Biology subjects

Ma, W. F.

Publications and source records attributed to Ma, W. F..

3 recordsLinked to original sources

bioRxiv2024

BST2 induces vascular smooth muscle cell plasticity and phenotype switching during cancer progression

BackgroundSmooth muscle cell (SMC) plasticity and phenotypic switching play prominent roles in the pathogenesis of multiple diseases, but their role in tumorigenesis is unknown. We investigated whether and how SMC diversity and plasticity plays a role in tumor angiogenesis and the tumor microenvironment. Methods and ResultsWe use SMC-specific lineage-tracing mouse models and single cell RNA sequencing to observe the phenotypic diversity of SMCs participating in tumor vascularization. We find that a significant proportion of SMCs adopt a phenotype traditionally associated with macrophage-like cells. These cells are transcriptionally similar to resolution phase M2b macrophages, which have been described to have a role in inflammation resolution. Computationally predicted by the ligand-receptor algorithm CellChat, signaling from BST2 on the surface of tumor cells to PIRA2 on SMCs promote this phenotypic transition; in vitro SMC assays demonstrate upregulation of macrophage transcriptional programs, and increased proliferation, migration, and phagocytic ability when exposed to BST2. Knockdown of BST2 in the tumor significantly decreases the transition towards a macrophage-like phenotype, and cells that do transition have a comparatively higher inflammatory signal typically associated with anti-tumor effect. ConclusionAs BST2 is known to be a poor prognostic marker in multiple cancers where it is associated with an M2 macrophage-skewed TME, these studies suggest that phenotypically switched SMCs may have a previously unidentified role in this immunosuppressive milieu. Further translational work is needed to understand how this phenotypic switch could influence the response to anti-cancer agents and if targeted inhibition of SMC plasticity would be therapeutically beneficial.

cancer biology↗

bioRxiv2021

Cell-specific chromatin landscape of human coronary artery resolves regulatory mechanisms of disease risk

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed CRE to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.

genomics↗

bioRxiv2020

Single-cell RNA-seq analysis of human coronary arteries using an enhanced workflow reveals SMC transitions and candidate drug targets

Background and AimsThe atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability or other plaque phenotypes are not yet available. We sought to investigate the human atherosclerotic cellular environment using scRNA-seq to uncover potential therapeutic approaches. We aimed to make our workflow user-friendly, reproducible, and applicable to other disease-specific scRNA-seq datasets. MethodsHere we incorporate automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into an enhanced and reproducible scRNA-seq analysis workflow. Notably, we also developed an R Shiny based interactive web application to enable further exploration and analysis of the scRNA dataset. ResultsWe applied this analysis workflow to a human coronary artery scRNA dataset and revealed distinct derivations of chondrocyte-like and fibroblast-like cells from smooth muscle cells (SMCs), and show the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several attractive avenues for future pharmacological repurposing in precision medicine. Further, our interactive web application, PlaqView (www.plaqview.com), allows other researchers to easily explore this dataset and benchmark applicable scRNA-seq analysis tools without prior coding knowledge. ConclusionsThese results suggest novel effects of chemotherapeutics on the atherosclerotic cellular environment and provide future avenues of studies in precision medicine. This publicly available workflow will also allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. PlaqView allows for rapid visualization and analysis of atherosclerosis scRNA-seq datasets without the need of prior coding experience. Future releases of PlaqView will feature additional larger scRNA-seq and scATAC-seq atherosclerosis-related datasets, thus providing a critical resource for the field by promoting data harmonization and biological interpretation.

genomics↗