Christopher W. Dunsby

This study assesses the reproducibility of a 3D spheroid-based assay across four institutes using dual-view oblique plane microscopy and finds high consistency in treatment effects with low technical noise.

This paper develops a CRISPR-engineered FRET biosensor to study PARP trapping dynamics in ovarian cancer cells and identifies reduced trapping in PARPi-resistant models.

This paper introduces a dual-view oblique plane microscope for high-resolution imaging of thick cleared tissue samples across multiple species.

This study identifies a reversible basal-like cell state in AKT-inhibitor resistant triple negative breast cancer using multimodal profiling and lineage tracing.

This paper introduces a machine learning-based 3D SMLM method called easyZloc that works with standard microscopes and reduces computational demands.

The paper uses single-cell imaging to show that drug-tolerant cells in EGFR-mutant lung cancer rewired ERK signaling through endocytic pathways and adhesion complexes, driven by YAP and PTPRS.

The paper introduces a segmentation pipeline combining neural networks and active meshes to segment and track cells in 3D time-lapse images of organoids and stem cells.

The paper uses geometric deep learning to analyze 3D cell shapes from melanoma cells, identifying morphological signatures and predicting small molecule mechanisms.