Nonsense suppressor therapies rescue peroxisome lipid metabolism and assembly in cells from patients with specific <i>PEX</i> gene mutations
Why this work is in the frame
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Bibliographic record
Abstract
Peroxisome biogenesis disorders (PBDs) are multisystemic autosomal recessive disorders resulting from mutations in PEX genes required for normal peroxisome assembly and metabolic activities. Here, we evaluated the potential effectiveness of aminoglycoside G418 (geneticin) and PTC124 (ataluren) nonsense suppression therapies for the treatment of PBD patients with disease-causing nonsense mutations. PBD patient skin fibroblasts producing stable PEX2 or PEX12 nonsense transcripts and Chinese hamster ovary (CHO) cells with a Pex2 nonsense allele all showed dramatic improvements in peroxisomal very long chain fatty acid catabolism and plasmalogen biosynthesis in response to G418 treatments. Cell imaging assays provided complementary confirmatory evidence of improved peroxisome assembly in G418-treated patient fibroblasts. In contrast, we observed no appreciable rescue of peroxisome lipid metabolism or assembly for any patient fibroblast or CHO cell culture treated with various doses of PTC124. Additionally, PTC124 did not show measurable nonsense suppression in immunoblot assays that directly evaluated the read-through of PEX7 nonsense alleles found in PBD patients with rhizomelic chondrodysplasia punctata type 1 (RCDP1). Overall, our results support the continued development of safe and effective nonsense suppressor therapies that could benefit a significant subset of individuals with PBDs. Furthermore, we suggest that the described cell culture assay systems could be useful for evaluating and screening for novel nonsense suppressor therapies.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it