from spatially resolved transcriptomic data","volume":"10","author":"Zhang","year":"2024","journal-title":"Sci. Adv."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1038\/s42003-025-07942-y","article-title":"scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures","volume":"8","author":"Yu","year":"2025","journal-title":"Commun. Biol."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"bbae524","DOI":"10.1093\/bib\/bbae524","article-title":"BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data","volume":"25","author":"Guo","year":"2024","journal-title":"Brief. Bioinform."},{"key":"ref_74","first-page":"101220","article-title":"stSCI: A multi-task learning framework for integrative analysis of single-cell and spatial transcriptomics data","volume":"7","author":"Shu","year":"2026","journal-title":"Innovation"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1038\/s41592-024-02215-8","article-title":"Benchmarking spatial clustering methods with spatially resolved transcriptomics data","volume":"21","author":"Yuan","year":"2024","journal-title":"Nat. Methods"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"bbad359","DOI":"10.1093\/bib\/bbad359","article-title":"Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics","volume":"24","author":"Li","year":"2023","journal-title":"Brief. Bioinform."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"7784","DOI":"10.1038\/s41467-025-62988-0","article-title":"Finding spatially variable ligand-receptor interactions with functional support from downstream genes","volume":"16","author":"Li","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"4645","DOI":"10.1038\/s41467-026-70528-7","article-title":"FineST: Contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis","volume":"17","author":"Li","year":"2026","journal-title":"Nat. Commun."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1038\/s41467-025-56618-y","article-title":"Benchmarking the translational potential of spatial gene expression prediction from histology","volume":"16","author":"Wang","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"bbad464","DOI":"10.1093\/bib\/bbad464","article-title":"THItoGene: A deep learning method for predicting spatial transcriptomics from histological images","volume":"25","author":"Jia","year":"2023","journal-title":"Brief. Bioinform."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"e14351","DOI":"10.1002\/advs.202514351","article-title":"HiST: Histological Images Reconstruct Tumor Spatial Transcriptomics via MultiScale Fusion Deep Learning","volume":"13","author":"Li","year":"2026","journal-title":"Adv. Sci."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"bbaf613","DOI":"10.1093\/bib\/bbaf613","article-title":"SciSt: Single-cell reference-informed spatial gene expression prediction from pathological images","volume":"26","author":"Li","year":"2025","journal-title":"Brief. Bioinform."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"bbac297","DOI":"10.1093\/bib\/bbac297","article-title":"Spatial transcriptomics prediction from histology jointly through Transformer and graph neural networks","volume":"23","author":"Zeng","year":"2022","journal-title":"Brief. Bioinform."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"3749","DOI":"10.1038\/s41591-025-03982-3","article-title":"A multimodal whole-slide foundation model for pathology","volume":"31","author":"Ding","year":"2025","journal-title":"Nat. Med."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"1411","DOI":"10.1016\/S1470-2045(23)00468-0","article-title":"Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab-bevacizumab in patients with hepatocellular carcinoma: A multicentre retrospective study","volume":"24","author":"Zeng","year":"2023","journal-title":"Lancet Oncol."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1986","DOI":"10.1038\/s41467-026-69797-z","article-title":"Tumor cell villages define the co-dependency of tumor and microenvironment in liver cancer","volume":"17","author":"Liu","year":"2026","journal-title":"Nat. Commun."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1038\/s41586-024-08087-4","article-title":"Tumour evolution and microenvironment interactions in 2D and 3D space","volume":"634","author":"Mo","year":"2024","journal-title":"Nature"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"e02979","DOI":"10.1002\/advs.202502979","article-title":"HLA-DR(+) Tumor Cells Show an Association with a Distinct Immune Microenvironment and CD8(+) T-Cell Exhaustion in HBV-Associated Hepatocellular Carcinoma","volume":"12","author":"Chang","year":"2025","journal-title":"Adv. Sci."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1007\/s13402-025-01147-5","article-title":"Multi-omics profiling reveals that Scissor(+) epithelial cells regulate intrahepatic metastasis of HCC via remodeling the metastatic microenvironment","volume":"49","author":"Zhu","year":"2026","journal-title":"Cell. Oncol."},{"key":"ref_90","first-page":"24","article-title":"STC2+ Malignant Cell State Associated with EMT, Tumor Microenvironment Remodeling, and Poor Prognosis Revealed by Single-Cell and Spatial Transcriptomics in Colorectal Cancer","volume":"34","author":"Gui","year":"2025","journal-title":"Oncol. Res."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1038\/s41698-025-01177-0","article-title":"Comprehensive molecular characterization of high-stemness gastric cancer cells using single-cell transcriptomics, spatial mapping, and machine learning","volume":"9","author":"Wang","year":"2025","journal-title":"npj Precis. Oncol."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1038\/s41467-023-36707-6","article-title":"Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas","volume":"14","author":"Ren","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"1557","DOI":"10.1038\/s43018-024-00824-y","article-title":"Spatial single-cell protein landscape reveals vimentin(high) macrophages as immune-suppressive in the microenvironment of hepatocellular carcinoma","volume":"5","author":"Qiu","year":"2024","journal-title":"Nat. Cancer"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"e70608","DOI":"10.1002\/ctm2.70608","article-title":"Integrative cross-tissue and spatially resolved single-cell profiling uncovers tumour-educated inflammatory remodelling of tissue-resident macrophage ecosystem with immunotherapeutic prognostic significance in pan-cancer","volume":"16","author":"Wang","year":"2026","journal-title":"Clin. Transl. Med."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1186\/s13046-024-03042-7","article-title":"Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication","volume":"43","author":"Chen","year":"2024","journal-title":"J. Exp. Clin. Cancer Res."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1007\/s12072-025-11016-w","article-title":"Multi-omics analysis of the lactylation-driven microenvironment and non-invasive clinical translation in hepatocellular carcinoma","volume":"20","author":"Gan","year":"2026","journal-title":"Hepatol. Int."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"101261","DOI":"10.1016\/j.cels.2025.101261","article-title":"Combining spatial transcriptomics and ECM imaging in 3D for mapping cellular interactions in the tumor microenvironment","volume":"16","author":"Pentimalli","year":"2025","journal-title":"Cell Syst."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.7150\/ijbs.108618","article-title":"Integrative Single-Cell and Spatial Transcriptomics Analysis Reveals ECM-remodeling Cancer-associated Fibroblast-Derived POSTN as a Key Mediator in Pancreatic Ductal Adenocarcinoma Progression","volume":"21","author":"Wu","year":"2025","journal-title":"Int. J. Biol. Sci."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1186\/s12967-025-06192-0","article-title":"Integration of single-cell and spatial transcriptomics reveals fibroblast subtypes in hepatocellular carcinoma: Spatial distribution, differentiation trajectories, and therapeutic potential","volume":"23","author":"Liu","year":"2025","journal-title":"J. Transl. Med."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"2806","DOI":"10.1038\/s41467-024-47068-z","article-title":"Deciphering the spatial landscape and plasticity of immunosuppressive fibroblasts in breast cancer","volume":"15","author":"Croizer","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"10637","DOI":"10.1038\/s41467-024-54671-7","article-title":"Spatially resolved gene expression profiling of tumor microenvironment reveals key steps of lung adenocarcinoma development","volume":"15","author":"Takano","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"e0597","DOI":"10.1097\/HC9.0000000000000597","article-title":"Spatial analyses revealed CXCL5 and SLC6A14 as the markers of microvascular invasion in intrahepatic cholangiocarcinoma","volume":"9","author":"Fan","year":"2025","journal-title":"Hepatol. Commun."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"101790","DOI":"10.1016\/j.jhepr.2026.101790","article-title":"Multiomics and multi-region spatial transcriptome analysis reveal cellular networks and pathways associated with HCC recurrence","volume":"8","author":"Seshachalam","year":"2026","journal-title":"JHEP Rep."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"1036","DOI":"10.1016\/j.jhep.2024.12.016","article-title":"Single-cell RNA sequencing-derived signatures define response patterns to atezolizumab + bevacizumab in advanced hepatocellular carcinoma","volume":"82","author":"Cappuyns","year":"2025","journal-title":"J. Hepatol."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1038\/s41416-025-02969-8","article-title":"The epigenetic basis of hepatocellular carcinoma\u2014Mechanisms and potential directions for biomarkers and therapeutics","volume":"132","author":"Lin","year":"2025","journal-title":"Br. J. Cancer"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1038\/s41586-022-05202-1","article-title":"The co-evolution of the genome and epigenome in colorectal cancer","volume":"611","author":"Heide","year":"2022","journal-title":"Nature"},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"e2424070122","DOI":"10.1073\/pnas.2424070122","article-title":"Unified molecular approach for spatial epigenome, transcriptome, and cell lineages","volume":"122","author":"Huang","year":"2025","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"10022","DOI":"10.1038\/s41467-025-66170-4","article-title":"scFFPE-ATAC enables high-throughput single cell chromatin accessibility profiling in formalin-fixed paraffin-embedded samples","volume":"16","author":"Yadav","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"2226","DOI":"10.1038\/s41588-026-02714-8","article-title":"Developmental and MAPK-responsive transcription factors regulate distinct malignant cell states and associated genetic dependencies in pancreatic cancer","volume":"58","author":"Laise","year":"2026","journal-title":"Nat. Genet."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"D1353","DOI":"10.1093\/nar\/gkac1046","article-title":"The next-generation Open Targets Platform: Reimagined, redesigned, rebuilt","volume":"51","author":"Ochoa","year":"2023","journal-title":"Nucleic Acids Res."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1080\/17501911.2024.2430169","article-title":"Cancer epigenetic therapy: Recent advances, challenges, and emerging opportunities","volume":"17","author":"Vatapalli","year":"2025","journal-title":"Epigenomics"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/s40164-023-00405-2","article-title":"EZH2 in hepatocellular carcinoma: Progression, immunity, and potential targeting therapies","volume":"12","author":"Wang","year":"2023","journal-title":"Exp. Hematol. Oncol."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"215899","DOI":"10.1016\/j.canlet.2022.215899","article-title":"DNMT and EZH2 inhibitors synergize to activate therapeutic targets in hepatocellular carcinoma","volume":"548","author":"Zhang","year":"2022","journal-title":"Cancer Lett."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1038\/s41587-022-01603-9","article-title":"Solid-phase capture and profiling of open chromatin by spatial ATAC","volume":"41","author":"Zamboni","year":"2023","journal-title":"Nat. Biotechnol."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1038\/s41586-019-1103-9","article-title":"Prioritization of cancer therapeutic targets using CRISPR\u2013Cas9 screens","volume":"568","author":"Behan","year":"2019","journal-title":"Nature"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1038\/s41592-024-02576-0","article-title":"Multiplexed spatial mapping of chromatin features, transcriptome and proteins in tissues","volume":"22","author":"Guo","year":"2025","journal-title":"Nat. Methods"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1038\/s41698-023-00474-w","article-title":"Spatial profiling of cancer-associated fibroblasts of sporadic early onset colon cancer microenvironment","volume":"7","author":"Furuhashi","year":"2023","journal-title":"npj Precis. Oncol."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1038\/s12276-025-01487-0","article-title":"Perturbomics: CRISPR-Cas screening-based functional genomics approach for drug target discovery","volume":"57","author":"Park","year":"2025","journal-title":"Exp. Mol. Med."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.1016\/j.cell.2022.02.015","article-title":"Spatial CRISPR genomics identifies regulators of the tumor microenvironment","volume":"185","author":"Dhainaut","year":"2022","journal-title":"Cell"},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1126\/science.aao2774","article-title":"Patient-derived organoids model treatment response of metastatic gastrointestinal cancers","volume":"359","author":"Vlachogiannis","year":"2018","journal-title":"Science"}],"container-title":["Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-7737\/15\/18\/1601\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T08:54:53Z","timestamp":1789116893000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-7737\/15\/18\/1601"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,11]]},"references-count":120,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["biology15181601"],"URL":"https:\/\/doi.org\/10.3390\/biology15181601","relation":{},"ISSN":["2079-7737"],"issn-type":[{"value":"2079-7737","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,11]]}}}