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Record W4396605065 · doi:10.1101/2024.04.30.591766

RV-specific Targeting of Snai1 Rescues Pulmonary Hypertension-induced Right Ventricular Failure by Inhibiting EndMT and Fibrosis <i>via</i> LOXL2 Mediated Mechanism

2024· preprint· en· W4396605065 on OpenAlexaff
Somanshu Banerjee, Varina R. Clark Onwunyi, Jason Hong, Sandra Martineau, Gregory A. Fishbein, Sandra Breuils Bonnet, Steeve Provencher, Sébastien Bonnet, Soban Umar

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMechanism (biology)SNAI1Pulmonary hypertensionFibrosisPulmonary fibrosisMedicineCardiologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Abstract Background Pulmonary hypertension (PH)-induced right ventricular (RV) failure (PH-RVF) is a significant prognostic determinant of mortality and is characterized by RV hypertrophy, endothelial-to-mesenchymal transition (EndMT), fibroblast-to-myofibroblast transition (FMT), fibrosis, and extracellular matrix (ECM)-remodeling. Despite the importance of RV function in PH, the mechanistic details of PH-RVF, especially the regulatory control of RV EndMT, FMT, and fibrosis, remain unclear. The action of transcription factor Snai1 is shown to be mediated through LOXL2 recruitment, and their co-translocation to the nucleus, during EndMT progression. We hypothesize that RV EndMT and fibrosis in PH-RVF are governed by the TGFβ1-Snai1-LOXL2 axis. Furthermore, targeting Snai1 could serve as a novel therapeutic strategy for PH-RVF. Methods Adult male Sprague Dawley rats (250-300g) received either a single subcutaneous injection of Monocrotaline (MCT, 60mg/kg, n=9; followed for 30-days) or Sugen (SU5416 20mg/kg, n=9; 10% O 2 hypoxia for 3-weeks followed by normoxia for 2-weeks) or PBS (CTRL, n=9). We performed secondary bioinformatics analysis on the RV bulk RNA-Seq data from MCT, SuHx, and PAB rats and human PH-PVF. We validated EndMT and FMT and their association with Snai1 and LOXL2 in the RVs of MCT and SuHx rat models and human PH-RVF using immunofluorescence, qPCR, and Western blots. For in vivo Snai1 knockdown (Snai1-KD), MCT-rats either received Snai1-siRNA (n=7; 5nM/injection every 3-4 days; 4-injections) or scramble (SCRM-KD; n=7) through tail vein from day 14-30 after MCT. Echocardiography and catheterization were performed terminally. Bulk RNASeq and differential expression analysis were performed on Snai1- and SCRM-KD rat RVs. In vitro Snai1-KD was performed on human coronary artery endothelial cells (HCAECs) and human cardiac fibroblasts (HCFs) under hypoxia+TGFβ1 for 72-hrs. Results PH-RVF had increased RVSP and Fulton index and decreased RV fractional area change (RVFAC %). RV RNASeq demonstrated EndMT as the common top-upregulated pathway between rat (MCT, SuHx, and PAB) and human PH-RVF. Immunofluorescence using EndMT- and FMT-specific markers demonstrated increased EndMT and FMT in RV of MCT and SuHx rats and PH-RVF patients. Further, RV expression of TGFβ1, Snai1, and LOXL2 was increased in MCT and SuHx. Nuclear co-localization and increased immunoreactivity, transcript, and protein levels of Snai1 and LOXL2 were observed in MCT and SuHx rats and human RVs. MCT rats treated with Snai1-siRNA demonstrated decreased Snai1 expression, RVSP, Fulton index, and increased RVFAC. Snai1-KD resulted in decreased RV-EndMT, FMT, and fibrosis via a LOXL2-dependent manner. Further, Snai1-KD inhibited hypoxia+TGFβ1-induced EndMT in HCAECs and FMT in HCFs in vitro by decreasing perinuclear/nuclear Snai1+LOXL2 expression and co-localization. Conclusions RV-specific targeting of Snai1 rescues PH-RVF by inhibiting EndMT and Fibrosis via a LOXL2-mediated mechanism.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.030
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.196
Teacher spread0.187 · 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 teacher head, not a consensus.

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

Citations3
Published2024
Admission routes1
Has abstractyes

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