Abstract 15534: Identification of Narciclasine, a Potential Drug to Treat PAH by Unbiased Pharmaco-Transcriptomic Study
Bibliographic record
Abstract
Introduction: Pulmonary arterial hypertension (PAH) is a life-threatening vascular disorder characterized by persistent vasoconstriction and detrimental remodeling of the pulmonary blood vessels. This incurable disease is marked by a complex gene expression reprogramming that triggers, among other, metabolic disorders, heightened by inflammation, and the development of a pro-survival phenotype in pulmonary arterial smooth muscle cells (PASMC).We conducted an unbiased transcriptomic study using lung samples from 16 PAH patients and 12 non-PAH controls and identified 4013 differentially expressed genes. Leveraging in silico pharmaco-transcriptomic analysis (utilizing the Lincs and Sigcom databases), we identified narciclasine as a potential drug. Hypothesis: Consequently, we hypothesized that narciclasine could offer improvements in PAH. Methods and Results: In vivo , we administered narciclasine treatment (1 mg/kg, 2 weeks, gavage) in a murine model of PH (monocrotaline model, 60 mg/kg, sc.) and observed improved PH hemodynamics (RVSP, PAAT, TPR), reduced inflammation (CD68 immunofluorescence (IF)), decreased PASMC survival (PCNA and cleaved caspase 3 IF), and alleviated adverse vascular remodeling (Elastic van Gieson Stain Kit). In vitro , narciclasine exhibited a dose-dependent reduction of cell proliferation (IF: ki67; Western blot Survivin, PCNA and PLK1) and increased apoptosis PAH-PASMC (IF: cleaved caspase 3; Wb: Bax and Bcl2). Transcriptomic study (conducted in treated PASMCs) reveals that the therapeutic effects of narciclasine in PAH may be attributed to decreased glycosylation (Gene Ontology analysis). We further observed increased glycosylation in remodeled arteries from PAH lungs, PH preclinical models, and cultured PASMC (Periodic Acid Schiff Kit). Subsequently, we validated that narciclasine reduced glycosylation and downregulated the expression of glycosylation enzymes (by wb: GFAT, NGT, OGT) both in vitro and in vivo. Statistical tests used: unpaired t (2 groups), ANOVA (> 2 groups). Conclusions: In conclusion, our unbiased pharmaco-transcriptomic study identifies narciclasine as a potential therapeutic drug for PAH. Notably, its efficacy appears to be mediated by the reduction of glycosylation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".