Candidate Biomarkers for Targeting in Type 1 Diabetes; A Bioinformatic Analysis of Pancreatic Cell Surface Antigens.

Abstract

Type 1 diabetes (T1Ds) is an autoimmune disease in which the immune system invades and destroys insulin-producing cells. Nevertheless, at the time of diagnosis, about 30-40% of pancreatic beta cells are healthy and capable of producing insulin. Bi-specific antibodies, chimeric antigen receptor regulatory T cells (CAR-Treg cells), and labeled antibodies could be a new emerging option for the treatment or diagnosis of type I diabetic patients. The aim of the study is to choose appropriate cell surface antigens in the pancreas tissue for generating an antibody for type I diabetic patients. In this bioinformatics study, we extracted pancreas-specific proteins from two large databases; the Human Protein Atlas (HPA) and Genotype-Tissue Expression (GTEx) Portal. Pancreatic-enriched genes were chosen and narrowed down by Protter software for the investigation of accessible extracellular domains. The immunohistochemistry (IHC) data of the protein atlas database were used to evaluate the protein expression of selected antigens. We explored the function of candidate antigens by using the GeneCards database to evaluate the potential dysfunction or activation/hyperactivation of antigens after antibody binding. The results showed 429 genes are highly expressed in the pancreas tissue. Also, eighteen genes encoded plasma membrane proteins that have high expression in the microarray (GEO) dataset. Our results introduced four structural proteins, including NPHS1, KIRREL2, GP2, and CUZD1, among all seventeen candidate proteins. The presented antigens can potentially be used to produce specific pancreatic antibodies that guide CARTreg, bi-specific, or labeling molecules to the pancreas for treatment, detection, or other molecular targeted therapy scopes for type I diabetes.