Abstract 3476: Mechanistic evaluation of VS-6766 (dual RAF/MEK inhibitor) and defactinib (FAK inhibitor) in low-grade serous ovarian cancer models with correlations to clinical response
Bibliographic record
Abstract
Abstract Background: Low-grade serous ovarian cancer (LGSOC) constitutes up to 10% of all ovarian cancer and has clinical and molecular characteristics (resistance to chemotherapy, presence of RAS/RAF mutations, lack of TP53 mutations) distinct from high-grade serous ovarian cancer. Here, we characterized the effects of the dual RAF/MEK inhibitor VS-6766 and the FAK inhibitor defactinib on signal transduction and viability in LGSOC cell lines and patient-derived organoids. To correlate molecular characteristics with clinical response, we characterized genomic alterations in archival tumor samples from patients with LGSOC treated with the combination of VS-6766 and defactinib on a clinical trial (FRAME). Material and Methods: We exposed 5 LGSOC cell lines to clinical Cmax concentrations adjusted for protein binding of VS-6766 and defactinib. We quantified phospho- and total proteins (n=66) with an antibody-bead based assay normalized to GAPDH. We also studied growth inhibitory effects of the combination on KRAS mutant (mt) LGSOC patient-derived organoids. We performed next generation sequencing on archival samples from LGSOC patients treated with VS-6766 in combination with defactinib. Results: Signal transduction changes at 1 hr included reduction of p-FAK in 5/5 cell lines in response to defactinib. Cells exposed to VS-6766 showed a reduction in p-ERK and p-p90-RSK in 4/5 cell lines. Additionally, VS-6766 decreased p-cJUN and increased p-IκB in 4/5 cell lines, changes correlated with apoptosis. At 24 hrs, p-ERK and p-p90-RSK inhibition were maintained in 3/5 cell lines. Both drugs increased cleaved PARP in 4/5 cell lines and VS-6766 increased p-SMAD3 and BIM levels, indicating an increase in cell death/apoptosis. The combination of VS-6766 + defactinib showed synergistic growth inhibition in a KRAS mt LGSOC organoid model (combination index 0.51). The clinical combination of VS-6766 and defactinib (September 2021 cut-off) has shown an objective response rate (ORR) of 11/24 (46%) across all patients with LGSOC, and an ORR of 64% (7/11) for patients with KRAS mt LGSOC (n=11). In addition to mutations in KRAS, emerging data may suggest a correlation of U2AF1 and MED12 mutations with response. Conclusions: VS-6766, the dual RAF/MEK inhibitor, induces significant inhibition of ERK pathway signaling in addition to perturbations in TNF/NFκB signaling. Both defactinib and VS-6766 induce apoptosis in LGSOC models. The results provide mechanistic insights into the encouraging response rates observed in patients with LGSOC treated with VS-6766 and defactinib (NCT03875820). These data support the ongoing randomized phase II ENGOTov60/GOG3052/RAMP201 study (NCT04625270). Citation Format: Adam R. Stewart, Lisa Pickard, Ekta Paranjape, Victoria Sanchez Perez, Sanjib Chowdhury, Stephanie Lustgarten, Silvia Coma, Jonathan A. Pachter, Mark S. Carey, Gabriel DiMattia, Hannah C. Badham, Toby Prout, Mona Parmar, Muneeb Mahmud, Christina Yap, Matthew G. Krebs, Susana Banerjee, Udai Banerji. Mechanistic evaluation of VS-6766 (dual RAF/MEK inhibitor) and defactinib (FAK inhibitor) in low-grade serous ovarian cancer models with correlations to clinical response [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 3476.
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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 | 0.001 |
| 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".