ArticleNature communications2022
Traject3d allows label-free identification of distinct co-occurring phenotypes within 3D culture by live imaging.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Beyond the Monolayer: Leveraging 3D Culture Systems to Decode Mechanisms of Drug Resistance and Therapeutic Vulnerabilities in Colorectal Cancer.Cancer medicine · 2026Review
- Identifying phenotype-genotype-function coupling in 3D organoid imaging using Shape, Appearance and Motion Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- 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
- Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamics.Scientific reports · 2026Article
- A statistically rigorous multi-scale texture analysis framework for 3D spheroid characterization: temporal autocorrelation correction and molecular validation.Scientific reports · 2026Article
- Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers.The EMBO journal · 2026Article
- Methods to analyze cell migration data: fundamentals and practical guidelines.Nature methods · 2026Review
- BEHAV3D Tumor Profiler to map heterogeneous cancer cell behavior in the tumor microenvironment.eLife · 2025Article
- Live-cell analyses with unsegmented images to study cancer cell response to modified T cell therapy.bioRxiv : the preprint server for biology · 2025Article
- CellRomeR: an R package for clustering cell migration phenotypes from microscopy data.Bioinformatics advances · 2025Article
- cellPLATO - an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data.Journal of cell science · 2024Article
- CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data.PLoS biology · 2024Article
- BEHAV3D: a 3D live imaging platform for comprehensive analysis of engineered T cell behavior and tumor response.Nature protocols · 2024Article
- Live-cell imaging in the deep learning era.Current opinion in cell biology · 2023Review
- Omentum-derived matrix enables the study of metastatic ovarian cancer and stromal cell functions in a physiologically relevant environment.Matrix biology plus · 2023Article
- cellPLATO: an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data.bioRxiv : the preprint server for biology · 2023Article
- Bridging live-cell imaging and next-generation cancer treatment.Nature reviews. Cancer · 2023Review
- PTEN deficiency exposes a requirement for an ARF GTPase module for integrin-dependent invasion in ovarian cancer.The EMBO journal · 2023Article
- Traject3d for studying 3D cellular heterogeneity.Nature reviews. Cancer · 2023Article
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Authors and funding
17 authors.
Funding
Abstract
Single cell profiling by genetic, proteomic and imaging methods has expanded the ability to identify programmes regulating distinct cell states. The 3-dimensional (3D) culture of cells or tissue fragments provides a system to study how such states contribute to multicellular morphogenesis. Whether cells plated into 3D cultures give rise to a singular phenotype or whether multiple biologically distinct phenotypes arise in parallel is largely unknown due to a lack of tools to detect such heterogeneity. Here we develop Traject3d (Trajectory identification in 3D), a method for identifying heterogeneous states in 3D culture and how these give rise to distinct phenotypes over time, from label-free multi-day time-lapse imaging. We use this to characterise the temporal landscape of morphological states of cancer cell lines, varying in metastatic potential and drug resistance, and use this information to identify drug combinations that inhibit such heterogeneity. Traject3d is therefore an important companion to other single-cell technologies by facilitating real-time identification via live imaging of how distinct states can lead to alternate phenotypes that occur in parallel in 3D culture.
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