Three-dimensional drug screen identifies HDAC inhibitors as therapeutic agents in mTORC1 <i>-</i> driven lymphangioleiomyomatosis
Bibliographic record
Abstract
ABSTRACT Lymphangioleiomyomatosis (LAM) is a rare disease involving cystic lung destruction by invasive LAM cells. These cells harbor loss-of-function mutations in TSC2 , conferring constitutive mTORC1 signaling. Rapamycin is the only clinically approved disease-modifying treatment, but its action is cytostatic and disease progresses upon its withdrawal. There is a critical need to identify novel agents that prevent the invasive phenotype and/or eradicate the neoplastic LAM cells. Here, we employed novel cellular and extracellular models to screen for candidate therapeutics in a physiologically relevant setting. We observed that lung-mimetic hydrogel culture of pluripotent stem cell-derived diseased cells more faithfully recapitulates human LAM biology compared to conventional culture on two-dimensional tissue culture plastic. Leveraging our culture system, we conducted a three-dimensional drug screen using a custom 800-compound library, tracking cytotoxicity and invasion modulation phenotypes at the single cell level. We identified histone deacetylase (HDAC) inhibitors as a group of anti-invasive agents that are also selectively cytotoxic towards TSC2 -/- cells. Unexpectedly, we observed that next generation ATP-competitive mTORC1/2 inhibitors potentiate invasion. We determined anti-invasive effects of HDAC inhibitors to be independent of genotype, while selective cell death is mTORC1-dependent and mediated by apoptosis. Drug performance was subsequently evaluated at the single cell level in zebrafish xenografts. We observed consistent therapeutic efficacy in vivo at equivalent concentrations to those used in vitro, substantiating HDAC inhibitors as potential therapeutic candidates for pursuit in patients with LAM. One Sentence Summary We performed a drug screen in 3D and discovered HDAC inhibitors exhibit therapeutic efficacy in models of the lung disease lymphangioleiomyomatosis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".