Abstract A41: Novel mithramycin analogues with improved pharmacologic profile and efficacy in ETS transcription factor-driven tumors
Bibliographic record
Abstract
Abstract Introduction: Chromosomal translocations of ETS family transcription factors (TF) are found in Ewing sarcoma, prostate cancer, and leukemia and lead to expression of aberrant ETS transcription factors driving tumorigenesis. Mithramycin (MTM) inhibits EWS-FLI1, the most common ETS-related TFs in Ewing sarcoma through interference at its DNA binding sites on promoters. However, MTM has a narrow therapeutic window marked by severe liver and hematologic toxicities and poor pharmacokinetic (PK) properties, as demonstrated recently in a pediatric clinical trial with Ewing sarcoma patients. Here, we sought to develop analogues with specificity toward ETS family TFs and improved pharmacologic properties. Methods: Guided by crystal structures of MTM/DNA/ETS, we used semisynthetic approaches to prepare a library of analogs by substitution on the 3-side chain of MTM-SA and MTM (analogs). To select analogs with specific activity toward cells with ETS-related chromosomal translocations, analog cytotoxicity was determined in TC32 cells before and after EWS-FLI1 silencing. To confirm selectivity, analogs were tested in a panel of Ewing sarcoma cell lines (n=8) expressing EWS-ETS translocations and compared to a panel of non-Ewing cell lines (n=9) that do not express these translocations. CETSA, FRET, and luciferase reporter assays were used to evaluate interactions with EWS-FLI1 and SP1 proteins and gene promoter regions they bind. Inhibition of select transcriptionally regulated genes was determined by qRT-PCR and immunoblotting. Select analogs were tested in vivo to assess PK in mice and primates, identify the maximum tolerated dose (MTD), and determine dose-dependent efficacy in mouse xenograft models. Results: MTM analogs had higher GI50 in silenced EWS-FLI1 cells and > 10-fold lower GI50 in ETS-dependent cell lines vs. non-ETS dependent cancer cells, as compared to ~3-fold for MTM. Target engagement was demonstrated in dose-dependent manner using a luciferase reporter TC32 cell line under control of the NR0B1 promoter, which is regulated by EWS-FLI1, and CETSA experiments showed increased physical interaction of the analogs with EWS-FLI1 as compared to MTM. Treatment with MTM and analogs produced comparable dose-dependent displacement of an ETS DNA binding domain from GGAA (microsatellite-like) DNA fragments as demonstrated by FRET. Exposure to analogs led to concentration-dependent downregulation of EWS-FLI1 and Sp1 regulated genes. In vivo studies showed that MTM analogs attained higher exposure at their respective MTD and had lower clearance in mice and primates. Unlike MTM, analogs reversed tumor growth and increased survival at the MTD and 2/3 of MTD. Conclusion: We demonstrated that MTM analogs are selectively more cytotoxic in tumor cell lines dependent on ETS family TFs and have vastly improved PK properties as confirmed in a primate model. Given their effectiveness at 2/3 of the MTD, they are expected to have an improved therapeutic window. Citation Format: Markos Leggas, Joseph Eckenrode, Yang Liu, Abhisek Mandal, Reiya Hayden, Oleg Tsodikov, Jon Thorson, Jurgen Rorh. Novel mithramycin analogues with improved pharmacologic profile and efficacy in ETS transcription factor-driven tumors [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A41.
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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".