CHARACTERIZATION OF THE ESOPHAGEAL TISSUE BY SINGLE CELL RNA SEQUENCING IN PEDIATRIC PATIENTS WITH EOSINOPHILIC ESOPHAGITIS AND IDENTIFICATION OF NOVEL BIOMARKERS TO PREDICT THE EARLY RELAPSE TO THE DISEASE
Eosinophilic esophagitis (EoE) is a recently described disease in which exposure to specific foods and allergens leads to type 2 inflammation. EoE has risen rapidly over the last 15 years in western countries. The pathogenesis of EoE results from the complex interaction between genetics and environment.
The first goal of the study will be to compare the transcriptome at a single cell resolution of the esophageal tissue taken from two pediatric patients with EoE and one age-matched healthy control, by using the single cell RNA sequencing (scRNA seq) technology, in order to delineate into specific cell subpopulations expressing unique sets of genes. Interestingly, biopsy samples will be taken from both the proximal and distal district of the esophagus of patients and control to highlight possible differences in their involvement in the disease pathogenesis. Results will allow to extend the knowledge on the pathogenesis of EoE by characterizing cell subsets and heterogeneity, identifying rare cell populations with a specific role in the disease development and discovering new markers able to discriminate between health and diseased tissues.
Furthermore, in a previous study, we showed for the first time that the different tendencies to relapse in children with EoE responding to topical steroids was related to an altered transcriptome profile. In particular, the gene SERPINB12 was differentially expressed among patients with early or late relapse.
Thus, a second goal of the project will be to confirm in a cohort of 40 EoE pediatric patients the ability of SERPINB12 to discriminate between patients having a relapse within 6 months after the end of therapy and those with a longer steroid-free remission, by using RT-PCR. Results will allow to better define the steroid-dependency and provide clinicians with a valid tool to predict relapse.