Combination Treatment with Histone Deacetylase and Carbonic Anhydrase 9 Inhibitors Shows Therapeutic Potential in Experimental Diffuse Intrinsic Pontine Glioma
Bibliographic record
Abstract
Abstract Purpose: Despite extensive research, an effective and safe treatment for diffuse intrinsic pontine glioma (DIPG) has not been established. In this study, we investigate the therapeutic potential of combination therapy with histone deacetylase (HDAC) and carbonic anhydrase 9 (CA9) inhibitors against DIPG.Methods: We used RNA sequencing data from DIPG patient samples to evaluate the expression of the carbonic anhydrase family and the activity of the hypoxia signaling pathway. Next, we performed a synergy screen using CA9 inhibitor SLC-0111 and the HDAC inhibitors panobinostat, vorinostat, entinostat, and pyroxamide. We selected the SLC-0111/HDACi combination showing the highest synergy, and its effects on cell proliferation, invasion, and migration were evaluated. We also measured changes in histone acetylation, apoptosis, cell cycle, and intracellular pH.Results: CA9 was significantly upregulated in human DIPG samples. Furthermore, pathways downstream of CA9 were found to be activated when compared to normal brain tissue. The synergy screen revealed that the combination of SLC-0111 and pyroxamide was most effective at inhibiting DIPG cell proliferation. Furthermore, this combination reduced cell migration and invasion potential while enhancing histone acetylation with subsequent reduction of cell population in S Phase. Finally, the SLC-0111 and pyroxamide combination showed greater reduction of intracellular pH as compared to each agent alone.Conclusion: Our in vitro data suggest that the combination of SLC-0111 and pyroxamide shows promise in the treatment of experimental DIPG. Based on these findings, further investigation of this combination therapy in preclinical models is warranted.
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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) | 0.001 | 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) | 0.001 | 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".