Can molecular stratification improve the treatment of inflammatory bowel disease?

Oral Delivery of Bioactive Glass-Loaded Core-Shell Hydrogel Microspheres for Effective Treatment of Inflammatory Bowel Disease

Resolving inflammation and promoting intestinal tissue regeneration are critical for inflammatory bowel disease (IBD) treatment. Bioactive glass (BG) is a clinically approved bone graft material and has been shown to modulate inflammatory response, but it is unknown whether BG can be applied to treat IBD. Here, it is reported that BG attenuates pro-inflammatory response of lipopolysaccharide (LPS)-stimulated macrophages and hence reduces inflammatory damage to intestinal organoids in vitro. In addition, zein/sodium alginate-based core-shell microspheres (Zein/SA/BG) are developed for oral delivery of BG, which helps prevent premature dissolution of BG in the stomach. The results show that Zein/SA/BG protects BG from a gastric-simulated environment while dissolved in an intestinal-simulated environment. When administered to acute and chronic colitis mice model, Zein/SA/BG significantly reduces intestinal inflammation, promotes epithelial tissue regeneration, and partially restores microbiota homeostasis. These findings are the first to reveal the therapeutic efficacy of BG against IBD, which may provide a new therapeutic approach at low cost for effective IBD treatment.

Advancing the precision management of inflammatory bowel disease in the era of omics approaches and new technology

There is great heterogeneity among inflammatory bowel disease (IBD) patients in terms of pathogenesis, clinical manifestation, response to treatment, and prognosis, which requires the individualized and precision management of patients. Many studies have focused on prediction biomarkers and models for assessing IBD disease type, activity, severity, and prognosis. During the era of biologics, how to predict the response and side effects of patients to different treatments and how to quickly recognize the loss of response have also become important topics. Multiomics is a promising area for investigating the complex network of IBD pathogenesis. Integrating numerous amounts of data requires the use of artificial intelligence.

Precision medicine and drug optimization in adult inflammatory bowel disease patients

Inflammatory bowel diseases (IBD) encompass two main entities including ulcerative colitis and Crohn's disease. Although having a common global pathophysiological mechanism, IBD patients are characterized by a significant interindividual heterogeneity and may differ by their disease type, disease locations, disease behaviours, disease manifestations, disease course as well as treatment needs. Indeed, although the therapeutic armamentarium for these diseases has expanded rapidly in recent years, a proportion of patients remains with a suboptimal response to medical treatment due to primary non-response, secondary loss of response or intolerance to currently available drugs. Identifying, prior to treatment initiation, which patients are likely to respond to a specific drug would improve the disease management, avoid unnecessary side effects and reduce the healthcare expenses. Precision medicine classifies individuals into subpopulations according to clinical and molecular characteristics with the objective to tailor preventative and therapeutic interventions to the characteristics of each patient. Interventions would thus be performed only on those who will benefit, sparing side effects and expense for those who will not. This review aims to summarize clinical factors, biomarkers (genetic, transcriptomic, proteomic, metabolic, radiomic or from the microbiota) and tools that could predict disease progression to guide towards a step-up or top-down strategy. Predictive factors of response or non-response to treatment will then be reviewed, followed by a discussion about the optimal dose of drug required for patients. The time at which these treatments should be administered (or rather can be stopped in case of a deep remission or in the aftermath of a surgery) will also be addressed. IBD remain biologically complex, with multifactorial etiopathology, clinical heterogeneity as well as temporal and therapeutic variabilities, which makes precision medicine especially challenging in this area. Although applied for many years in oncology, it remains an unmet medical need in IBD.

ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients

Rheumatoid arthritis (RA) is a chronic autoimmune condition, characterised by joint pain, damage and disability, which can be addressed in a high proportion of patients by timely use of targeted biologic treatments. However, the patients, non-responsive to the treatments often suffer from refractoriness of the disease, leading to poor quality of life. Additionally, the biologic treatments are expensive. We obtained plasma samples from N = 144 participants with RA, who were about to commence anti-tumour necrosis factor (anti-TNF) therapy. These samples were sent to Olink Proteomics, Uppsala, Sweden, where proximity extension assays of 4 panels, containing 92 proteins each, were performed. A total of n = 89 samples of patients passed the quality control of anti-TNF treatment response data. The preliminary analysis of plasma protein expression values suggested that the RA population could be divided into two distinct molecular sub-groups (endotypes). However, these broad groups did not predict response to anti-TNF treatment, but were significantly different in terms of gender and their disease activity. We then labelled these patients as responders (n = 60) and non-responders (n = 29) based on the change in disease activity score (DAS) after 6 months of anti-TNF treatment and applied machine learning (ML) with a rigorous 5-fold nested cross-validation scheme to filter 17 proteins that were significantly associated with the treatment response. We have developed a ML based classifier ATRPred (anti-TNF treatment response predictor), which can predict anti-TNF treatment response in RA patients with 81% accuracy, 75% sensitivity and 86% specificity. ATRPred may aid clinicians to direct anti-TNF therapy to patients most likely to receive benefit, thus save cost as well as prevent non-responsive patients from refractory consequences. ATRPred is implemented in R.

A Series of Genes for Predicting Responses to Anti-Tumor Necrosis Factor α Therapy in Crohn's Disease

Background: Patients with Crohn’s disease (CD) experience severely reduced quality of life, particularly those who do not respond to conventional therapies. Antitumor necrosis factor (TNF)α is commonly used as first-line therapy; however, many patients remain unresponsive to this treatment, and the identification of response predictors could facilitate the improvement of therapeutic strategies.

Methods: We screened Gene Expression Omnibus (GEO) microarray cohorts with different anti-TNFα responses in patients with CD (discovery cohort) and explored the hub genes. The finding was confirmed in independent validation cohorts, and multiple algorithms and in vitro cellular models were performed to further validate the core predictor.

Results: We screened four discovery datasets. Differentially expressed genes between anti-TNFα responders and nonresponders were confirmed in each cohort. Gene ontology enrichment revealed that innate immunity was involved in the anti-TNFα response in patients with CD. Prediction analysis of microarrays provided the minimum misclassification of genes, and the constructed network containing the hub genes supported the core status of TLR2. Furthermore, GSEA also supports TLR2 as the core predictor. The top hub genes were then validated in the validation cohort (GSE159034; p < 0.05). Furthermore, ROC analyses demonstrated the significant predictive value of TLR2 (AUC: 0.829), TREM1 (AUC: 0.844), and CXCR1 (AUC: 0.841). Moreover, TLR2 expression in monocytes affected the immune–epithelial inflammatory response and epithelial barrier during lipopolysaccharide-induced inflammation (p < 0.05).

Conclusion: Bioinformatics and experimental research identified TLR2, TREM1, CXCR1, FPR1, and FPR2 as promising candidates for predicting the anti-TNFα response in patients with Crohn’s disease and especially TLR2 as a core predictor.

A Combined CRISP3 and SPINK1 Prognostic Grade in EPS-Urine and Establishment of Models to Predict Prognosis of Patients With Prostate Cancer

Background

Prostate cancer (PCa) is characterized by significant heterogeneity. Thus, novel prognostic indicators are required to improve prognosis and treatment.

Methods

Cysteine rich secretory protein 3 (CRISP3) and serine peptidase inhibitor Kazal type 1 (SPINK1) levels in expressed prostatic secretion (EPS)-urine collected during digital rectal examination of 496 patients histologically diagnosed with PCa were detected via enzyme-linked immunosorbent assay. A combined CRISP3 and SPINK1 prognostic grade (CSPG) was defined using cut-off values from receiver operating characteristic curves. Log-rank Kaplan-Meier survival curves investigated differences in prognosis between groups. Univariate and multivariate Cox analyses investigated the CSPG relationship with biochemical recurrence (BCR), cancer-specific survival (CSS), and overall survival (OS). Three prognostic models were developed and validated.

Conclusions

CRISP3 and SPINK1 levels increased with Gleason score progression, pathological T stage, and metastasis status. CSPG in EPS-urine, which was an effective independent prognostic variable, accurately predicted the prognosis of patients with PCa. Three clinical prognostic models using the CSPG for BCR, CSS, and OS were developed and validated.

Immunological Networks Defining the Heterogeneity of Inflammatory Bowel Diseases

Current practice in IBD is to classify patients based on clinical signs and symptoms and provide treatments accordingly. However, the response of IBD patients to available treatments is highly variable, highlighting clinically significant heterogeneity among patients. Thus, more accurate patient stratification is urgently needed to more effectively target therapeutic interventions to specific patients. Here we review the degree of heterogeneity in IBD, discussing how the microbiota, genetics, and immune system may contribute to the variation among patients. We highlight how molecular heterogeneity may relate to clinical phenotype, but in other situations may be independent of clinical phenotype, encouraging future studies to fill the gaps. Finally, we discuss novel stratification methodologies as a foundation for precision medicine, in particular a novel stratification strategy based on conserved genes across species. All of these dimensions of heterogeneity have potential to provide strategies for patient stratification and move IBD practice towards personalised medicine.

Optimal treatment sequence for targeted immune modulators for the treatment of moderate to severe ulcerative colitis

BACKGROUND: Ulcerative colitis is a chronic immune-mediated inflammatory condition of the large intestine and rectum. Several targeted immune modulators (TIMs) have demonstrated effectiveness for the treatment of moderate to severe ulcerative colitis and are approved by the FDA. Patients may try multiple TIMs, and currently there are no biomarkers or prognostic factors to guide choice of treatment sequence. In 2020, the Institute for Clinical and Economic Review (ICER) conducted a review of TIMs for the treatment of ulcerative colitis as individual agents relative to conventional treatment but did not address the relative ranking of various treatment sequences to each other. OBJECTIVE: To extend the ICER framework to identify the optimal treatment sequence as informed by metrics such as maximizing incremental net health benefit (NHB), minimizing incremental total cost, or maximizing incremental quality-adjusted life-years (QALYs). METHODS: The model was developed as a Markov model with 8-week cycles over a lifetime time horizon from a US payer perspective, including only direct health care costs. Health states consisted of active moderate to severe ulcerative colitis, clinical response without achieving remission, clinical remission, and death. Efficacy of TIMs were informed by the ICER-conducted network meta-analysis. Up to 3 treatments were modeled in a sequence that consisted of 2 different TIMs followed by conventional treatment. Sequences were ranked according to each objective. NHB was calculated using a threshold of $150,000 per QALY gained. Probabilistic sensitivity analysis (PSA) was undertaken to estimate the probability of each sequence having the highest NHB rank under each objective. RESULTS: 21 possible sequences were evaluated in the base case. Two attempts at conventional treatment represented the lowest cost option and, while yielding the fewest QALYs, resulted in the highest NHB. None of the sequences had an incremental cost per QALY below $150,000 relative to 2 attempts with conventional treatment, so the resulting NHB was negative for all sequences. The sequence with the highest NHB was infliximab-dyyb followed by tofacitinib (-0.116). This regimen also had the lowest incremental costs ($37,266). For orally and subcutaneously administered TIMs, the sequence of golimumab-tofacitinib had the highest NHB (-0.344). Ustekinumab-vedolizumab was the top-ranked sequence as measured by QALY maximization (0.172 incremental QALYs) but also had the highest total incremental cost ($166,094). Results of the PSA were consistent with deterministic rankings for the top-ranking sequences but also showed that the top 2 or 3 regimens were often close together. CONCLUSIONS: Based on the results of this analysis, the optimal sequence of TIMs as measured by NHB and cost minimization was infliximab or biosimilars as first-line treatment, then moving to tofacitinib, adalimumab, or vedolizumab. Sequences that generated the most QALYs began with ustekinumab, followed by vedolizumab, tofacitinib, and adalimumab. DISCLOSURES: This study was based on an evidence synthesis and economic evaluation sponsored by the Institute for Clinical and Economic Review (ICER). Pandey and Fazioli are employees of ICER. Bloudek reports grants from ICER during the conduct of the study and personal fees from Astellas, Akcea, Dermira, GlaxoSmithKline, Sunovion, Seattle Genetics, and TerSera Therapeutics, outside the submitted work. Pandey reports grants from California Healthcare Foundation, Harvard Pilgrim Healthcare, Kaiser Foundation Health Plan Inc., and the Donoghue Foundation, during the conduct of the study, and other support from Aetna, America's Health Insurance Plans, Anthem, AbbVie, Alnylam, AstraZeneca, Biogen, Genentech/Roche, GlaxoSmithSline, Harvard Pilgrim, Health Care Service Corporation, Health Partners, Johnson & Johnson (Janssen), Kaiser Permanente, LEO Pharma, Mallinckrodt, Merck, Novartis, National Pharmaceutical Council, Premera, Prime Therapeutics, Regeneron, Sanofi, Spark Therapeutics, United Healthcare, HealthFirst, Pfizer, Boehringer-Ingelheim, uniQure, Evolve Pharmacy Solutions, and Humana, outside the submitted work. Fazioli reports grants from Arnold Ventures, California Healthcare Foundation, Harvard Pilgrim Healthcare, Kaiser Foundation Health Plan Inc., and The Donaghue Foundation, during the conduct of the study, and other support from Aetna, America's Health Insurance Plans, Anthem, AbbVie, Alnylam, AstraZeneca, Biogen, Blue Shield of CA, Cambia Health Services, CVS, Editas, Express Scripts, Genentech/Roche, GlaxoSmithKline, Harvard Pilgrim, Health Care Service Corporation, Health Partners, Johnson & Johnson (Janssen), Kaiser Permanente, LEO Pharma, Mallinckrodt, Merck, Novartis, National Pharmaceutical Council, Premera, Prime Therapeutics, Regeneron, Sanofi, Spark Therapeutics, United Healthcare, HealthFirst, Pfizer, Boehringer-lngelheim, uniQure, Evolve Phamacy Solutions, and Humana, outside the submitted work. Ollendorf reports grants from ICER, during the conduct of the study, along with other support from CEA Registry sponsors and personal fees from EMD Serono, Amgen, Analysis Group, Aspen Institute/University of Southern California, GalbraithWight, Cytokinetics, Sunovion, University of Colorado, Center for Global Development, and Neurocrine, outside the submitted work. Carlson reports grants from ICER, during the conduct of the study, and personal fees from Allergan, outside the submitted work. The inputs and model framework that were leveraged for this analysis were presented as part of the ICER assessment of TIMs for the treatment of moderate to severe ulcerative colitis.

Berberine improves colitis by triggering AhR activation by microbial tryptophan catabolites

Inflammatory bowel diseases (IBD) are kind of recurrent inflammatory issues that occur in the gastrointestinal tract, and currently clinical treatment is still unideal due to the complex pathogenesis of IBD. Basically, gut barrier dysfunction is triggered by gut microbiota dysbiosis that is closely associated with the development of IBD, we thus investigated the therapeutic capacity of berberine (BBR) to improve the dysregulated gut microbiota, against IBD in rats, using a combinational strategy of targeted metabolomics and 16 s rDNA amplicon sequencing technology. Expectedly, our data revealed that BBR administration could greatly improve the pathological phenotype, gut barrier disruption, and the colon inflammation in rats with dextran sulfate sodium (DSS)-induced colitis. In addition, 16S rDNA-based microbiota analysis demonstrated that BBR could alleviate gut dysbiosis in rats. Furthermore, our targeted metabolomics analysis illustrated that the levels of microbial tryptophan catabolites in the gastrointestinal tract were significantly changed during the development of the colitis in rats, and BBR treatment can significantly restore such changes of the tryptophan catabolites accordingly. At last, our in vitro mechanism exploration was implemented with a Caco-2 cell monolayer model, which verified that the modulation of the dysregulated gut microbiota to change microbial metabolites coordinated the improvement effect of BBR on gut barrier disruption in the colitis, and we also confirmed that the activation of AhR induced by microbial metabolites is indispensable to the improvement of gut barrier disruption by BBR. Collectively, BBR has the capacity to treat DSS-induced colitis in rats through the regulation of gut microbiota associated tryptophan metabolite to activate AhR, which can greatly improve the disrupted gut barrier function. Importantly, our finding elucidated a novel mechanism of BBR to improve gut barrier function, which holds the expected capacity to promote the BBR derived drug discovery and development against the colitis in clinic setting.

Pterostilbene reduces colonic inflammation by suppressing dendritic cell activation and promoting regulatory T cell development

Dendritic cells (DCs) and T cells play important roles in immune regulation, and modulating their function is an approach for developing preventive or therapeutic strategies against immune disorders. Herein, the effect of pterostilbene (PSB) (3',5'-dimethoxy-resveratrol)-a resveratrol-related polyphenol found in blueberries-on immune regulation was evaluated. Using an in vitro co-culture system, PSB was found to exert the strongest inhibitory effect among all tested resveratrol derivatives on DC-mediated T cell proliferation; moreover, PSB treatment decreased the Th1 and Th17 populations and increased the regulatory T cell (Treg) population. Upon co-stimulation with anti-CD3 and anti-CD28 antibodies, PSB inhibited CD4⁺ T cell proliferation and differentiation into Th1 cells. Additionally, PSB acted on DCs to suppress the lipopolysaccharide-induced transactivation of genes encoding antigen presentation-related molecules and inflammatory cytokines by attenuating the DNA-binding ability of the transcription factor PU.1. Furthermore, PSB promoted DC-mediated Foxp3⁺ Treg differentiation, and PU.1 knockdown increased DC-induced Treg activity. Oral administration of PSB alleviated the symptoms of dextran sulfate sodium-induced colitis and decreased tumor necrosis factor-α expression in mice. Thus, PSB treatment ameliorates colonic inflammation.

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

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.

What's new in IBD therapy: An "omics network" approach

The industrial revolution that began in the late 1800s has resulted in dramatic changes in the environment, human lifestyle, dietary habits, social structure, and so on. Almost certainly because this rapid evolution has outpaced the ability of the body to adapt to a number of environmental and behavioral changes, there has been a parallel emergence of several chronic inflammatory diseases, among which are inflammatory bowel diseases (IBD), primarily ulcerative colitis and Crohn's disease. The ability to treat these conditions has progressively improved in the last 50 years, particularly in the last couple of decades with the introduction of biological therapy targeting primarily soluble mediators produced by inflammatory cells. A large number of biologics are now available, but all of them induce similarly unsatisfactory (<50%) rates of clinical response and remission, and most of them lose efficacy over time, requiring dose escalation or switching from one biologic to another. So, treatment of IBD still needs improvement that will occur only if different approaches are taken. A reason why even the most recent forms of IBD therapy are unsatisfactory is because they target only selected components of an exceedingly complex pathophysiological process, a reality that must be honestly considered if better IBD therapies are to be achieved. Brand new approaches must integrate all relevant factors in their totality - the "omes" - and identify the key controllers of biological responses. This can be accomplished by using systems biology-based approaches and advanced bioinformatics tools, which together represent the essence of network medicine. This review looks at the past and the present of IBD pathogenesis and therapy, and discusses how to develop new therapies based on a network medicine approach.