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Record W2400235072 · doi:10.1158/1557-3265.ovca15-a01

Abstract A01: A comparison of the mechanisms and cytotoxic activity of dianhydrogalactitol (VAL-083) to cisplatin in ovarian tumor models harboring wild-type and mutant p53.

2016· article· en· W2400235072 on OpenAlexaff
Jeffrey Bacha, Michelle Martinez-Rivera, Guanghan He, Xiaolei Xie, Anne Steinø, Sarath Kanekal, Dennis Brown, Zahid H. Siddik

Bibliographic record

VenueClinical Cancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsDelmar (Canada)
Fundersnot available
KeywordsCarboplatinCisplatinOvarian cancerDNA damageCancer researchMedicineSerous carcinomaOvarian carcinomaOncologyMutantCancerInternal medicinePharmacologyBiologyChemotherapyDNAGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Ovarian cancers are usually treated with platinum-based therapies, which produce a 70% response rate. However, many patients relapse as tumors become resistant to cisplatin and carboplatin, resulting in a 5-year survival rate of about 20%. Onset of drug resistance is a major factor limiting the clinical utility of platinum-based therapeutic regimens drugs and, therefore, new agents are needed to circumvent resistance. Dianhydrogalactitol (VAL-083) is a bi-functional alkylating agent, whose cytotoxic activity is due to the formation of DNA cross links at the N7 position of guanine. Unlike cisplatin and carboplatin, which predominantly form intrastrand DNA cross-links, VAL-083 derives its anti-cancer activity interstrand DNA cross-links. More importantly, VAL-083 has demonstrated clinical activity against a range of tumor types, including ovarian cancer in historical NCI-sponsored clinical studies. Platinum drug resistance is normally ascribed to several mechanisms, with mutation in wild-type p53 playing a critical role, particularly in high-grade ovarian serous carcinoma (HGOSC), where the incidence of this mutation can be substantial. However, recent analysis of the TCGA database indicates that the survival rate in wild-type p53 HGOSC is no better or perhaps even worse. Using a 5-day MTT assay and fitting a sigmoidal curve to the dose-response data to determine IC50 values, we have similarly found that resistance to cisplatin in a panel of ovarian tumor models is greater when p53 is wild-type (median IC50: 4-7 µM vs. 1-2 µM for mutant/null p53 models; in comparison, sensitive wild-type p53 A2780 cells have an IC50 of 0.2-0.3 μM). Previous studies in our lab suggest that factors downstream from p53, including MDM4 and p21, may contribute to cisplatin-resistance in ovarian cancer models with high cisplatin-resistance and wild-type 53, like 2780CP-16. We thus sought to investigate the potential of VAL-083 to circumvent cisplatin-resistance in five p53 wild-type ovarian cancer models: one cisplatin-sensitive A2780, and four cisplatin-resistant 2780CP-16, OVCAR-10, Hey and OVCA-433. IC50 values of VAL-083 were generated using the MTT assay and sigmoidal curve fitting of data, as described above. The baseline IC50 for VAL-083 against A2780 cell was about 0.5 μM. The IC50 for VAL-083 in the cisplatin-resistant cell-lines 2780CP-16, OVCAR-10, Hey and OVCA-433 were 4- to 7-fold greater; however, VAL-083 was substantially more potent in comparison to cisplatin in these models where corresponding IC50 values were 10- to over 25-fold greater. These results demonstrate that there is only partial cross-resistance between cisplatin and VAL-083 further suggesting distinct modes of action for the two drugs. In order to examine whether the partial circumvention of cisplatin-resistance was p53-dependent, cytotoxicity was determined in isogenic HCT-116p53-/- and HCT-116p53+/+ models. These studies demonstrated that loss of p53 increased resistance to cisplatin by 2-5-fold whereas loss of p53 only increased resistance to VAL-083 about 1.7-fold. These results suggest that VAL-083 is less dependent on p53 for its cytotoxic activity. Immunoblots confirmed this in 2780CP-16 cells, where VAL-083 was more effective than cisplatin at increasing p53 and p21 levels, and induced relatively greater Ser-15 and Ser-20 phosphorylations, further supporting different modes of action for the two drugs. In contrast, both drugs were equally effective in inducing these markers of DNA damage in A2780 cells. The non-overlapping mechanisms of action suggested a potential therapeutic benefit for combinations of VAL-083 with cisplatin. We have previously reported that the combination of VAL-083 with cisplatin in wild-type p53 NSCLC models H460 and A549, and mutant p53 NSCLC H1975 demonstrated significant super-additivity (p<0.05) and synergy (CI < 1) in all three cell-lines. Taken together these results demonstrate the effectiveness of VAL-083 against refractory cisplatin-resistant ovarian cancers and raise the potential for treatment of platinum-resistant ovarian cancers or a combination regimen with cisplatin. (Supported in part by NCI RO1 CA160687 to ZHS). Citation Format: Jeffrey A. Bacha, Michelle Martinez-Rivera, Guanghan He, Xiaolei Xie, Anne Steino, Sarath Kanekal, Dennis M. Brown, Zahid H. Siddik. A comparison of the mechanisms and cytotoxic activity of dianhydrogalactitol (VAL-083) to cisplatin in ovarian tumor models harboring wild-type and mutant p53. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr A01.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.192
GPT teacher head0.475
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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