Epigenetic Regulation of RGS2 in Cystic Fibrosis
Bibliographic record
Abstract
Cystic fibrosis (CF) is a recessive autosomal disease that affects the respiratory, gastrointestinal and reproductive systems. At pulmonary level, the absence of CFTR function (cystic fibrosis transmembrane conductance regulator encoding an ion channel chlorine) leads to a decrease in mucociliary clearance, resulting in mucus accumulation. A new approach based on epigenetic regulation of gene expression has been investigated and we identified a list of hypermethylated genes in dF508 cell lines, the most frequently observed mutation in the CF population. Among the CF hypermethylated genes, RGS2 (Regulator of G protein signaling 2) gene demonstrated either transcript or protein downregulation. RGS2 is a key modulator of bronchial hyperresponsiveness, plays a critical role in fibrosis‐related diseases and inflammation. We hypothesized that variation in RGS2 protein expression could be the result of modulation of promoter methylation and has an impact on cytokine regulation. The first objective was to verify that methylation observed on RGS2 promoter in dF508 homozygous cell lines induces a modulation of protein expression. Then, to assess the consequences of this downregulation of RGS2, we performed an shRNA‐mediated RGS2 knockdown followed by DMNQ treatment in non‐CF cells and monitored the expression of inflammatory mediators. We confirmed that methylation of RGS2 promoter has an impact on RGS2 gene expression using azacythidine and oxidative stress treatments and that RGS2 is downregulated at the protein level in CF cells and in dF508 homozygous patients. We observed a relation between RGS2 downregulation by shRNA and the upregulation of 3 modulators of early inflammation: CHI3L1, S100A12 and TNFa.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".