Detection of Novel Autoantibodies to Nucleolin's RNA-binding Domains as a Serum Tumor Biomarker Through ELISA

Fatemeh Ezzatifar; Alireza Rafiei; Reza Valadan; Hossein Asgarian-Omran; Mahmood  Jeddi-Tehrani

doi:10.18502/ijaai.v21i6.11520

Fatemeh Ezzatifar Molecular and Cell biology Research Center, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
Alireza Rafiei Molecular and Cell biology Research Center, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
Reza Valadan Molecular and Cell biology Research Center, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
Hossein Asgarian-Omran Department of Immunology, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
Mahmood Jeddi-Tehrani Monoclonal Antibody Research Center, Avicenna Research Institute, Tehran, Iran

DOI: https://doi.org/10.18502/ijaai.v21i6.11520

Keywords: Autoantibodies; Biomarkers; Enzyme-linked immunosorbent assay; Neoplasms; Nucleolin

Abstract

Expression and location of nucleolin are often abnormal in malignancies, which may result in the production of autoantibodies. Despite this, the identification of such autoantibodies may be essential for the early diagnosis and prognosis of cancers.

In this investigation, the recombinant nucleolin protein was generated using an Escherichia coli expression system and was used an indirect enzyme-linked immunosorbent assay to detect anti-nucleolin autoantibodies in cancer patients' sera.

Lung cancer patients' autoantibodies displayed the highest seroreactivity with the recombinant protein, with area under the curve of 0.948 and sensitivity and specificity of 85% and 96.67%, respectively (accuracy=92%). Anti-nucleolin autoantibodies were linked with lung tumor size (r=0.793), tumor, node, metastasis staging (r=0.643), and proliferation (r=0.744).

These autoantibodies distinguished patients with early-stage lung cancer from healthy controls. Since anti-nucleolin autoantibodies are strongly linked to tumor size, clinical staging, and growth, they can be used to measure how well a treatment is working.