MétaCan
Menu
← Back to cohort

Abstract 4139022: Targeting Aurora Kinase B Improves Vascular Remodeling in Pulmonary Arterial Hypertension

2024· article· en· W4404364175 on OpenAlexaff
Sarah‐Eve Lemay, Manon Mougin, Mélanie Sauvaget, EL-Kabbout Reem, Chanil Valasarajan, Keiko Yamamoto, Sandra Martineau, Andréanne Pelletier, Yann Grobs, Alice Bourgeois, Charlotte Romanet, Sandra Breuils Bonnet, Mónica S. Montesinos, Min Lü, Huidong Chen, Charlie Théberge, François Potus, Soni Savai Pullamsetti, Steeve Provencher, Sébastien Bonnet, Olivier Boucherat

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsQuebec - Clinical Research Organization in CancerInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicinePulmonary hypertensionCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Pulmonary arterial hypertension (PAH) is a progressive and fatal disease characterized by pulmonary artery (PA) remodeling. Extensive proliferation of PA smooth muscle cells (PASMCs) is perhaps the most important feature of PAH accounting for vascular remodeling for which current treatments have limited efficacy. Methods and Results: To discover novel actionable targets involved in vascular remodeling, we performed a comparative RNA-sequencing analysis between control and PAH-PASMCs, and next enriched our experiment with two publicly available datasets conducted on comparable cell lines. After merging the three datasets, 136 genes were found to overlap, of which 126 and 10 were up- and down-regulated in PAH-PASMCs, respectively. A connectivity map analysis using SigCom Library of Integrated Network-based Cellular Signatures was performed on the commonly upregulated genes and identified an aurora kinase B (AURKB) inhibitor as the top reverser drug of PAH-PASMCs gene signature. In this regard, aurora kinase B (AURKB), known to play a critical role in the onset and progression of mitosis, was present among the overlapping upregulated genes in PAH-PASMCs. Further experiments revealed that FOXM1 positively regulates AURKB expression. Pharmacological (Barasertib) and molecular (siRNA) inhibition of AURKB reduced PAH-PASMC proliferation (EDU incorporation, Ki67 labeling&WB PLK1), survival (TUNEL assay,&WB Survivin) and was associated with mitotic defects. Acquisition of a senescence-like phenotype was observed in PAH-PASMCs that escaped apoptosis following AURKB inhibition (SA-βGal, p21, p53, SASP…). Barasertib treatment significantly improved pulmonary vascular remodeling and hemodynamics in MCT and Su/Hx rats with established PAH (RHC&EVG) and resulted in a marked increase in p21 in small PAs. Similar effects were also observed in human precision-cut lung slices isolated from PAH patients. Finally, the combination of Barasertib with the p21 attenuator UC2288 was more effective in reducing vascular remodeling in Su/Hx rats than either drug alone (EVG, RHC, echocardiography). Conclusion: Our research identified AURKB as a novel therapeutic target and suggests that combining anti-remodeling drugs with senotherapeutics may be more effective in counteracting vascular remodeling in PAH.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.031
GPT teacher head0.281
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCirculation→Same topicPulmonary Hypertension Research and Treatments→French-language works237,207→