Evidence map›Paper›PMID 42090705›Full record

ArticleAnalytical chemistry2026

Sequential MALDI-MSI-Based Multiomics Reveals Spatial Lipid, Glycan, and Tryptic Peptide Signatures in Breast Tumor Histopathology.

Seyed M J Seyed Golestan, Nicole Monza, Farnaz Fatahian, Lisa Pagani, Mohammad Ali AS'habi, Hossein Behboudi, Andrew Smith, Alireza Ghassempour, Vanna Denti

Abstract read
In one paragraph

Article in Analytical chemistry, 2026. 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.

  1. 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

9 authors.

Seyed M J Seyed GolestanMedicinal Plants and Drug Research Institute, Shahid Beheshti University, Tehran 1983969411, Iran.
Nicole MonzaUniversity of Milano Bicocca, Department of Medicine and Surgery, Proteomics and Metabolomics Unit, Vedano al Lambro, 20854, Italy.ORCID 0009-0003-9392-8069
Farnaz FatahianMedicinal Plants and Drug Research Institute, Shahid Beheshti University, Tehran 1983969411, Iran.
Lisa PaganiUniversity of Milano Bicocca, Department of Medicine and Surgery, Proteomics and Metabolomics Unit, Vedano al Lambro, 20854, Italy.
Mohammad Ali AS'habiMedicinal Plants and Drug Research Institute, Shahid Beheshti University, Tehran 1983969411, Iran.
Hossein BehboudiMedicinal Plants and Drug Research Institute, Shahid Beheshti University, Tehran 1983969411, Iran.ORCID 0000-0002-6613-3936
Andrew SmithUniversity of Milano Bicocca, Department of Medicine and Surgery, Proteomics and Metabolomics Unit, Vedano al Lambro, 20854, Italy.ORCID 0000-0001-6530-6113
Alireza GhassempourMedicinal Plants and Drug Research Institute, Shahid Beheshti University, Tehran 1983969411, Iran.
Vanna DentiUniversity of Milano Bicocca, Department of Medicine and Surgery, Proteomics and Metabolomics Unit, Vedano al Lambro, 20854, Italy.ORCID 0000-0001-6373-689X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high molecular heterogeneity of breast cancer (BC) poses a significant challenge for its classification and biological characterization. Despite numerous efforts, conventional immunohistochemical techniques and traditional mass spectrometry (MS) have failed to provide an exhaustive characterization of tumor subtypes. This limitation is likely due to the loss of spatial information, which significantly impacts the interpretation of the results. In this study, we present a matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) approach that spatially integrates three multiomics layers, including lipids, N-glycans, and tryptic peptides, on the same tissue microarray (TMA) section with BC and normal tissue cores. The analysis of individual layers and their integration demonstrates the potential of multiomics MALDI-MSI in discriminating between healthy and tumor tissues and in capturing molecular differences associated with different subtypes of BC. Specifically, the approach adopted highlighted the significant contribution of lipids and glycans to characterizing breast tumor subtypes. The proteomic layer provides complementary information on the proliferative state and biological heterogeneity of the tumors, clearly distinguishing between the healthy and neoplastic conditions. Overall, this proof-of-concept study demonstrates the potential of spatial multiomics MALDI-MSI as a tool for a more in-depth characterization of BC subtypes, laying the groundwork for future applications on larger sample cohorts.

Indexed as

Breast NeoplasmsLipidsPeptidesPolysaccharidesSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTrypsinFemaleHumansMultiomicsProteomicsLipidsPeptidesPolysaccharidesTrypsin

Identifiers

PMID42090705
PMCPMC13191728

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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.