PS2 - 153 Dianhydrogalactitol (VAL-083) Treatment Causes Irreparable DNA Double-Strand Breaks, S/G2 Phase Cell-Cycle Arrest and Cell Death in Cancer Cells
Bibliographic record
Abstract
Dianhydrogalactitol (VAL-083) is a unique bi-functional alkylating agent causing N7-guanine-methylation and inter-strand DNA crosslinks. VAL-083 readily crosses the blood-brain barrier, accumulates in brain tumor tissue and has shown activity in prior NCI-sponsored clinical trials against various cancers, including glioblastoma (GBM) and medulloblastoma. VAL-083 is also active against GBM cancer stem cells and acts as a radiosensitizer independent of O6-methylguanine-DNA methyltransferase activity (in contrast to e.g. temozolomide and BCNU). Here we report new insights into VAL-083 mechanism of action by showing that VAL-083 induces irreversible cell-cycle arrest and cell death caused by replication-dependent DNA damage. In lung (H2122, H1792, H23, A549) and prostate (PC3, LNCaP) cancer cell lines VAL-083 treatment caused irreversible S/G2 cell-cycle arrest and cell death (IC50 range 3.06-25.7 µM). VAL-083 pulse-treatment led to persistent phosphorylation of DNA double-strand breaks (DSB) sensors ATM, single-strand DNA-binding Replication Protein A (RPA32), and histone variant H2A.X, suggesting persistent DNA lesions. After 10 months in culture with increasing VAL-083 concentrations, H1792 and LNCaP cells survive at concentrations up to 9.4 µM and 7.4 µM, respectively, suggesting that efficient resistance mechanisms are not easily acquired by the cancer cells. Taken together with previous results showing that VAL-083 circumvents cisplatin-resistance and is less dependent on p53 activity than cisplatin, these results suggest a molecular mechanism for VAL-083 that differs from both TMZ, BCNU and cisplatin. They further suggest that irreparable DNA damage induced by VAL-083 is impervious to common strategies employed by cancer cells to escape effects of alkylating drugs used in GBM treatment.
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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) | 0.002 | 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".