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Record W3097549198 · doi:10.1182/blood-2020-136190

Frequency and Prognostic Significance of Recurrent Gene Mutations in Pediatric B-ALL: Report from the DFCI ALL Consortium

2020· article· en· W3097549198 on OpenAlexaff
Giacomo Gotti, Mäneka Puligandla, Kristen E. Stevenson, Brenton G. Mar, Barbara L. Asselin, Uma H. Athale, Luis A. Clavell, Peter D. Cole, Lisa Gennarini, Justine M. Kahn, Kara M. Kelly, Caroline Laverdière, Jean‐Marie Leclerc, Bruno Michon, Marshall A. Schorin, Maria Luisa Sulis, Thai Hoa Tran, Jennifer Welch, Kimberly Stegmaier, Marian H. Harris, Lewis B. Silverman, Yana Pikman

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsCentre hospitalier de l'Université LavalCentre Hospitalier Universitaire Sainte-JustineMcMaster UniversityCentre hospitalier universitaire de QuébecMcMaster Children's Hospital
Fundersnot available
KeywordsKRASNeuroblastoma RAS viral oncogene homologMedicineOncologyCDKN2ACancer researchPTENInternal medicineCancerBiologyGeneticsPI3K/AKT/mTOR pathway

Abstract

fetched live from OpenAlex

The application of next-generation sequencing (NGS) approaches to leukemia markedly expanded our understanding of the molecular landscape of pediatric acute lymphoblastic leukemia (ALL), but NGS integration into clinical care and therapeutic decision making is still limited. The prognostic impact of discovered mutations in uniformly treated patients with newly diagnosed B-ALL is not well characterized, and there is no consensus regarding the clinical significance of many of these findings. We investigated the frequency of mutations affecting common molecular pathways in pediatric B-ALL that are potentially druggable with targeted therapies, to define the prognostic role of these mutations, as measured by end-induction minimal residual disease (MRD) and event-free survival (EFS). We analyzed 159 patients (median age 6 years, range 1-18) with newly diagnosed Ph-negative B-ALL treated between 2005-2015 according to the Dana-Farber Cancer Institute (DFCI) ALL Consortium Protocols 05-001 and 11-001. Diagnostic leukemia samples were sequenced using a validated clinical NGS panel. We focused on mutations affecting the following pathways: Ras (NRAS, KRAS, PTPN11, NF1 and BRAF), cell cycle regulation (CCND3, CDKN2A/B and RB1), PI3K signaling (PTEN, PIK3CA, PIK3R1, PIK3C2B, MTOR, TSC1 and TSC2), Polycomb repressive complex 2 (PRC2) (EED, EZH2 and SUZ12), and JAK/STAT signaling (CRLF2, JAK2, JAK3, MPL, SH2B3 and SOCS1). Additionally, we analyzed mutations affecting CREBBP, FLT3, PAX5, SETD2 and TP53. Mutations occurring in the ExAC database at a frequency greater than 0.01% were excluded. A Fisher exact test and Wilcoxon rank sum test were used for categorical and continuous variables. High end-induction MRD, defined as > 10-3, was assessed by an Ig-TCR PCR assay. EFS was estimated using Kaplan and Meier method and tested between groups using a log-rank test. Induction death/failure, relapse or death were considered as events. Overall, 108 of the 159 patients (68%) carried at least one mutation in the studied genes. Most common mutations were in the Ras pathway (47%), CREBBP (9%), JAK pathway (8%), FLT3 (8%), PI3K pathway (5%), PAX5 (4%), SETD2 (4%), TP53 (4%), cell cycle regulation (3%) and PRC2 complex (3%). We investigated the distribution of mutations among common cytogenetic groups: ETV6-RUNX1, high hyperdiploidy (HHD) (51-65 chromosomes), hypodiploidy (<45 chromosomes), KMT2A-rearranged, TCF3-PBX1, and intra-amplification chromosome 21 (iAMP21). There was a strong association between TP53 and hypodiploidy (43% vs 2%; p=0.001). Ras pathway and FLT3 mutations were enriched in HHD (67% vs 39%; p=0.004) and (17% vs 4%; p=0.016), respectively. FLT3 mutations were mutually exclusive with ETV6-RUNX1 (12% vs. 0%, p=0.038), and Ras pathway mutations were rare in this subgroup (p=0.018). PAX5 mutations were enriched in children >10 years of age (p=0.035). There were no associations with sex. Ras pathway mutations were associated with high end-induction MRD (68% vs 42%; p=0.045), and this association was stronger for clonal (variant allele frequency (VAF) >25%) mutations (n=33) (63% vs 19%; p=0.0002). Focusing on HHD, CREBBP mutations frequently co-occurred with clonal Ras pathway mutations (83% vs 17%; p=0.032). Among HHD patients with evaluable MRD (n=33), 7 patients had high MRD, and 3 of these had CREBBP mutations (p=0.052). The analyzed cohort was enriched for higher risk ALL disease (Table 1). The 5-year EFS was 80%±3% among these 159 patients. Overall, no EFS difference was observed based on Ras pathway (p=0.35). Among HHD ALL, the presence of CREBBP or clonal Ras pathway mutations was significantly associated with inferior 5-yr EFS (50%±20% vs 97%±3%; p=0.0006, Figure 1) and (70%±13% vs 100%; p=0.007, Figure 2), respectively. In conclusion, our findings provide insight into the prognostic significance of the most common mutations in pediatric HHD B-ALL in a uniformly treated cohort of patients as part of the DFCI ALL Consortium. The presence of CREBBP and clonal Ras pathway mutations may be associated with upfront chemotherapy resistance as demonstrated by high end-induction MRD. Further analysis of Ras pathway mutations segregated by VAF is warranted. Future trials may integrate these findings into risk stratification of HHD ALL. With prospective continued clinical use of NGS assays, we will further clarify the role of mutations and their contribution to disease outcomes in B-ALL. Disclosures Mar: Blueprint Medicines Corporation: Current Employment, Current equity holder in publicly-traded company. Stegmaier:Novartis: Research Funding; Auron Therapeutics: Consultancy. Silverman:Takeda: Other: advisory board; Servier: Other: advisory board; Syndax: Other: advisory board.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.035
GPT teacher head0.292
Teacher spread0.258 · 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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Citations1
Published2020
Admission routes1
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