Abstract 4755: Screening non-small cell lung cancer organoids with epigenetic probes
Bibliographic record
Abstract
Abstract Introduction: NSCLC is associated with high cancer-related mortality worldwide. Epigenetic modifications at the chromatin level have widely been linked to carcinogenesis. Epigenetic regulation not only contributes to the development of cancer, but it may also confer resistance to therapies by promoting the survival of clones that can overcome treatment-induced stress or give rise to complex tumor heterogeneity in response to cancer therapy. Investigating susceptibility resulting from epigenetic aberrations in tumor cells may reveal novel markers of therapies that target epigenetic aberrations. In this study, we treated NSCLC organoid models with a library of 41 epigenetic probes to identify epigenetic targets that affect tumor cell survival. Methods: Epigenetic screen. NSCLC organoid models were established from resected patient tumors or patient-derived xenografts. Organoids were dissociated into single cells and plated in matrigel-coated 384-well plate. Each model was treated with a library of epigenetic probes (1uM) and a DMSO control over a period of 8 days. Library was provided by Structural Genomics Consortium (www.thesgc.org) and contained compounds targeting a variety of protein domains some of which had activity on acetylation, methylation, histone de-methylation etc. CellTiter-Glo assay was performed to measure cell survival. Results: Among the epigenetic probe compounds tested on 26 models, LLY 283 (PRMT5 inhibitor) showed the most significant effect on inhibition of cell growth in 69% of organoid models (18/26) with suppression of >=40% as compared to the DMSO control. To assess differential responses to treatment with LLY 283, four organoid models were treated with 21 different concentrations of PRMT5 inhibitor. Growth curves of a sensitive (XDO181) and a less sensitive (XDO4056) models were compared. For XDO181 and XDO4056, IC50 values were calculated to be 4.7 nM and 31.8 nM respectively, indicating that a less sensitive model is associated with a 7-fold increase in IC50 value compared to the sensitive model. Conclusion: A screen using epigenetic compounds on NSCLC patient-derived organoids revealed sensitivity to PRMT5 inhibitor in 69% of the organoid models tested. Further investigation will explore the mechanisms that are associated with sensitivity to PRMT5 inhibition. Citation Format: Khadija Jafarova, Panagiotis Prinos, Nikolina Radulovich, Takamasa Koga, Cheryl Arrowsmith, Geoffrey Liu, Ming Sound Tsao. Screening non-small cell lung cancer organoids with epigenetic probes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4755.
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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) | 0.001 | 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) | 0.003 | 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".