{"doi":"10.1002/ctm2.696","title":"Spatial omics: Navigating to the golden era of cancer research","abstract":"<jats:title>Abstract</jats:title><jats:p>The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high‐throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi‐modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.</jats:p>","journal":"Clinical and Translational Medicine","year":2022,"id":632112,"datarank":3.6550252548643742,"base_score":4.90527477843843,"endowment":4.90527477843843,"self_citation_contribution":0.7357912167657645,"citation_network_contribution":2.9192340380986095,"self_endowment_contribution":0.7357912167657645,"citer_contribution":2.9192340380986095,"corpus_percentile":null,"corpus_rank":null,"citation_count":134,"citer_count":128,"citers_with_citation_signal":111,"citers_with_endowment":111,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1638427,"name":"Yifei Cheng","orcid":null,"position":1,"is_corresponding":false},{"id":346923,"name":"Xiangdong Wang","orcid":"0000-0002-8406-7928","position":2,"is_corresponding":false},{"id":298731,"name":"Jia Fan","orcid":"0000-0001-5158-629X","position":3,"is_corresponding":false},{"id":1363339,"name":"Qiang Gao","orcid":"0000-0002-6695-9906","position":4,"is_corresponding":false},{"id":1638426,"name":"Yingcheng Wu","orcid":"0000-0001-9473-546X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Spatial omics: Navigating to the golden era of cancer research","abstract":"<jats:title>Abstract</jats:title><jats:p>The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high‐throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi‐modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.</jats:p>","is_dataset_classified":null,"base_score":4.90527477843843,"endowment":4.90527477843843,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"35040595","pmcid":"PMC8764875","openalex_id":"https://openalex.org/W4205541212","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"81961128025","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"91942313","title":null},{"funder_name":"Program of Shanghai Academic Research Leader","grant_id":"19XD1420700","title":null},{"funder_name":"Sanming Project of Medicine in Shenzhen","grant_id":"SZSM202003009","title":null},{"funder_name":"Shanghai Municipal Key Clinical Specialty","grant_id":"","title":null},{"funder_name":"Shanghai Municipal Key Clinical Specialty","grant_id":"","title":null}],"total_grants":6,"fwci":9.4837,"citation_percentile":0.98999363,"influential_citations":0,"citation_trend":[{"year":2022,"count":19},{"year":2023,"count":28},{"year":2024,"count":39},{"year":2025,"count":35},{"year":2026,"count":13}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.1002/ctm2.696","host_type":"journal"},{"url":"https://doi.org/10.1002/ctm2.696","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/ctm2.696","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ctm2.696","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/35040595","host_type":"repository"},{"url":"https://doaj.org/article/e2d12b94be634fdeb0f88e35a37a687e","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8764875","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC8764875","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC8764875?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Single-cell and spatial transcriptomics","Cancer Genomics and Diagnostics","Bioinformatics and Genomic Networks","Biomedical Research","Neoplasms","Precision Medicine","Spatial Analysis","Tumor Microenvironment"],"mesh_terms":["Neoplasms","Biomedical Research","Precision Medicine","Tumor Microenvironment","Spatial Analysis"],"keywords":["Omics","Spatial analysis","Data science","Genomics","Precision medicine","Surprise","Computer science","Bioinformatics","Biology","Medicine","Geography","Genome","Pathology","Psychology","Tumour Microenvironment","Cancer Ecology","Single-cell Rna-seq","Spatial Omics"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T02:20:11.821626Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}