Biology subjects

Tsang, V.

Publications and source records attributed to Tsang, V..

2 recordsLinked to original sources

bioRxiv2023

Label-free and non-destructive pathology of human lung adenocarcinomas with ultraviolet single-plane illumination microscopy

Lung cancer is one of the leading causes of cancer death worldwide. The diagnosis of lung cancer based on the analysis of formalin-fixed and paraffin-embedded (FFPE) tissues is laborious and time-consuming, failing to guide surgeons intraoperatively. Here we proposed a rapid histological imaging method, termed microscopy with ultraviolet single-plane illumination (MUSI), to enable rapid ex-or in-vivo imaging of fresh and unprocessed tissues in a label-free and non-destructive manner. The MUSI system allows surgical specimens with large irregular surfaces to be screened at a speed of 0.5 mm2/s with a subcellular resolution, which is sufficient to provide immediate feedback to surgeons and pathologists for intraoperative decision-making. We demonstrate that MUSI can differentiate between different subtypes of human lung adenocarcinomas, revealing diagnostically important features that are comparable to the gold standard FFPE histology. As an assistive imaging platform, MUSI could facilitate the development of precise image-guided surgery and revolutionize the current practice in surgical pathology.

pathology↗

bioRxiv2021

Characterisation of tumour immune microenvironment remodelling following oncogene inhibition in preclinical studies using an optimised imaging mass cytometry workflow

Mouse models are critical in pre-clinical studies of cancer therapy, allowing dissection of mechanisms through chemical and genetic manipulations that are not feasible in the clinical setting. In studies of the tumour microenvironment (TME), multiplexed imaging methods can provide a rich source of information. However, the application of such technologies in mouse tissues is still in its infancy. Here we present a workflow for studying the TME using imaging mass cytometry with a panel of 27 antibodies on frozen mouse tissues. We optimise and validate image segmentation strategies and automate the process in a Nextflow-based pipeline (imcyto) that is scalable and portable, allowing for parallelised segmentation of large multi-image datasets. With these methods we interrogate the remodelling of the TME induced by a KRAS G12C inhibitor in an immune competent mouse orthotopic lung cancer model, highlighting the infiltration and activation of antigen presenting cells and effector cells.

cancer biology↗