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Medical Department, Division of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
Medical Department, Division of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
Medical Department, Division of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, GermanyDeutsches Zentrum Immuntherapie (DZI), University Hospital Erlangen, Erlangen, Germany
Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, GermanyDeutsches Zentrum Immuntherapie (DZI), University Hospital Erlangen, Erlangen, Germany
Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, GermanyDeutsches Zentrum Immuntherapie (DZI), University Hospital Erlangen, Erlangen, Germany
Medical Department, Division of Gastroenterology, Infectiology and Rheumatology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, GermanyDeutsches Zentrum Immuntherapie (DZI), University Hospital Erlangen, Erlangen, Germany
Reprint requests: Sebastian Zundler, Department of Medicine 1, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, D-91054 Erlangen, Germany
Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, GermanyDeutsches Zentrum Immuntherapie (DZI), University Hospital Erlangen, Erlangen, Germany
Inflammatory bowel diseases are medically intractable and require constant therapy in many cases. While a growing number of biologicals and small molecules is available for treatment, a substantial portion of patients experiences primary non-response to these compounds and head-to-head evidence for therapy selection is scarce. Thus, approaches to predict treatment success in individual patients are a huge unmet need.
We had previously suggested that the expression and function of α4β7 integrin on T cells in the peripheral blood correlate to outcomes of therapy with the anti-α4β7 integrin antibody vedolizumab. Here, we conducted a translational multicenter trial to prospectively evaluate this hypothesis.
In a cohort of 89 patients with inflammatory bowel disease undergoing regular therapy with vedolizumab, lower baseline expression of α4β7 was associated with short-term clinical response. Consistently, low α4β7 expression in patients achieving remission predicted sustained remission in week 30. Moreover, high dynamic adhesion of CD4+ T cells to MAdCAM-1 and high reduction of adhesion by vedolizumab in vitro at baseline were associated with clinical remission.
These data substantiate the potential of α4β7 integrin function and expression to forecast outcomes of vedolizumab therapy. Further translational efforts are necessary to improve the performance of the assays and to implement the concept in clinical practice.
Despite a growing number of therapeutic options, the treatment of inflammatory bowel diseases remains challenging. In particular, many patients do not sufficiently respond to therapy, but biomarkers to predict treatment success are not established so far. This also concerns the anti-α4β7 integrin antibody vedolizumab. Here, we performed a prospective multicenter trial to translationally evaluate, whether α4β7 integrin expression and function forecast outcomes of therapy.
Translational Significance
Our data prove the concept that α4β7 integrin function and expression correlate with the success of vedolizumab treatment. Thus, they inform further translational efforts to optimize their assessment and to implement the concept in clinical practice.
Introduction
Inflammatory bowel diseases (IBD) such as Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammatory disorders of the gastrointestinal tract that often manifest at young age and cause symptoms such as abdominal pain and diarrhea.
They are considered to arise from a multifactorial interplay of host and environmental factors leading to a dysregulated immune response in the mucosal tissues of the intestine.
Approved therapeutic approaches are designed to abrogate these pathologic immune responses by neutralizing pro-inflammatory cytokines, inducing apoptosis or preventing the recruitment of pro-inflammatory immune cells.
Although the number of treatment options has been constantly rising over the past years, disease activity cannot be sufficiently controlled in many patients.
Specifically, only a portion of the patients responds to available therapeutics due to so far unknown reasons, while head-to-head evidence for therapy selection is scarce
Ustekinumab versus adalimumab for induction and maintenance therapy in biologic-naive patients with moderately to severely active Crohn’s disease: a multicentre, randomised, double-blind, parallel-group, phase 3b trial.
Thus, precisely tailoring IBD therapy to the individual patients is a huge unmet need and hopes have been placed in biomarker-driven decision strategies.
One established therapeutic option is the anti-α4β7 integrin antibody vedolizumab that blocks immune cell homing to the gut by disrupting adhesion of α4β7 integrin on the surface of immune cells to its ligand mucosal addressin cell adhesion molecule (MAdCAM)-1 on the intestinal endothelium.
Vedolizumab has been successfully used for the treatment of both UC and CD. However, randomized trials and real-world observations have demonstrated induction of remission in only a minority of patients.
We had previously reported the association of integrin expression and function on peripheral blood T cells with the outcome of therapy with vedolizumab in retrospective cohorts of patients with IBD.
Baseline levels of dynamic CD4+ T cell adhesion to MAdCAM-1 correlate with clinical response to vedolizumab treatment in ulcerative colitis: a cohort study.
Fuchs F, Schillinger D, Atreya R, et al. Clinical Response to Vedolizumab in Ulcerative Colitis Patients Is Associated with Changes in Integrin Expression Profiles. Front Immunol. 2017;8:764. https://doi.org/10.3389/fimmu.2017.00764.
Thus, here, we performed a translational multicenter study to prospectively validate the value of peripheral blood T cell α4β7 integrin expression and adhesion to MAdCAM-1 to predict the success of vedolizumab treatment.
Indeed, baseline integrin expression and function in our cohort correlated with short-term clinical response and remission, respectively, with high specificity and positive predictive value. While further efforts are necessary to optimize the performance of the assays, the data substantiate a novel translational concept for guiding therapeutic decisions in IBD.
Material and methods
Study design
Patients with established diagnosis of CD or UC that regularly started vedolizumab treatment were recruited for the study at the IBD outpatient clinics of the University Hospital Erlangen and the Charité - Universitätsmedizin Berlin after obtaining informed written consent. Further inclusion criteria were clinically active disease (Harvey-Bradshaw-Index (HBI) ≥ 5 for CD; partial Mayo score [PMS] ≥ 2 for UC) and/or steroid dependency. Patients with stoma, previous anti-integrin antibody treatment or previous colectomy were excluded.
Following informed written consent, blood samples were sequentially collected prior to treatment initiation (week 0), after induction therapy (week 6), at the fifth application of vedolizumab (week 14–22, mean week 17.5) and after 30 weeks (Fig. 1). Blood was drawn immediately (<1 hour) prior to vedolizumab applications.
Fig 1Schematic overview of study procedures. Patients were assessed at week 0, 6, 14-22 (fifth application of vedolizumab, mean 17.5 weeks) and 30 for patient and physician reported outcomes. Moreover, peripheral blood was analysed by flow cytometry. In addition, at week 0 and 6, dynamic adhesion assays were performed with peripheral blood CD4+ T cells.
On all visits, patient and physician reported outcomes were assessed (blinded for the experimental data). Clinical response to therapy was defined as reduction of the PMS ≥ 2 or HBI ≥ 3 points from baseline to the fifth application of vedolizumab (T5, mean 17.5 ± 0.38 weeks) in patients with UC and CD, respectively. Patients with steroid-dependent disease, in which steroids could be reduced by at least 20 mg without an increase in disease activity were also considered as therapy responders. Clinical remission was defined as PMS ≤ 1 or HBI ≤ 4 at T5. Additionally, switch to another treatment before T5 was categorized as treatment failure (non-response/non-remission).
The study procedures were performed according to The Code of Ethics of the World Medical Association (Declaration of Helsinki) and had previously been approved of by the Ethics Committee of the Charité – Universitätsmedizin Berlin (EA4/162/17).
Flow cytometry
In order to measure integrin expression on T cells, peripheral blood mononuclear cells (PBMCs) were isolated from each blood sample with standard density gradient centrifugation with Lymphocyte Separation Medium (Anprotec). Then, the cells were stained with antibodies listed in Suppl. Table 1 and fixed with FoxP3/Transcription Factor Staining Buffer Set (eBioscience). Subsequently, flow cytometry was run on MACSQuant (Miltenyi Biotec) and LSR Fortessa (BD) instruments. For data analysis we used FlowJo 10.8.1 software (BD Life Sciences) with fluorescence minus one (FMO) controls for the gating on integrins.
In additional experiments peripheral blood cells were stained with fluorescently labeled vedolizumab in addition to antibodies targeting the markers listed in Suppl. Table 1.
Dynamic adhesion assays
In a part of the cohort, dynamic adhesion assays were performed as previously described in week 0 and week 6.
To this end, CD4+ T cells were isolated from PBMCs with immunomagnetic beads (Miltenyi) and labeled with carboxyfluorescein succinimidyl ester (CFSE; Life Technologies). Then, the cells were incubated with and without 10 µg/mL vedolizumab (Takeda) in vitro for 1 h at 37° and suspended in adhesion buffer (pH 7.4; 150 mM NaCl, 10 mM HEPES, 1 mM CaCl2, 1 mM MgCl2, 1 mM MnCl2) at a concentration of 1.5 mio cells per mL. In parallel, miniature borosilicate capillaries (Vitrocom) were coated with 5 µg/mL Fc chimera of recombinant human MAdCAM-1 (R&D Systems) diluted in coating buffer (150 mM NaCl, 20 mM HEPES) or only coating buffer as a control. Unspecific binding sites in all capillaries were blocked with 10% fetal bovine serum (FBS) or 5% bovine serum albumin (BSA). Finally, capillaries were connected to plastic tubes, through which the previously prepared T cells (untreated for the control capillary, untreated and treated with vedolizumab for the coated capillaries) were perfused at a speed of 10 µL/min by a peristaltic pump (Boading Shenchen Precision Pump Company) (Suppl. Fig. 1A, Suppl. Video). Dynamic adhesion to MAdCAM-1 was monitored over a period of 3 minutes with time-lapse confocal microscopy (Leica SP8) and pictures being taken every 2 seconds. The adhesion was then quantified using ImageJ (NIH): 3 consecutive images from the beginning and end of the sequence each were colored in red, green or blue and then merged. That is, cells, which remained at the same position throughout the consecutive images, appeared white (as a result of merging red, green and blue) and were defined as adherent, whereas any other color indicated that cells had been at a different position in at least one image and were therefore defined as non-adherent. To retrieve the dynamic adhesion during the 3 minutes, we calculated the difference between adherent cells at the beginning and the end of this period (Suppl. Fig. 1B).
Statistics
For statistical analysis, GraphPad Prism (GraphPad Software, Inc.) was used. We used student's t test to compare two groups with normally distributed data. We considered P < 0.05 to be statistically significant and significance values are indicated by asterisks in the graphs as follows: * P< 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001. We performed receiver operator characteristics (ROC) to analyze a parameter's ability to identify patients reaching the endpoints and determined cut-offs for 4-fold table statistics. In some analyses, we were not able to include the whole patient cohort due to missing data for specific read-outs at specific visits.
In scatter plots and bar plots, unless otherwise indicated, mean ± SEM are displayed. In the patients’ baseline characteristics, categorial variables are indicated as frequencies and continuous variables are shown with mean values and range as indicated.
Results
Patient characteristics and efficacy of vedolizumab
Ninety-nine patients were recruited for the study. Ten patients dropped out of the study (predominantly due to loss to follow-up), so that 89 patients could be included in the final analysis (Fig 2).
From these 89 patients, 61 patients suffered from UC and 28 from CD. In general, most patients of the cohort had long-standing disease and were previously exposed to anti-TNF agents. Around one half received adjunctive steroids at induction.
Clinical response and remission at T5 were noted in 59.6% (62.3% - UC, 46.4% - CD) and 49.4 % (52.5% - UC, 42.9% - CD) of the patients, respectively.
Baseline characteristics of responders and non-responders are summarized in Tables 1 and 2, clinical efficacy at T5 is displayed in Table 3.
Table 1Baseline characteristics of patients with CD.
Responders
Non-responders
P-value
Number of patients
15
13
-
Age at vedolizumab induction (mean, range)
31.3 (18-64)
42.0 (22-58)
0.03 (*)
Age at diagnosis (mean, range)
23.9 (10-49)
23.0 (12-36)
0.82
Female
23.1%
60%
0.07
Harvey Bradshaw Index at vedolizumab induction (mean, range)
10.2 (5-20)
7.1 (3-15)
0.06
Adjunctive therapy at vedolizumab induction
Steroids
38.5%
46.7%
0.72
Immunosuppressants
23.1%
20.0%
>0.99
Previous exposure to anti-TNF
76.9%
86.7%
0.64
Previous surgery
76.9%
26.7%
0.02 (*)
Localization
L1
30.8%
20%
0.54
L2
23.1%
13.3%
L3
46.2%
66.7%
Family history for IBD
First-degree relatives
23.1%
33.3%
0.63
Other relatives
7.7%
0%
None
61.5%
53.3%
Unknown
7.7%
13.3%
Smoking status
Current
38.5%
46.7%
0.55
Former
38.5%
20%
Never
23.1%
33.3%
Parameters with significant differences between responders and non-responders do not correlate with baseline α4β7 expression (Suppl. Fig. 2).
Expression of α4β7 correlates with clinical response to vedolizumab
To explore, whether the expression of α4β7 at baseline indicates the subsequent success of vedolizumab therapy, we determined α4β7 expression on T cells by flow cytometry and correlated it to clinical outcomes at T5.
While only present as a trend in the CD8+ T cell subset (Suppl. Fig. 3A), the portion of CD3+ and CD4+ T cells expressing α4β7 integrin was higher in responders than in non-responders (Fig 3, A and B, Suppl. Fig. 3B), while expression levels of α4 and β7 on these cells were similar (Suppl. Fig. 3C). These findings were specific for T cells expressing α4β7, since the differences within the fraction of α4+β7− T cells between responders and non-responders were only marginal and not significant (Suppl. Fig. 3D). The area under the curve (AUC) for the abundance of α4β7-expressing CD3+ T cells for the prediction of clinical response on receiver-operator-characteristics (ROC) analysis was 0.706 (Fig 3, C, 95 % CI 0.593–0.819). Accordingly, a cut-off of 14.95 % expression was associated with a sensitivity of 38.5 %, a specificity of 88.2 %, a negative predictive value (NPV) of 48.4 % and a positive predictive value (PPV) of 83.3 % (Suppl. Table 2). For CD4+ T cells, a cut-off of 14.7 % expression yielded a sensitivity of 56.6 % a specificity of 73.5 %, a NPV of 52.1 % and a PPV of 76.9 % (Suppl. Table 3). When considering remission, there was a trend towards higher portions of T cells expressing α4β7 in patients not entering remission (Suppl. Fig. 3E).
Fig 3Association of integrin α4β7 expression with success of vedolizumab treatment. A, Representative flow cytometry of α4+β7+ cells in gated peripheral blood CD3+ T cells at week 0 from a responder and a non-responder to VDZ treatment. B, Quantitative flow cytometry of α4+β7+ cells in gated peripheral blood CD3+ T cells at week 0 in responders (n = 52) and non-responders (n = 34) to VDZ treatment. C, Receiver-operator characteristic (ROC) of the abundance of α4β7-expressing CD3+ T cells at week 0 for predicting the response to VDZ at T5. VDZ, Vedolizumab.
Importantly, the fraction of CD3+ T cells expressing α4β7 integrin did not differ between responders and non-responders in a small cohort of patients treated with infliximab, in which the same analyses were performed (Suppl. Fig. 3F).
Since several studies have associated low inflammatory burden with higher rates of response to vedolizumab therapy, we further sought to exclude that disease activity is associated with α4β7 expression. Indeed, neither C-reactive protein levels (Suppl. Fig. 4A) nor PMS (Suppl. Fig. 4B) or HBI (Suppl. Fig. 4C) correlated with the abundance of T cells expressing α4β7 at baseline. Moreover, although previous anti-TNF-α therapy has been shown to relate to the success of vedolizumab therapy in previous studies, the amount of α4β7-expressing T cells at baseline was independent on whether patients were previously treated with an anti-TNF-α agent (Suppl. Fig. 4D).
We also addressed the possibility that in our staining, in which we used antibodies for the α4 and β7 integrin monomers to avoid epitope competition with therapeutic vedolizumab, α4+β7+ cells might actually not be expressing the α4β7 heterodimer, e.g. due to co-expression of α4β1 and αEβ7. To this end, we stained peripheral blood samples from donors that did not receive vedolizumab therapy with fluorescently labeled vedolizumab in addition to the rest of the panel (Suppl. Fig. 5A,B). As expected, we observed that virtually all α4+β7+ CD4+ T cells were co-detected by vedolizumab staining indicating that they indeed express the integrin heterodimer (Suppl. Fig. 5C). Consistently, co-expression of α4 and β7 correlated very well with co-staining for β7 and vedolizumab (Suppl. Fig. 5D) suggesting that our data well reflect α4β7 integrin heterodimer expression and no competition with vedolizumab occurs in samples previously exposed to vedolizumab in vivo.
Function of α4β7 correlates with clinical remission under vedolizumab therapy
To investigate the association of α4β7 integrin function with the success of therapy, we explored α4β7-dependent adhesion to MAdCAM-1 as well as the effect of in vitro vedolizumab on such adhesion at baseline and correlated the data to clinical outcomes.
To this end, we used a dynamic adhesion assay, specifically determining the interaction of α4β7 integrin with MAdCAM-1 (Suppl. Fig. 1, Suppl. Fig. 6). The dynamic adhesion to MAdCAM-1 was significantly higher for CD4+ T cells from patients achieving remission than for cells of patients, who did not enter remission (Suppl. Fig. 7A). Consistently, the AUC of ROC analysis (AUROC) was 0.642 (95 % CI 0.512-0.773, Suppl. Fig. 7B). A cut-off of 9.5 adhering cells was the best to predict remission and reached a specificity of 84.6 % and a PPV of 70 % (Suppl. Table 4).
Likewise, the reduction of dynamic adhesion induced by vedolizumab treatment in vitro was higher in patients, in which vedolizumab induced remission than in those, in which it did not and the AUROC was 0.686 (95 % CI 0.563-0.810, Fig. 4). A reduction of more than 5.5 adhering cells yielded a specificity of 81.6% and a PPV of 68.2 % (Suppl. Table 5).
Fig 4Association of integrin α4β7 function with success of vedolizumab treatment. A, Representative baseline dynamic adhesion of peripheral blood CD4+ T cells with or without VDZ treatment in vitro to MAdCAM-1 from a patient achieving remission and a patient not achieving remission. Adhering cells are displayed in white. B, Reduction of baseline dynamic adhesion of CD4+ T cells to MAdCAM-1 by VDZ treatment in vitro in patients achieving clinical remission (n = 33) or not (n = 38) at T5. C Receiver-operator characteristic (ROC) of the reduction of baseline dynamic adhesion of CD4+ T cells to MAdCAM-1 by VDZ treatment in vitro for the prediction of remission at T5. VDZ, Vedolizumab.
With regard to clinical response, there was a trend towards increased MAdCAM-1 adhesion of CD4+ T cells from responders compared with non-responders, while the reduction induced by vedolizumab was similar (Suppl. Fig. 7C). Interestingly, when comparing the adhesion of untreated CD4+ T cells to MAdCAM-1 at baseline with CD4+ T cells obtained at week 6, we noted a decrease in patients that later achieved response or remission, but not in those without response or remission. This was significantly different between patients with and without remission (Suppl. Fig. 7D), but there was no meaningful correlation to changes in α4β7 expression (Suppl. Fig. 7E).
Low integrin expression in patients with remission at T5 predicts sustained remission at week 30
We further investigated, whether expression of α4β7 integrin on CD4+ T cells at T5 from patients, in which vedolizumab induced remission, might be predictive of remission at week 30. Similar to the correlation of baseline expression with outcomes at T5, α4β7 levels at T5 were clearly lower in patients that maintained remission in week 30 than in those, who did not (Fig. 5, A and B). AUROC was 0.854 (95% CI 0.687–1.000, Fig. 5, C) and a cut-off of 8.8% expression was associated with a sensitivity of 48.5%, a specificity of 100%, an NPV of 26.1% and a PPV of 100% (Suppl. Table 6).
Fig 5Association of integrin α4β7 expression with sustained success of vedolizumab. A, Representative flow cytometry of α4+β7+ cells in gated peripheral blood CD4+ T cells at T5 from a patient in sustained remission at week 30 and a patient without sustained remission at week 30. B, Quantitative flow cytometry of α4+β7+ cells in gated peripheral blood CD4+ T cells at T5 in patients with (n = 33) and without (n = 6) sustained remission. C, Receiver-operator characteristic (ROC) of the abundance of α4β7-expressing CD4+ T cells at T5 for the prediction of sustained remission at week 30.
Collectively, these data showed that α4β7 integrin expression and function at baseline and during therapy are potential biomarkers for the outcome of vedolizumab therapy.
Discussion
The importance of establishing biomarkers to predict the response to therapy in IBD has been repetitiously highlighted.
In current practice, the selection of therapies often relies on aspects of clinical presentation, co-morbidities, expected side-effects or preferred routes of administration.
While these are important aspects to take into account, this approach also includes elements of trial and error. However, to expedite the induction of clinical remission in patients, and since there is evidence for a negative correlation between the advancement in therapy lines and treatment outcomes,
more tailored approaches are desirable. Biomarkers have been suggested to help us move toward precision medicine, but no biomarker-driven approach has been implemented in clinical practice to date.
Here, we performed a translational prospective study at 2 German IBD centers to explore the link between integrin expression and function and outcomes of vedolizumab therapy.
While studies on the association of integrin expression and therapeutic success of vedolizumab have been previously performed,
Moreover, it is the first prospective evaluation of α4β7 integrin function for the prediction of response to vedolizumab.
Collectively, our data showed that low integrin expression and high dynamic adhesion to MAdCAM-1 at baseline correlate with clinical response and remission, respectively.
It is important to note that this direction of association between integrin expression is in contrast to a previous study: De Galan et al. had reported higher expression of α4β7 integrin on CD4+ T cells from responders compared with non-responders with UC.
These differences highlight the heterogeneity of patient cohorts. Moreover, they might be attributable to differences in the experimental workflows (eg, whether cells were previously frozen). Thus, additional multicentric efforts with harmonized protocols are necessary to further develop the idea of exploiting α4β7 integrin expression on T cells as a predictive biomarker.
Our data indicating decreased expression on T cells from responders compared with non-responders are, however, well in line with previous retrospective data reported by our group.
Fuchs F, Schillinger D, Atreya R, et al. Clinical Response to Vedolizumab in Ulcerative Colitis Patients Is Associated with Changes in Integrin Expression Profiles. Front Immunol. 2017;8:764. https://doi.org/10.3389/fimmu.2017.00764.
We had also previously suggested a mechanistic explanation for this finding by showing that the fraction of α4β7-expressing T cells in the peripheral blood inversely correlates with the capacity of T cells to adhere to MAdCAM-121. Thus, increased functionality of α4β7 in patients predisposed to respond to vedolizumab might lead to increased extravasation of α4β7-expressing T cells resulting in their reduced abundance in the peripheral blood. Consistently, increased mucosal expression of α4β7 integrin has been described in patients achieving remission than in patients without remission
The functional data on CD4+ T cell adhesion to MAdCAM-1 and associated vedolizumab response characteristics also corroborate earlier observations in a retrospective patient cohort.
Baseline levels of dynamic CD4+ T cell adhesion to MAdCAM-1 correlate with clinical response to vedolizumab treatment in ulcerative colitis: a cohort study.
One has to acknowledge that, while the specificity and positive predictive values of our read-outs are high, AUROCs and sensitivity do not yet meet the expectations one would have for a broadly applicable biomarker assay to direct therapeutic algorithms in IBD. Yet, it must also be noted that these numbers are similar or come close to several other previously reported concepts.
Expression levels of 4 genes in colon tissue might be used to predict which patients will enter endoscopic remission after vedolizumab therapy for inflammatory bowel diseases.
Moreover, there also still seems to be considerable potential to standardize and optimize the assays employed here to improve their performance, although their complexity probably limits their broad applicability. Further, given the interindividual variability of the parameters assessed in this study, they will probably require combination with other aspects to result in a useful biomarker tool. Additional limitations that need to be mentioned are the lack of standardized endoscopic or histological read-outs of disease activity, the heterogeneous study population, the missing correlation with tissue expression of α4β7 and that we were not able to comprehensively assess correlation to expression and function of α4β7 in the variety of α4β7-expressing immune cell subsets in the frame of this study. In conclusion, our work does not establish a useful clinical biomarker so far, but lays the groundwork for future studies predicting the response to treatment with vedolizumab and other therapies.
While some of the other recently described potential biomarker strategies for predicting the success of vedolizumab made use of complex techniques such as microbiome analysis or molecular endoscopy,
the easy availability of peripheral blood and the low level of invasiveness might be an advantage of this blood-based assay for potential real-world application. Since vedolizumab is deemed to prevent peripheral blood immune cells from entering the gut tissue,
using blood also makes sense from a mechanistic point of view.
In conclusion, our study demonstrates a link between expression and function of α4β7 integrin and clinical outcomes of vedolizumab therapy. These read-outs have the potential to contribute to biomarker strategies for the prediction of therapeutic success, but require confirmation in larger multi-centric studies and further efforts to improve and standardize the assays.
Acknowledgments
The authors thank Julia Derdau, Julia Marcks, Julia Schuster and Dorothee Dziony for excellent technical assistance.
Conflicts of interest: MFN has served as an advisor for Pentax, Giuliani, MSD, Abbvie, Janssen, Takeda and Boehringer. BS has served as consultant for Abbvie, Arena, BMS, Boehringer, Celgene, Falk, Galapagos, Janssen, Lilly, Pfizer, Prometheus and Takeda and received speaker's fees from Abbvie, CED Service GmbH, Falk, Ferring, Janssen, Novartis, Pfizer, Takeda [served as representative of the Charité]. SZ received received speaker's fees from Takeda, Roche, Galapagos, Ferring, Lilly and Janssen. MFN and SZ received research support from Takeda, Shire (a part of Takeda) and Roche. The other authors declare no conflicts of interest. All authors have read the journal's policy on disclosure of potential conflicts of interest.
This research was funded by Takeda (IISR-2017-102273) and the German Research Foundation (Deutsche Forschungsgemeinschaft, ZU377/4-1, TRR241 B08).
The present work was performed in (partial) fulfillment of the requirements for obtaining the degree “Dr. med.” for IS.
The research of IA, TMM, RA, MFN and SZ was supported by the Interdisciplinary Center for Clinical Research (IZKF) and the ELAN program of the University Erlangen-Nuremberg, the Else-Kröner-Fresenius-Stiftung, the Thyssen-Stiftung, the Fritz Bender-Stiftung, the Dr. Robert Pfleger Stiftung, the Litwin IBD Pioneers Initiative of the Crohn's and Colitis Foundation of America (CCFA), the Kenneth Rainin Foundation, the Ernst Jung-Stiftung for Science and Re-search, the German Crohn's and Colitis Foundation (DCCV) and the German Research Founda-tion (DFG) through individual grants (ZU 377/4-1) and the Collaborative Research Centers TRR241 and SFB 1181. The research of BS is supported by the DFG through the TRR241, SFB 1449 and the SFB 1340.
Author contributions: IS, CA, LM, MM performed the experiments, DL, BS, MFN and SZ designed the research. DL, FV, EB, IA, TMM, RA, BS, MFN and SZ contributed samples or protocols. IS, CA, LM, BS, EM, RG, MFN and SZ analyzed and interpreted the data. IS and SZ drafted the manuscript; all authors critically read and revised the manuscript for important intellectual content and approved the final version. All authors have read the journal's authorship agreement.
Ustekinumab versus adalimumab for induction and maintenance therapy in biologic-naive patients with moderately to severely active Crohn’s disease: a multicentre, randomised, double-blind, parallel-group, phase 3b trial.
Baseline levels of dynamic CD4+ T cell adhesion to MAdCAM-1 correlate with clinical response to vedolizumab treatment in ulcerative colitis: a cohort study.
Fuchs F, Schillinger D, Atreya R, et al. Clinical Response to Vedolizumab in Ulcerative Colitis Patients Is Associated with Changes in Integrin Expression Profiles. Front Immunol. 2017;8:764. https://doi.org/10.3389/fimmu.2017.00764.
Expression levels of 4 genes in colon tissue might be used to predict which patients will enter endoscopic remission after vedolizumab therapy for inflammatory bowel diseases.
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