P915 Multi-Omics Biomarkers for the Prediction of Response to Biologics in Patients with Inflammatory Bowel Disease

Abstract

Abstract Background The treatment concept for inflammatory bowel disease (IBD) has been transformed with biologics now recommended as the first-line therapy for moderate-to-severe patients. However, the significant heterogeneity among IBD patients has limited the efficacy of selected biologics based on traditional clinical factors. Therefore, it is imperative to molecularly stratify patients to match them with the most appropriate biologics. In this study, we systematically reviewed baseline omics biomarkers that have the potential to predict response to biological therapies, aiming to facilitate precision medicine in IBD. Methods We conducted a comprehensive literature search using PubMed by which we included studies that explore the role of omics biomarkers in predicting the efficacy of various biologics including anti-TNFα, anti-integrin, anti-IL-12/23P40 and anti-IL-23 P19 in patients with IBD. Results Our review included 110 studies. Of these, 86 studies focused on anti-TNFα, 17 focused on anti-integrin and 7 focused on anti-IL-12/23P40 and/or anti-IL-23P19. These studies investigated multi-levels baseline biomarkers, including genomics, transcriptomics (bulk RNA and sc-RNA sequence), proteomics, microbiome, and metabolomics (derived from serum, urine, or stool). Furthermore, recent studies already focused on integrating multiple omics analysis and showed that the predictive model based on multi-omics data could significantly enhance their performance. Among the available biomarkers, mucosal transcription of OSM (AUROC = 0.83), IL-13RA2 (AUROC = 0.90), and TREM-1 transcription in mucosal biopsy (AUROC = 0.77) as well as in PBMC ( AUROC varies between 0.78 and 0.94) could accurately predict the response to anti-TNFα. The mucosal IL-23A transcription could discriminate responders from non-responders to anti-IL-12/23P40 with an AUROC of 0.90. OSM, biomarkers of intestinal collagen turnover like C4M, IL-17, IL-22, and TNFα in serum also showed significant potential in predicting the response to anti-TNFα, anti-integrin and anti-IL-12/23P40. In addition, single-cell molecular signatures with sc-RNA sequencing provided more profound insights into predicting the response to biologics. The lack of reproducibility in results across different groups may be due to the disparity in patient selection, methodology, and study designs among different investigations. Conclusion Numerous omics markers have shown great potential in predicting the efficacy of biologics. However, it is crucial to explore and validate these novel biomarkers in larger cohorts using harmonized protocols to facilitate their evaluation into actual clinical practice, especially for newer biologics like anti-IL-12/23P40 and anti-IL-23P19.