P0172 In silico drug repurposing approach for the discovery of therapeutics for intestinal fibrosis in crohn’s disease
Authors: Nikolakis D , Li Yim A Y F , Lartey D , Rieder F , D’Haens G R , van de Sande M G H , Löwenberg M 
Published: January 2025

Abstract

Background
Intestinal fibrosis in Crohn’s disease (CD) can lead to stricture formation and other disease-related complications.1,2 Given the lack of anti-fibrotic drugs, current treatment strategies are limited to anti-inflammatory therapies, endoscopic balloon dilation and surgery.1 Our aim was to identify compounds and druggable targets that can reverse the gene expression signature in mucosal fibroblasts associated with intestinal fibrosis.

Methods
A signature associated with fibrotic CD was derived from three publicly available transcriptomic datasets of fibroblasts isolated from fibrostenotic strictures of CD patients. We conducted a meta-regression analysis across the transcriptomic datasets to identify significant differentially expressed genes (DEGs) associated with fibrostenotic CD. Three drug repurposing platforms (iLINCS, L1000 CDS2 and CLUE io), connected to the NIH LINCS database,3,4 were used to identify compounds that could reverse the fibrotic signature, ranked by their anti-fibrotic potential using the CoDReS (Composite Drug Reranking Scoring) tool. Transcription factors and miRNAs targeting the fibrostenotic signature were identified via the TRRUST and miRWalk databases. A gene interaction network was constructed, incorporating transcription factors (TRRUST TF), miRNAs and DEGs. Drugs targeting key network components were identified using the DGiDb database.

Results
Via the analysis of combined transcriptomic datasets from fibrostenotic- versus non-stenosis-associated mucosal fibroblasts, fibroblast activation protein (FAP), IL7 receptor and transcription factor AP-2 gamma, emerged as the most significantly upregulated genes in fibrostenotic CD (Figure 1). Out of 6,783 compounds, PI3K/Akt/mTOR inhibitors, Src kinase family inhibitors and histone deacetylase inhibitors were predicted as being most effective in reversing this pathologic gene signature. The gene interaction network revealed 15 hub genes as central components with the most interconnections (Table 1). Among these top 15 key gene regulators, IL6, PPARγ and angiotensin receptor type 1 (AGTR1) were the highest ranked druggable targets, based on the drug-gene interaction analysis.

Conclusion
Our in silico drug repurposing approach identified several potential anti-fibrotic compounds and druggable targets for the treatment of CD-associated intestinal fibrosis. These findings open novel avenues for the development of anti-fibrotic drugs and provide a foundation for future research on cell and pathway-specific mechanisms driving fibrosis in CD.

References
1.Bettenworth D, Bokemeyer A, Baker M, Mao R, Parker CE, Nguyen T, Ma C, Panés J, Rimola J, Fletcher JG, Jairath V, Feagan BG, Rieder F; Stenosis Therapy and Anti-Fibrotic Research (STAR) Consortium. Assessment of Crohn’s disease-associated small bowel strictures and fibrosis on cross-sectional imaging: a systematic review. Gut. 2019 Jun;68(6):1115-1126. doi: 10.1136/gutjnl-2018-318081. Epub 2019 Apr 3. PMID: 30944110; PMCID: PMC6580870.
2.Mukherjee PK, Nguyen QT, Li J, Zhao S, Christensen SM, West GA, Chandra J, Gordon IO, Lin S, Wang J, Mao R, Czarnecki D, Rayan C, Goren I, Banerjee S, Kotak P, Plesec T, Lal S, Fabre T, Asano S, Bound K, Hart K, Park C, Martinez R, Dower K, Wynn TA, Hu S, Naydenov N, Decaris M, Turner S, Holubar SD, Steele SR, Fiocchi C, Ivanov AI, Kravarik KM, Rieder F. Stricturing Crohn’s Disease Single-Cell RNA Sequencing Reveals Fibroblast Heterogeneity and Intercellular Interactions. Gastroenterology. 2023 Nov;165(5):1180-1196. doi: 10.1053/j.gastro.2023.07.014. Epub 2023 Jul 26. PMID: 37507073.
3.Keenan AB, Jenkins SL, Jagodnik KM, et al. (2018). The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations. Cell Syst. 2018;6(1):13-24. doi:10.1016/j.cels.2017.11.001.
4.Lamb, Justin et al. (2006). The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science (New York, N.Y.) vol. 313,5795: 1929-35. doi:10.1126/science.1132939.