Latent transforming growth factor binding protein 4 regulates transforming growth factor beta receptor stability
Bibliographic record
Abstract
Mutations in the gene for the latent transforming growth factor beta binding protein 4 (LTBP4) cause autosomal recessive cutis laxa type 1C. To understand the molecular disease mechanisms of this disease, we investigated the impact of LTBP4 loss on transforming growth factor beta (TGFβ) signaling. Despite elevated extracellular TGFβ activity, downstream signaling molecules of the TGFβ pathway, including pSMAD2 and pERK, were down-regulated in LTBP4 mutant human dermal fibroblasts. In addition, TGFβ receptors 1 and 2 (TGFBR1 and TGFBR2) were reduced at the protein but not at the ribonucleic acid level. Treatment with exogenous TGFβ1 led to an initially rapid increase in SMAD2 phosphorylation followed by a sustained depression of phosphorylation and receptor abundance. In mutant cells TGFBR1 was co-localized with lysosomes. Treatment with a TGFBR1 kinase inhibitor, endocytosis inhibitors or a lysosome inhibitor, normalized the levels of TGFBR1 and TGFBR2. Co-immunoprecipitation demonstrated a molecular interaction between LTBP4 and TGFBR2. Knockdown of LTBP4 reduced TGFβ receptor abundance and signaling in normal cells and supplementation of recombinant LTBP4 enhanced these measures in mutant cells. In a mouse model of Ltbp4 deficiency, reduced TGFβ signaling and receptor levels were normalized upon TGFBR1 kinase inhibitor treatment. Our results show that LTBP4 interacts with TGFBR2 and stabilizes TGFβ receptors by preventing their endocytosis and lysosomal degradation in a ligand-dependent and receptor kinase activity-dependent manner. These findings identify LTBP4 as a key molecule required for the stability of the TGFβ receptor complex, and a new mechanism by which the extracellular matrix regulates cytokine receptor signaling.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".