Evidence mapPaperPMID 41645178Full record

SynthesisJournal of biomedical science2026

Mass spectrometry-based human spatial omics: fundamentals, innovations, and applications.

Ching-Chia Yang, Ching-Ya Lin, Hsin-Yo Yuan, Hsuan-Cheng Huang, Hsueh-Fen Juan

Abstract readSystematic ReviewReview
In one paragraph

Synthesis in Journal of biomedical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Ching-Chia YangDepartment of Life Science, National Taiwan University, Taipei, 106, Taiwan.
Ching-Ya LinCenter for Computational and Systems Biology, National Taiwan University, Taipei, 106, Taiwan.
Hsin-Yo YuanGraduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, 106, Taiwan.
Hsuan-Cheng HuangInstitute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan. hsuancheng@nycu.edu.tw.
Hsueh-Fen JuanDepartment of Life Science, National Taiwan University, Taipei, 106, Taiwan. yukijuan@ntu.edu.tw.

Funding

Ministry of Education NTU-CC-114L892702National Science and Technology Council NSTC 112-2221-E-A49-061-MY3National Science and Technology Council NSTC 113-2320-B-002-025-MY3
6 · The paper itself

Abstract

Mass spectrometry-based spatial omics is a powerful approach for visualizing the spatial organization of proteins, metabolites, lipids, and other biomolecules in situ, combining the molecular depth of mass spectrometry with spatially resolved imaging. This systematic review traces the rapid technological and computational evolution of this field, including innovations in mass spectrometry imaging (MSI), labeling-based approaches, and proximity labeling techniques. It also highlights recent advances that enhance spatial resolution, expand molecular coverage, and enable deep molecular characterization and review analytical pipelines that integrate deep learning, cross-modality registration, and cloud-optimized data formats. From the multimodal and practical perspective, the integration of MSI with other spatial omics platforms and its transformative applications in tumor microenvironment profiling, neurodegenerative disease, developmental biology, biomarker discovery, and precision medicine are discussed. Finally, this review outlines challenges and opportunities, emphasizing the need for standardization, clinical validation, and interpretable artificial intelligence to enable broader adoption. These advances position MS-based spatial omics as a foundational pillar for multimodal spatial biology and personalized healthcare.

Indexed as

Mass SpectrometryPrecision MedicineHumansMultiomicsBiomarker discoveryMass spectrometryMultimodal data integrationPrecision medicineSpatial omics

Identifiers

PMID41645178
PMCPMC12879364

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.