Abstract 3867: Epigenetic siRNA and chemical screens identify SETD8 inhibition as a therapeutic strategy to reactivate p53 in high-risk neuroblastoma
Bibliographic record
Abstract
Abstract Neuroblastoma (NB) is considered a failure of sympathoadrenal differentiation. High-risk neuroblastoma (HR-NB) is an aggressive pediatric tumor accounting for 15% of all pediatric oncology deaths. Less than 50% of HR-NB patients have long-term survival, despite intense multimodality treatment. Given the paucity of druggable mutations and findings that epigenetic drivers contribute to NB tumorigenesis, we undertook a chromatin-focused siRNA screen to uncover epigenetic regulators critical for survival of high-risk NBs. Of the 400 genes analyzed, high-content Opera imaging identified 53 genes whose loss of expression led to significant decreases in NB cell number with 16 also inducing differentiation. A screen with 21 epigenetic compounds in 8 NB cell lines and 2 non-transformed cell lines prioritized those siRNA hits with active tool compounds in the drug development pipeline. This revealed UNC0379 (targets SETD8) inhibited NB cell growth and identified SETD8 as an important and druggable NB target. SETD8 is the H4K20me1 methyltransferase which regulates DNA replication, chromosome condensation and gene expression. Analysis of primary NB revealed that high expression of SETD8 is associated with poor prognosis in NB (R2 platform ex. Kocak; p=1.4e-07). Levels of SETD8 were not significantly different between Stage 4 MYCN-amp compared to MYCN-WT tumors but high SETD8 levels were only associated with poor prognosis in the Stage 4 MYCN-WT(p=0.03). To understand SETD8-mechanism of action, we performed RNA-seq transcriptome analyses after genetic or pharmacological inhibition of SETD8. Ingenuity Pathway Analysis revealed that SETD8 ablation rescued p53 pro-apoptotic and cell-cycle arrest functions by activating the canonical p53 pathway. Functional studies showed SETD8 methylates p53 (K382) leading to its inactivation. Levels of p53K382me1 are higher in MYCN-WT NB cell lines compared to those with MYCN-amp. Less than 2% of NB tumors have p53 mutations but multiple mechanisms have been identified in MYCN-amp NB that functionally inactivate p53. This study identified that SETD8 inactivates p53 in NB and may be an important mechanism to inactivate p53 in MYCN-WT HR-NB. This subgroup represents 60-70% of HR-NB tumors. SETD8 inhibition led to increases in caspase-dependent cell death only in p53-WT but not -mutant or -null NB cells. Genetic rescue experiments confirmed that SETD8-induced cell death is p53 dependent and p53K382 is important for this activity. Our in vivo xenograft NB models, showed that genetic or pharmacologic (UNC0379) inhibition of SETD8 confers a significant survival advantage. This work identifies that SETD8 is a novel therapeutic target and its inhibition may be especially relevant for the subset of high-risk NB tumors with wildtype MYCN. This is the first in vivo preclinical study showing that targeting SETD8 inhibits tumor growth. Citation Format: Veronica Veschi, Zhihui Liu, Ty C. Voss, Laurent Ozbun, Berkley Gryder, Chunhua Yan, Ying Hu, Anqi Ma, Jian Jin, Sharlyn J. Mazur, Norris Lam, Barbara K. Souza, Giuseppe Giannini, Gordon L. Hager, Cheryl H. Arrowsmith, Javed Khan, Ettore Appella, Carol Thiele. Epigenetic siRNA and chemical screens identify SETD8 inhibition as a therapeutic strategy to reactivate p53 in high-risk neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3867. doi:10.1158/1538-7445.AM2017-3867
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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) | 0.005 | 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".