ReviewNature reviews. Cancer2024
Multiplex protein imaging in tumour biology.
Review in Nature reviews. Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 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
54 citing papers in PubMed.
- Understanding and targeting the tumour matrisome.Nature reviews. Clinical oncology · 2026Review
- Emerging technologies in the spatial proteomics landscape.Analytical and bioanalytical chemistry · 2026Review
- Spatially-resolved single-cell imaging of melanoma brain metastases identifies localized immune patterns predictive of immune checkpoint blockade response.Neuro-oncology · 2026Article
- PASTA: versatile tyramide-oligonucleotide amplification for multimodal spatial biology.Nature methods · 2026Article
- Article
- Translational insights and clinical challenges of targeting cancer stem cells.Signal transduction and targeted therapy · 2026Review
- ISPAT-3D: Spatially Varying Conditional Volumetric Network Estimation for 3D Tumor Imaging.Research square · 2026Article
- NOS2 and COX2 impact the spatial landscape of CD8Redox biology · 2026Review
- Regulatory B-cell states in NSCLC immunotherapy resistance: mechanisms, spatial context and translational implications.Cancer immunology, immunotherapy : CII · 2026Review
- A Roadmap to Transform Lung Cancer Outcomes: Priorities in Biology, Therapeutic Innovation, Early Detection, Prevention, and Interception.Cancer discovery · 2026Review
- Review
- ISPAT-3D: Spatially Varying Conditional Volumetric Network Estimation for 3D Tumor Imaging.bioRxiv : the preprint server for biology · 2026Article
- Protocol for iterative indirect immunofluorescence imaging of frozen mouse intestinal tissues.STAR protocols · 2026Article
- miniMTI: minimal multiplex tissue imaging enhances biomarker expression prediction from histology.Research square · 2026Article
- TiRank prioritizes phenotypic niches in tumor microenvironment for clinical biomarker discovery.Genome medicine · 2026Article
- Spatial architecture of development and disease.Nature reviews. Genetics · 2026Review
- High-dimensional imaging using combinatorial channel multiplexing and deep learning.Nature biotechnology · 2026Article
- Spatial omics and its applications for a tumour microenvironment characterization and precision medicine approach of gastric cancer.Ecancermedicalscience · 2026Review
- Turning cold tumors into hot tumors to ignite immunotherapy.Molecular cancer · 2025Review
- Elemental mass spectrometry imaging of biomolecules using metal-conjugated probes.Nature reviews. Chemistry · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.
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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.