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Record 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 on 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

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsBC Cancer AgencyGenome British Columbia
Fundersnot available
KeywordsBiologyRefSeqGeneticsGeneOncologyBioinformaticsGenomeMedicine

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.287
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2009
Admission routes1
Has abstractyes

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