Abstract 1944: Integrated analysis of copy number and miRNA profiling in triple negative breast cancer of Latina women
Notice bibliographique
Résumé
Abstract Triple negative breast cancer (TNBC) is a clinically and molecularly heterogeneous disease, which incidence and outcome vary among the different ethnic and racial groups. These tumors are more commonly seen in younger women of African and Latinas/Hispanic descents, usually diagnosed at more advanced stages, with non-localized disease. Molecular studies have shown differences in the biology of these tumors in Latinas as key contributors for high mortality. The main objective of our study was to identify a miRNA signature associated with TNBC of Latina patients by integrating miRNA and array-CGH data. Archived paraffin samples of 32 TNBC and 25 non-TNBC cases from Latina patients, obtained from the Clinical Hospital (UFPR) in Brazil, were profiled for miRNA and array-CGH using the Nanostring and the Agilent SurePrint G3 Human array-CGH platforms, respectively. The miRNA and array-CGH data, obtained in the same samples, was directly integrated and combinatorial target predicted algorithms in conjunction with functional and pathway annotation enrichment systems were performed to identify the most relevant miRNAs and their corresponding gene targets. Eight-nine miRNAs were observed differentially expressed between the TNBC and non-TNBC lesions. Using miRBase and MiRDB target prediction databases 3,378 miRNAs targets were identified. After integration with array-CGH, a number of 15 miRNAs presented concomitant DNA copy number and miRNA alterations, reducing the number of targets to 1,242. Ingenuity pathway analysis identified the most affected canonical pathways, including IL-8, TGF-beta, PI3K-AKT and HER2 signaling pathways. Using our integration approach we were able to identify a robust miRNA signature associated with TNBC of Latina patients and to identify the potential molecular mechanism (s) that underline the observed miRNA deregulation in these patients. This signature revealed miRNAs and corresponding targets biologically relevant, involved in critical cancer signaling pathways and gene networks. Once this signature is functionally validated, its direct role in the aggressive clinical phenotype of these tumors will be determined. In summary, the findings of our study contributes to the identification of race/ethnic specific molecular targets that can set the basis for new TNBC treatments and for the future design of the most appropriate clinical trials and cancer control interventions for Latina women. Funding:This project was supported by the Georgetown University Center of Excellence in Regulatory Science and Innovation (CERSI; U01FD004319), a collaborative effort between the university and the U.S. Food and Drug Administration to promote regulatory science through innovative research and education. This research does not necessarily reflect the views of the FDA. Citation Format: Bruna M. Sugita, Mandeep Gill, Silma R. Pereira, Yara R. Zabala, Aline S. Fonseca, Selene E. Esposito, Catalin Marian, Iglenir J. Cavalli, Enilze MF Ribeiro, Yuriy Gusev, Luciane R. Cavalli. Integrated analysis of copy number and miRNA profiling in triple negative breast cancer of Latina women. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1944.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,000 |
| 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 source (Gemma direct ou Codex distillé), 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 ».