Bibliographic record
Abstract
Protein degradation is a highly regulated process that is required for maintaining cellular homeostasis, and its deregulation is associated with development of a number of diseases including cancer. Neddylation is a posttranslational modification that involves conjugation of the ubiquitin-like protein NEDD8 (neural precursor cell expressed, developmentally downregulated) to target proteins such as oncoproteins and tumor suppressors to regulate their functions through a cascade of enzymes including NEDD8-activating enzyme (E1), NEDD8-conjugating enzyme (E2), and NEDD8 ligases (E3).1 As such, the neddylation pathway presents an attractive oncogenic target for development of anticancer therapies. The main cellular substrates for neddylation include components of the Cullin-RING E3 ligase (CRL), which is the largest multicomponent ubiquitin ligase family regulating the turnover of multiple tumor suppressor proteins such as p21, p27, and NF-Kappa-B Inhibitor Alpha, among others (Fig. 1A).2 An overview of posttranslational NEDDylation of cullin (CUL) and its disruption by MLN4924. NEDDylation of CUL involves the transfer of the ubiquitin-like molecule NEDD8 (neural precursor cell expressed, developmentally downregulated 8) to CUL by NEDD8-activating enzyme E1 (NAE), NEDD8 conjugating enzyme E2 (UBE2M/Ubc12, UBE2F), and the NEDD8-E3 ligase cascade. MLN4924 is a highly potent and selective first-in-class inhibitor of NAE activity that covalently binds to the active site of the NAE and leads to inactivation of CRL and accumulation of its substrates, including tumor suppressor proteins p21 and p27 (A). Treatment of glioma cell lines with MLN4924 results in inhibition of cell cycle progression at the G2 phase and induction of apoptosis or senescence in a cell line-dependent manner. Administration of MLN4924 to an orthotopic xenograft model of glioblastoma (GBM) causes formation of smaller tumors expressing lower levels of proliferation marker Ki67 and increased amounts of the cell cycle regulator protein p21. This study identifies a potential new drug for targeting GBMs through specific inhibition of NAE. In an elegant study, Hua et al systematically investigated the effectiveness of the NAE inhibitor, MLN4924, against glioblastoma (GBM) in vitro and in vivo. MLN4924 is a newly developed small molecule inhibitor of the neddylation pathway that specifically inhibits NAE by binding to its active site and hindering its enzymatic activity.3 Several other groups have shown that treatment of cancer cells with MLN4924 results in induction of DNA damage response, cell cycle arrest, apoptosis, or senescence.4,5 MLN4924 is currently under investigation in several phase 1/2 clinical trials for multiple solid tumor types and hematologic malignancies.6 The ability of MLN4924 to cross the blood-brain barrier, its low toxicity, and clinical efficacy in other cancers suggests that this drug is an attractive treatment against GBM. Analysis of overall survival of GBM patients, as well as correlation with expression of global protein neddylation, indicated that higher global protein neddylation correlates with poor patient survival. They also found that GBM tumors generally express higher levels of NEDD8 and neddylation enzymes such as NAE1/UBA3 and UBC12 compared with adjacent normal brain tissue, with recurrent GBM tumors displaying even higher global protein neddylation. These findings further supported their hypothesis that MLN4924 could be considered as a therapeutic option for GBM and that an overactivated neddylation pathway may play a role in the development or progression of GBM. Analysis of MLN4924's effect on cellular proliferation showed that this drug induces G2 cell cycle arrest in GBM cells, followed by the induction of apoptosis or senescence depending on the cell line used (Fig. 1B). Although it is likely that increased expression of CRL substrates, such as p21 and p27, is responsible for this effect, it would be interesting to see how other glioma cell lines routinely used in the laboratory and primary cells such as glioma stem cells would react to this treatment and exactly what mechanism is associated with that outcome. On the other hand, results from in vivo experiments conducted in orthotopic xenograft mouse models of human GBM indicated that MLN4924 was highly effective at suppressing the growth of tumors without major adverse reactions. Consistent with their work in glioma cell lines, Hua et al discovered through immunohistochemical analysis that the level cellular proliferation marker Ki67 was reduced, whereas the expression of cell cycle inhibitor p21 increased in tumor sections obtained from xenografted mice treated with MLN4924 (Fig. 1B). While the results also demonstrated a decrease in global protein neddylation, analysis of dose response to MLN4924 and relative expression of these marker proteins would be highly informative. A notable finding of this study is that recurrent GBMs show higher neddylation activity than primary GBM, suggesting that follow-up studies should focus on testing the effect of MLN4924 treatment on GBM recurrence and its effect on sensitivity of cells and tumors to chemotherapy and radiation treatment. While these analyses may be the focus of future investigations, results from the work performed by Hua et al suggest promising therapeutic potential for MLN4924. In addition, their findings suggest that it may be possible to stratify patients based on their neddylation activity profile and use this information to predict outcomes for treatment with a potentially specific anticancer drug such as MLN4924.
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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 | 0.001 | 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".