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High-sensitivity profiling of glycoproteins from ovarian cancer sera using lectin-affinity and LC-ESI-Q-TOF-MS/MS

  • Arekal N. Roopashri
  • , M. S. Divyashree
  • , J. Savitha*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Lectins act as effective diagnostic tools for screening potential cancer biomarkers because of their ability to recognize the carbohydrate moiety of glycoproteins present in most complex tissues and fluids. This study aimed to propose an ideal procedure for the precise recovery of glycoprotein-derived oligosaccharides using freshwater microalgal lectins and to validate their effectiveness in the enrichment of glycoproteins present in the sera. A total of 5 ovarian cancer (OC) patients with grade III were included in the present study to identify potential biomarkers present in the serum samples. Proteomic analysis of OC serum samples was carried out using lectin-affinity entrapment followed by affinity chromatography coupled with liquid chromatography-electrospray ionization-quadrupole-time of flight-mass spectrometry (LC-ESI-Q-TOF-MS/MS) methods. Proteins with the highest Mascot score were found to be expressed in the OC III serum group and were identified as serotransferrin (TRF), haptoglobin, hemopexin, serine protease 1 (Sp1), ceruloplasmin, alpha-1-antitrypsin, alpha-1-antichymotrypsin (ACT), alpha-2-HS glycoprotein (AHSG), and immunoglobulins (Igs). Among them serine protease 1 was recovered at a high-level using lectin-affinity techniques. PRSS 1 gene is responsible for the expression of Sp1 in OC serum. The present study evaluated the usefulness of microalgal lectins in the identification of molecular markers present in serum samples of OC. This data provide novel insights regarding the presence of Sp1 in OC serum specimen, paving the way for further investigations related to glycosylation patterns of Sp1 and clinical applicability.

Original languageEnglish
Article number100122
JournalCurrent Research in Biotechnology
Volume5
DOIs
Publication statusPublished - 01-2023

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

All Science Journal Classification (ASJC) codes

  • Biotechnology

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