High throughput imaging identifies a spatially localized response of primary fetal pulmonary artery endothelial cells to insulin-like growth factor 1 treatment
Kim, C.; Seedorf, G. J.; Abman, S. H.; Shepherd, D. P.
Show abstract
A common strategy to measure the efficacy of drug treatment is the in vitro comparison of ensemble readouts with and without treatment, such as proliferation and cell death. A fundamental assumption underlying this approach is there is minimal cell to cell variability in the response to drug. Here, we demonstrate that ensemble and non-spatial single cell readouts applied to primary cells lead to incomplete conclusions due to cell to cell variability. We exposed primary fetal pulmonary artery endothelial cells (PAEC) isolated from healthy newborn healthy and persistent pulmonary hypertension of the newborn (PPHN) sheep to the growth hormone insulin-like growth factor 1 (IGF-1). We found that IGF-1 increased proliferation and branch points in tube formation assays but not angiogenic signaling proteins at the population level for both cell types. We hypothesized that this molecular ambiguity was due to the presence of cellular subpopulations with variable responses to IGF-1. Using high throughput single cell imaging, we discovered a spatially localized response to IGF-1. This suggests localized signaling or heritable cell response to external stimuli may ultimately be responsible for our observations. Discovering and further exploring these rare cells is critical to finding new molecular targets to restore cellular function.
Matching journals
The top 12 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Drug resistant pancreatic cancer cells exhibit altered biophysical interactions with stromal fibroblasts in imaging studies of 3D co-culture models 94%
- TRAP seq in 3D Angiogenesis Assays Reveals a Distinct Endothelial Translatome Associated with Early and Late Stages of Morphogenesis. 94%
- Emerin deficiency drives MCF7 cells to an invasive phenotype 93%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.