ArticleNature communications2021
Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 256 papers.
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Who cites it
256 citing papers in PubMed, 380 citations in OpenAlex.
- Safety and Efficacy Assessment of Trastuzumab Emtansine in Indian Patients With Human Epidermal Growth Factor Receptor 2-Positive Unresectable Locally Advanced or Metastatic Breast Cancer Previously Treated With Trastuzumab and a Taxane: An Open-Label, Single-Arm, Phase IV Study.Asia-Pacific journal of clinical oncology · 2026Trial
- Spatially guided translation from histology images to transcriptomic profiles using foundation model-driven contrastive learning.PLoS computational biology · 2026Article
- ST-ConMa: a multimodal foundation framework for spatial transcriptomics via image-gene contrastive and matching learning.Briefings in bioinformatics · 2026Article
- OT-knn: A neighborhood-aware optimal transport framework for aligning spatial transcriptomics data.PLoS computational biology · 2026Article
- ProST: an image prompt-guided multimodal representation learning framework for spatial domain identification.Bioinformatics (Oxford, England) · 2026Article
- HisToSpatialCNV: an interpretable deep learning method predicting spatial copy number variations from histopathology images.Nature biomedical engineering · 2026Article
- DFCE-KanT: predicting spatial gene expression from histology images via contrastive learning.Bioinformatics (Oxford, England) · 2026Article
- PSSD: Progressive Spatial-Semantic Decoupling for flow-based gene expression prediction from histology images.Bioinformatics (Oxford, England) · 2026Article
- Cross-Propagative Graph Learning Reveals Spatial Tissue Domains in Multi-Modal Spatial Transcriptomics.Small methods · 2026Article
- Tumor evolution: signaling pathways, molecular mechanisms and therapeutic targets.Signal transduction and targeted therapy · 2026Review
- Toward simultaneous pseudo-space reconstruction and cell-type deconvolution of single-cell spatial transcriptome using SpaDicer.Cell reports methods · 2026Article
- SPP1-positive macrophages drive trastuzumab resistance in HER2-positive breast cancer.Cell communication and signaling : CCS · 2026Article
- Tumor heterogeneity: development, mechanisms, and therapeutic implications.Signal transduction and targeted therapy · 2026Review
- Investigating Spatial Dynamics in Spatial Omics Data with StarTrail.Journal of the American Statistical Association · 2026Article
- Prognostic RNA-splicing archetypes in breast cancer identified by extended pre-training of histopathology foundation models.Nature communications · 2026Article
- STRESS: spatial transcriptomics resolution enhancing method based on the state-space model.Briefings in bioinformatics · 2026Article
- Review
- Histopathology-centered computational evolution of spatial omics: integration, mapping, and foundation models.Briefings in bioinformatics · 2026Review
- SpaBiT: enhancing spatial transcriptomics resolution via bidirectional attention transformers.Bioinformatics (Oxford, England) · 2026Article
- Stromal Cell Subsets Modulate T-cell Infiltration in Early Breast Cancer.Cancer research communications · 2026Article
196 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon response overlapping with regions of T-cell and macrophage subset colocalization. We construct a predictive model to infer presence of tertiary lymphoid-like structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define a high resolution map of cellular interactions in tumors and provide tools generalizing across tissues and diseases.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.