ArticleNature communications2023
MetaTiME integrates single-cell gene expression to characterize the meta-components of the tumor immune microenvironment.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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
20 citing papers in PubMed.
- scProtoTransformer: Scalable reference mapping across molecules, cells, and donors.Science advances · 2026Article
- Cancer Heterogeneity and Cancer Cell Plasticity: Molecular Mechanisms and Precision Therapy.MedComm · 2026Review
- Robust integration and annotation of single-cell and spatial omics data using interpretable gene programs.Cell genomics · 2026Article
- Single-cell sequencing-guided design of synergistic chemo-immunotherapy nanodrugs for cGAS-STING activation in prostate cancer therapy.Journal of nanobiotechnology · 2026Article
- Nucleo-mitochondrial asymmetry profiles the proliferative engine and spatial niche reconstruction in clear cell renal cell carcinoma.Frontiers in immunology · 2026Article
- Endothelial plasticity as a continuum in the tumor microenvironment.Vascular biology (Bristol, England) · 2026Article
- Circulating and tumor-infiltrating immune cell profiles in cervical cancer checkpoint blockade: multi-omics biomarkers of response and resistance.Frontiers in immunology · 2026Review
- Article
- scKAN: interpretable single-cell analysis for cell-type-specific gene discovery and drug repurposing via Kolmogorov-Arnold networks.Genome biology · 2025Article
- SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection.Nucleic acids research · 2025Article
- Metallic nanomedicine in cancer immunotherapy.Acta pharmaceutica Sinica. B · 2025Review
- STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition.Genome biology · 2025Article
- Integrated single-cell and bulk transcriptomic analysis identifies a novel macrophage subtype associated with poor prognosis in breast cancer.Cancer cell international · 2025Article
- Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics.Nature communications · 2025Article
- Single-cell RNA sequencing reveals immune microenvironment niche transitions during the invasive and metastatic processes of ground-glass nodules and part-solid nodules in lung adenocarcinoma.Molecular cancer · 2024Article
- Knowledge-based inductive bias and domain adaptation for cell type annotation.Communications biology · 2024Article
- HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics.Nature communications · 2024Article
- JMnorm: a novel joint multi-feature normalization method for integrative and comparative epigenomics.Nucleic acids research · 2024Article
- Revealing the characteristics of SETD2-mutated clear cell renal cell carcinoma through tumor heterogeneity analysis.Frontiers in genetics · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Recent advances in single-cell RNA sequencing have shown heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can indicate common cell types and states in the tumor microenvironment (TME). We develop a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.
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.