Network-based response module comprised of gene expression biomarkers predicts response to infliximab at treatment initiation in ulcerative colitis.

Autor: Ghiassian SD; Scipher Medicine Corporation, Waltham MA., Voitalov I; Scipher Medicine Corporation, Waltham MA., Withers JB; Scipher Medicine Corporation, Waltham MA., Santolini M; Center for Research and Interdisciplinarity (CRI), University Paris Descartes, Paris, France., Saleh A; Scipher Medicine Corporation, Waltham MA., Akmaev VR; Scipher Medicine Corporation, Waltham MA. Electronic address: slava.akmaev@sciphermedicine.com.
Jazyk: angličtina
Zdroj: Translational research : the journal of laboratory and clinical medicine [Transl Res] 2022 Aug; Vol. 246, pp. 78-86. Date of Electronic Publication: 2022 Mar 16.
DOI: 10.1016/j.trsl.2022.03.006
Abstrakt: This cross-cohort study aimed to (1) determine a network-based molecular signature that predicts the likelihood of inadequate response to the tumor necrosis factor-ɑ inhibitor (TNFi) therapy, infliximab, in ulcerative colitis (UC) patients, and (2) address biomarker irreproducibility across different cohort studies. Whole-transcriptome microarray data were derived from biopsies of affected colon tissue from 2 cohorts of infliximab-treated UC patients (training N = 24 and validation N = 22). Response was defined as endoscopic and histologic healing at 4-6 weeks and 8 weeks, respectively. From the training cohort, genes with RNA expression that significantly correlated with clinical response outcomes were mapped onto the Human Interactome network map of protein-protein interactions to identify a largest connected component (LCC) of proteins indicative of infliximab response status in UC. Expression levels of transcripts within the LCC were fed into a probabilistic neural network model to generate a classifier that predicts inadequate response to infliximab. A classifier predictive of inadequate response to infliximab was generated and tested in a cross-cohort, blinded fashion; the AUC was 0.83 and inadequate response was predicted with a 100% positive predictive value and 64% sensitivity. Genes separately identified from the 2 cohorts that correlated with response to infliximab appeared distinct but mapped onto the same network region of the Human Interactome, reflecting a common underlying biology of response among UC patients. Cross-cohort validation of a classifier predictive of infliximab response status in UC patients indicates that a molecular signature of non-response to TNFi therapies is present in patients' baseline gene expression data. The goal is to develop a diagnostic test that predicts which patients will have an inadequate response to targeted therapies and define new targets and pathways for therapeutic development.
(Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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