MétaCan
Menu
← Back to cohort

RUNX1 Mutation in Cytogenetically Normal Acute Myeloid Leukemia : Clinical Implications, Co-Mutation Analysis

2016· article· en· W2613537197 on OpenAlexaff
Seung-Shin Lee, Jae‐Sook Ahn, Tae-Hyung Kim, Hyeoung Joon Kim, Yeo‐Kyeoung Kim, Seo‐Yeon Ahn, Sung‐Hoon Jung, Deok‐Hwan Yang, Je‐Jung Lee, Hee Jung ParK, Seung Hyun Choi, Chul Won Jung, Jun‐Ho Jang, Hee‐Je Kim, Joon Ho Moon, Sang Kyun Sohn, Jong-Ho Won, Sung‐Hyun Kim, Zhaolei Zhang, Dennis Dong Hwan Kim

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsCEBPANPM1Neuroblastoma RAS viral oncogene homologRUNX1Myeloid leukemiaMutationLeukemiaBiologyMyeloidOncologyMedicineCancer researchInternal medicineGeneticsKaryotypeGeneHaematopoiesisChromosomeStem cellKRAS

Abstract

fetched live from OpenAlex

Abstract Background and Objectives Acute Myeloid Leukemia (AML) is a cytogenetically and molecularly heterogeneous disease. In the recent decades, many genetic mutations and their clinical significances in AML have been identified with the development of new genomics technology. Based on these advances, new 2 entities were added to the WHO 2008 classification : AML with mutated NPM1 and AML with mutated CEBPA. Likewise, AML with RUNX1 mutation are now considered as a new provisional entity in the next update of WHO classification. In this work, we characterized patients with cytogenetically normal AML according to RUNX1 mutational status and analyzed several co-mutations by next generation sequencing. Patients and Methods A total of 419 patients were included in the present study who met the following eligibility criteria: 1) age ≥ 15 years; 2) a diagnosis of AML with normal karyotype confirmed by conventional cytogenetic analysis. Analysis of genetic mutations were performed using targeted resequencing by Illumina Hiseq 2000 (Sureselect custom probe set targeting 94 myeloid gene panel including RUNX1 mutation). Samples for the confirmation of first complete response were also analyzed in 163 patients. The majority of patients (97%) received '3+7' standard induction chemotherapy. Median age was 53(range 15-84). Results Overall, most common mutations for this cohort were NPM1(33.9%), DNMT3A(30.3%), NRAS(20.2%), IDH2(15.0%), FLT3(12.2%), CEBPA(11.1%). RUNX1 mutations were found in 22 of 419 (5.4%) patients. 7 of 13 available samples in complete remission still had RUNX1 mutation. The patients with RUNX1 mutations were older than those with wild-type RUNX1. (p=0.006) and RUNX1 mutation had a trend of male preponderance. The WBC count and blast percentage of peripheral blood and bone marrow were not different according to RUNX1 mutational status. The complete response rate was significantly lower in RUNX1 mutated group compared with wild-type group. (57% vs. 84%, p=0.005) In univariable survival analysis, RUNX1 mutations were significantly associated with inferior event-free survival (EFS) (p<0.001), relapse-free survival (RFS) (p=0.009) and overall survival (OS) (p=0.002). However, in multivariable analysis, RUNX1 mutation was not an independent prognostic factor for inferior EFS (hazard ratio(HR) 1.48, p=0.286), RFS (HR 2.15, p=0.057) OS (HR 1.14, p=0.716). Co-mutation analysis revealed that ASXL1 (26%,p=0.001), KRAS (26%, p=0.009), BCOR (16%, p=0.032) were correlated with RUNX1 mutation. None of the patients with RUNX1 mutation had NPM1 mutation and only one patient had CEBPA mutation. Conclusion In cytogenetically normal AML, RUNX1 mutation is observed in 5.4% and is mutually exclusive of the NPM1 and CEBPA mutation. Older age and lower complete response rate is correlated with RUNX1 mutation. In univariable survival analysis, RUNX1 mutation is associated with poor clinical outcomes. 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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.364
Teacher spread0.335 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueBlood→Same topicAcute Myeloid Leukemia Research→French-language works237,207→