Evidence map›Paper›PMID 42609020›Full record

ArticleJournal of mass spectrometry : JMS2026

Discovery of Breast Cancer Diagnostic Markers Using Lipase-Based Plasma Proteomics of Lipid-Bound Proteins.

Eun Joo Kang, Youngshik Choe, Kwan Ho Lee, Sangkyu Lee

Abstract read
In one paragraph

Article in Journal of mass spectrometry : JMS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

4 authors.

Eun Joo KangSchool of Pharmacy, Sungkyunkwan University, Suwon, Republic of Korea.
Youngshik ChoeKorea Brain Research Institute, Daegu, Republic of Korea.ORCID https://orcid.org/0000-0002-2132-4771
Kwan Ho LeeDepartment of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-6526-3333
Sangkyu LeeSchool of Pharmacy, Sungkyunkwan University, Suwon, Republic of Korea.ORCID https://orcid.org/0000-0001-5343-701X

Funding

KBSMC-SKKU Future Clinical Convergence Research Program Grant
6 · The paper itself

Abstract

Membrane-associated proteins, including those embedded in exosomal membranes or bound to plasma lipids, are promising disease biomarkers. However, their hydrophobic nature limits detection through conventional proteomic workflows, which primarily capture soluble proteins. In this study, we developed and optimized a lipase-based pretreatment strategy to improve the detection of insoluble membrane proteins in human plasma. Lipase treatment using porcine pancreas-derived enzymes was optimized to 37°C, 3 U, and 1 h, based on overall protein yield and membrane protein enrichment. Sequential application after depletion of high-abundance proteins increased the proportion of membrane proteins from 12%-20%. Using this optimized workflow, we performed data-independent acquisition-based LC-MS/MS analysis of plasma samples from patients with early-stage breast cancer and benign disease (n = 6 each). Notably, 38% of the uniquely detected or enriched proteins in cancer plasma were membrane-associated. Among them, protocadherin 12 (PCDH12) was significantly elevated in the plasma of patients with breast cancer, indicating its potential as a novel diagnostic biomarker. This study highlights the use of lipase-enhanced proteomics for revealing plasma membrane proteins and advancing noninvasive biomarker discovery for cancer.

Indexed as

Biomarkers, TumorBreast NeoplasmsLipaseMembrane ProteinsProteomicsAnimalsFemaleHumansLiquid Chromatography-Mass SpectrometrySwineTandem Mass SpectrometryBiomarkers, TumorLipaseMembrane Proteinsbreast cancerdiagnostic biomarkerslipase pretreatmentmembrane proteins

Identifiers

PMID42609020
PMCPMC13482137

What OpenQuestion holds

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Registered trials

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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.