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Record W2588242563 · doi:10.1182/blood.v118.21.67.67

Novel Chromosomal Rearrangements and Sequence Mutations in High-Risk Ph-Like Acute Lymphoblastic Leukemia

2011· article· en· W2588242563 on OpenAlexaff
Kathryn G. Roberts, Ryan D. Morin, Jinghui Zhang, Martin Hirst, Richard C. Harvey, Corynn Kasap, Xiang Chen, Michael N. Edmonson, I‐Ming Chen, Neil P. Shah, Meenakshi Devidas, Gregory H. Reaman, Malcolm A. Smith, Ching‐Hon Pui, James R. Downing, Daniela S. Gerhard, Cheryl L. Willman, Mignon L. Loh, Stephen P. Hunger, Marco A. Marra, Charles G. Mullighan

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsBiologyPDGFRBSanger sequencingGene rearrangementGeneticsCancer researchMolecular biologyABLFrameshift mutationMutationGeneTyrosine kinaseSignal transduction

Abstract

fetched live from OpenAlex

Abstract Abstract 67 Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy, and relapsed B-lineage ALL remains a leading cause of cancer death in young people. Recent genomic analyses by our group and others identified a unique subtype of BCR-ABL-negative, high-risk B-ALL, with deletion or mutation of IKZF1 and a gene expression profile similar to BCR-ABL1-positive ALL (Ph-like ALL). Up to 50% of Ph-like patients harbor rearrangements of the cytokine receptor gene, CRLF2, with concomitant JAK mutations detected in ∼30%. However, the nature of genetic alterations activating kinase signaling in the remaining cases is unknown. To identify novel genetic alterations in Ph-like ALL, we performed transcriptome sequencing (RNA-seq) on 11 cases of Ph-like B-ALL (10 from the P9906 Children's Oncology Group trial and 1 from the St Jude Total XV study), and whole genome sequencing (WGS) on two of these. Using multiple complementary analysis pipelines including deFuse, Mosaik, CREST and CONSERTING, we identified novel rearrangements, structural variations and sequence mutations dysregulating cytokine receptor and kinase signaling in 10 cases. Putative rearrangements and sequence mutations were validated using RT-PCR, genomic PCR and Sanger sequencing. The spectrum of alterations included 3 cases with known IGH@CRLF2 rearrangement, 2 cases with the NUP214-ABL1 rearrangement, 1 case each with the in-frame fusions EBF1-PDGFRB, BCR-JAK2 or STRN3-JAK2, and 1 case with a cryptic IGH@-EPOR rearrangement. Detailed analysis of RNA-seq data revealed a 7.5 kb insertion of EPOR downstream of the enhancer domain in the IGH@ locus, which was not detected by fluorescence in situ hybridization. WGS identified an in-frame activating insertion in the transmembrane domain of IL7R (L242>FPGVC) in 1 index case, and recurrence screening identified similar IL7R sequence mutations in 8 cases from the P9906 cohort (N=188). This patient also harbored a focal homozygous deletion removing the first two exons of SH2B3 that was not evident by SNP array analysis. SH2B3 encodes LNK, a negative regulator of JAK2 signaling. Notably, all patients harbor genetic lesions affecting B-lymphoid development (e.g IKZF1), suggesting these events cooperate to drive B-lineage ALL. To determine the frequency of each fusion, candidate RT-PCR was performed on 231 cases from the COG AALL0232 trial of high-risk B-ALL, 40 (17%) of which were identified as Ph-like using Predictor Analysis of Microarrays (PAM). The EBF1-PDGFRB fusion was detected in 3 additional patients, each containing an intact PDGFRB kinase domain. No additional cases of NUP214-ABL1, BCR-JAK2, or STRN3-JAK2 were identified. Phosphoflow analysis on 3 primary ALL samples demonstrated increased CKRL phosphorylation in the NUP214-ABL1 case and tyrosine phosphorylation in the cases with BCR-JAK2 and STRN3-JAK2 fusions. Importantly, this activation was reduced with the tyrosine kinase inhibitors (TKI) imatinib, dasatinib and the T315I inhibitor XL228 in cells harboring the ABL1 fusion, and the JAK2 inhibitor, XL019, in the JAK2-rearranged samples. Furthermore, the novel EBF1-PDGFRB fusion transformed Ba/F3 cells to growth factor independence, induced constitutive activation of pSTAT5, pAkt, pERK1/2, and responded with low IC50 values to imatinib, dasatinib and the specific PDGFRB/FGFR inhibitor, dovitinib. Using complementary genomic approaches we show that rearrangements, sequence mutations and DNA copy number alterations dysregulating cytokine receptor and kinase signaling are a hallmark of Ph-like ALL. These data support the screening of patients at diagnosis to identify those with Ph-like ALL, characterize the genomic lesions driving this phenotype, and to determine those that may benefit from TKI treatment. Disclosures: Hunger: Bristol-Myers Squibb: Author's children own stock in BMS, Membership on an entity's Board of Directors or advisory committees.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.270
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2011
Admission routes1
Has abstractyes

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