Memory T Cell Subpopulations as Early Predictors of Remission to Vedolizumab in Ulcerative Colitis

Lymphocyte subsets for predicting inflammatory bowel disease progression and treatment response: a systematic review

Background

Lymphocytes play a key role in the pathogenesis of inflammatory bowel disease (IBD) and are widely explored as promising prognostic indicators. We aimed to outline the existing evidences on the capability of lymphocyte subpopulations to predict disease progression and treatment response in patients with IBD.

Methods

The protocol for this review was registered in PROSPERO (registration ID: CRD 42022364126). Systematic retrieval was conducted using PubMed, Embase, and Web of Science databases. Original articles on the prognostic value of lymphocyte subsets in IBD published up to April 8, 2023 were eligible for inclusion. The Newcastle-Ottawa Scale was used to evaluate the risk of bias.

Results

Twenty studies were ultimately included: eight evaluated the prediction of disease progression and 12 focused on the prediction of treatment response. According to the Newcastle-Ottawa Scale, three studies were of high quality, 16 were of moderate quality, and only one was of low quality. T-cell subpopulations, including CD4+ T cells, CD8+ T cells, and γδ T cells, are revealed to have prognostic capacity. Transmembrane tumor necrosis factor α-bearing lymphocytes, CD4+ T cells, CD8+ T cells, and Plasma cells are found to have the potential to predict the response to anti-TNFα agents. In contrast memory T cells, CD4+ T cells, and naïve B cells may predict the response to vedolizumab.

Conclusions

This systematic review identified several potential lymphocyte subset-related predictors. If verified in large cohort prospective studies, these findings could aid clinical decision-making.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022364126.

Applications of Flow Cytometry in Drug Discovery and Translational Research

Flow cytometry is a mainstay technique in cell biology research, where it is used for phenotypic analysis of mixed cell populations. Quantitative approaches have unlocked a deeper value of flow cytometry in drug discovery research. As the number of drug modalities and druggable mechanisms increases, there is an increasing drive to identify meaningful biomarkers, evaluate the relationship between pharmacokinetics and pharmacodynamics (PK/PD), and translate these insights into the evaluation of patients enrolled in early clinical trials. In this review, we discuss emerging roles for flow cytometry in the translational setting that supports the transition and evaluation of novel compounds in the clinic.

Ginsenoside Rg1 Alleviates Ulcerative Colitis in Obese Mice by Regulating the Gut Microbiota-Lipid Metabolism-Th1/Th2/Th17 Cells Axis

Ginsenoside Rg1 (G-Rg1) has various pharmacological properties including antiobesity, immunomodulatory, and anti-inflammatory effects. This study aimed to explore the therapeutic effects and underlying mechanisms of G-Rg1 on colitis complicated by obesity. The results indicate that G-Rg1 effectively alleviates colitis in obese mice and improves serum lipid levels and liver function. Importantly, G-Rg1 improved the composition of gut microbiota in obese mice with colitis, with increases in alpha diversity indexes Sobs, Ace, and Chao, a significant down-regulation of the relative abundance of Romboutsia, and a significant up-regulation of Rikenellaceae_RC9_gut_group, Lachnospiraceae_NK4A136_group, Enterorhabdus, Desulfovibrio, and Alistipes. Meanwhile, G-Rg1 improved lipid metabolism in the colonic contents of obese mice with colitis. Additionally, G-Rg1 significantly reduced the percentages of helper T (Th)1, Th17, central memory T (TCM), and effector memory T (TEM) cells in obese mice with colitis while significantly increasing Naïve T and Th2 cells. In conclusion, G-Rg1 could be a promising therapeutic option for alleviating obesity complicated by colitis through regulation of the gut microbiota and lipid metabolism as well as Th1/Th2/Th17 cell differentiation.

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.