{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["37(6)"],"submitter":["Singh A"],"funding":["UiT The Arctic University of Norway"],"pubmed_abstract":["Background
In ulcerative colitis (UC), the molecular mechanisms that drive disease development and patient response to therapy are not well understood. A significant proportion of patients with UC fail to respond adequately to biologic therapy. Therefore, there is an unmet need for biomarkers that can predict patients' responsiveness to the available UC therapies as well as ascertain the most effective individualised therapy. Our study focused on identifying predictive signalling pathways that predict anti-integrin therapy response in patients with UC.Methods
We retrieved and pre-processed two publicly accessible gene expression datasets (GSE73661 and GSE72819) of UC patients treated with anti-integrin therapies: (1) 12 non-IBD controls and 41 UC patients treated with Vedol"],"journal":["International journal of colorectal disease"],"pagination":["1321-1333"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9167201"],"repository":["biostudies-literature"],"pubmed_title":["Identifying predictive signalling networks for Vedolizumab response in ulcerative colitis."],"pmcid":["PMC9167201"],"pubmed_authors":["Paulssen RH","Singh A","Fenton CG","Anderssen E"],"additional_accession":[]},"is_claimable":false,"name":"Identifying predictive signalling networks for Vedolizumab response in ulcerative colitis.","description":"Background
In ulcerative colitis (UC), the molecular mechanisms that drive disease development and patient response to therapy are not well understood. A significant proportion of patients with UC fail to respond adequately to biologic therapy. Therefore, there is an unmet need for biomarkers that can predict patients' responsiveness to the available UC therapies as well as ascertain the most effective individualised therapy. Our study focused on identifying predictive signalling pathways that predict anti-integrin therapy response in patients with UC.Methods
We retrieved and pre-processed two publicly accessible gene expression datasets (GSE73661 and GSE72819) of UC patients treated with anti-integrin therapies: (1) 12 non-IBD controls and 41 UC patients treated with Vedol","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Jun","modification":"2026-05-10T01:38:45.29Z","creation":"2025-02-19T01:12:18.42Z"},"accession":"S-EPMC9167201","cross_references":{"pubmed":["35543875"],"doi":["10.1007/s00384-022-04176-w"]}}