Molecular Profiling of Ulcerative Colitis Subjects from the TURANDOT Trial Reveals Novel Pharmacodynamic/Efficacy Biomarkers

Abstract

Background and aims: To define pharmacodynamic and efficacy biomarkers in ulcerative colitis [UC] patients treated with PF-00547659, an anti-human mucosal addressin cell adhesion molecule-1 [MAdCAM-1] monoclonal antibody, in the TURANDOT study.

Methods: Transcriptome, proteome and immunohistochemistry data were generated in peripheral blood and intestinal biopsies from 357 subjects in the TURANDOT study.

Results: In peripheral blood, C-C motif chemokine receptor 9 [CCR9] gene expression demonstrated a dose-dependent increase relative to placebo, but in inflamed intestinal biopsies CCR9 gene expression decreased with increasing PF-00547659 dose. Statistical models incorporating the full RNA transcriptome in inflamed intestinal biopsies showed significant ability to assess response and remission status. Oncostatin M [OSM] gene expression in inflamed intestinal biopsies demonstrated significant associations with, and good accuracy for, efficacy, and this observation was confirmed in independent published studies in which UC patients were treated with infliximab or vedolizumab. Compared with the placebo group, intestinal T-regulatory cells demonstrated a significant increase in the intermediate 22.5-mg dose cohort, but not in the 225-mg cohort.

Conclusions: CCR9 and OSM are implicated as novel pharmacodynamic and efficacy biomarkers. These findings occur amid coordinated transcriptional changes that enable the definition of surrogate efficacy biomarkers based on inflamed biopsy or blood transcriptomics data.ClinicalTrials.gov identifierNCT01620255.

Keywords: MAdCAM-1; PF-00547659; Ulcerative colitis; biomarkers; inflammatory bowel disease.

© The Author(s) 2019. Published by Oxford University Press on behalf of European Crohn’s and Colitis Organisation.

Figures

Figure 1.

Fold changes in CCR9 gene expression from baseline [BL] to Week 4 or Week 12 by treatment group. *0.01 < FDR ≤ 0.1; †0.00001 < FDR ≤ 0.01; #FDR ≤ 0.00001 vs placebo.

Figure 2.

Network constructed by querying the Ingenuity Pathways Knowledge Base on 97 genes associated with clinical efficacy in the TURANDOT dataset and confirmed in all three public datasets [GSE23597, GSE16879, and GSE73661]. Genes coloured in green indicate greater decrease from baseline among patients who reached remission at 12 weeks compared with those who did not; genes coloured in red indicate opposite associations.

Figure 3.

Associations between changes of OSM at Week 12 from baseline [RNA expression in the inflamed biopsies, RNA expression in blood and serum protein concentration], and clinical end points in the TURANDOT Trial [A], the GSE23597 and GSE16879 datasets [B], and the GSE73661 dataset [C]. remi, remission; resp, response; mh, mucosal healing. Blue boxes and lines indicate mean estimates and 95% confidence intervals, respectively. The p values were calculated by comparing those achieving remission vs those not achieving remission, responders vs non-responders, or patients who achieved mucosal healing vs those who did not, in terms of changes of OSM gene expression from baseline. Yes and No indicate in remission [Yes] and not in remission [No], responders [Yes] and non-responders [No], or patients who achieved mucosal healing [Yes] and who did not [No]. *0.01 < FDR ≤ 0.1; †0.00001 < FDR ≤ 0.01; #FDR ≤ 0.00001.

Figure 4.

Receiver operator characteristic analysis of OSM [RNA expression in the inflamed biopsies, RNA expression in blood and serum protein level] changes at Week 12 after adjusting baseline levels, distinguishing patients who achieved clinical efficacy in the TURANDOT Trial [A], the GSE23597 and GSE16879 datasets [B], and the GSE73661 dataset [C]. remi, remission; resp, response; mh, mucosal healing.

Figure 5.

[A] Comparisons of model performance for three representative machine learning approaches [linear model in blue, network-based model in green, non-linear model in red] in all 12 contrasts of interest. Performance of each model is given as c-statistic or area under the receiver operating curve [AUROC] with 95% confidence intervals. Random performance of 0.5 is depicted by a grey line, and relevant performance is shown by a dashed line at an AUROC of 0.8. Three models for assessing clinical response or clinical remission reach relevant levels of performance [blood, remission; inflamed tissue, remission; inflamed tissue, response]. See text for more details. [B] Transcripts [out of a total of 14 000] contributing most strongly to performance in the linear models assessing clinical remission and clinical response based on whole blood or inflamed tissue biopsies at Week 12. Transcripts are ranked by relative importance as described in the Methods section. Transcripts that are shared between the clinical remission and clinical response contrasts are highlighted in lighter red to indicate their robust role in driving model performance [NR2E1, NECAB1, CD177, and SLC51 for blood and OSM for tissue biopsy data].

Figure 6.

Treg [CD3+/CD25+/FoxP3+] differences [A] at baseline between inflamed and non-inflamed biopsies; [B] between high and low MAYO score patients across treatment groups in the inflamed biopsies; [C] between high and low MAYO score patients across treatment groups in the non-inflamed biopsies.