Abstract LB-391: Hsa_circ_001783 regulates breast cancer progression via sponging miR-200c
Notice bibliographique
Résumé
Abstract Introduction: Increasing evidence suggests circRNAs exert vital functions in tumor progression via sponging miRNAs. However, the role of circular RNAs in breast cancer remains mostly unclear. Here we reported the molecular mechanisms of a novel circRNA, hsa_circ_001783 in regulating breast cancer progression and its ability in predicting clinical outcomes by integrating high throughput computation, experimental technologies in vitro and clinical investigation. Methods: We extracted sequences and annotations of circRNAs and miRNAs from circbase and miRbase respectively. Four algorithms were used to predict the potential bindings of miRNAs to the conserved sequences of individual circRNAs. Computationally screening Ingenuity knowledge database (Qiagen), PubMed and Embase identified breast cancer associated miRNAs and their related functions in cancer. Five essential functional features were used to score the strength associations between miRNAs and breast cancer, which was subsequently employed to rank the network branches across circRNA-miRNA-breast cancer. Expression levels of hsa_circ_001783 in human breast tissue and cancer cells were quantified by FISH and qPCR. The effects of knocking down hsa_circ_001783 on breast cancer cells were examined by Edu, CCK-8, colony formation and transwell assays. K-M model was used to define the predictor performance of hsa_circ_001783 in a Chinese breast cancer cohort of 128 patients. Results: Our computational pipeline identified hsa_circ_001783 as the one with highest score out of 594 breast cancer-associated circRNA candidates. We found the circRNA was enriched in cytoplasma and overexpressed in breast tumor as compared to paired non-cancerous tissue. High expression of hsa_circ_001783 correlated with higher tumor burden (p=0.047) and poor overall survival (p=0.025) in 128 patients. Knock-down of hsa_circ_001783 remarkably inhibited the proliferation and invasion of MDA-MB-231 and MDA-MB-468 cells. We found hsa_circ_001783 increased significantly by 1.5-2 folds while 7 miRNAs, predicted targets of hsa_circ_001783, were remarkably reduced (fold change>1.5) in mRNA expression levels in BT549, MDA-MB-468 and MDA-MB-231 as compared with MCF-7 breast cancer cell lines. Among all the targets, miR-200c was the one in the strongest correlation with hsa_circ_001783 in expression levels. Knockdown of hsa_circ_00178 in MDA-MB-231 breast cancer cells suppressed expression of miR-200c-targeted genes ZEB1, ZEB2 and CCNA2. The expression level of hsa_circ_001783 in human breast cancer tissues negatively correlated with expression of miR-200c (p=0.0286), but positively correlated with that of ZEB1 (p=0.002), ZEB2 (p=0.0001) and CCNA2 (p=0.005). Conclusion: Hsa_circ_001783 regulates breast cancer progression via sponging miR-200c. The circRNA may serve as a novel predictor of clinical outcomes for breast cancer. Citation Format: Zihao Liu#, You Zhou#, Gehao Liang, Yun Ling, Luyuan Tan, Yan Wang, Wenjing Zhong, Chang Gong*. Hsa_circ_001783 regulates breast cancer progression via sponging miR-200c [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-391.
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 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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».