Abstract 5221: The first-in-class ERK inhibitor ulixertinib (BVD-523) shows activity in MAPK-driven pediatric low-grade glioma models as single agent and in combination with MEK inhibitors or senolytics
Bibliographic record
Abstract
Abstract Ulixertinib (BVD-523) is a well-tolerated, orally delivered, catalytic ERK1/2 inhibitor, which has shown promising responses in adult patients with mitogen-activated protein kinase (MAPK)-driven solid tumors. Pediatric low grade gliomas (pLGGs) are the most common pediatric brain tumors, with the most frequent driving alterations (KIAA:BRAF fusion, BRAF V600E mutation) occurring in the MAPK pathway. To investigate the anti-tumoral activity of ulixertinib in pLGG, cell lines recapitulating both main MAPK alterations were used: DKFZ-BT66 (pilocytic astrocytoma; KIAA:BRAF fusion) and BT40 (pleomorphic xanthoastrocytoma; BRAF V600E mutation and CDKN2A/B deletion). The potential synergism of combinations with MEK inhibitors, senolytics, and chemotherapy was investigated in vitro using metabolic activity and MAPK activity assays. The most promising combinations were validated in vitro by analysis of viable, dead, and apoptotic cells through high-content microscopy. The most clinically relevant combinations were further validated in vivo: 1) in two zebrafish embryo models (respectively, BT40 and DKFZ-BT66 yolk sac injection) and 2) in NSG mice (BT40 orthotopic PDX) including in vivo pharmacokinetic and -dynamic analyses. Our data demonstrate ulixertinib’s ability to inhibit MAPK pathway activity in all used models. Ulixertinib treatment reduced cell viability in the BRAF V600E mutated cell line at a remarkably low concentration of 62.7 nM (compared to other cell lines’ IC50 from the Genomics of Drug Sensitivity in Cancer database). In vivo pharmacokinetic and -dynamic analyses showed good penetrance of the drug into mouse brain tissue, with concentrations above the in vitro IC50 and reduction of MAPK activity as assessed by Western blot. Furthermore, ulixertinib treatment slowed tumor growth and significantly increased survival in NSG mice with orthotopic BT40 xenografts. Ulixertinib showed indications for anti-proliferative synergy in vitro, according to the Loewe and Bliss independence models, in combination with MEK inhibitors (trametinib, binimetinib) or senolytics (navitoclax, A1331852). Combinations with chemotherapy (carboplatin, vinblastine) were at most additive. Indications for synergy with binimetinib and navitoclax were confirmed in the zebrafish embryo xenograft models for both MAPK-altered backgrounds. The combination of ulixertinib with navitoclax was further investigated in the BT40 PDX mouse model, where tumor growth and survival were comparable to ulixertinib monotherapy. In conclusion, our data indicate a strong potential for ulixertinib as a clinically relevant therapeutic option for the treatment of pLGG to be further investigated in upcoming clinical trials. Potential synergism with MEK inhibitors and senolytics was noted and warrants further investigation. Citation Format: Romain Sigaud, Lisa Rösch, Charlotte Gatzweiler, Julia Benzel, Laura von Soosten, Heike Peterziel, Sara Najafi, Simay Ayhan, Nina Hofmann, Kathrin I. Förster, Jürgen Burhenne, Rémi Longuespée, Cornelis M. van Tilburg, David T. Jones, Stefan M. Pfister, Deborah Knoerzer, Brent Kreider, Max Sauter, Kristian W. Pajtler, Marc Zuckermann, Ina Oehme, Olaf Witt, Till Milde. The first-in-class ERK inhibitor ulixertinib (BVD-523) shows activity in MAPK-driven pediatric low-grade glioma models as single agent and in combination with MEK inhibitors or senolytics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5221.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".