Abstract 2493: Identification of MGMT-binding proteins involved in the negative regulation of angiogenesis and invasion.
Notice bibliographique
Résumé
Abstract Background: Glioblastoma multiforme (GBM) is the most frequent and most aggressive form of primary malignant brain tumors in adults. The dismal prognosis of GBM patients stems from the highly angiogenic and invasive behavior of GBM tumor cells. O6-methylguanine-DNA methyltransferase (MGMT), a DNA repair protein ubiquitously expressed in normal tissues has been extensively characterized for its role in resistance to alkylating agents used in GBM treatment. We reported for the first time an inverse relationship between expression of MGMT and the angiogenic and invasive profile of GBM cell lines. The mechanisms by which MGMT affects angiogenesis and invasion are unknown. We hypothesized that interactions of MGMT with binding proteins (BPs) may account for additional functions beyond its known role as a DNA repair protein. Methods: As a first screening to identify MGMT-BPs with a functional relevance for invasion and angiogenesis, we performed affinity purification of MGMT-BPs following overexpression of FLAG-tagged MGMT and mass spectrometry analysis using 293T-Flag/MGMT and control Flag-tagged empty vector (293T-Flag/EV). Lysates were subjected to affinity purification using an anti-Flag monoclonal antibody covalently attached to agarose resin. The affinity bound FLAG fusion proteins were eluted and separated on SDS-PAGE. Coomassie Blue staining enabled the identification of 6 bands including Flag-MGMT in 293T-Flag/MGMT but not the Flag/EV control. The bands were excised from the gel, subjected to trypsin digestion and identified by liquid chromatography-tandem mass spectrometry. The resultant MS/MS spectra were searched against a proteome database for peptide matching and protein identification. Proteins were identified with high confidence using Scaffold software. Results: Our analysis provided evidence for binding of MGMT to 120 BPs. Using gene ontology (GO) database to search for functional categories, we identified proteins involved in DNA repair, ubiquitin pathway, DNA replication and transcription, RNA metabolism and processing, cell cycle and division, response to stress and cell death. Importantly, we identified proteins involved in cell motility and/or angiogenesis, cytoskeletal-related proteins (15 proteins), small GTPases family and their regulators (10 proteins, such as Rho guanine nucleotide exchange factor 2) and two proteins involved in angiogenesis (Endoribonuclease Dicer and Ribonuclease inhibitor). We also used T98G a human GBM cell line with constitutive expression of MGMT to perform immunoprecipitation of endogenous MGMT (anti-MGMT antibody or the IgG1 isotype control). Mass spectrometry and proteomic analysis of MGMT-BPs in T98G is underway. Conclusion: Our data provide new structural aspects of MGMT and shed light into the multifaceted role of MGMT, which may lead to the identification of novel therapeutic targets in GBM. Citation Format: Siham Sabri, Yaoxian Xu, Nicolas Stifani, Bassam S. Abdulkarim. Identification of MGMT-binding proteins involved in the negative regulation of angiogenesis and invasion. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2493. doi:10.1158/1538-7445.AM2013-2493
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 | 0,000 | 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) | 0,003 | 0,002 |
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 ».