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Ching Yeung Lam

University of Toronto

ORCID: 0009-0006-4506-5432

Publishes on Single-cell and spatial transcriptomics, Cell Image Analysis Techniques, Advanced Proteomics Techniques and Applications. 3 papers and 60 citations.

3Publications
60Total Citations

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Top publicationsby citations

Translocation of nucleophosmin from nucleoli to nucleoplasm requires ATP
Cited by 32Open Access

The movement of nucleophosmin from nucleoli to nucleoplasm in HeLa cells induced by cytotoxic drugs and detected by immunofluorescence is inhibited by concomitant treatment with antimycin A in glucose-free medium. Incubation of HeLa cells with antimycin A (300 nM; 30 min) and glucose-free medium resulted in an approximately 90% decrease in cellular ATP pools. To study the biochemical events involved in nucleophosmin translocation, we used an in vitro system consisting of Triton-permeabilized HeLA cells. Incubation of permeabilized cells with ATP (0.5 mM; 1 h) resulted in the translocation of nucleophosmin from nucleoli to nucleoplasm and cytoplasm. Similarly to drug-induced nucleophosmin translocation in whole cultured cells, there is no reduction (measured by e.l.i.s.a.) or degradation of nucleophosmin or change in the ratio of the high-molecular-mass form to the monomeric form (ascertained by Western blotting) during ATP treatment of permeabilized cells. Together, these results indicate a requirement for ATP for redistribution of nucleophosmin from nucleoli to nucleoplasm. Because this permeabilized cell model is simple and efficient and works effectively with exogenous factors, it should provide a powerful tool for investigating the biochemical features of nucleophosmin translocation from nucleoli to nucleoplasm.

Signal amplification by cyclic extension enables high-sensitivity single-cell mass cytometry
Xiao‐Kang Lun, Kuanwei Sheng, Xueyang Yu et al.|Nature Biotechnology|2024
Cited by 28Open Access

Mass cytometry uses metal-isotope-tagged antibodies to label targets of interest, which enables simultaneous measurements of ~50 proteins or protein modifications in millions of single cells, but its sensitivity is limited. Here, we present a signal amplification technology, termed Amplification by Cyclic Extension (ACE), implementing thermal-cycling-based DNA in situ concatenation in combination with 3-cyanovinylcarbazole phosphoramidite-based DNA crosslinking to enable signal amplification simultaneously on >30 protein epitopes. We demonstrate the utility of ACE in low-abundance protein quantification with suspension mass cytometry to characterize molecular reprogramming during the epithelial-to-mesenchymal transition as well as the mesenchymal-to-epithelial transition. We show the capability of ACE to quantify the dynamics of signaling network responses in human T lymphocytes. We further present the application of ACE in imaging mass cytometry-based multiparametric tissue imaging to identify tissue compartments and profile spatial aspects related to pathological states in polycystic kidney tissues.

Automated registration of spatial expression data scales multimodal integration to large cohorts
Caitlin F. Harrigan, Ching Yeung Lam, Danian Chen et al.|bioRxiv (Cold Spring Harbor Laboratory)|2025
Cited by 0Open Access

Recent advances in spatial proteomics enable quantification of the spatial distribution of protein expression across a variety of scales, resolutions, and multiplexing. Registering images from such technologies across modalities is an essential task that enables both the integration of complementary imaging technologies and validation of biological findings. This can be particularly challenging when the modalities capture fundamentally different types of data, such as light intensity, probe counts, or heavy metal counts. However, few datasets and methods address this problem at scale. Here, we introduce the largest dataset to date of cross-modality imaging of both cell line and tissue slides suitable for benchmarking registration methods. We further present Twocan, a Bayesian optimization framework that enables robust automated registration between immunofluorescence imaging and highly multiplex spatial proteomics data. Our method achieves significantly higher registration success rates compared to existing approaches across our comprehensive dataset of 954 image pairs.