Dataset Information

Proteomic profiling of plasma-derived extracellular vesicles using Mag-Net for biomarker discovery in pancreatic ductal adenocarcinoma

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer, with a five-year survival rate of less than 10%. In South Africa, PDAC was the seventh leading cause of cancer deaths among men and the sixth among women in 2020. Approximately 85% of patients are diagnosed at an advanced stage, highlighting the urgent need for ongoing research to identify reliable biomarkers that could improve clinical outcomes. Circulating proteins are present not only as soluble molecules but also encapsulated within extracellular vesicles (EVs), which protect and transport biologically active cargo in plasma. This study compared the plasma proteomes of patients with PDAC with those of patients with benign biliary pathologies (BBP) and healthy controls (HC). We employed Mag-Net, a magnetic bead-based method that combines the enrichment of membrane-bound vesicles with the depletion of high-abundance plasma proteins. On average, 2,339 protein groups were identified across all sample groups. Comparative analyses revealed both unique and overlapping dysregulated proteins among the PDAC, BBP, and HC cohorts. PDAC was characterised by coordinated extracellular matrix (ECM) remodelling, chronic immune-inflammatory activation, and metabolic disruption, particularly affecting lipid homeostasis. This molecular profile was marked by elevated ECM-associated and matricellular proteins (such as THBS2, TGFBI, MFAP4, ANPEP, and ITIH4) alongside increased inflammatory mediators (including ORM1, C1QC, CTSS, SPP1, FBLN2, LTBP2, SDC1, HP, SAA1, PTX3, and LRG1). This overlap suggests that dynamic ECM remodelling within the tumour microenvironment is mirrored systemically by the release or shedding of matrix-associated proteins into the circulation. Notably, LRG1 demonstrated the strongest association with disease severity and clustered with acute-phase proteins, complement components, and pancreatic injury markers, supporting its role within an inflammation-stromal remodelling network characteristic of aggressive PDAC. Collectively, these findings demonstrate that plasma proteomics provides valuable discriminatory and severity-related information. While several candidate proteins show promise for inclusion in multi-analyte panels, further validation in larger, independent cohorts is necessary to establish their diagnostic and translational utility for early detection, risk stratification, and improved differential diagnosis of PDAC.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

DISEASE(S): Pancreas Adenocarcinoma

SUBMITTER: Rethabile Mokoena

LAB HEAD: Rethabile Mokoena

PROVIDER: PXD074950 | Pride | 2026-08-06

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20251219_155227_20251219_PDAC_Hela_QC.sne	Other
	20260114_110749_14-08-2024_PDAC_MagNet_Pool.sne	Other
	29-10-2024_PDAC_MagNet_V2.sne	Other
	50ng_Hela_S1-B10_1_3360.d.zip	Other
	50ng_Hela_S1-B11_1_3361.d.zip	Other

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Publications

Proteomic Profiling of Extracellular Vesicle-Enriched Plasma Using Mag-Net for Biomarker Discovery in Pancreatic Ductal Adenocarcinoma.

Buthelezi Sindisiwe S Elebo Nnenna N Naicker Previn P Mokoena Rethabile R Dubazana Sinegugu S Govender Ireshyn I Mamputha Sipho S Ellero Andrea A Stoychev Stoyan S Mazibuko Jeanet J Ojo Dupe D Candy Geoffrey G Devar John J Cacciatore Stefano S Omoshoro-Jones Jones J Nweke Ekene Emmanuel EE

Journal of proteome research 20260630

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer and was ranked among the top seven leading causes of cancer-related deaths in South Africa in 2020. Highlighting the urgent need for ongoing research to identify reliable biomarkers to improve clinical outcomes. This study compared the plasma proteomes of patients with PDAC, those with benign biliary pathologies (BBP), and healthy controls (HC). We used Mag-Net, a magnetic-bead-based method that enriches membrane-bound vesicle ...[more]

PMID: 42378051

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