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.
Notice bibliographique
Résumé
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.
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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.
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| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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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.
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