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Differentially expressed glycosylated patterns of α-1-antitrypsin as serum biomarkers for the diagnosis of lung cancer

  • Yiqian Liang
  • , Tianran Ma
  • , Asmitananda Thakur
  • , Hanjie Yu
  • , Lei Gao
  • , Puyu Shi
  • , Xuetian Li
  • , Hui Ren
  • , Liyuan Jia
  • , Shuo Zhang
  • , Zheng Li
  • , Mingwei Chen
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • Northwest University China

Research output: Contribution to journal › Article › peer-review

68 Scopus citations

Abstract

Lung cancer is the most common malignancy worldwide. Thus, there is a critical need for diagnostic biomarkers with adequate sensitivity and specificity for lung cancer detection. Glycans in glycoproteins are significantly altered in cancer, and may serve as a tool for identifying potential diagnostic biomarkers. Recent studies have reported changes in α-1-antitrypsin (A1AT) glycosylation in lung cancer serum, tissue and cell lines. In this study, a lectin microarray was used to detect glycosylation changes in serum A1AT from patients with lung adenocarcinoma (ADC), squamous cell lung cancer, small-cell lung cancer (SCLC) and benign pulmonary diseases. Differentially expressed glycosylated patterns of A1AT were identified by lectin arrays and were confirmed by lectin-based enzyme-linked immunosorbent assay (ELISA). We found that galactosylated A1AT could distinguish non-small-cell lung cancer (NSCLC) from benign pulmonary diseases (AUC = 0.834); fucosylated A1AT showed exceptional capability in distinguishing ADC from benign diseases (AUC = 0.919) or other lung cancer subtypes (AUC = 0.844), and A1AT containing poly-LacNAc could detect SCLC from benign diseases (AUC = 0.905) or NSCLC (AUC = 0.707). The present study indicates that glycosylated patterns of A1AT may serve as potential biomarkers for detection of lung cancer. Further studies in larger sample sizes are necessary to validate the clinical utility of these markers.

Original languageEnglish
Pages (from-to)331-340
Number of pages10
JournalGlycobiology
Volume25
Issue number3
DOIs
StatePublished - 5 Aug 2014
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • glycosylation
  • lectin microarray
  • lectin-based ELISA
  • lung cancer
  • α-1-antitrypsin

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