ArticleNature communications2023
Deep topographic proteomics of a human brain tumour.
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
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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.
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, 21 citations in OpenAlex.
- Multimodal spatial omics: From data acquisition to computational integration.Patterns (New York, N.Y.) · 2026Review
- USP24 is a cross-reactive DUB targeting MOV10 to regulate IFN-I production.Nature communications · 2026Article
- Spatial protein expression patterns across pathologically-associated fibers revealed molecular specialization in inclusion body myositis.Cell communication and signaling : CCS · 2026Article
- The evolving landscape of spatial proteomics technologies in the AI age.Fundamental research · 2026Review
- The pursuit of ultrasensitive phosphoproteomics to unravel signalling in rare cells.Communications biology · 2025Review
- Proteomic Insight Into Alzheimer's Disease Pathogenesis Pathways.Proteomics · 2025Review
- Deciphering transcriptomic changes in chemobrain: a comprehensive review.Acta neuropathologica communications · 2025Review
- A new paradigm of islet adaptations in human pregnancy: insights from immunohistochemistry and proteomics.Nature communications · 2025Article
- The evolution of analytical techniques for multiplex analysis of protein biomarkers.Expert review of proteomics · 2025Review
- In-depth and high-throughput spatial proteomics for whole-tissue slice profiling by deep learning-facilitated sparse sampling strategy.Cell discovery · 2025Article
- Integrative spatially resolved proteomic and metabolomic imaging reveals synovitis endotypes implicated in osteoarthritis progression.Theranostics · 2025Article
- Spatial Proteomics towards cellular Resolution.Expert review of proteomics · 2024Article
- A new understanding of tissue biology from MS-based proteomics at single-cell resolution.Nature methods · 2024Article
- Bridging the Gap From Proteomics Technology to Clinical Application: Highlights From the 68th Benzon Foundation Symposium.Molecular & cellular proteomics : MCP · 2024Article
- Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis.Clinical and translational medicine · 2024Review
- Spatial proteomics: unveiling the multidimensional landscape of protein localization in human diseases.Proteome science · 2024Review
- Proteomic study of left ventricle and cortex in rats after myocardial infarction.Scientific reports · 2024Article
- Deep learning links localized digital pathology phenotypes with transcriptional subtype and patient outcome in glioblastoma.GigaScience · 2024Article
- Deep topographic proteomics of a human brain tumour.Nature communications · 2023Article
- Crosstalk between Immune Checkpoint Modulators, Metabolic Reprogramming and Cellular Plasticity in Triple-Negative Breast Cancer.Current oncology (Toronto, Ont.) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
The spatial organisation of cellular protein expression profiles within tissue determines cellular function and is key to understanding disease pathology. To define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping proteomes within tissue structures. Here, we present a workflow for spatially-resolved, quantitative proteomics of tissue that generates maps of protein abundance across tissue slices derived from a human atypical teratoid-rhabdoid tumour at three spatial resolutions, the highest being 40 µm, to reveal distinct abundance patterns of thousands of proteins. We employ spatially-aware algorithms that do not require prior knowledge of the fine tissue structure to detect proteins and pathways with spatial abundance patterns and correlate proteins in the context of tissue heterogeneity and cellular features such as extracellular matrix or proximity to blood vessels. We identify PYGL, ASPH and CD45 as spatial markers for tumour boundary and reveal immune response-driven, spatially-organised protein networks of the extracellular tumour matrix. Overall, we demonstrate spatially-aware deep proteo-phenotyping of tissue heterogeneity, to re-define understanding tissue biology and pathology at the molecular level.
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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.