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Enregistrement 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 sur OpenAlexaff
Jeffrey Bacha, Michelle Martinez-Rivera, Guanghan He, Xiaolei Xie, Anne Steinø, Sarath Kanekal, Dennis Brown, Zahid H. Siddik

Notice bibliographique

RevueClinical Cancer Research · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueCancer-related Molecular Pathways
Établissements canadiensDelmar (Canada)
Organismes subventionnairesnon disponible
Mots-clésCarboplatinCisplatinOvarian cancerDNA damageCancer researchMedicineSerous carcinomaOvarian carcinomaOncologyMutantCancerInternal medicinePharmacologyBiologyChemotherapyDNAGeneticsGene

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,192
Tête enseignante GPT0,475
Écart entre enseignants0,282 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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