4.8 Article

Cell-centred meta-analysis reveals baseline predictors of anti-TNFα non-response in biopsy and blood of patients with IBD

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GUT
卷 68, 期 4, 页码 604-614

出版社

BMJ PUBLISHING GROUP
DOI: 10.1136/gutjnl-2017-315494

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资金

  1. Helmsley Charitable Trust
  2. Bill and Melinda Gates Foundation
  3. NIH [5K12HL120001-02]
  4. Lady Davis postdoctoral fellowship
  5. NIH'NIAID [U19AI090019, U19AI109662, U 19AI057229, U54I117925]

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Objective Although anti-tumour necrosis factor alpha (anti-TNF alpha) therapies represent a major breakthrough in IBD therapy, their cost-benefit ratio is hampered by an overall 30% non-response rate, adverse side effects and high costs. Thus, finding predictive biomarkers of non-response prior to commencing anti-TNF alpha therapy is of high value. Design We analysed publicly available whole-genome expression profiles of colon biopsies obtained from multiple cohorts of patients with IBD using a combined computational deconvolution-meta-analysis paradigm which allows to estimate immune cell contribution to the measured expression and capture differential regulatory programmes otherwise masked due to variation in cellular composition. Insights from this in silico approach were experimentally validated in biopsies and blood samples of three independent test cohorts. Results We found the proportion of plasma cells as a robust pretreatment biomarker of non-response to therapy, which we validated in two independent cohorts of immune-stained colon biopsies, where a plasma cellular score from inflamed biopsies was predictive of non-response with an area under the curve (AUC) of 82%. Meta-analysis of the cell proportion-adjusted gene expression data suggested that an increase in inflammatory macrophages in anti-TNF alpha non-responding individuals is associated with the upregulation of the triggering receptor expressed on myeloid cells 1 (TREM-1) and chemokine receptor type 2 (CCR2)-chemokine ligand 7 (CCL7) -axes. Blood gene expression analysis of an independent cohort, identified TREM-1 downregulation in non-responders at baseline, which was predictive of response with an AUC of 94%. Conclusions Our study proposes two clinically feasible assays, one in biopsy and one in blood, for predicting non-response to anti-TNF alpha therapy prior to initiation of treatment. Moreover, it suggests that mechanism-driven novel drugs for non-responders should be developed.

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