Evidence map›Paper›PMID 41315396›Full record

ArticleScientific reports2025

One section, two worlds: single-cell integration of MALDI-MSI and spatial transcriptomics on the same single tissue section.

Tim F E Hendriks, Gert B Eijkel, Theodoros Visvikis, Benjamin Balluff, Ron M A Heeren, Eva Cuypers

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Mapping multipathology via spatial omic integration.Current opinion in biotechnology · 2026
    Review
  9. Review
  10. Review
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

6 authors.

Tim F E HendriksThe Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry (IMS), Maastricht University, 6229 ER, Maastricht, The Netherlands.
Gert B EijkelThe Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry (IMS), Maastricht University, 6229 ER, Maastricht, The Netherlands.
Theodoros VisvikisThe Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry (IMS), Maastricht University, 6229 ER, Maastricht, The Netherlands.
Benjamin BalluffThe Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry (IMS), Maastricht University, 6229 ER, Maastricht, The Netherlands.
Ron M A HeerenThe Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry (IMS), Maastricht University, 6229 ER, Maastricht, The Netherlands.
Eva CuypersThe Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry (IMS), Maastricht University, 6229 ER, Maastricht, The Netherlands. e.cuypers@maastrichtuniversity.nl.

Funding

Fonds Wetenschappelijk Onderzoek TBM T001919NInterreg Vlaanderen-Nederland Molecular Brain Tumor DetectorNWO-STEM 19013
6 · The paper itself

Abstract

Understanding tissue complexity requires spatially resolved multi-omics data at single-cell resolution. Here, we present a workflow integrating high-resolution matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) with Xenium spatial transcriptomics (SPT) on a single tissue section. This strategy ensures pixel-scale spatial correspondence between metabolic and transcriptomic features, avoiding misalignment issues of serial sections, where even minor offsets result in sampling different cells. We investigated MALDI-MSI compatibility with downstream SPT revealing that the number of transcripts per cell decreased by ~ 30% after MSI, whilst cell recovery and cell-type assignments are preserved. Validated using mouse brain and demonstrated using human glioblastoma tissues, we achieved pixel-scale modality co-registration, enabling per-cell MALDI spectra extraction aligned with gene expression. Integrated clustering revealed enhanced cell-type resolution and identified metabolic heterogeneity within transcriptionally defined populations. This facilitates precise correlations of a cell's function and its biochemical state, providing a holistic view of cellular function, heterogeneity, and interaction in health and disease. Our workflow provides a scalable path to multi-omic atlases, advancing both data integration and translational research.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTranscriptomeAnimalsBrainBrain NeoplasmsGlioblastomaHumansMice

Identifiers

PMID41315396
PMCPMC12663239

What Socratic holds

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LicenceCC BY-NC-ND
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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.