Potential molecular biomarkers used to predict the response to biological therapies in ulcerative colitis.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhang RF
PROVIDER: S-EPMC8116026 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Publications
Potential molecular biomarkers used to predict the response to biological therapies in ulcerative colitis.
Zhang Run-Feng RF Liu Shuang S Wang Yun-Wei YW Li Ji J
Chinese medical journal 20210203 9
Similar Datasets
Project description:Background and aimsRitlecitinib, an oral JAK3/TEC family kinase inhibitor, was well-tolerated and efficacious in the phase 2b VIBRATO study in participants with moderate-to-severe ulcerative colitis [UC]. The aim of this study was to identify baseline serum and microbiome markers that predict subsequent clinical efficacy and to develop noninvasive serum signatures as potential real-time noninvasive surrogates of clinical efficacy after ritlecitinib.MethodsTissue and peripheral blood proteomics, transcriptomics, and faecal metagenomics were performed on samples before and after 8 weeks of oral ritlecitinib induction therapy [20 mg, 70 mg, 200 mg, or placebo once daily, N = 39, 41, 33, and 18, respectively]. Linear mixed models were used to identify baseline and longitudinal protein markers associated with efficacy. The combined predictivity of these proteins was evaluated using a logistic model with permuted efficacy data. Differential expression of faecal metagenomics was used to differentiate responders and nonresponders.ResultsPeripheral blood serum proteomics identified four baseline serum markers [LTA, CCL21, HLA-E, MEGF10] predictive of modified clinical remission [MR], endoscopic improvement [EI], histological remission [HR], and integrative score of tissue molecular improvement. In responders, 37 serum proteins significantly changed at Week 8 compared with baseline [false discovery rate of <0.05]; of these, changes in four [IL4R, TNFRSF4, SPINK4, and LAIR-1] predicted concurrent EI and HR responses. Faecal metagenomics analysis revealed baseline and treatment response signatures that correlated with EI, MR, and tissue molecular improvement.ConclusionsBlood and microbiome biomarkers stratify endoscopic, histological, and tissue molecular responses to ritlecitinib, which may help guide future precision medicine approaches to UC treatment. ClinicalTrials.gov NCT02958865.
| S-EPMC11369066 | biostudies-literature
Project description:ObjectivesTo reveal the molecular mechanisms of ulcerative colitis (UC) and provide potential biomarkers for UC gene therapy.MethodsWe downloaded the GSE87473 microarray dataset from the Gene Expression Omnibus (GEO) and identified the differentially expressed genes (DEGs) between UC samples and normal samples. Then, a module partition analysis was performed based on a weighted gene coexpression network analysis (WGCNA), followed by pathway and functional enrichment analyses. Furthermore, we investigated the hub genes. At last, data validation was performed to ensure the reliability of the hub genes.ResultsBetween the UC group and normal group, 988 DEGs were investigated. The DEGs were clustered into 5 modules using WGCNA. These DEGs were mainly enriched in functions such as the immune response, the inflammatory response, and chemotaxis, and they were mainly enriched in KEGG pathways such as the cytokine-cytokine receptor interaction, chemokine signaling pathway, and complement and coagulation cascades. The hub genes, including dual oxidase maturation factor 2 (DUOXA2), serum amyloid A (SAA) 1 and SAA2, TNFAIP3-interacting protein 3 (TNIP3), C-X-C motif chemokine (CXCL1), solute carrier family 6 member 14 (SLC6A14), and complement decay-accelerating factor (CD antigen CD55), were revealed as potential tissue biomarkers for UC diagnosis or treatment.ConclusionsThis study provides supportive evidence that DUOXA2, A-SAA, TNIP3, CXCL1, SLC6A14, and CD55 might be used as potential biomarkers for tissue biopsy of UC, especially SLC6A14 and DUOXA2, which may be new targets for UC gene therapy. Moreover, the DUOX2/DUOXA2 and CXCL1/CXCR2 pathways might play an important role in the progression of UC through the chemokine signaling pathway and inflammatory response.
| S-EPMC7073481 | biostudies-literature
Project description:BackgroundGlucocorticoids (GCS) remain one of the mainstay treatments in the management of ulcerative colitis (UC) but up to a third of patients will ultimately fail to respond and progress to a more severe and difficult to manage disease state. Previous clinical studies suggest that the Toll-Like Receptor 9 (TLR9) agonist DIMS0150 not only induces production of key anti-inflammatory cytokines as IL-10 but interestingly also enhances steroid sensitivity in steroid refractory UC patients. We investigated, in the context of a clinical study, whether a pre-selection of steroid response genes could identify steroid refractory UC subjects most likely to respond to DIMS0150 treatment.MethodsIn a non-interventional pilot study, blood from steroid refractory UC patients and healthy volunteers was taken and thirty-four previously described steroid response genes were analysed by real time PCR analysis. To establish clinical utility of the identified biomarkers, a placebo controlled, randomized, double blinded study in active steroid dependent and steroid resistant UC patients on concomitant steroid therapies was used (EudraCT number: 2006-001846-15).ResultsWe identified three potential biomarkers CD163, TSP-1 and IL-1RII whose response to steroids was significantly enhanced when DIMS0150 was applied. Thirty-four subjects were randomized to receive a single rectal administration of placebo or 30 mg of DIMS0150. Blood derived PBMCs were obtained prior to dosing and assayed for evidence of a steroid enhancing effect following steroid incubation in the presence of DIMS0150. Comparison to established steroid sensitivity marker IL-6 confirmed that clinical responders are steroid refractory UC patients. Upon study completion and un-blinding, the biomarker assay correctly predicted a clinical response in over 90% of the patients.ConclusionUsing specific steroid response biomarkers, GCS refractory UC patients most likely to benefit from DIMS0150 treatment could be identified and illustrates the usefulness of a personalized treatment approach.
| S-EPMC4005617 | biostudies-literature
Project description:Ulcerative colitis (UC) is a major form of inflammatory bowel disease (IBD) worldwide. Better understanding of the pathogenesis of UC has led to the development of novel therapeutic agents that target specific mediators of the inflammatory cascade. A number of biological agents have been approved by the U.S. Food and Drug Administration (FDA) for the treatment of UC and several more are currently in various phases of drug development. The commonly used agents include TNFα antagonists (e.g. infliximab, adalimumab, and golimumab) and anti-integrin agents (vedolizumab). These biological agents have profoundly influenced the management of UC patients, especially those with refractory disease. This paper reviews the currently available knowledge and evidence for the use of various biological agents in the treatment of UC.
| S-EPMC4423460 | biostudies-literature
Project description:BackgroundDevelop a clinical and biological predictive model for colectomy risk in children newly diagnosed with ulcerative colitis (UC).MethodsThis was a multicenter inception cohort study of children (ages 4-17 years) newly diagnosed with UC treated with standardized initial regimens of mesalamine or corticosteroids (CS) depending upon initial disease severity. Therapy escalation to immunomodulators or infliximab was based on predetermined criteria. Patients were phenotyped by clinical activity per the Pediatric Ulcerative Colitis Activity Index (PUCAI), disease extent, endoscopic/histologic severity, and laboratory markers. In addition, RNA sequencing defined pretreatment rectal gene expression and high density DNA genotyping by the Affymetrix UK Biobank Axiom Array. Coprimary outcomes were colectomy over 3 years and time to colectomy. Generalized linear models, Cox proportional hazards multivariate regression modeling, and Kaplan-Meier plots were used.ResultsFour hundred twenty-eight patients (mean age 13 years) started initial theapy with mesalamine (n = 136), oral CS (n = 144), or intravenous CS (n = 148). Twenty-five (6%) underwent colectomy at ≤1 year, 33 (9%) at ≤2 years, and 35 (13%) at ≤3 years. Further, 32/35 patients who had colectomy failed infliximab. An initial PUCAI ≥ 65 was highly associated with colectomy (P = 0.0001). A logistic regression model predicting colectomy using the PUCAI, hemoglobin, and erythrocyte sedimentation rate had a receiver operating characteristic area under the curve of 0.78 (95% confidence interval [0.73, 0.84]). Addition of a pretreatment rectal gene expression panel reflecting activation of the innate immune system and response to external stimuli and bacteria to the clinical model improved the receiver operating characteristic area under the curve to 0.87 (95% confidence interval [0.82, 0.91]).ConclusionsA small group of children newly diagnosed with severe UC still require colectomy despite current therapies. Our gene signature observations suggest additional targets for management of those patients not responding to current medical therapies.
| S-EPMC8804885 | biostudies-literature
Project description:IntroductionBiological therapies are widely used for the treatment of ulcerative colitis. However, only a low proportion of patients achieve clinical remission and even less mucosal healing. There is currently scarce knowledge about the early markers of therapeutic response, with particular regard to mucosal healing. The aim of this prospective study was to evaluate the role of fecal calprotectin (FC) as early predictor of mucosal healing.MethodsA prospective observational study was conducted on patients with ulcerative colitis, who started biological therapy with infliximab, adalimumab, golimumab, or vedolizumab at our center. All patients underwent colonoscopy, performed by 2 blinded operators, at baseline and week 54 or in case of therapy discontinuation because of loss of response. FC was assessed at baseline and week 8 and evaluated as putative predictor of mucosal healing at week 54.ResultsWe enrolled 109 patients, and 97 were included in the analysis. Twenty-six patients (27%) experienced loss of response. Over 71 patients (73%) with clinical response at week 54, clinical remission was obtained in 60 patients (61.9%) and mucosal healing in 45 patients (46.4%). After 8 weeks of treatment, FC predicted mucosal healing at week 54 (P < 0.0001). Sensitivity, specificity, positive predictive value, and negative predictive value were estimated to be 75%, 88.9%, 86.6%, and 75.5%, respectively, based on a cutoff of 157.5 mg/kg.DiscussionThe present study suggests that FC assessment after 8 weeks of treatment with all the biological drugs could represent a promising early marker of response to therapy in terms of mucosal healing.
| S-EPMC7263645 | biostudies-literature
Project description: Not available
| S-EPMC11842905 | biostudies-literature
Project description:Background/aimsAlthough fecal microbiota transplantation (FMT) has been proven as one of the promising treatments for patients with ulcerative colitis (UC), potential prognostic markers regarding the clinical outcomes of FMT remain elusive.MethodsWe collected fecal samples of 10 participants undergoing FMT to treat UC and those from the corresponding donors. We categorized them into two groups: responders and nonresponders. Sequencing of the bacterial 16S rRNA gene was conducted on the samples to explore bacterial composition.ResultsAnalyzing the gut microbiota of patients who showed different outcomes in FMT presented a distinct microbial niche. Source tracking analysis showed the nonresponder group had a higher rate of preservation of donor microbiota, underscoring that engraftment degrees are not one of the major drivers for the success of FMT. At the phylum level, Bacteroidetes bacteria were significantly depleted (p<0.003), and three genera, including Enterococcus, Rothia, and Pediococcus, were enriched in the responder group before FMT (p=0.003, p=0.025, and p=0.048, respectively). Furthermore, we applied a machine learning algorithm to build a prediction model that might allow the prediction of FMT outcomes, which yielded an area under the receiver operating characteristic (ROC) curve of 0.844. Notably, the microbiota-based model was much better at predicting outcomes than the clinical features model (area under the ROC curve=0.531).ConclusionsThis study is the first to suggest the significance of indigenous microbiota of recipients as a critical factor. The result highlights that bacterial composition should be evaluated before FMT to select suitable patients and achieve better efficiency.
| S-EPMC9474483 | biostudies-literature
Project description:BackgroundAs a T cell-mediated disease of the colonic epithelium, ulcerative colitis (UC) is likely to share pathogenic elements with other T cell-mediated inflammatory diseases. Recently, microarray analysis revealed large-scale molecular changes in T cell-mediated rejection of kidney and heart transplants. We hypothesized that similar disturbances might be operating in UC and could provide insights into responsiveness to therapy.MethodsWe studied 56 colon biopsies from patients with colitis characterizing the clinical and histological features and using microarrays to define the messenger RNA phenotype. We expressed the microarray results using previously defined pathogenesis-based transcript sets. We also studied 48 published microarray files from human colon biopsies downloaded from the Gene Expression Omnibus database, classified by response to infliximab therapy, to examine whether the molecular measurements derived from our studies correlated with nonresponsiveness to treatment.ResultsUC biopsies manifested coordinate transcript changes resembling rejecting transplants, with effector T cell, IFNG-induced, macrophage, and injury transcripts increasing while parenchymal transcripts decreased. The disturbance in gene expression, summarized as principal component 1 (PC1), correlated with conventional clinical and histologic assessments. When assessed in microarray results from published studies, the disturbance (PC1) predicted response to infliximab: patients with intense disturbance did not achieve clinical response, although quantitative improvement was seen even in many clinical nonresponders. Similar changes were seen in Crohn's colitis.ConclusionsThe molecular phenotype of UC manifests a large-scale coordinate disturbance reflecting changes in inflammatory cells and parenchymal elements that correlates with conventional features and predicts response to infliximab.
| S-EPMC4985265 | biostudies-literature
Project description:MotivationResistance to anti-TNF therapy in subgroups of ulcerative colitis (UC) patients is a major challenge and incurs significant treatment costs. Identification of patients at risk of nonresponse to anti-TNF is of major clinical importance. To date, no quantitative computational framework exists to develop a complex biomarker for the prognosis of UC treatment. Modelling patient-wise receptor to transcription factor (TF) network connectivity may enable personalized treatment.ResultsWe present an approach for quantitative diffusion analysis between receptors and TFs using gene expression data. Key TFs were identified using pandaR. Network connectivities between immune-specific receptor-TF pairs were quantified using network diffusion in UC patients and controls. The patient-specific network could be considered a complex biomarker that separates anti-TNF treatment-resistant and responder patients both in the gene expression dataset used for model development and separate independent test datasets. The model was further validated in rheumatoid arthritis where it successfully discriminated resistant and responder patients to tocilizumab treatment. Our model may contribute to prognostic biomarkers that may identify treatment-resistant and responder subpopulations of UC patients.Availability and implementationSoftware is available at https://github.com/Amy3100/receptor2tfDiffusion.Supplementary informationSupplementary data are available at Bioinformatics Advances online.
| S-EPMC9710619 | biostudies-literature