DIPG-38. DIANHYDROGALACTITOL (VAL-083) WITH AZD1775 INCREASES SURVIVAL IN DIFFUSE INTRINSIC PONTINE GLIOMA (DIPG), IN VIVO
Bibliographic record
Abstract
VAL-083 is a bi-functional DNA-targeting agent that crosses the blood-brain barrier and accumulates in brain tumors. VAL-083 induces interstrand crosslinks leading to DNA double-strand breaks and S/G2 cell-cycle arrest. We hypothesized that by inhibiting G2 checkpoint regulator kinase Wee1, cancer cells with VAL-083 induced DNA damage would progress past the G2 checkpoint leading to premature mitosis and cancer cell death. Herein we assess the activity of VAL-083 as well as in combination with the Wee1 inhibitor AZD1775 in patient-derived model systems of DIPG. DIPG derived cell-lines SF8628 and NEM157 (H3.3K27) were treated with increasing concentrations of single agent VAL-083 and in combination with AZD1775. To determine synergistic activity, we calculated the combination index (CI) using the Chou-Talalay method. In vivo activity of VAL-083 (3 mg/kg) as single agent or in combination with AZD1775 (60 mg/kg) was assessed in an orthotopic engraftment model of DIPG (SF8628). The IC50 of single agent VAL-083 ranged from 1µM to 10µM. The combination of VAL-083 and AZD 1775 exhibited synergistic activity in SF8628 and NEM157 with CI values ranging from 0.4 to 0.95 (CI<1 indicating synergy). In vivo, single-agent VAL-083 and in combination with AZD1775 conferred significant survival benefit compared to both untreated control and single-agent AZD1775. The median survival for mice treated with VAL-083 alone was 54.5 days vs. control (44 days, p=0.0004) and the combination was 62 days vs. control (44 days, p<0.0001) or mice treated with single-agent AZD1775 (47 days, p=0.0839). Our results suggest that VAL-083 in combination with a Wee1 inhibitor such as AZD1775 might offer a promising new therapeutic strategy for children with DIPG. Ongoing studies assessing the in vivo activity in other DIPG models as well as exploring the underlying mechanism-of-action of the combination strategy will be reported.
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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) | 0.001 | 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".