Evidence map›Paper›PMID 42619640›Full record

ArticleChemical communications (Cambridge, England)2026

Multi-omic analyses of the same sample using metabolomics, lipidomics, proteomics, phosphoproteomics, and glycoproteomics.

Yuefan Wang, Xuejun Peng, Hongyi Liu, Mia Gidley, Beth Kelly, Erika L Pearce, Edward J Pearce, Xianlin Han, Hui Zhang

Abstract read
In one paragraph

Article in Chemical communications (Cambridge, England), 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

9 authors.

Yuefan WangDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland, 21231, USA. ywang298@jhmi.edu.ORCID http://orcid.org/0000-0001-5731-6143
Xuejun PengBruker Scientific, San Jose, California 95134, USA.
Hongyi LiuDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland, 21231, USA. ywang298@jhmi.edu.ORCID http://orcid.org/0000-0002-9444-3632
Mia GidleyBloomberg-Kimmel Institute for Cancer Immunotherapy, Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA.
Beth KellyBloomberg-Kimmel Institute for Cancer Immunotherapy, Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA.ORCID http://orcid.org/0000-0002-3195-6860
Erika L PearceBloomberg-Kimmel Institute for Cancer Immunotherapy, Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA.
Edward J PearceBloomberg-Kimmel Institute for Cancer Immunotherapy, Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA.
Xianlin HanSam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center, San Antonio, TX, 78299, USA.ORCID http://orcid.org/0000-0002-8615-2413
Hui ZhangDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland, 21231, USA. ywang298@jhmi.edu.ORCID http://orcid.org/0000-0001-8726-7098

Funding

Proteogenomic Characterization of Tumor Tissues and Preclinical Models with High PrecisionU24CA271079 · NCI · JOHNS HOPKINS UNIVERSITY · PI DANIEL Wanyui CHAN, Hui Zhang · 2022 to 2026
$6.6M
Biomarker Reference LaboratoryU2CCA271895 · NCI · JOHNS HOPKINS UNIVERSITY · PI DANIEL Wanyui CHAN · 2023 to 2026
$4.6M
Development of a panel of multiplex biomarkers for the early detection of pancreatic ductal adenocarcinoma and high-risk lesionsU01CA274514 · NCI · JOHNS HOPKINS UNIVERSITY · PI Randall Brand, DANIEL Wanyui CHAN · 2023 to 2026
$3.2M
NCI NIH HHS U01 CA274514NCI NIH HHS U24 CA271079NCI NIH HHS U2C CA271895
6 · The paper itself

Abstract

Mass spectrometry (MS)-based multi-omics offers powerful tools to comprehensively characterize proteins, post-translational modifications, metabolites, and lipids. However, these measurements are typically performed using separate sample preparation workflows and modality-specific liquid chromatography mass spectrometry (LC-MS) platforms, limiting integration and constraining applications to small amounts of sample materials, especially scarce clinical specimens. Here, we describe a unified nano-LC-MS framework that enables metabolomic, lipidomic, proteomic, phosphoproteomic, and glycoproteomic analyses from the same starting material using a single nano-LC-MS platform, with only the chromatographic conditions, acquisition methods, and enrichment procedures tailored to each omics. This integrated strategy reduces workflow complexity and sample consumption while improves analytical continuity across molecular layers. By enabling deep multi-omics characterization from the same sample, this platform provides a practical foundation for comprehensive analysis of precious clinical samples.

Indexed as

GlycoproteinsLipidomicsMetabolomicsPhosphoproteinsProteomicsHumansLiquid Chromatography-Mass SpectrometryMultiomicsGlycoproteinsPhosphoproteins

Identifiers

PMID42619640
PMCPMC13491391

What OpenQuestion holds

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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 OpenQuestion graph.