A combinatorial chemical epigenetics screen identifies an off‐target modulation of drug transporter function
Bibliographic record
Abstract
Anticancer drug response is determined by genetic and epigenetic mechanisms. To identify the epigenetic regulators of anticancer drug response, we conducted a chemical epigenetics screen using chemical probes that target different epigenetic modulators. In this screen, we tested 31 epigenetic probes in combination with 14 mechanistically diverse anticancer agents and measured the viability in A549 lung adenocarcinoma cells by the Resazurin assay. We identified 6 epigenetic probes that significantly potentiated the cytotoxicity of TAK‐243, a first‐in‐class ubiquitin‐activating enzyme (UBA1) inhibitor evaluated in several solid and hematologic malignancies. These probes include TP‐472, GSK‐864, A‐196, UNC1999, SGC‐CBP30 and PFI‐4, and target BRD9/7, mutant IDH1, SUV420H1/H2, EZH2/H1, p300/CBP and BRPF1B, respectively. To validate the screen results, we assessed the viability after combination of TAK‐243 and the identified probes and observed 4‐ to 30‐fold potentiation of TAK‐243 cytotoxicity in myeloma cells. Moreover, we tested the identified probes in 13 additional cell lines and observed profound potentiation. Upon combination with a panel of anticancer agents, epigenetic probes did not potentiate their cytotoxicity suggesting the observed effects are selective for TAK‐243. In contrast to epigenetic probes, negative chemical controls did not have a significant impact on TAK‐243 cytotoxicity. As assessed by immunoblotting, potentiation of TAK‐243 cytotoxicity was associated with reduced ubiquitylation and induction of apoptosis. Using the cellular thermal shift assay (CETSA), UBA1 displayed increased engagement with TAK‐243, suggesting the epigenetic probes enhanced intracellular drug accumulation. Mechanistically, the epigenetic probes exerted their potentiation by inhibiting the efflux transporter ABCG2 without inducing significant changes in ubiquitylation pathways or ABCG2 expression levels. Additionally, the identified probes shared significant chemical scaffold similarities with TAK‐243. Based on the screen results, we developed a cell‐based assay that exploits TAK‐243 and ABCG2‐overexpressing cells to reliably quantify the ABCG2‐inhibitory activity of novel compounds. In conclusion, our study identifies epigenetic probes that profoundly potentiate TAK‐243 cytotoxicity through off‐target ABCG2 inhibition. We also provide experimental evidence of the inability of negative controls to exclude a subset of off‐target effects of chemical probes. Finally, we have developed a robust cell‐based assay that can quantitatively evaluate ABCG2 inhibition by drug candidates.
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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) | 0.002 | 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".