Evidence map›Paper›PMID 42563187›Full record

ArticleExperimental hematology & oncology2026

The spatial and multi-omic landscape of Down syndrome leukemogenesis: moving beyond cellular heterogeneity.

Edoardo Peroni, Rosario Amato, Martina Bado, Mosè Favarato, Antonio Rosato

Abstract readLetter
In one paragraph

Article in Experimental hematology & oncology, 2026. 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

5 authors.

Edoardo PeroniImmunology and Molecular Oncology Unit, Veneto Institute of Oncology, IOV-IRCCS, Padova, 35128, Italy. edoardo.peroni@iov.veneto.it.ORCID https://orcid.org/0000-0002-2551-6295
Rosario AmatoUOC Genetica Medica, Azienda Ospedaliera Universitaria Dulbecco, Università Magna Graecia, Catanzaro, Italy.
Martina BadoImmunology and Molecular Oncology Unit, Veneto Institute of Oncology, IOV-IRCCS, Padova, 35128, Italy.
Mosè FavaratoDipartimento di Direzione Medica del Presidio Ospedaliero di Mestre, UOSD Genetica e Citogenetica, Serenissima, AULSS3, Venice, 30172, Italy.
Antonio RosatoImmunology and Molecular Oncology Unit, Veneto Institute of Oncology, IOV-IRCCS, Padova, 35128, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Down syndrome (DS) confers a developmentally rooted predisposition to both myeloid and lymphoid leukemias, particularly myeloid leukemia associated with DS (ML-DS) and acute lymphoblastic leukemia associated with DS (ALL-DS). While trisomy 21-driven gene dosage imbalance is central to this risk, DS leukemogenesis cannot be fully explained by recurrent mutations alone; it reflects a dynamic interplay between altered hematopoietic development, cell-intrinsic programs, and tissue microenvironmental cues. In this perspective, we argue that the field should move beyond cataloging cellular heterogeneity and adopt a topographic, multi-omic framework of DS leukemogenesis. We discuss how fetal niche biology shapes pre-leukemic evolution in ML-DS, including the developmental context of GATA1-mutant clones, and how therapy-driven bottlenecks may promote persistence of spatially protected residual disease in ALL-DS. We further highlight the translational potential of integrating spatially resolved transcriptomics with single-cell and protein-aware multi-omics to identify compartment-specific signaling programs and clinically actionable vulnerabilities. A spatially informed model of DS leukemia may improve biological stratification, clarify mechanisms of relapse and toxicity, and support the development of more effective and less toxic therapeutic strategies.

Indexed as

Acute lymphoblastic leukemiaDown syndromeMicroenvironmentMyeloid leukemiaSpatially resolved transcriptomicsSpatial omicsSpatial transcriptomics

Identifiers

PMID42563187
PMCPMC13445933

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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.