Lung-tropic dual AAV-SP-C and microRNA gene therapy attenuates lung injury in mutant Sftpc mice
Bibliographic record
Abstract
Mutations in the surfactant protein C (SP-C) gene (SFTPC) impair surfactant homeostasis, leading to respiratory distress in newborns or progressive interstitial lung disease. The most frequent mutation, I73T, results in the expression of a toxic dominant-negative form of SP-C, insinuating that for gene replacement therapy to be successful, suppression of the toxic form of the SP-C protein may also be necessary. Here, we capitalized on our rationally designed lung-tropic adeno-associated virus (AAV)6.2FF vector to develop a combinatorial gene therapy approach for treating SP-C disorders. In I73T-knockin mice exhibiting decreased Sftpc expression and toxic prosurfactant protein C (proSP-C) accumulation resulting in focal airspace enlargement, gene replacement therapy via airway delivery of AAV6.2FF expressing SP-C restored wild-type (WT) Sftpc and mature SP-C protein expression while significantly improving lung function and focal airspace enlargement. Next, we developed a dual-function AAV6.2FF to express functional SP-C and suppress the toxic 173T SFTPC gene (AAV-SPC-miR). The dual-function AAV6.2FF-SP-C-miR decreased endogenous Sftpc expression, restored WT Sftpc, re-expressed the mature SP-C protein without significant proSP-C protein accumulation, and attenuated airspace enlargement. These findings suggest that combination gene therapy is feasible and represents a promising tool for treating SP-C deficiencies and SFTPC mutation-linked lung diseases in humans.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".