Abstract A078: Differential functions of splicing factors in breast cancer initiation and metastasis
Notice bibliographique
Résumé
Abstract Cancer cells display aberrant alternative splicing profiles, leading to the production of isoforms that can increase cell proliferation and migration, resistance to apoptosis, or alter cell metabolism. Recently, recurrent somatic mutations in components of the splicing machinery have been identified in human tumors, raising a new interest in the field and suggesting that alterations in splicing factors are a new hallmark of cancer. Splicing factors elicit changes in splicing in a concentration-dependent manner. Thus, changes in the expression of these proteins, as reported in different types of cancers, can affect the splicing of multiple genes and are likely involved in splicing deregulation in cancer, even in the absence of mutations. Changes in the expression of splicing factors have been reported in various types of cancers, including breast. We demonstrated previously that the splicing factor SRSF1 is upregulated in human breast cancers and can transform mammary epithelial cells in vivo and in vitro. SRSF1 is a prototypical member of the SR protein family, composed of 12 members sharing structural similarities. However, little is known about differences and redundancies in their splicing targets and thus in their specific biological functions. We are now investigating whether additional splicing factors also promote mammary epithelial cell transformation by using models that mimic the correct biological context in which tumors arise. We first identified splicing factors overexpressed at the transcript and protein levels in a large collection of human breast tumors and cancer cell lines. We then compared the ability of 10 selected splicing factors to transform human mammary epithelial MCF-10A cells grown in organotypic 3-D culture. These cells undergo a 16-day differentiation program, forming growth-arrested, hollow acinar structures with polarized architecture, similar to the terminal units of mammary ducts. Various breast cancer oncogenes are known to disrupt acinar growth and/or architecture. We assessed how splicing-factor overexpression affects differentially cell proliferation and apoptosis, as well as cell migration and invasion. Interestingly, only certain splicing factors are oncogenic in this context, suggesting functional differences. Furthermore, specific splicing factors increase cell migration and invasion, without promoting transformation. We are now characterizing the splicing targets relevant for specific splicing-factor-mediated transformation by next-generation RNA-sequencing. Furthermore, we are investigating which splicing factors are necessary or sufficient to promote metastatic properties of human breast cancer cell lines in vitro and in vivo. Finally, we have identified splicing factors that cooperate specifically with the MYC oncogene and are co-expressed with MYC in human breast tumors. In conclusion, by identifying oncogenic splicing factors, their targets and their regulators, we hope to establish novel targets for targeted cancer therapies. Citation Format: Olga Anczukow, Kuan-Ting Lin, Shipra Das, Jie Wu, Martin Akerman, Senthil K. Muthuswamy, Adrian R. Krainer. Differential functions of splicing factors in breast cancer initiation and metastasis. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr A078.
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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 | 0,000 | 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 | 0,000 |
| 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) | 0,000 | 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 ».