Search bioRxiv⌕ Search

Biology subjects

Dean, J. A.

Publications and source records attributed to Dean, J. A..

3 recordsLinked to original sources

Functional consequences of a p53-MDM2-p21 incoherent feedforward loop

Genetically identical tumor cells can respond heterogeneously to therapy, with a subpopulation of cells often entering a temporarily arrested treatment-tolerant state before repopulating the tumor. To investigate how heterogeneity in the cell cycle arrest protein p21 arises, we imaged the dynamics of p21 transcription and protein expression along with those of p53, its transcriptional regulator, in single MCF-7 cells using live cell fluorescence microscopy. Using this approach, we found that the rate of p21 transcription depends on the change in p53 rather than its absolute level. Through combined theoretical and experimental modeling, we determined that p21 transcription is governed by an incoherent feedforward loop mediated by MDM2. This network architecture facilitates rapid induction of p21 expression and variability in p21 transcription. Abrogating the feedforward loop overcomes rapid S-phase p21 degradation, with cells transitioning into a quiescent state that transcriptionally resembles a treatment-tolerant persister state. The potential implications of our findings warrant consideration in the design of therapeutic strategies based on activating p53.

systems biology↗

Live-imaging reveals Coordinated Cell Migration and Cardiac Fate Determination during Mammalian Gastrulation.

Heart development involves the specification of cardiac progenitors at distinct stages and locations. Using live-imaging of mouse embryos between gastrulation and heart tube formation, we tracked individual mesodermal cells and reconstructed their lineage trees for up to five cell divisions. We found independent unipotent progenitors emerging at specific times, contributing exclusively to either left ventricle/atrioventricular canal (LV/AVC) or atrial myocytes. LV/AVC progenitors differentiated early to form the cardiac crescent, while atrial progenitors later generated the heart tubes inflow tract during morphogenesis. We also identified short-lived bipotent progenitors with broad potential, illustrating early developmental plasticity. Sister cells from bipotent progenitors displayed greater dispersion and more diverse migratory trajectories within the anterior mesoderm than those from unipotent progenitors. Bipotent progenitors contributing to extraembryonic mesoderm (ExEm) exhibited the fastest and most dispersed migrations, whereas those giving rise to endocardial, LV/AVC, and pericardial cells showed a more gradual divergence, with late-stage behavioural shifts: endocardial cells increased in speed, while pericardial cells slowed relative to LV/AVC cells. Together the data reveal the regulation of individual cell directionality and cardiac fate allocation within the seemingly unorganised migratory pattern of mesoderm cells.

developmental biology↗

Combining radiomics and mathematical modeling to elucidate mechanisms of resistance to immune checkpoint blockade in non-small cell lung cancer

Immune therapies have shown promise in a number of cancers, and clinical trials using the anti-PD-L1/PD-1 checkpoint inhibitor in lung cancer have been successful for a number of patients. However, some patients either do not respond to the treatment or have cancer recurrence after an initial response. It is not clear which patients might fall into these categories or what mechanisms are responsible for treatment failure. To explore the different underlying biological mechanisms of resistance, we created a spatially explicit mathematical model with a modular framework. This construction enables different potential mechanisms to be turned on and off in order to adjust specific tumor and tissue interactions to match a specific patient's disease. In parallel, we developed a software suite to identify significant computed tomography (CT) imaging features correlated with outcome using data from an anti-PDL-1 checkpoint inhibitor clinical trial for lung cancer and a tool that extracts these features from both patient CT images and \"virtual CT\" images created from the cellular density profile of the model. The combination of our two toolkits provides a framework that feeds patient data through an iterative pipeline to identify predictive imaging features associated with outcome, whilst at the same time proposing hypotheses about the underlying resistance mechanisms.

cancer biology↗