Biology subjects

Yeung, C. C.

Publications and source records attributed to Yeung, C. C..

4 recordsLinked to original sources

bioRxiv2025

B cells specific for polyomavirus-derived oncoprotein are predictive of Merkel cell carcinoma progression

Merkel cell carcinomas typically arise from clonal integration of the Merkel cell polyomavirus. Immunogenic viral oncoproteins then lead to tumorigenesis. Oncoprotein-specific T cells are essential for anti-MCC immunity, but it is unclear whether B cells promote tumor control. Here, we analyzed the frequency and phenotype of viral oncoprotein-specific and total B cells in 47 blood samples and 19 unmatched tumors from MCC patients-- of which 8 out 19 progressed. The phenotype of blood B cells did not correlate with MCC patient outcomes. In contrast, all 11 patients with robust oncoprotein-specific antibody-secreting and/or germinal center B cells in tumors experienced long-term MCC control. In vitro, B cells engineered to be specific for viral oncoproteins increased the sensitivity of oncoprotein-specific CD4+ T cells by over 50-fold. Together, our findings suggest that cancer-specific B cells promote anti-tumor immunity via increased T cell responses and that cancer-specific B cell augmentation could be therapeutically relevant. Statement of SignificanceThe link between cancer-specific B cells in anti-tumor immunity and clinical outcomes remains poorly defined. Here, we show that tumor-associated B cells specific for a viral oncoprotein expressed in MCC patient tumors predict disease control with remarkable accuracy, establishing their potential as active participants in tumor immunity.

immunology↗

bioRxiv2025

Graphical and Interactive Spatial Proteomics Image Analysis Workflow

Spatial proteomics provides a spatially resolved view of protein expression and localization within cells and tissues by mapping the location and abundance of proteins. There is a need for fully-integrated end-to-end imaging workflows for spatial proteomic analysis that are flexible, high-throughput, and support graphical and interactive visualizations. We present a modular and interactive spatial proteomic image analysis workflow with individual steps containerized that empowers biomedical researchers to reproducibly execute and customize complex analyses. Our workflow consists of cell segmentation, unsupervised clustering, validation of clusters on the image, and cell type clustering results visualization. Users can utilize a form-based graphical interface to execute and customize multi-step workflows with a single click or interactively adjust image processing steps within the workflow, apply workflows to various datasets, and modify input parameters as needed. We illustrated the functionality of our workflow using a cancer imaging dataset consisting of a tissue microarray (TMA) stained by high-plex immunohistochemistry. This TMA contained a variety of cancer and tissue cell types to assess the broad applicability of this workflow to different biopsy and tissue types.

bioinformatics↗

bioRxiv2022

Single-cell profiling uncovers a Muc4-expressing metaplastic gastric cell type sustained by Helicobacter pylori-specific inflammation

AbstractMechanisms for Helicobacter pylori (Hp)-driven stomach cancer are not fully understood. In a transgenic mouse model of gastric preneoplasia, concomitant Hp infection and induction of constitutively active KRAS (Hp+KRAS+) alters metaplasia phenotypes and elicits greater inflammation than either perturbation alone. Gastric single-cell RNA-seq showed that Hp+KRAS+ mice had a large population of metaplastic pit cells that expressed the intestinal mucin Muc4 and the growth factor amphiregulin. Metaplastic pit cells were associated with macrophage and T cell inflammation and prevented by gastric immunosuppression. Lineage tracing showed that Muc4 was not dependent on cell-intrinsic KRAS activity, and lineage-derived cells had a limited propensity for growth as organoids, demonstrating that metaplastic pit cells are largely not self- renewing. Finally, MUC4 expression was significantly associated with proliferation in human gastric cancer samples. These studies identify an Hp-associated metaplastic pit cell lineage, also found in human gastric cancer tissues, whose expansion is driven by Hp-dependent inflammation. Statement of SignificanceUsing a mouse model, we have delineated metaplastic pit cells as a pre-cancerous cell type whose expansion requires H. pylori-driven inflammation. In humans, metaplastic pit cells show enhanced proliferation as well as enrichment in precancer and early cancer tissues, highlighting an early step in the gastric metaplasia to cancer cascade.

microbiology↗

bioRxiv2021

A graphical, interactive and GPU-enabled workflow to process long-read sequencing data

We present a graphical cloud-enabled workflow for fast, interactive analysis of nanopore sequencing data using GPUs. Users customize parameters, monitor execution and visualize results through an accessible graphical interface. To facilitate reproducible deployment, we use Docker containers and provide an Amazon Machine Image (AMI) with all software and drivers pre-installed for GPU computing on the cloud. We observe a 34x speedup and a 109x reduction in costs for the rate-limiting basecalling step in the analysis of blood cancer cell line data. The graphical interface and greatly simplified deployment facilitate the adoption of GPUs for rapid, cost-effective analysis of long-read sequencing.

bioinformatics↗