Abstract 926: Whole genome and transcriptome sequencing defines the spectrum of somatic changes in high-risk neuroblastoma
Notice bibliographique
Résumé
Abstract The NCI's Therapeutically Applicable Research to Generate Effective Targets (TARGET) initiative uses state-of-the-art genome-wide approaches to identify therapeutic targets for pediatric cancers. Applications of 2nd-generation sequencing technologies to the analysis of adult solid tumors and hematopoietic malignancies have led to novel, often clinically relevant insights into these diseases. The objective of this study is to utilize 2nd-generation sequencing approaches on a highly annotated set of ten high-risk neuroblastomas (NBLs). We performed whole genome shotgun sequencing of six stage 4 MYCN-non-amplified and four stage 4 MYCN-amplified NBL TARGET cases and matched peripheral blood, as well as whole transcriptome sequencing (RNA-Seq) of the corresponding tumor RNA. The tumor and normal genomes were sequenced to 30X haploid coverage, and an average 10.3 Gb of aligned sequence was generated for each tumor transcriptome. The level of sequencing redundancy allowed us to achieve at least 10X coverage across 90% of the genome enabling genome-wide detection of sequence and copy number changes in the tumor DNA. We used alignment and de novo assembly approaches to identify somatic and germline SNVs, indels, structural variants, regions of copy number gains and losses, and genome rearrangements. We used RNA-Seq data to determine whether the detected sequence changes were expressed, and to identify transcripts differentially or alternatively expressed between MYCN-amplified and non-amplified cases. Our analysis of tumor and normal genomes identified an average of 1664 candidate somatic mutations per case, the majority of which were SNVs and small indels falling within introns or intergenic sequence. We also detected two candidate germline mutations in the ALK oncogene, one of which was previously characterized in NBL. An average of 10% of candidate somatic mutations in coding sequence was expressed in the transcriptome representing candidate oncogenic events. In addition, we detected and validated using PCR 9 novel genomic rearrangements resulting in expressed products, 5 of which were somatic and 4 of which were germline. We report on two novel somatic gene fusions, between TRIM37 on chromosome 17 and RNF121 on chromosome 11, and between LSAMP and STAG1 on chromosome 3, previously uncharacterized in NBL. The fusions did not recur in our sample set. This work provides an initial genome-wide view of the landscape of somatic changes that occur in high-risk neuroblastoma and highlights novel candidate oncogenic events that may drive the malignancy. Ongoing efforts will catalogue discovered somatic mutation frequencies in a large set of cases and explore the role of germline DNA variations in NBL tumorigenesis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 926. doi:10.1158/1538-7445.AM2011-926
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 ».