G9a/GLP Targeting Ameliorates Pulmonary Vascular Remodeling in Pulmonary Arterial Hypertension
Bibliographic record
Abstract
Pulmonary arterial hypertension (PAH) is characterized by progressive vascular remodeling of small pulmonary arteries (PAs) causing sustained elevation of PA pressure, right ventricular failure, and death. Similar to cancer cells, PA smooth muscle cells (PASMCs), which play a key role in pulmonary vascular remodeling, have adopted multiple mechanisms to sustain their survival and proliferation in the presence of stress. The histone methyltransferase G9a and its partner protein GLP (G9a-like protein) have been shown to exert oncogenic effects and to serve as a buffer against an exaggerated transcriptional response. Therefore, we hypothesized that upregulation of G9a and GLP in PAH plays a pivotal role in pulmonary vascular remodeling by maintaining the abnormal phenotype of PAH-PASMCs. We found that G9a is increased in PASMCs from patients with PAH as well as in remodeled PAs from animal models. Pharmacological inhibition of G9a/GLP activity using BIX01294 and UNC0642 significantly reduced the prosurvival and proproliferative potentials of cultured PAH-PASMCs. Using RNA sequencing, further exploration revealed that G9a/GLP promotes extracellular matrix production and affords protection against the negative effects of an overactive stress response. Finally, we found that therapeutic treatment with BIX01294 reduced pulmonary vascular remodeling and lowered mean PA pressure in fawn-hooded rats. Treatment of Sugen/hypoxia-challenged mice with BIX01294 also improved pulmonary hemodynamics and right ventricular function. In conclusion, these findings indicate that G9a/GLP inhibition may represent a new therapeutic approach in PAH.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".