ReviewCell2020
The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.
Review in Cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 358 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
358 citing papers in PubMed, 1 synthesis or guideline pooled it, 574 citations in OpenAlex.
- Applications and challenges of biomarker-based predictive models in proactive health management.Frontiers in public health · 2025Pooled it
- Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Decoding epithelial-mesenchymal transitions with multi-omics.Nature reviews. Genetics · 2026Review
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- Spatial Integration of Protein and Chromosomal States Reveals Early Copy-Number Changes and Genotype-Associated Immune Neighborhoods in Serous Ovarian Cancer Evolution.Cancer discovery · 2026Article
- Data-centric feedback loops for next-generation immunotherapy development.Nature biomedical engineering · 2026Review
- HuBMAP Data Portal: a resource for multimodal spatial and single-cell data of healthy human tissues.ArXiv · 2026Article
- Development of a universal imaging "phenome" using shape, appearance and motion (SAM) features and the SAM Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- Spatial omics illuminates tumor heterogeneity.Cell reports methods · 2026Review
- SpatioTemporal Omics Consortium: a global effort for biological discovery across species, space and time.Nature methods · 2026Article
- NicheTrans: spatial-aware cross-omics translation.Nature methods · 2026Article
- Spatium: A Protein Language Foundation Model for Spatial Proteomics.bioRxiv : the preprint server for biology · 2026Article
- FERRET: Framework to Evaluate Robustness in Regulatory Networks Using Heterogeneous Cell Types.bioRxiv : the preprint server for biology · 2026Article
- Mechanisms and therapeutic targets in distant metastasis of lung adenocarcinoma.Signal transduction and targeted therapy · 2026Article
- Trimodal, uncertainty-guided whole-slide framework for genome-scale spatial expression and image-only virtual perturbation in cancer cohorts.Genome medicine · 2026Article
- Multimodal spatial omics: From data acquisition to computational integration.Patterns (New York, N.Y.) · 2026Review
- The Single-Cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors.Cell genomics · 2026Article
- Dissecting human organ development using spatial technologies.Developmental cell · 2026Review
- Foundation models in omics research: a comprehensive survey.Briefings in bioinformatics · 2026Review
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
298 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
38 authors at 20 institutions in 1 country.
Funding
Abstract
Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.