ArticleScience advances2024
SpaTopic: A statistical learning framework for exploring tumor spatial architecture from spatially resolved transcriptomic data.
Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Deep Learning-Assisted Prioritization of Candidate Drug Targets in Tumors Using Spatial Multi-Omics.Biology · 2026Review
- Tertiary lymphoid structures in cancer: their development, composition, clinical prognosis, and the drivers of the anti-tumor responses.Molecular biomedicine · 2026Review
- Spatial multi omic profiling maps hypoxia-driven pro-fibrotic SPP1Experimental hematology & oncology · 2026Article
- Scalable multi-group nonnegative spatial factorization for spatial genomics data with cell-type heterogeneity.bioRxiv : the preprint server for biology · 2026Article
- Unveiling gene modules at Atlas scale through hierarchical clustering of single-cell data.Nature communications · 2026Article
- scSurvival: Single-Cell Survival Analysis of Clinical Cancer Cohort Data at Cellular Resolution.Cancer discovery · 2026Article
- AKAP12-LMOD1 signaling defines stromal CAF activation and epithelial junction loss in colorectal cancer.Scientific reports · 2026Article
- Robust integration and annotation of single-cell and spatial omics data using interpretable gene programs.Cell genomics · 2026Article
- Luteolin Disrupts Keratinocyte-Dendritic Cell Communication in Psoriasis by Targeting Rh Family C Glycoprotein.Mediators of inflammation · 2026Article
- Unraveling tumor cell heterogeneity and epithelial-mesenchymal plasticity in gastric adenocarcinoma: an integrative multi-omics framework evaluating PVR/CD155 as a tumor cell-intrinsic EMT-associated target.Frontiers in immunology · 2026Article
- Comprehensive analysis based on spatial domains identifies CD44 as a potential target of puerarin.Journal of cancer research and clinical oncology · 2025Article
- The landscape of dynamic tumor immunophenotyping on neoadjuvant chemotherapy combined with trastuzumab for the treatment of HER2-positive breast cancer.Molecular cancer · 2025Article
- Tertiary lymphoid structures in cancer: spatiotemporal heterogeneity, immune orchestration, and translational opportunities.Journal of hematology & oncology · 2025Review
- Spatial Transcriptomics Reveals Distinct Architectures but Shared Vulnerabilities in Primary and Metastatic Liver Tumors.Cancers · 2025Article
- Spatial transcriptomics: a bibliometric analysis with large language model on English literatures.Briefings in bioinformatics · 2025Article
- Article
- Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments.NPJ precision oncology · 2025Review
- Single-cell genomics and spatial transcriptomics in islet transplantation for diabetes treatment: advancing towards personalized therapies.Frontiers in immunology · 2025Review
- Deciphering spatially confined immune evasion niches in osteosarcoma with 3-D spatial transcriptomics: a literature review.Frontiers in oncology · 2025Review
- SpaTopic: A statistical learning framework for exploring tumor spatial architecture from spatially resolved transcriptomic data.Science advances · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
Tumor tissues exhibit a complex spatial architecture within the tumor microenvironment (TME). Spatially resolved transcriptomics (SRT) is promising for unveiling the spatial structures of the TME at both cellular and molecular levels, but identifying pathology-relevant spatial domains remains challenging. Here, we introduce SpaTopic, a statistical learning framework that harmonizes spot clustering and cell-type deconvolution by integrating single-cell transcriptomics and SRT data. Through topic modeling, SpaTopic stratifies the TME into spatial domains with coherent cellular organization, facilitating refined annotation of the spatial architecture with improved performance. We assess SpaTopic across various tumor types and show accurate prediction of tertiary lymphoid structures and tumor boundaries. Moreover, marker genes derived from SpaTopic are transferrable and can be applied to mark spatial domains in other datasets. In addition, SpaTopic enables quantitative comparison and functional characterization of spatial domains across SRT datasets. Overall, SpaTopic presents an innovative analytical framework for exploring, comparing, and interpreting tumor SRT data.
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