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G Protein‐Coupled Receptors in Human Lung Fibroblasts: Novel Therapeutic Approaches for Idiopathic Pulmonary Fibrosis?

2018· article· en· W3174074055 on OpenAlexafffund
Alexander V. Michkov, Krishna Sriram, Subhendu Mukherjee, Luke J. Janssen, Paul A. Insel

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMyofibroblastFibroblastG protein-coupled receptorIdiopathic pulmonary fibrosisExtracellular matrixLungReceptorFibrosisPulmonary fibrosisCancer researchCell biologyBiologySignal transductionChemistryPathologyMedicineInternal medicineCell culture

Abstract

fetched live from OpenAlex

Idiopathic Pulmonary Fibrosis (IPF) is a progressive, often fatal interstitial lung disease and thus in need of new, effective therapies. A feature of IPF is fibroblast‐to‐myofibroblast transition and resultant increased deposition of extracellular matrix (ECM) proteins, which can lead to loss of functional lung tissue. Previous studies have shown that increases in cyclic AMP (cAMP) can decrease the number and function of myofibroblasts. Cellular synthesis of cAMP is mediated by adenylyl cyclase, the activity of which is regulated by G‐protein signaling and G‐protein coupled receptors (GPCRs). We hypothesized that alteration in GPCR expression in lung fibroblasts from IPF patients may identify new therapeutic targets for lung fibrosis. Using RNA‐seq, we have identified and quantified GPCRs of lung fibroblasts isolated from six IPF patients and six controls grown in low passage primary cultures. RNA‐seq analysis revealed the expression of ~120 GPCRs (of ~380 endoGPCRs [regulated by endogenous ligands]). On average ~20 highly expressed GPCR were detected in all samples, with small differences in biological replicates; these may be “housekeeping” GPCRs. We also identified a group of GPCRs with highly variable expression and found that lung fibroblasts from IPF patients selectively expressed a subset of GPCRs. To assess changes in GPCR expression during fibroblast‐to‐myofibroblast transition, we treated fibroblasts with TGFβ1 (10 ng/ml, 48 hrs or 20 ng/ml, 16 hrs). As expected, TGFβ1 treatment increased the expression of pro‐fibrotic markers (e.g., collagens Iα1, Iα2, III; α‐smooth muscle actin; plasminogen activator inhibitor‐1). In addition, TGFβ1 altered (increased or decreased) the expression of numerous GPCRs. TGFβ1 treatment of control fibroblasts did not fully mimic the GPCR expression changes of fibroblasts from IPF patients. We conclude that GPCR expression (GPCRomic) analysis identifies GPCRs that may contribute to the fibrotic state in the lung and thus, may be novel therapeutic targets for lung fibrosis. Support or Funding Information Supported by NIH T32 HL 098062‐04, Bristol Myers Squibb and CIHR 201403MOP‐RS‐323925. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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

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 head0.035
GPT teacher head0.274
Teacher spread0.239 · 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
Published2018
Admission routes2
Has abstractyes

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