ReviewNature reviews. Cancer2023
Bridging live-cell imaging and next-generation cancer treatment.
Review in Nature reviews. Cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed.
- Broadband backscattering confocal microscopy enables label-free 3D live cell nanoscale sensitive imaging.Science advances · 2026Article
- Leveraging Microphysiological Systems to Facilitate Neutrophil-Based Cancer Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Development of a universal imaging "phenome" using shape, appearance and motion (SAM) features and the SAM Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- 3D Bioprinted Breast Cancer-Stroma Model with Tailored Migration-Permissive Bioink Reveals Impact of Adipose-Derived Stromal Cells on Cancer Cell Migration and Invasion Dynamics.Advanced healthcare materials · 2026Article
- xCELLigence™ RTCA system in cancer biology: innovations in real-time functional profiling.Cytotechnology · 2026Review
- Tumor evolution: signaling pathways, molecular mechanisms and therapeutic targets.Signal transduction and targeted therapy · 2026Review
- Celldetective, an AI-enhanced image analysis tool for unraveling dynamic cell interactions.eLife · 2026Article
- Virtual Overlay Staining With Plasmonic Oligomer Metasurface.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamics.Scientific reports · 2026Article
- Engineered CRISPR/Cas12a2 Nanoprobe Imaging in Living Cells for Precise Tumor Diagnosis.Small methods · 2026Article
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Deep Learning-Powered Scalable Cancer Organ Chip for Cancer Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Multidimensional data analysis and classification using SMIAL.Communications biology · 2026Article
- Review
- Tumor-associated macrophages and lineage plasticity in prostate cancer: from established myeloid programs to emerging spatial hypotheses.Frontiers in immunology · 2026Review
- Contrastive learning for cell division detection and tracking in live cell imaging data.BMC bioinformatics · 2025Article
- CellSAM: a foundation model for cell segmentation.Nature methods · 2025Article
- Mapping T cell dynamics to molecular profiles through behavior-guided transcriptomics.Nature protocols · 2025Review
- Article
- Live-cell analyses with unsegmented images to study cancer cell response to modified T cell therapy.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
By providing spatial, molecular and morphological data over time, live-cell imaging can provide a deeper understanding of the cellular and signalling events that determine cancer response to treatment. Understanding this dynamic response has the potential to enhance clinical outcome by identifying biomarkers or actionable targets to improve therapeutic efficacy. Here, we review recent applications of live-cell imaging for uncovering both tumour heterogeneity in treatment response and the mode of action of cancer-targeting drugs. Given the increasing uses of T cell therapies, we discuss the unique opportunity of time-lapse imaging for capturing the interactivity and motility of immunotherapies. Although traditionally limited in the number of molecular features captured, novel developments in multidimensional imaging and multi-omics data integration offer strategies to connect single-cell dynamics to molecular phenotypes. We review the effect of these recent technological advances on our understanding of the cellular dynamics of tumour targeting and discuss their implication for next-generation precision medicine.
Indexed as
Identifiers
37704740What 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.