ReviewTrends in cancer2019
The Spatial and Genomic Hierarchy of Tumor Ecosystems Revealed by Single-Cell Technologies.
Review in Trends in cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning.BMC bioinformatics · 2026Article
- Lactate metabolism-driven lactylation: paradoxical modulation of intestinal inflammation and malignancy.Journal of translational medicine · 2026Review
- MISSTE: a multiscale integrative spatial simulator for understanding the mechanisms underlying tissue ecosystems.bioRxiv : the preprint server for biology · 2026Article
- Crosstalk between ferroptosis and extracellular vesicles in cancer: from interaction to clinical application.Experimental hematology & oncology · 2026Review
- Cellular neighborhoods in cancer.Nature cancer · 2026Article
- Beyond counting: how single-cell long-read sequencing turns transcriptome complexity into precision targets.Frontiers in oncology · 2026Review
- Review
- Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.Science advances · 2025Article
- GASTON-Mix: a unified model of spatial gradients and domains using spatial mixture-of-experts.Bioinformatics (Oxford, England) · 2025Article
- ARL8B regulates lysosomal function and predicts poor prognosis in hepatocellular carcinoma.Scientific reports · 2025Article
- The depth of tumor hierarchy and its impact on hypertumor susceptibility.Scientific reports · 2025Article
- From morphology to single-cell molecules: high-resolution 3D histology in biomedicine.Molecular cancer · 2025Review
- Mapping the topography of spatial gene expression with interpretable deep learning.Nature methods · 2025Article
- Single Cell Spatial Transcriptomics Reveals Immunotherapy-Driven Bone Marrow Niche Remodeling in AML.bioRxiv : the preprint server for biology · 2025Article
- Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A Review.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2025Article
- Myeloid-driven immunosuppression in head and neck cancer: single-cell ATAC/RNA and spatial transcriptomic perspectives.Frontiers in oncology · 2025Review
- Article
- Integrated transcriptomics of human blood vessels defines a spatially controlled niche for early mesenchymal progenitor cells.Developmental cell · 2024Article
- Integrative analysis of pan-cancer single-cell data reveals a tumor ecosystem subtype predicting immunotherapy response.NPJ precision oncology · 2024Article
- Optimizing the design of spatial genomic studies.Nature communications · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Many malignancies display heterogeneous features that support cancer progression. Emerging high-resolution methods provide a view of heterogeneity that recognizes the influence of diverse cell types and cell states of the tumor microenvironment. Here we outline a hierarchical organization of tumor heterogeneity from a genomic perspective, summarize the origins of spatially patterned metabolic features, and review recent developments in single-cell and spatially resolved techniques for genome-wide study of multicellular tissues. We also discuss how integrating these approaches can yield new insights into human cancer and emerging immune therapies. Applying these technologies for the analysis of primary tumors, patient-derived xenografts, and in vitro systems holds great promise for understanding the hierarchical structure and environmental influences that underlie tumor ecosystems.
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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.