RESUMO
B lymphocytes play an important role in the regulation of immune response in both normal and pathological conditions. Traditionally, the main functions of B cells were considered to be antibody production and antigen presentation, but in recent decades there have been discovered several subpopulations of regulatory B lymphocytes (Bregs), which maintain immunological tolerance and prevent overactivation of the immune system. Memory (mBregs, CD19+CD24hiCD27+) and transitional (tBregs, CD19+CD24hiCD38hi) subpopulations of Bregs are usually considered in the context of studying the role of these B cells in various human pathologies. However, the mechanisms by which these Breg subpopulations exert their immunosuppressive activity remain poorly understood. In this work, we used bioinformatic analysis of open-source RNA sequencing data to propose potential mechanisms of B cell-mediated immunosuppression. Analysis of differential gene expression before and after activation of these subpopulations allowed us to identify six candidate molecules that may determine the functionality of mBregs and tBregs. IL4I1-, SIRPA-, and SLAMF7-dependent mechanisms of immunosuppression may be characteristic of both Breg subsets, while NID1-, CST7-, and ADORA2B-dependent mechanisms may be predominantly characteristic of tBregs. In-depth understanding of the molecular mechanisms of anti-inflammatory immune response of B lymphocytes is an important task for both basic science and applied medicine and could facilitate the development of new approaches to the therapy of complex diseases.
Assuntos
Linfócitos B Reguladores , Humanos , Linfócitos B Reguladores/metabolismo , Linfócitos B Reguladores/patologia , Tolerância Imunológica , Imunossupressores/metabolismo , Terapia de Imunossupressão , L-Aminoácido Oxidase/metabolismoRESUMO
The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling.