Rare Drivers at Low Prevalence with High Cancer Effects in T-Cell and B-Cell Pediatric Acute Lymphoblastic Leukemia.

Jeffrey D Mandell, Saathvika Diviti, Mina Xu, Jeffrey P Townsend

Abstract read

In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Comparative Analysis ofGenes · 2026
Article

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

4 authors.

Jeffrey D MandellProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.

Saathvika DivitiBiology Department, Colby College, Waterville, ME 04901, USA.

Mina XuDepartment of Pathology, Yale School of Medicine, New Haven, CT 06510, USA.ORCID 0000-0001-9513-245X

Jeffrey P TownsendProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.ORCID 0000-0002-9890-3907

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The genomic analyses of pediatric acute lymphoblastic leukemia (ALL) subtypes, particularly T-cell and B-cell lineages, have been pivotal in identifying potential therapeutic targets. Typical genomic analyses have directed attention toward the most commonly mutated genes. However, assessing the contribution of mutations to cancer phenotypes is crucial. Therefore, we estimated the cancer effects (scaled selection coefficients) for somatic substitutions in T-cell and B-cell cohorts, revealing key insights into mutation contributions. Cancer effects for well-known, frequently mutated genes like

Indexed as

Precursor B-Cell Lymphoblastic Leukemia-LymphomaPrecursor T-Cell Lymphoblastic Leukemia-LymphomaChildChild, PreschoolGenes, NeoplasmHumansMutationPolymorphism, Single NucleotidePrevalenceB-cellcancer effectgenomicspediatric acute lymphoblastic leukemiapersonalized medicineprevalencep valuesubtypesT-celltherapeutic targets

Identifiers

PMID38928295

DOI10.3390/ijms25126589

PMCPMC11203805

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

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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 OpenQuestion graph.