Biology subjects

Thompson, E. W.

Publications and source records attributed to Thompson, E. W..

8 recordsLinked to original sources

bioRxiv2025

In vivo imaging of reactive oxygen species after myocardial ischemia-reperfusion injury: a large animal multimodal imaging and transcriptomic study

BackgroundReactive oxygen species (ROS) contribute to myocardial ischemia-reperfusion injury (IRI), but in-vivo data on the spatial myocardial distribution and systemic effects of ROS after IRI remain limited. This multimodal CMR and PET/CT study aimed to non-invasively image ROS activity in a clinically-relevant swine model of IRI using [18F]ROStrace, a fluorine-18-labeled analogue of dihydroethidium (DHE), and to investigate regional changes in ROS activity in the infarcted myocardium during the subacute post-IRI phase. MethodsIRI was induced by percutaneous occlusion of the left anterior descending artery for 90 minutes in swine (N=9). CMR and whole-body PET/CT imaging with [18F]ROStrace were performed before myocardial infarction (MI) and 3-5 days post-MI to assess ROS in non-infarct myocardium, lungs, bone marrow, spleen and skeletal muscle. Late gadolinium enhanced CMR was performed to structurally characterize infarct regions. Post-MI, in vivo [18F]ROStrace signal in infarcted myocardium was compared with remote, non-infarcted myocardium and validated via ex vivo DHE fluorescent imaging. Bulk RNA-sequencing (RNA-seq) and Gene Ontology pathway analysis were conducted on biopsies from infarct and remote myocardial tissue to identify differentially expressed genes and pathways connected to oxidative stress. ResultsDuring the subacute phase following MI, [18F]ROStrace fractional uptake rate (FUR; min-1) was significantly increased in skeletal muscle, compared to baseline (0.011{+/-}0.003 vs 0.016{+/-}0.005, p=0.04), with a trend toward increased FUR in bone marrow (0.046{+/-}0.009 vs 0.056{+/-}0.011, p=0.12) and the left ventricular free wall (0.067{+/-}0.007 vs 0.073{+/-}0.010, p=0.15). Within the myocardium, [18F]ROStrace FUR ((min-1)/(mL/min/g)) was significantly higher in infarcted compared to non-infarcted myocardium regions (0.110{+/-}0.034, vs 0.148{+/-}0.035, p=0.0005). DHE staining confirmed elevated ROS levels in the infarcted myocardium. RNA-seq identified 8,707 differentially expressed genes between infarct and remote myocardium, with downregulated pathways in the infarct associated with mitochondrial function, cellular respiration, and metabolic adaptation. ConclusionThis study demonstrated MI ROS imaging using [18F]ROStrace using a whole-body PET/CT scanner and structural assessment with CMR. Systemic and myocardial increases in ROS activity were observed post-MI, accompanied by substantial molecular alterations in infarcted tissue. These findings show potential imaging strategies to evaluate therapeutic targets that can mitigate oxidative stress after MI.

bioengineering↗

bioRxiv2024

An aortic hemodynamic fingerprint reduced order modeling analysis reveals traits associated with vascular disease in a medical biobank

PurposeTo determine the clinical relevance of reduced order model (ROM) aortic hemodynamic imaging-derived phenotypes (IDPs) for a range of flow conditions applied to computed tomography (CT) scan data in the Penn Medicine Biobank (PMBB). MethodsThe human thoracic aorta was automatically segmented in 3,204 chest CT scans from patients in the Penn Medicine Biobank (PMBB) patients using deep learning. Thoracic aorta anatomic IDPs such as aortic diameter and length were computed. Resistance, and flow boundary conditions, were varied, resulting in 125,000 ROM simulations, producing a fingerprint of aortic hemodynamics IDPs for a range of flow conditions. To determine the clinical relevance of the aortic hemodynamic fingerprint, untargeted phenome wide association studies (PheWAS) for disease conditions were performed using aortic geometries and pulse pressure as IDPs. ResultsBy utilizing patient metadata from the PMBB, the human aortic radius for different age groups over a normalized radius was visualized, showing how the vessel deforms with age, as well as other characteristic geometric information. The average radius of the ascending thoracic aortic data set was 26.6 {+/-} 3.1 mm, with an average length of 310 {+/-} 37 mm. A combination of pathology codes (phecodes) and hemodynamic simulations were utilized to develop a relationship between them, showing a strong relationship between the resulting pulse pressure and diseases relating to aortic aneurysms and heart valve disorders. The average pulse pressure calculated by the model was 22.5 {+/-} 8.5 mmHg, with the maximum pressure modeled by the system being 201 mmHg, with the minimum being 63.6 mmHg. The pulse pressures of the most significant phecodes were examined for patients with and without the condition, showing a slight separation between the two cases. The pulse pressure was also slightly negatively correlated with the calculated tapering angle of the ascending thoracic aorta. ConclusionsROM hemodynamic simulations can be applied to aortic imaging traits from thoracic imaging data in a medical biobank. The derived hemodynamic fingerprint, describing the response of the aorta to a range of flow conditions, shows clinically relevant associations with disease.

bioengineering↗

bioRxiv2023

Cell-state transitions and frequency-dependent interactions among subpopulations together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity in breast cancer

Individual cells in a tumour can be distributed among Epithelial (E) and Mesenchymal (M) cell-states, as characterised by the levels of canonical E and M markers. Even after E and M (E-M) subpopulations are isolated and then cultured independently, E-M heterogeneity can re-equilibrate in each population over time, sometimes regaining the initial distribution of the parental cell population. However, it remains unclear which population-level processes give rise to the dynamical changes in E-M heterogeneity observed experimentally, including 1) differential growth, 2) cell-state switching, and 3) frequency-dependent growth or state-transition rates. Here, we analyse the necessity of these three processes in explaining the dynamics of E-M population distributions as observed in PMC42-LA and HCC38 breast cancer cells. We find that growth differences among E and M subpopulations, with and without any frequency-dependent interactions (cooperation or suppression) among E-M sub-populations, are insufficient to explain the observed population dynamics. This insufficiency is ameliorated by including cell-state transitions, albeit at slow rates, in explaining both PMC42-LA and HCC38 cells data. Further, our models predict that treatment of HCC38 cells with TGF{beta} signalling and JAK2/3 inhibitors could significantly enhance the transition rates from M state to E state, but does not prevent transitions from E to M. Finally, we devise a selection criterion to identify the next most informative time points for which future experimental data can optimally improve the identifiability of our estimated best fit model parameters. Overall, our study identifies the necessary population-level processes shaping the dynamics of E-M heterogeneity in breast cancer cells.

systems biology↗

bioRxiv2023

Metastable Intermediates Identified in Epithelial to Mesenchymal Transition are Regulated by G-Quadruplex DNA Structures

Cancer is a heterogenous disease, with multiple cellular subpopulations present within a single tumour mass that differ genetically and morphologically, and thus respond differently to chemotherapeutics. Epithelial-to-Mesenchymal transition (EMT) has been shown to play a role in tumour heterogeneity. Single-cell sequencing is critical to identify cell-type-specific transcriptomic differences with multiplexing methods increasing experimental scope with reduced cost. Cell hashing with barcoded antibodies is commonly used to multiplex samples but is limited to samples expressing target antigens. Antigen-independent methods of barcoding cells, such as barcoded lipid-anchors, have gained traction but present substantial populations that cannot be unambiguously demultiplexed. Herein we report a multiplexed single-cell transfection-enabled cell hashing sequencing (scTECH-seq) platform, which uses antigen-independent endocytic uptake to barcode cells, resulting in efficient, uniform barcoding with high cell recovery. We apply this methodology to identify distinct metastable cell states in human mammary cells undergoing EMT and show that stabilisation of G-quadruplex DNA has the potential to inhibit EMT.

genomics↗

bioRxiv2022

Population dynamics of epithelial-mesenchymal heterogeneity in cancer cells

Phenotypic heterogeneity is a hallmark of aggressive cancer behaviour and a clinical challenge. Despite much characterisation of this heterogeneity at a multi-omics level in many cancers, we have a limited understanding of how this heterogeneity emerges spontaneously in an isogenic cell population. Some longitudinal observations of dynamics in epithelial-mesenchymal heterogeneity, a canonical example of phenotypic heterogeneity, have offered us opportunities to quantify the rates of phenotypic switching that may drive such heterogeneity. Here, we offer a mathematical modeling framework that explains the salient features of population dynamics noted in PMC42-LA cells: a) predominance of EpCAMhigh subpopulation, b) re-establishment of parental distributions from the EpCAMhigh and EpCAMlow subpopulations, and c) enhanced heterogeneity in clonal populations established from individual cells. Our framework proposes that fluctuations or noise in content duplication and partitioning of SNAIL - an EMT-inducing transcription factor - during cell division can explain spontaneous phenotypic switching and consequent dynamic heterogeneity in PMC42-LA cells observed experimentally at both single-cell and bulk level analysis. Together, we propose that asymmetric cell division can be a potential mechanism for phenotypic heterogeneity.

systems biology↗

bioRxiv2020

The role of mechanical interactions in EMT

The detachment of cells from the boundary of an epithelial tissue and the subsequent invasion of these cells into surrounding tissues is important for cancer development and wound healing, and is strongly associated with the epithelial-mesenchymal transition (EMT). Chemical signals, such as TGF-{beta}, produced by surrounding tissue can be up-taken by cells and induce EMT. In this work, we present a novel cell-based discrete mathematical model of mechanical cellular relaxation, cell proliferation, and cell detachment driven by chemically-dependent EMT in an epithelial tissue. A continuum description of the model is then derived in the form of a novel nonlinear free boundary problem. Using the discrete and continuum models we explore how the coupling of chemical transport and mechanical interactions influences EMT, and postulate how this could be used to help control EMT in pathological situations.

biophysics↗

bioRxiv2020

Heparanase promotes Syndecan-1 expression to mediate fibrillar collagen and mammographic density in human breast tissue cultured ex vivo.

Mammographic density (MD) is a strong and independent factor for breast cancer (BC) risk and is increasingly associated with BC progression. We have previously shown in mice that high MD, which is characterised by the preponderance of a fibrous stroma, facilitates BC xenograft growth and metastasis. This stroma is rich in extracellular matrix (ECM) factors, including heparan sulfate proteoglycans (HSPGs), such as the BC-associated syndecan-1 (SDC1). These proteoglycans tether growth factors, which are released by heparanase (HPSE). MD is positively associated with estrogen exposure and, in cell models, estrogen has been implicated in the upregulation of HPSE, the activity of which promotes SDC expression. Herein we describe a novel measurement approach (single-sided NMR) using a patient-derived explant (PDE) model of normal human (female) mammary tissue cultured ex vivo to investigate the role(s) of HPSE and SDC1 on MD. Relative HSPG gene and protein analyses determined in patient-paired high versus low MD tissues identified SDC1 and SDC4 as potential mediators of MD. Using the PDE model we demonstrate that HPSE promotes SDC1 rather than SDC4 expression and cleavage, leading to increased MD. In this model system, synstatin (SSTN), an SDC1 inhibitory peptide designed to decouple SDC1-ITGv{beta}3 parallel collagen alignment, reduced the abundance of fibrillar collagen as assessed by picrosirius red viewed under polarised light, and reduced MD. Our results reveal a potential role for HPSE in maintaining MD via its direct regulation of SDC1, which in turn physically tethers collagen into aligned fibres characteristic of MD. We propose that inhibitors of HPSE and/or SDC1 may afford an opportunity to reduce MD in high BC risk individuals and reduce MD-associated BC progression in conjunction with established BC therapies.

cancer biology↗

bioRxiv2017

DNA methylation profiling of breast cancer cell lines along the epithelial mesenchymal spectrum - implications for the choice of circulating tumour DNA methylation markers

Epithelial-mesenchymal plasticity (EMP) is a dynamic process whereby epithelial carcinoma cells reversibly acquire morphological and invasive characteristics typical of mesenchymal cells, which facilitates metastasis. Understanding the methylation differences between epithelial and mesenchymal states may assist in the identification of optimal DNA methylation biomarkers for the blood-based monitoring of cancer. Methylation-sensitive high-resolution melting (MS-HRM) was used to examine the promoter methylation status of a panel of established and novel markers in a range of breast cancer cell lines spanning the epithelial-mesenchymal spectrum. Pyrosequencing was used to validate the MSHRM results. The results indicate an overall distinction in methylation between epithelial and mesenchymal phenotypes. The mesenchymal expression markers VIM, DKK3 and CRABP1 were methylated in the majority of epithelial breast cancer cell lines while methylation of the epithelial expression markers GRHL2, MIR200C and CDH1 was restricted to mesenchymal cell lines. We also examined EMP association of several methylation markers that have been used to assess minimal residual disease. Markers such as AKR1B1 and APC methylation proved to be selective for epithelial breast cell lines, however RASSF1A, RAR{beta}, TWIST1 and SFRP2 methylation was seen in both epithelial and mesenchymal cell lines, supporting their suitability for a multi-marker panel.

cancer biology↗