Abstract 4795: A novel gene fusion in glioblastoma and a radiation response methylation signature identified by genomic characterization of glioma sphere-forming cells
Notice bibliographique
Résumé
Abstract Purpose: High fidelity models of the lethal primary brain tumor glioblastoma (GBM) are essential to develop new therapies. Glioma sphere-forming cells (GSCs) are derived from surgical specimens and are thought to play important roles in tumor maintenance and treatment resistance. We performed genomic characterization of the largest reported panel of GSCs. We hypothesized that GSCs would recapitulate the genomic alterations of their GBMs of origin while identifying novel changes identifiable only in a pure tumor cell population. Methods: All GSCs were obtained at the time of surgical resection and all analyses were conducted at early passage. We performed exome and transcriptome sequencing, DNA methylation profiling (Illumina Infinium 450K Bead Arrays) and DNA copy number determination (Affymetrix OncoScan). Radiation (RT) sensitivity was determined by clonogenic survival and in vivo survival by orthotopic xenograft. Results: We analyzed 43 GSCs, 40 of which had tissue available from their tumors of origin. Somatically mutated genes previously described in GBM, such as TP53, EGFR, PTEN, NF1, PIK3CA and RB1, were found at similar mutation frequencies. Likewise, DNA copy number variations were similar to their matched tumor and those reported by the TCGA, with novel or more pronounced alterations, such as MYC application and QKI deletion, identified in the GSCs. GSCs were classified into TCGA GBM subtypes by expression signatures, identifying a subset of GSCs with a subtype differing from their matched tumors that correlated to decreased stromal enrichment. GSCs exhibited upregulation of self-renewal pathways, such as MYC, WNT, and NOTCH, and of stem-cell factors, such as MSI1, NESTIN, OLIG2, and SOX2, consistent with the stem-like phenotype attributed to GSCs. Transcript analyses identified the previously reported FGFR3-TACC3 and EGFR-SEPT14 gene fusions as well as a novel KIF1B-KMT2A (MLL) fusion, which was found to have been retained in the matching recurrent GBM as well as the GSC derived from the recurrence. A signature derived by the differential methylation pattern of RT sensitive vs. resistant GSCs was applied to the subset of TCGA cases that received upfront RT. Survival by methylation class in this subset was significantly different (median survival 84 vs. 61 weeks; HR 1.64 adjusting for patient age, p-value<0.008), suggesting this signature is predictive of clinical RT response. Conclusions: Based on genomic analyses, GSCs are robust models of GBM which can be used for therapeutic development. We have identified a novel gene fusion involving MLL with a predicted driving role suggesting a new mode of gliomagenesis. A methylation signature predictive of RT response may have potential for personalizing RT treatment of GBM patients and provides insights into RT sensitivity phenotypes. Citation Format: Qianghu Wang, Ravesanker Ezhilarasan, Lindsey D. Goodman, Joy Gumin, Siyuan Zheng, Kosuke Yoshihara, Peng Sun, Jie Yang, Tim Heffernan, Giulio Draetta, Kenneth D. Aldape, Frederick F. Lang, Roel G.W. Verhaak, Erik P. Sulman. A novel gene fusion in glioblastoma and a radiation response methylation signature identified by genomic characterization of glioma sphere-forming cells. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4795. doi:10.1158/1538-7445.AM2015-4795
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) | 0,001 | 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 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 ».