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Enregistrement W2585466194 · doi:10.1182/blood.v114.22.704.704

Next Generation Transcriptomic Resequencing Identifies Novel Genetic Alterations in High-Risk (HR) Childhood Acute Lymphoblastic Leukemia (ALL): A Report From the Children's Oncology Group (COG) HR ALL TARGET Project.

2009· article· en· W2585466194 sur OpenAlexaff
Charles G. Mullighan, Ryan D. Morin, Jinghui Zhang, Martin Hirst, Yongjun Zhao, Chunhua Yan, Richard Finney, Michael N. Edmonson, Xiaoping Su, Kenneth Buetow, William L. Carroll, I‐Ming Chen, Meenakshi Devidas, Daniela S. Gerhard, Richard C. Harvey, Ying Hu, Mignon L. Loh, Gregory H. Reaman, Mary V. Relling, Malcolm A. Smith, James R. Downing, Stephen P. Hunger, Cheryl L. Willman, Marco A. Marra

Notice bibliographique

RevueBlood · 2009
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Lymphoblastic Leukemia research
Établissements canadiensBC Cancer AgencyGenome British Columbia
Organismes subventionnairesnon disponible
Mots-clésBiologyRefSeqGeneticsGeneOncologyBioinformaticsGenomeMedicine

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 704 Relapsed ALL is a leading cause of childhood cancer death, and the biologic factors responsible for relapse are poorly understood, particularly in cases lacking sentinel chromosomal alterations. Recent studies from the Children's Oncology Group high risk ALL TARGET (Therapeutically Applicable Research to Generate Effective Targets) project that used genome-wide profiling of DNA copy number alterations and candidate gene resequencing have identified novel biomarkers of relapse (IKZF1 alteration) and therapeutic targets (JAK mutation). As a complementary approach to identify novel genomic alterations, we used second generation sequencing technology to sequence the tumor transcriptome of three cases from the COG P9906 high risk (HR) B-precursor ALL trial. The selected cases had previously been profiled by high resolution SNP and gene expression arrays and candidate gene resequencing, and lacked known sentinel chromosomal rearrangements. Each case bore features previously associated with poor treatment outcome: a gene expression profile (GEP) similar to that of BCR-ABL1 positive ALL (all cases), deletion or mutation of IZKF1 (two cases), and JAK mutation (JAK2 R867Q, one case). cDNA libraries were generated from poly-A enriched RNA and 36-50 base paired-end sequencing performed using the Illumina Genome Analyzer. Sequence alignment, variant detection and fusion transcript identification were performed using custom scripts and multiple published reference alignment and de-novo assembly algorithms. A total of 115-127 million total and 93-97 million mapped, unique reads were obtained per case. The average depth of coverage of Refseq exons ranged from 25- to 39-fold. A minimum of 5 putative fusion transcripts were identified per case, some of which were known from prior transcriptome sequencing to be recurring false positives. However, a novel transcript with an in-frame fusion of exon 9 of the striatin gene STRN3 to exon 18 of JAK2 (STRN3-JAK2) was identified in one case, and confirmed by RT-PCR and direct Sanger sequencing. Fusion of NUP214 to ABL1 was identified in a second case and also confirmed by direct sequencing. The NUP214-ABL1 rearrangement has previously only been identified in T-lineage ALL. In this case, the translocation was accompanied by amplification of the NUP214-ABL1 region at 9q. RT-PCR screening of an additional 60 high-risk ALL cases with GEP data suggestive of kinase alteration identified an additional two cases with NUP214-ABL1 fusion, each of which was accompanied by NUP214-ABL1 amplification. These two novel fusion transcripts are predicted to result in aberrant kinase signaling, and are candidates for novel therapeutic intervention. Both occurred in ALLs with a BCR-ABL1-like GEP that lacked known JAK mutations, suggesting that additional novel activating kinase mutations can be discovered via detailed sequence analysis of the 50% of BCR-ABL1-like ALLs that do not have JAK mutations. Aberrant splice variants and truncated isoforms arising from DNA copy number alterations, including internal deletions of PAX5 and truncating deletions of BTG1 were also identified using the transcriptome sequencing data. In addition, these data identified over 400 candidate non-synonymous single nucleotide and insertion/deletion variations in each patient. Known mutations involving PAX5, IKZF1 and JAK2 were robustly identified. Whole genome sequencing of matched normal DNA is underway to remove germline variation from the list of putative variants, and transcriptomic sequencing of additional cases of HR childhood ALL are being performed. Together, these data indicate that transcriptomic sequencing is a powerful method to identify novel genetic alterations in ALL, and may be used to identify novel targets for therapeutic intervention. Disclosures: No relevant conflicts of interest to declare.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,910
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,028
Tête enseignante GPT0,287
Écart entre enseignants0,260 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations20
Publié2009
Routes d'admission1
Résumé présentoui

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