OP10 Response to biologics in IBD patients assessed by Computerized image analysis of Probe Based Confocal Laser Endomicroscopy with molecular labeling and gene expression profiling. (27th May 2021)

• Record Type: Journal Article
• Authors: Iacucci, M; Jeffery, L; Acharjee, A; Nardone, O M; Smith, S C; Labarile, N; Zardo, D; Cannatelli, R; Shivaji, U N; Ungar, B; Buda, A; Grisan, E; Gkoutos, G; Subrata, G
• Is Part Of: Journal of Crohn's and colitis. Volume 15(2021)Supplement 1
• Page Start: S009
• Page End: S010
• Publication Date: 2021-05-27
• Subjects: Inflammatory bowel diseases -- Periodicals; 616.344005
• DOI: 10.1093/ecco-jcc/jjab075.009
• Languages: English
• ISSNs: 1873-9946

Abstract

Abstract: Background: Biologics are being used increasingly in the treatment of Inflammatory Bowel Disease. However, up to 40% of patients do not respond to biologics. Therefore, methods to predict response are imperative. We aimed to identify novel genes and pathways predictive of anti-TNF response in patients with Ulcerative Colitis (UC) undergoing electronic chromoendoscopy and probe confocal laser endomicroscopy (pCLE). We further evaluated the ex-vivo binding of fluorescent labelled biologics as markers of response Methods: 26 UC patients starting anti-TNF therapy as standard of care were recruited. Pre-treatment colonoscopy, with electronic chromoendoscopy and pCLE (Cellvizio, Mauna Kea) by injecting intravenous fluorescein (2.5- 5 mls), was performed to assess disease activity. Targeted biopsies were taken for fluorescein isothiocyanate (FITC)-labelled infliximab staining and RNA extraction and gene expression analysis. Ex vivo labelling was evaluated by an automated analysis: after a first pre-processing step to remove biases, the labelled regions were identified using statistical multi-level thresholding, and evaluated as area and intensity. To assess response, the same endoscopic procedure was repeated at week 12–14 after anti-TNF. cDNA libraries were prepared using QIAseq UPX 3'Transcriptome reagents and sequenced. Normalised gene expressions were obtained through the CLC Genomics Workbench. Differentially expressed genes (DEGs) (FDR-corrected P-value<0.05) were determined using the Limma package and PLS-DA modelling performed to calculate their importance (VIP score). Functionally related genes were identified and classified using DAVID tools. Strongest indicators of response were predicted by Random Forest area under the curve (AUC) analysis in this cohort and a similar validation cohort Results: At baseline increased binding of the labelled biologic was associated with a higher likelihood of response to treatment (AUROC81%, accuracy77%, PPV100%, NPV63%). 342 DEGs (75 up-regulated, 267 down-regulated) distinguished responders from non-responders, 76 fell within enriched pathways. Pathways related to inflammation, chemotaxis, TGF-beta signalling, extracellular matrix and carbohydrate metabolism were reduced and cell-cell adhesion increased in responders pre-treatment. Among the 37 genes with VIP>1, CRIP2, CXCL6, EMILIN1, GADD 45 B, LAMA4 and MAPKAPK2 were upregulated in non-responders pre-treatment and were good predictors of response (AUROC>0.7) in this cohort and validation cohort Conclusion: A higher mucosal binding of the biologics before treatment was observed in anti-TNF responders. Responsive UC patients have a less inflamed and fibrotic state pre-treatment. Chemotactic pathways, involving CXCL6 may be novel targets to treat non-responders