Abstract
Growing evidence defines macrophages (Mφ) as plastic cells with wide-ranging states of activation and expression of different markers that are time and location dependent. Distinct from the simple M1/M2 dichotomy initially proposed, extensive diversity of macrophage phenotypes have been extensively demonstrated as characteristic features of monocyte-macrophage differentiation, highlighting the difficulty of defining complex profiles by a limited number of genes. Since the description of macrophage activation is currently contentious and confusing, the generation of a simple and reliable framework to categorize major Mφ phenotypes in the context of complex clinical conditions would be extremely relevant to unravel different roles played by these cells in pathophysiological scenarios. In the current study, we integrated transcriptome data using bioinformatics tools to generate two macrophage molecular signatures. We validated our signatures in in vitro experiments and in clinical samples. More importantly, we were able to attribute prognostic and predictive values to components of our signatures. Our study provides a framework to guide the interrogation of macrophage phenotypes in the context of health and disease. The approach described here could be used to propose new biomarkers for diagnosis in diverse clinical settings including dengue infections, asthma and sepsis resolution.
Highlights
As lately suggested regulating blood supply and metabolism[6,7]
The expression of some selected markers was confirmed by real time quantitative polymerase chain reaction (RT-qPCR) in in vitro monocyte-derived macrophages (MDM) derived from healthy human peripheral blood mononuclear cells (PBMC) and in commonly used differentiated human cell lines (THP-1 and U-937)
Using GEO2R tool analysis in each selected dataset we obtained two differentially expressed gene signatures that we termed the M(IFNγ + LPS, TNFα ) and M(IL-4, IL-13) phenotypes (Fig. 1B), following the guidelines recently suggested by Murray et al.[15]
Summary
As lately suggested regulating blood supply and metabolism[6,7]. Sub-populations of Mφ exist within a continuum of diverse interchangeable phenotypic spectrums designated in the literature for simplicity as M1 (classically activated), or M2a, M2b and M2c (collectively termed alternatively activated). Since different Mφ subsets are profoundly involved in the development and outcome of many of the so called “Western diseases” (e.g.: autoimmune diseases, atherosclerosis, cancer, microorganisms infections and asthma) and are key cells in controlling normal physiological processes[2,5,16,17,18,19,20], here we question whether a restricted set of marker molecules could be helpful to define a particular functional phenotype encountered in the context of diseases. We demonstrated prognostic and predictive values of selected biomarkers associated with diseases in diverse clinical settings such as dengue infections, asthma and sepsis resolution
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