ArticleNature communications2025
Learning the cellular origins across cancers using single-cell chromatin landscapes.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Single-cell epigenomics of colorectal cancer.Experimental & molecular medicine · 2026Review
- Bacterioruberin fromInternational journal of molecular sciences · 2026Article
- Cellular hallmarks and aging clock of the human lung parenchyma.Nature communications · 2026Article
- Unmasking biomarkers in small cell lung cancer: implication for precision oncology.Frontiers in oncology · 2026Review
- TMPRSS11B promotes an acidified microenvironment and immune suppression in squamous lung cancer.EMBO reports · 2025Article
- Article
- Single cell profiling of human airway identifies tuft-ionocyte progenitor cells displaying cytokine-dependent differentiation bias in vitro.Nature communications · 2025Article
- Epigenetic control of antigen presentation failure in osteosarcoma: from single-cell chromatin maps to therapeutic strategies.Frontiers in immunology · 2025Review
- Intratumoral heterogeneity and potential treatment strategies in small cell lung cancer.Frontiers in oncology · 2025Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Deciphering the pre-malignant cell of origin (COO) of different cancers is critical for understanding tumor development and improving diagnostic and therapeutic strategies in oncology. Prior work demonstrates that somatic mutations preferentially accumulate in closed chromatin regions of a cancer's COO. Leveraging this information, we combine 3,669 whole genome sequencing patient samples, 559 single-cell chromatin accessibility cellular profiles, and machine learning to predict the COO of 37 cancer subtypes with high robustness and accuracy, confirming both the known anatomical and cellular origins of numerous cancers, often at cell subset resolution. Importantly, our data-driven approach predicts a basal COO for most small cell lung cancers and a neuroendocrine COO for rare atypical cases. Our study also highlights distinct cellular trajectories during cancer development of different histological subtypes and uncovers an intermediate metaplastic state during tumorigenesis for multiple gastrointestinal cancers, which have important implications for cancer prevention, early detection, and treatment stratification.
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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.