Research Papers:

Identification of urine biomarkers associated with lung adenocarcinoma

Weiwei Wang, Shanshan Wang and Man Zhang _

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Oncotarget. 2017; 8:38517-38529. https://doi.org/10.18632/oncotarget.15870

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Weiwei Wang1,*, Shanshan Wang1,* and Man Zhang2,3

1Department of Pulmonary and Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China

2Clinical Laboratory Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China

3Beijing Key Laboratory of Urinary Cellular Molecular Diagnostics, Beijing, China

*These authors have contributed equally to this work

Correspondence to:

Man Zhang, email: [email protected]

Keywords: urine peptides, lung adenocarcinoma, MALDI-TOF MS, immunohistochemistry, biomarker

Received: November 30, 2016    Accepted: January 24, 2017    Published: March 03, 2017


Lung adenocarcinoma (LAC) progression is accompanied by changes in protein levels that may be reflected in body fluids, such as urine. Urine collected from LAC patients (n=34) and healthy controls (n=36) was analyzed via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. The results revealed 76 urinary polypeptides significantly different between LAC patients and normal controls (P<0.05). Twenty-two of these peptides were up-regulated and 54 were down-regulated. Thirteen peptides had average peak intensities >600. Twelve of these 13 peptides were successfully identified using nano-liquid chromatography-tandem MS. Receiver operating characteristic analyses identified seven peptides with superior LAC diagnostic performances. Immunohistochemical staining in 20 paired LAC and adjacent normal tissues showed that IGKC, AAT, SH3BGRL3, osteopontin and gelsolin levels were higher in LAC tissues than in adjacent tissuesand were closely associated with LAC. Urinary peptides assessments may thus provide a novel, noninvasive, repeatable method for detecting and monitoring LAC. New, low-cost detection methods and bioinformatics tools are therefore urgently needed for the analysis of low abundance proteins and peptides in body fluids.

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