Abstract 246: Transdifferentiation of Human Fibroblasts to Endothelial Cells: Role of Innate Immunity
Bibliographic record
Abstract
Cell fate is fluid, and may be altered experimentally by the forced expression of master regulators mediating cell lineage. Such nuclear reprogramming has been achieved using viral vectors encoding transcription factors. We recently discovered that the viral vectors are more than passive vehicles for transcription factors, as they participate actively in the process of nuclear reprogramming to pluripotency. Viral vectors, by activating innate immunity, cause global changes in the expression of epigenetic modifiers, favoring an open chromatin state (Cell, 151 2012). Based on the recognition that activation of innate immunity increases epigenetic plasticity, we hypothesized that small molecule activators of toll-like receptor 3 (TLR3), together with external microenvironmental cues that drive EC specification, might be sufficient to induce transdifferentiation of fibroblasts into ECs (iECs). Here we show that TLR3 agonist Poly I:C, combined with exogenous EC growth factors, transdifferentiated human fibroblasts into ECs (in the absence of viral vectors or transcription factors). These iECs were comparable to HMVEC in immunohistochemical, genetic and functional assays, including the ability to form capillary-like structures and to incorporate acetylated-LDL. Furthermore, iECs significantly improved limb perfusion and neovascularization in the murine ischemic hindlimb compared to parental fibroblasts. Finally, using genetic knockdown studies, we find that the effective transdifferentiation of human fibroblasts to endothelial cells requires innate immune activation. This study suggests that manipulation of innate immune signaling may be generally used to modify cell fate. Our observations raise the question as to whether epigenetic plasticity and cell fate fluidity generally participate in the immune defense against pathogens. Because similar signaling pathways are activated by damage associated molecular patterns, epigenetic plasticity induced by innate immunity may play a fundamental role in transdifferentiation during wound healing and regeneration. Finally, this study is a first step toward development of a small molecule strategy for therapeutic transdifferentiation in vivo.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".