Abstract 6316: High throughput small molecule screening with synthetic 3D lung-mimetic hydrogels in the rare lung cancer lymphangioleiomyomatosis
Bibliographic record
Abstract
Abstract Lymphangioleiomyomatosis (LAM) is a rare lung cancer characterized by immature smooth muscle-like cell invasion of the lung parenchyma, leading to cystonodular destruction and respiratory decline. Interestingly, LAM is a monogetic disease caused by loss of TSC2, conferring constitutive mTORC1 activation. Currently, there are no approved therapeutics which exhibit LAM cell-specific cytotoxicity. Here, we describe a novel 3D drug screening platform which couples a rationally designed, synthetic, lung-mimetic hydrogel to high content imaging. We have designed and synthesized a hyaluronic acid-based hydrogel which mimics endogenous lung tissue. Human LAM cell models maintain mTORC1 activation in the hydrogel compared to matched controls, reflective of human LAM lesions. We observe LAM cells to exhibit both protease-dependent and independent modes of invasion: the former imparted by gel crosslinking with an MMP-cleavable peptide, the latter enabled by methylcellulose conjugation. Proliferation is inhibited as LAM cells actively invade through the gel. We coupled our culture system to high content confocal microscopy, permitting measurements of cell viability and invasion depth in response to therapeutic screening. We subsequently tested an 800-drug library of Health Canada-approved small molecule cancer therapeutics on LAM cells and matched controls. Surprisingly, LAM cells exhibited pan-therapeutic resistance as measured by both invasion and viability metrics. Enrichment analysis revealed categories of therapeutics which demonstrated LAM-selective cytotoxicity and/or anti-invasiveness. We performed a refinement screen on select therapeutics and identified AURA inhibition as an effective LAM cell-specific therapeutic avenue. Work is ongoing to establish the most efficacious small molecule inhibitor. In conclusion, we describe a novel drug screening platform which enables high content measurements of viability and invasion in response to drug screening in a lung-mimetic system. We have identified AURA inhibition as a potential therapeutic avenue for LAM patients using this screening platform. Future work will involve target validation, elucidation of the mechanism of action, and testing in a pre-clinical mouse model. As these small molecules are Health Canada-approved, we anticipate rapid clinical translation of our preferred candidate. Citation Format: Adam Pietrobon, Julien Yockell-Lelievre, Carole Doré, Roger Y. Tam, Sean P. Delaney, Molly Shoichet, William L. Stanford. High throughput small molecule screening with synthetic 3D lung-mimetic hydrogels in the rare lung cancer lymphangioleiomyomatosis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6316.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".