Spatial transcriptomics to predict treatment response in Crohn’s disease (PI Espen Bækkevold)

Anti-TNF therapy is currently the first treatment choice for newly diagnosed patients with Crohn’s disease (CD). However, approximately 30% of CD patients have no effect of anti-TNF therapy, and because there are no clinical criteria to identify non-responders, all patients are initially given such treatment. The aim of this project is to identify biomarkers that with high accuracy predict which patients that will fail anti-TNF treatment. Clinical implementation of such biomarkers will personalize the treatment of CD with significant health benefits.
To untangle the cellular networks associated with durable remission upon anti-TNF therapy, we will take advantage of the most recent advances in experimental and computational methods and study the disease process in CD-lesions with two complementary high dimensional techniques:
1) Analyses of datasets from single-cell RNA sequencing (scRNAseq) of tissue-derived cells from inflamed and health intestine will give an unbiased characterization of the gene expression levels of all cells, and 2) the Spatial Transcriptomics (ST) method will reveal the spatial pattern of gene expression levels within the tissue.
Advanced bioinformatics to integrate the two methods will give unbiased and comprehensive tissue maps with unprecedented molecular resolution.
Based on this analysis we will construct a single cell transcriptome atlas with spatial information across tissues from both anti-TNF responders and non-responders. This will give a unique possibility to identify differences at the cellular and molecular level in time and space in the search for predictive biomarkers for treatment response.

Flow cytometry analysis of macrophages (macs) isolated from Crohn’s disease lesions (obtained by colonoscopy, right image) and adjacent uninflamed mucosa showing a large expansion of inflammatory macrophages in the lesions.