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Record W2914654146 · doi:10.1182/blood-2018-99-119235

Germline GAB2 Mutations in Childhood Acute Lymphoblastic Leukemia

2018· article· en· W2914654146 on OpenAlexaff
Adam J. de Smith, Geneviève Lavoie, Kyle M. Walsh, Sumeet Aujla, Erica Evans, Helen M. Hansen, Ivan Smirnov, Alice Y. Kang, Martin Zenker, John Ceremsak, Elliot Stieglitz, Roberta McKean‐Cowdin, Catherine Metayer, Philippe P. Roux, Joseph L. Wiemels

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
Fundersnot available
KeywordsNeuroblastoma RAS viral oncogene homologSanger sequencingMultiplex ligation-dependent probe amplificationGermline mutationGeneticsBiologyGermlineKRASExome sequencingExomeCancer researchMutationGeneExon

Abstract

fetched live from OpenAlex

Abstract Recent studies using next-generation sequencing of selected individuals, such as those with familial leukemia or congenital syndromes, have identified rare and highly penetrant germline mutations that predispose to childhood acute lymphoblastic leukemia (ALL). High hyperdiploidy (HD), the most common cytogenetic subtype of childhood ALL, is enriched in children with RASopathies who develop ALL and, similarly, a high proportion of ALL patients with germline ETV6 or IKZF1 mutations presented with the HD subtype. Here, we aimed to identify novel predisposition genes in a selected group of HD-ALL patients. Targeted sequencing of 538 cancer-relevant genes was carried out using the UCSF500 Cancer Gene Panel in diagnostic bone marrow (i.e. tumor) DNA from 57 HD-ALL patients from the California Childhood Leukemia Study (CCLS). HD-ALL patients were selected based on absence of somatic KRAS or NRAS hotspot mutations detectable by Sanger sequencing, and absence of somatic copy number deletions from multiplex ligation-dependent probe amplification (MLPA) assays. After filtering out likely somatic mutations (mutant allele fraction <0.44), and restricting to variants with low frequency in unselected individuals (allele frequency <0.01% in the Exome Aggregation Consortium, ExAC) and with predicted functional effects (Combined Annotation Dependent Depletion, CADD score ≥20), we identified 151 putative predisposing mutations. Of 41 mutations of interest selected for validation, 37 (90.2%) were confirmed as germline in origin via Sanger sequencing of remission or newborn bloodspot DNA. Rare and predicted functional germline mutations in known (NBN, SH2B3, ETV6, CREBBP, MSH6) or suspected (MLL, ABL1, FLT3, MYH9) ALL predisposition genes were identified in nine out of 57 patients (15.8%). Three additional patients harbored germline mutations in the GRB2-associated binding protein 2 (GAB2), a known binding partner of PTPN11-encoded SHP2 and activator of the ERK/MAPK and PI3K/AKT pathways. Two GAB2 mutations, a missense mutation S592F and frameshift mutation P621fs, were predicted to be highly functional (CADD scores = 34 and 36 respectively) and absent in ExAC. Frequency of rare and damaging GAB2 mutations was significantly higher in our patient set (2.6%) than in ExAC (0.28%, P = 2.70 x 10-6). We replicated this finding in sequencing data from 309 ALL patients in the TARGET (Therapeutically Applicable Research to Generate Effective Treatments) project (0.81% vs. 0.28%, P = 0.015). Patient GAB2 mutations were cloned into HEK293 cells and, following EGF stimulation, we found that the P621fs mutation reduced SHP2 binding and ERK1/2 phosphorylation but increased AKT phosphorylation. This suggested possible Ras-independent leukemogenic effects, supported by a lack of somatic Ras pathway mutations in the three GAB2 mutant patients. Additional functional analyses and sequencing of larger patient cohorts will be required to elucidate the role of germline GAB2 mutations in childhood ALL. 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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

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 head0.011
GPT teacher head0.278
Teacher spread0.268 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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