Abstract 13205: Everolimus Induces Human Leukocyte Antigen-G Expression In Human Coronary Artery Smooth Muscle Cells: Impact on Graft Rejection and Cardiac Allograft Vasculopathy
Bibliographic record
Abstract
Background: Human leukocyte antigen-G (HLA-G) is a non-classical MHC I protein that plays an important role in immune tolerance. Its expression in serum and endomyocardial biopsies of heart transplant patients is associated with a lower incidence of graft rejection and cardiac allograft vasculopathy (CAV). However, the mechanisms of HLA-G expression remain vague. Previous clinical studies found that patients treated with everolimus expressed significantly higher levels of HLA-G in the blood plasma. Our objective was to determine if everolimus up-regulates HLA-G in human coronary artery smooth muscle cells (HCASMC), explaining a potential mechanism of HLA-G expression after heart transplant. We also tested if the soluble HLA-G inhibits HCASMC proliferation, a main cause of intimal hyperplasia associated with CAV. Methods: Commercially available HCASMC (n=6) were cultured in media containing 5% fetal bovine serum. After reaching full confluence the cells were exposed to various doses of everolimus (0.1-1000 ng/ml) for 24 hours. HLA-G expression was assessed by Western blot. We also cultured HCASMC (n=6) in conditioned media from Jeg-3 cells, choriocarcinoma cells known to release soluble HLA-G. Cell proliferation was measured at various time points (24-120 hours) post treatment. Results: There was a significant dose-dependent increase in HLA-G expression in the cells treated with 1000ng/ml of everolimus when compared to the control group (p=.005). Interestingly, there was no significant difference in proliferation between the cells treated with HLA-G conditioned media and the control group. Conclusion: We have shown for the first time that everolimus induces HLA-G expression in HCASMC in a dose-dependent manner. We have also shown that soluble HLA-G does not inhibit HCASMC proliferation in an in-vitro setting. Induction of HLA-G expression in HCASMC may represent a promising and novel therapeutic strategy to protect against graft rejection after heart transplantation. Although higher HLA-G levels protect against graft rejection, our results suggest that HLA-G does not inhibit SMC proliferation, implying that other cellular pathways may play a role in reducing CAV formation post transplant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".