Evidence map›Paper›PMID 40788820›Full record

ArticleMolecular oncology2025

Data-driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes.

Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo

Abstract read
In one paragraph

Article in Molecular oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mona NourbakhshCancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
Nikola TomCancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
Anna Schrøder LassenCancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
Helene Brasch Lind PetersenCancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
Ulrik Kristoffer StoltzeDepartment of Clinical Genetics, Copenhagen University Hospital Rigshospitalet, Denmark.
Karin WadtDepartment of Clinical Genetics, Copenhagen University Hospital Rigshospitalet, Denmark.
Kjeld SchmiegelowDepartment of Pediatrics and Adolescent Medicine, University Hospital Rigshospitalet, Copenhagen, Denmark.
Matteo TibertiCancer Structural Biology, Danish Cancer Institute, Copenhagen, Denmark.
Elena PapaleoCancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.ORCID 0000-0002-7376-5894

Funding

Danmarks Grundforskningsfond DNRF125Interreg
6 · The paper itself

Abstract

Acute lymphoblastic leukemia (ALL), the most common cancer in children, is overall divided into two subtypes, B-cell precursor ALL (B-ALL) and T-cell ALL (T-ALL), which have different molecular characteristics. Despite massive progress in understanding the disease trajectories of ALL, ALL remains a major cause of death in children. Thus, further research exploring the biological foundations of ALL is essential. Here, we examined the diagnostic, prognostic, and therapeutic potential of gene expression data in pediatric patients with ALL. We discovered a subset of expression markers differentiating B- and T-ALL: CCN2, VPREB3, NDST3, EBF1, RN7SKP185, RN7SKP291, SNORA73B, RN7SKP255, SNORA74A, RN7SKP48, RN7SKP80, LINC00114, a novel gene (ENSG00000227706), and 7SK. The expression level of these markers all demonstrated significant effects on patient survival, comparing the two subtypes. We also discovered four expression subgroups in the expression data with eight genes driving separation between two of these predicted subgroups. A subset of the 14 markers could distinguish B- and T-ALL in an independent cohort of patients with ALL. This study can enhance our knowledge of the transcriptomic profile of different ALL subtypes.

Indexed as

Biomarkers, TumorGene Expression Regulation, LeukemicPrecursor Cell Lymphoblastic Leukemia-LymphomaAdolescentChildChild, PreschoolFemaleGene Expression ProfilingHumansInfantMalePrognosisBiomarkers, Tumoracute lymphoblastic leukemiaB‐cell precursor acute lymphoblastic leukemiacancer markergene expressionRNA sequencingT‐cell acute lymphoblastic leukemia

Identifiers

PMID40788820
PMCPMC12688183

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.