MétaCan
Menu
Back to cohort
Record W3029298233 · doi:10.1158/1538-7445.am2019-3649

Abstract 3649: Allelic imbalance in <i>KMT2A</i>-rearranged infant acute lymphoblastic leukemia

2019· article· en· W3029298233 on OpenAlexaff
Byunggil Yoo, Midhat S. Farooqi, Rumen Kostadinov, Warren Cheung, Emily Farrow, Shannon Kelley, Neil Miller, Bing Ge, Margaret Gibson, Patrick A. Brown, Erin Guest, Tomi Pastinen

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsAlleleBiologyGeneGeneticsSingle-nucleotide polymorphismLeukemiaGenomeGenotype

Abstract

fetched live from OpenAlex

Abstract Background Infant acute lymphoblastic leukemia (ALL) is a malignant disorder with poor clinical outcome. It is well-known that infant ALL cases with rearrangement of the KMT2A gene (KMT2A-r) have an even poorer prognosis than non-KMT2A-r cases. Interestingly, KMT2A-r infant ALL cases have remarkably few other genetic alterations. We hypothesized that non-coding events in cancer genomes (e.g. loss of expression or methylation) may play a role in this disease. Such events can be captured using genomic analyses in haploid genomes using analytical approaches for allelic imbalance quantification. Here, we examine whether allelic imbalance is a feature of infant ALL. Methods We performed whole genome sequencing (WGS) and RNA sequencing on peripheral blood or bone marrow specimens from 29 KMT2A-r cases and 14 non-KMT2A-r cases at diagnosis (DX), remission (MD), and relapse (RL) as applicable. WGS data from MD samples was phased using a 1000 Genomes reference panel. Biallelic expression was measured on the phased genome for transcripts with at least 2 SNPs and at least 15 aligned reads. Lesser allele fraction (LAF; allele fraction for the less prevalent allele) for DX/RL versus MD samples was compared for transcripts that had LAFs available in at least 3 cases using t-test. Transcript-level p-values were aggregated at the gene level using the Sidak method. Results Allelic imbalance in expression (LAF <= 0.2) was observed in an average of about 600 genes per sample in infant ALL regardless of timepoint. Disease-specific allelic imbalance (skewed in DX samples but not in paired MD samples) was detected in 431 genes for the KMT2A-r cohort and 77 genes for the non-KMT2A-r cohort. A total of 38 genes with allelic imbalance were shared between the two cohorts. Notably, KMT2A was observed to be imbalanced in KMT2A-r samples. Genes of known significance that were found to be skewed included HOXA9 and PARP8. Discussion Our study suggests that allelic imbalance quantification may help uncover novel molecular mechanisms in infant ALL, especially KMT2A-r cases. However, similar to gene expression, the patterns of allelic imbalance in KMT2A-r cases at DX do not allow efficient prediction of which patients go on to relapse. Citation Format: Byunggil Yoo, Midhat S. Farooqi, Rumen Kostadinov, Warren Cheung, Emily Farrow, Shannon Kelley, Neil Miller, Bing Ge, Margaret Gibson, Patrick Brown, Erin M. Guest, Tomi Pastinen. Allelic imbalance in KMT2A-rearranged infant acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3649.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.032
GPT teacher head0.366
Teacher spread0.334 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicAcute Lymphoblastic Leukemia researchFrench-language works237,207