Cultured blood T‐cell responses predict anti‐<scp>TNF</scp> therapy response in patients with ulcerative colitis

Magnusson, Maria K.; Strid, Hans; Isaksson, Stefan; Bajor, Antal; Lasson, Anders; Ung, Kjell-Arne; Öhman, Lena

doi:10.1111/apt.13192

Cited by 10 publications

(7 citation statements)

References 28 publications

(35 reference statements)

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“…A created prediction model was subsequently tested in a validation cohort. Correct classification of future therapy response was here achieved in 91% of the cases ( 113 ). In UC patients, primary anti-TNF non-responders had significantly increased TNF, IFNγ, IL-1β, and IL-10 levels compared to responders.…”

Section: Blood Markersmentioning

confidence: 79%

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

2020

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The advent of anti-TNF agents as the first approved targeted therapy in the treatment of inflammatory bowel disease (IBD) patients has made a major impact on our existing therapeutic algorithms. They have not only been approved for induction and maintenance treatment in IBD patients, but have also enabled us to define and achieve novel therapeutic outcomes, such as combination of clinical symptom control and endoscopic remission, as well as mucosal healing. Nevertheless, approximately one third of treated patients do not respond to initiated anti-TNF therapy and these treatments are associated with sometimes severe systemic side-effects. There is therefore the currently unmet clinical need do establish predictive markers of response to identify the subgroup of IBD patients, that have a heightened probability of response. There have so far been approaches from different fields of IBD research, to descry markers that would empower us to apply TNF-inhibitors in a more rational manner. These markers encompass findings from disease-related and clinical factors, pharmacokinetics, biochemical markers, blood and stool derived parameters, pharmacogenomics, microbial species, metabolic compounds, and mucosal factors. Furthermore, changes in the intestinal immune cell composition in response to therapeutic pressure of anti-TNF treatment have recently been implicated in the process of molecular resistance to these drugs. Insights into factors that determine resistance to anti-TNF therapy give reasonable hope, that a more targeted approach can then be utilized in these non-responders. Here, IL-23 could be identified as one of the key factors determining resistance to TNF-inhibitors. Growing insights into the molecular mechanism of action of TNF-inhibitors might also enable us to derive critical molecular markers that not only mediate the clinical effects of anti-TNF therapy, but which level of expression might also correlate with its therapeutic efficacy. In this narrative review, we present an overview of currently identified possible predictive markers for successful anti-TNF therapy and discuss identified molecular pathways that drive resistance to these substances. We will also point out the necessity and difficulty of developing and validating a diagnostic marker concerning clinically relevant outcome parameters, before they can finally enter daily clinical practice and enable a more personalized therapeutic approach.

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Section: Blood Markersmentioning

confidence: 79%

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

2020

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“…Decreased frequencies of CD25+ T cells, increased annexin V+ CD4+CD8+ T cells and decreased concentrations of serum CD25 and TNFR2 were also associated with initial response . In addition, a combination of T‐cell receptor CD25 suppression and a decrease in IL‐5 secretion was predictive of treatment response with 85% accuracy . Reduction in tenascin C (an extracellular matrix glycoprotein) predicted downregulation of CCL2 (a proinflammatory chemokine), which was associated with response at week 14 .…”

Section: Resultsmentioning

confidence: 98%

“…Recent findings suggest that analysing material close to or directly from the location of disease yields the highest concentration of potential biomarkers . Accordingly, mucosal tissue has yielded several promising signals for both anti‐TNF and EZM . Interestingly, the rigorous analysis of different mucosal gene expression studies appears to be a valuable platform for biomarker discovery, as illustrated by the identification of oncostatin M and its receptor as potential marker for anti‐TNF response …”

Section: Discussionmentioning

confidence: 99%

Systematic review: predictive biomarkers of therapeutic response in inflammatory bowel disease—personalised medicine in its infancy

Stevens

Matheeuwsen

Lönnkvist

et al. 2018

Aliment Pharmacol Ther

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Summary Background Inflammatory bowel disease (IBD) is characterised by substantial heterogeneity in treatment response. With an expanding number of therapeutic agents, identifying optimal treatment at the patient level remains a major challenge. Aim To systematically review the available literature on predictive biomarkers of therapeutic response in IBD. Methods An electronic literature search was performed on 30 January 2018 using MEDLINE, EMBASE and the Cochrane Library. Retrospective, prospective, uncontrolled and controlled studies reporting on biomarkers predicting therapeutic response in paediatric and adult IBD populations were eligible for inclusion. The methodological quality of the included studies was assessed using the QUIPS tool. Due to anticipated heterogeneity and limited data, a qualitative, rather than quantitative, assessment was planned. Results Of the 10 638 citations identified, 92 articles met the inclusion criteria. Several potential DNA, mRNA and protein markers were evaluated as predictive biomarkers. Most studies focused on predicting response to anti‐TNF agents. Substantial between‐study heterogeneity was identified with respect to both the biomarkers studied and the definition of response. None of the included studies received a low risk of bias rating for all six domains. Currently, none of the biomarkers is sufficiently predictive for clinical use. Conclusions The search for predictive biomarkers is still in its infancy and current evidence is limited. Future research efforts should take into account the high patient heterogeneity within prospective trials with objective response assessment. Predictive models will most likely comprise a combination of several molecular markers from integrated omics‐levels and clinical characteristics.

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“…Gene microarray experiments have revealed a signature CD8 T-cell transcriptional profile that may be predictive of the need for future treatment escalation, which may allow for the potential of a worsening disease evolution to be recognised at diagnosis of UC [19]. Preliminary findings suggest that expression of the peripheral blood T-cell surface marker CD25 and levels of interleukin-5 secretion in vitro may predict response to anti-TNF drugs [74].…”

Section: Patient-focused Unmet Needsmentioning

confidence: 99%

“…Clinical data demonstrating and validating correlations between inflammatory mediators and their metabolites with levels of disease severity in UC could form a useful basis for the development of routine tests to inform the likely effectiveness of treatments [71,74].…”

Section: Patient-focused Unmet Needsmentioning

confidence: 99%

Unmet Medical Needs in Ulcerative Colitis: An Expert Group Consensus

Danese

Allez

Bodegraven

et al. 2019

Dig Dis

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Background: The authors aimed to conduct an extensive literature review and consensus meeting to identify unmet needs in ulcerative colitis (UC) and ways to overcome them. UC is a relapsing and remitting inflammatory bowel disease with varied, and changing, incidence rates worldwide. UC has an unpredictable disease course and is associated with a high health economic burden. During 2016 and 2017, a panel of experts was convened to identify, discuss and address areas of unmet need in UC. Methods: PubMed and Cochrane Library databases were searched for relevant articles describing studies performed in patients with UC. These findings were used to generate a set of statements relating to unmet needs in UC. Consensus on these statements was then sought from a panel of 9 expert gastroenterologists using a modified Delphi review process that consisted of anonymous surveys followed by live meetings. Results: In 2 literature reviews, over 5,000 unique records were identified and a total of 138 articles were fully reviewed. These were used to consider 26 areas of unmet need, which were explored in 2 face-to-face meetings, in which the statements were debated and amended, resulting in consensus on 30 final statements. The unmet needs identified were categorised into 7 areas: impact of UC on patients’ daily life; importance of early diagnosis and treatment; drawbacks of existing treatments; urgent need for new treatments; and disease-, practice- or patient-focused unmet needs. Conclusions: These expert group meetings found a number of areas of unmet needs in UC, which is an important first step in tackling them in the future. Future research and development should be focused in these areas for the management of patients with UC.

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Cultured blood T‐cell responses predict anti‐TNF therapy response in patients with ulcerative colitis

Abstract: SUMMARY BackgroundAnti-tumour necrosis factor (TNF) therapy is used for treatment of ulcerative colitis (UC). As approximately 30% of patients with UC do not benefit from the treatment, it is of clinical interest to identify biomarkers of response before therapy is initiated.

Cited by 10 publications

References 28 publications

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

Systematic review: predictive biomarkers of therapeutic response in inflammatory bowel disease—personalised medicine in its infancy

Unmet Medical Needs in Ulcerative Colitis: An Expert Group Consensus

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