ArticleNature communications2024
METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Trimodal, uncertainty-guided whole-slide framework for genome-scale spatial expression and image-only virtual perturbation in cancer cohorts.Genome medicine · 2026Article
- SP-printer: reconstruction of tumor stage-specific microenvironments via phenotype-integrated spatial transcriptomics.Journal of translational medicine · 2026Article
- Stromal FAPClinical and translational medicine · 2026Article
- SAGE: Spatially Aware Gene Selection and Dual-View Embedding Fusion for Domain Identification in Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics.bioRxiv : the preprint server for biology · 2026Article
- SpaLSTF: Diffusion-based generative model with BiLSTM and XCA-Transformer for spatial transcriptomics imputation.PLoS computational biology · 2026Article
- A review on in-silico analysis of immune cell trafficking and interactions with the tumour microenvironment.Frontiers in oncology · 2026Review
- Computational pathology annotation enhances the resolution and interpretation of breast cancer spatial transcriptomics data.NPJ precision oncology · 2025Article
- Neutrophil-Inspired Film for Nonadhesive Capture of Tumor Cells through Synergistic Functionalization of Zwitterions and Aptamers.Chem & bio engineering · 2025Article
- Thor: a platform for cell-level investigation of spatial transcriptomics and histology.Nature communications · 2025Article
- Quantitative analysis of cancer cell morphology using digital holography technology under high temperature stimulation.Histochemistry and cell biology · 2025Article
- Conserved spatial subtypes and cellular neighborhoods of cancer-associated fibroblasts revealed by single-cell spatial multi-omics.Cancer cell · 2025Article
- Metabolites and metabolic pathway reactions links to sensitization of immunotherapy in pan-cancer.Molecular therapy. Oncology · 2025Article
- Resolving tissue complexity by multimodal spatial omics modeling with MISO.Nature methods · 2025Article
- Role of CD4Journal of translational medicine · 2025Review
- Integrated single-cell and spatial transcriptomics combined with whole-exome sequencing reveal key hub genes and epithelial heterogeneity in bladder cancer.Frontiers in oncology · 2025Article
- Single-cell genomics and spatial transcriptomics in islet transplantation for diabetes treatment: advancing towards personalized therapies.Frontiers in immunology · 2025Review
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Authors and funding
30 authors.
Funding
Abstract
Recent advances in spatial transcriptomics (ST) techniques provide valuable insights into cellular interactions within the tumor microenvironment (TME). However, most analytical tools lack consideration of histological features and rely on matched single-cell RNA sequencing data, limiting their effectiveness in TME studies. To address this, we introduce the Morphology-Enhanced Spatial Transcriptome Analysis Integrator (METI), an end-to-end framework that maps cancer cells and TME components, stratifies cell types and states, and analyzes cell co-localization. By integrating spatial transcriptomics, cell morphology, and curated gene signatures, METI enhances our understanding of the molecular landscape and cellular interactions within the tissue. We evaluate the performance of METI on ST data generated from various tumor tissues, including gastric, lung, and bladder cancers, as well as premalignant tissues. We also conduct a quantitative comparison of METI with existing clustering and cell deconvolution tools, demonstrating METI's robust and consistent performance.
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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.