Inhibition of BET Bromodomain Targets Genetically Diverse Glioblastoma
Bibliographic record
Abstract
PURPOSE: Glioblastoma is refractory to conventional therapies. The bromodomain and extraterminal domain (BET) proteins are epigenetic readers that selectively bind to acetylated lysine residues on histone tails. These proteins recently emerged as important therapeutic targets in NUT midline carcinoma and several types of hematopoietic cancers. In this study, the therapeutic potential of a novel BET bromodomain inhibitor, JQ1, was assessed in a panel of genetically heterogeneous glioblastoma samples. EXPERIMENTAL DESIGN: The antineoplastic effects of JQ1 were shown using ex vivo cultures derived from primary glioblastoma xenograft lines and surgical specimens of different genetic background. The in vivo efficacy was assessed in orthotopic glioblastoma tumors. RESULTS: We showed that JQ1 induced marked G1 cell-cycle arrest and apoptosis, which was phenocopied by knockdown of individual BET family members. JQ1 treatment resulted in significant changes in expression of genes that play important roles in glioblastoma such as c-Myc, p21(CIP1/WAF1), hTERT, Bcl-2, and Bcl-xL. Unlike the observations in some hematopoietic cancer cell lines, exogenous c-Myc did not significantly protect glioblastoma cells against JQ1. In contrast, ectopically expressed Bcl-xL partially rescued cells from JQ1-induced apoptosis, and knockdown of p21(CIP1/WAF1) attenuated JQ1-induced cell-cycle arrest. Cells genetically engineered for Akt hyperactivation or p53/Rb inactivation did not compromise JQ1 efficacy, suggesting that these frequently mutated signaling pathways may not confer resistance to JQ1. Furthermore, JQ1 significantly repressed growth of orthotopic glioblastoma tumors. CONCLUSION: Our results suggest potentially broad therapeutic use of BET bromodomain inhibitors for treating genetically diverse glioblastoma tumors.
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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".