Abstract P5-03-11: Sensitivity to cell cycle inhibitors in taxane resistant breast cancer models
Notice bibliographique
Résumé
Abstract Background: The use of anthracycline and taxane chemotherapy has improved overall and disease-free survival in breast cancer. However these agents have significant toxicity. In addition, breast cancers can acquire or possess intrinsic chemoresistance. It is imperative to identify patients who will benefit most from adjuvant taxane treatment and those with resistant tumours who could be spared unnecessary toxicity. Methods: A panel of in vitro derived cell lines models of taxane resistance were generated by serial culture in escalating doses of either paclitaxel or docetaxel until resistance was achieved. Taxane resistant cells were characterised by 2D growth, cell cycle and apoptosis analyses. Genomic profiling using the NanoString® platform was performed to identify differentially expressed genes. The identification of kinases which target the chemoresistant models was achieved through a small molecule kinase inhibitor screen. Effects of selected target kinases on cell proliferation, cell cycle, apoptosis and protein expression were assessed. Results: Resistant cell lines exhibited an IC50 at least 40-fold higher than that of the parental cells and displayed cross-resistance to the non-establishing taxane. Cell cycle analysis revealed taxane treatment failed to induce G2/M arrest in the resistant models. A reduced apoptotic response was demonstrated. Genomic profiling identified pathways associated with the cell cycle as being significantly altered. Dinaciclib, a CDK inhibitor of CDK1, CDK2, CDK5 and CDK9, inhibited taxane resistant cell growth with IC50s comparable to the parental lines. Upon exposure to dinaciclib, cell cycle arrest at G2/M was induced and marked apoptosis demonstrated. A reduction in cyclin B1, PLK1 and pRB was observed by western blotting. Table 1:Sensitivity of taxane resistant cell lines models to paclitaxel and docetaxelCell line modelPaclitaxel (μM)Docetaxel (μM)MDA-MB-231 Parent0.004 ± 0.0030.002 ± 0.003MDA-MB-231 PACR0.184 ± 0.030.017 ± 0.02MDA-MB-231 DOCR0.414 ± 0.0470.262 ± 0.058MCF7 Parent0.004 ± 0.00050.005 ± 0.001MCF PACR0.769 ± 0.1050.07 ± 0.02 Table 2:Gene ontology enrichment analysis of biological process terms significantly over-represented in MDA-MB-231 PACR cell line modelGO TermP-valueFDRpositive regulation of transcription from RNA polymerase II promoter1.11E-162.44E-13positive regulation of cell proliferation9.99E-161.10E-12activation of cysteine-type endopeptidase activity involved in apoptotic process1.43E-106.27E-08negative regulation of apoptotic process2.13E-095.83E-07extrinsic apoptotic signaling pathway8.33E-091.62E-06cell cycle arrest8.89E-091.62E-06positive regulation of cell migration2.83E-084.42E-06 Conclusion: In this study we identified candidate resistance-associated pathways which were differentially expressed between in vitro derived taxane resistant cell line models and the sensitive parental line. The CDK inhibitor, dinaciclib, demonstrated potent activity against the taxane resistant cell line models. Clinical validation to ascertain the role of dinaciclib as a novel therapeutic in the treatment of chemorefractory breast cancer is required. Citation Format: Taylor KJ, Lyttle N, Liao L, Gourley C, Cameron DA, Bartlett JM, Spears M. Sensitivity to cell cycle inhibitors in taxane resistant breast cancer models [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-03-11.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».