Abstract NTOC-108: ACTIVITY OF DIANHYDROGALACTITOL (VAL–083) IN OVARIAN TUMOR MODELS, SENSITIVE OR RESISTANT TO CISPLATIN
Bibliographic record
Abstract
Abstract PURPOSE: Platinum drug resistance is a major clinical impediment that is normally ascribed to several mechanisms, with dysfunctional p53 playing a critical role, particularly in the highly lethal high-grade ovarian serous carcinoma, where p53 mutations can be >80%. Since restoration of p53 function could restore drug-dependent cytotoxicity, the goal of this study was to examine dianhydrogalactitol (VAL-083) for its potential in an ovarian tumor panel representing different p53 statuses and cisplatin-resistance. VAL-083 has demonstrated clinical activity against a range of tumor types, including ovarian cancer, in historical NCI-sponsored clinical studies, but its activity in a cisplatin-resistance setting is not known. VAL-083 is a bi-functional alkylating agent with a distinct mechanism of action, forming DNA interstrand cross links at the N7 position of guanine, whereas cisplatin and carboplatin predominantly form intrastrand DNA cross-links. METHODS: The tumor panel was composed of cisplatin-sensitive wild type (wt) p53 ovarian cancer cell line A2780, cisplatin-resistant A2780-derived heterozygous p53-V172F mutant 2780CP/Cl-16 cells, and three other cisplatin-resistant models harboring mutant (OVCAR-10) or wt p53 (Hey and OVCA-433). Cells were exposed to cisplatin or VAL-083 and the IC50 cytotoxic parameter was determined by fitting the 5-day MTT cell survival data to a 4-parameter sigmoidal curve. MTT assay was used in conjunction with Bliss Independence Model and combination index approaches to assess VAL-083/cisplatin combinations. Immunoblot analysis assessed p53 response. RESULTS: The IC50 of cisplatin in the cisplatin-sensitive A2780 model was 0.2-0.3 µM. In contrast, the IC50 in the four cisplatin-resistant models (2780CP/Cl-16, OVCAR-10, Hey and OVCA-433) was 3-8 µM; a 10- to 27-fold increase. The corresponding IC50 for VAL-083 was about 0.5 µM in A2780 cells and 2-4 µM in the four cisplatin-resistant models; a 4- to 7-fold increase, suggesting a distinct mode of action of VAL-083 and the ability to circumvent cisplatin resistance. In addition, these results further indicate that VAL-083 activity is less dependent on p53 status. However, immunoblots of 2780CP/Cl-16 cells suggest partial dependency on p53 by demonstrating that VAL-083, unlike cisplatin, can activate mutant p53-V172F through Ser20 phosphorylation, thereby preventing binding to p53 of inhibitory MDM4. VAL-083 thus restores p53 function, which is consistent with its greater potency in p53 mutated cisplatin-resistant ovarian cancer. These results suggest that VAL-083 have two mechanisms: one dependent on p53 and another on a different pathway. The apparent differences in the mechanism between cisplatin and VAL-083 prompted a combination study with the two agents, and consistent synergy was demonstrated. CONCLUSIONS: VAL-083 can circumvent cisplatin-resistance in ovarian tumor models, and its activity is less dependent on p53 status. Together with overt synergy between VAL-083 and cisplatin, our results demonstrate the effectiveness of VAL-083 against cisplatin-resistant ovarian cancer as a single agent or in combination with cisplatin. Citation Format: Anne Steino, Michelle Martinez-Rivera, Guanghan He, Xiaolei Xie, Jeffrey A. Bacha, Dennis M. Brown and Zahid H. Siddik. ACTIVITY OF DIANHYDROGALACTITOL (VAL–083) IN OVARIAN TUMOR MODELS, SENSITIVE OR RESISTANT TO CISPLATIN [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr NTOC-108.
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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".