PubMed Health⌕ Search

PubMed · 15843093

Multi-dysfunctional pathophysiology in ITP.

Abstract

Idiopathic thrombocytopenic purpura (ITP) is an organ-specific autoimmune disorder characterized by a low platelet count and mucocutaneous bleeding. The decrease of platelets is caused by increased autoantibodies against self-antigens, particularly IgG antibodies against GPIIb/IIIa. The production of these autoantibodies by B cells depends on a number of cellular mechanisms that form a network of modulation, with T cells playing a pivotal role in pathophysiology. Delineation of the dysfunction of cellular immunity has recently been attempted. This review will focus on these recent advances applicable to ITP and to highlight how these may translate into novel approaches to treatment in the future. Multi-dysfunction in these networks may include a failure of self-antigen recognition and tolerance, involvement of abnormal cell surface molecules, altered Th1/Th2 cytokine profiles, impaired megakaryocytopoiesis and impaired cell-mediated cytotoxicity. In ITP, multi-step dysfunctions in these networks may take place that finally lead to the occurrence of the disease. Therefore, unveiling these dysfunctions is vital in understanding the pathophysiology of ITP and will finally lead to the development of new therapies to fight the disease.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bin Zhou, Hui Zhao, Ren Chi Yang, Zhong Chao Han. 2005. Multi-dysfunctional pathophysiology in ITP.. https://doi.org/10.1016/j.critrevonc.2004.12.004

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal.

MOTIVATION: Algorithms for ligand-receptor network inference have emerged as commonly used tools to estimate cell-cell communication from reference single-cell data. Many studies employ these algorithms to compare signaling between conditions and lack methods to statistically identify signals that are significantly different. We previously developed the cell communication inference algorithm Domino, which considers ligand and receptor gene expression in association with downstream transcription factor activity scoring. We developed the dominoSignal software to innovate upon Domino and extend its functionality to test statistically differential cellular signaling. RESULTS: This new functionality includes the compilation of active signals as linkages from multiple subjects in a single-cell data set and testing condition-dependent signaling linkage. The software is applicable for analysis of single-cell data sets with multiple subjects as biological replicates as well as with bootstrapped replicates from data sets with few or pooled subjects. We use simulation studies to benchmark the number of subjects in compared groups and cells within an annotated cell type sufficient to accurately identify differential linkages. We demonstrate the application of the Differential Cell Signaling Test (DCST) in the dominoSignal software to investigate consequences of cancer cell phenotypes and immunotherapy on cell-cell communication in tumor microenvironments. These applications in cancer studies demonstrate the ability of differential cell signaling analysis to infer changes to cell communication networks from therapeutic or experimental perturbations, which is broadly applicable across biological systems. AVAILABILITY: dominoSignal is available through Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/dominoSignal.html.

Cell Communication↗

Human monocytes as intermediaries between allogeneic endothelial cells and allospecific T cells: a role for direct scavenger receptor-mediated endothelial membrane uptake in the initiation of alloimmunity.

Recipient monocytes, T cells, and donor endothelial cells (ECs) are recognized as critical components of allograft rejection. We have recently shown that human monocytes infiltrate vascularized allografts before clinical rejection and have thus hypothesized that monocytes, rather than costimulation-poor ECs, initiate an alloimmune response. However, the nature of the interactions between ECs, monocytes, and T cells has been incompletely defined. Specifically, it is not clear whether these cells interact in a hierarchical manner, nor is it apparent what constitutes an interaction. We therefore studied human ECs, monocytes, and T cells in various isolated in vitro combinations to define the salient features of their contact and to determine whether their interactions were sequential in nature. We find that T cells proliferate poorly to allogeneic ECs and autologous monocytes but well to autologous monocytes following allogeneic EC contact. We show that monocytes gain their stimulatory capacity by phagocytizing allogeneic but not autologous EC membranes in a process governed by scavenger receptors. This process facilitates the subsequent presentation of intact donor HLA molecules to T cells (semidirect presentation). Moreover, monocytes are receptive to T cell help only after exposure to ECs and require CD4+ T cells to optimally express costimulatory molecules and foster Ag presentation. Our results indicate that monocytes engage allogeneic ECs through scavenger receptors and are then primed to facilitate T cell activation in a codependent manner. This reciprocal codependence allows for monocytes to serve as a regulated bridge between the allograft and T cells.

Cell Communication↗

EndoNet: an information resource about endocrine networks.

EndoNet is a new database that provides information about the components of endocrine networks and their relations. It focuses on the endocrine cell-to-cell communication and enables the analysis of intercellular regulatory pathways in humans. In the EndoNet data model, two classes of components span a bipartite directed graph. One class represents the hormones (in the broadest sense) secreted by defined donor cells. The other class consists of the acceptor or target cells expressing the corresponding hormone receptors. The identity and anatomical environment of cell types, tissues and organs is defined through references to the CYTOMER ontology. With the EndoNet user interface, it is possible to query the database for hormones, receptors or tissues and to combine several items from different search rounds in one complex result set, from which a network can be reconstructed and visualized. For each entity, a detailed characteristics page is available. Some well-established endocrine pathways are offered as showcases in the form of predefined result sets. These sets can be used as a starting point for a more complex query or for obtaining a quick overview. The EndoNet database is accessible at http://endonet.bioinf.med.uni-goettingen.de/.

Cell Communication↗