Unknown,Transcriptomics,Genomics,Proteomics

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A Systematic Approach to Identify Markers of Distinctly Activated Human Macrophages

ABSTRACT: Polarization has been a useful concept for describing activated macrophage phenotypes and gene expression profiles. However, macrophage activation status within tumors and other settings are often inferred based on only a few markers. Complicating matters for relevance to human biology, many of the best studied macrophage activation markers have been best characterized in mice and sometimes are not similarly regulated in human macrophages. To identify novel markers of activated human macrophages, gene expression profiles for human macrophages of a single donor subjected to 33 distinct activating conditions were obtained and a set of putative activation markers were subsequently evaluated in macrophages from multiple donors using integrated fluidic circuit (IFC)-based RT-PCR. Using unsupervised hierarchical clustering of the microarray screen, highly-altered transcripts (>4-fold change in expression) sorted the macrophage transcription profiles into two major and 13 minor clusters. Among the 1874 highly-altered transcripts, over 100 were uniquely altered in one major or two related minor clusters. IFC PCR-derived data confirmed the microarray results and to show the kinetics of expression of potential macrophage activation markers. Transcripts encoding chemokines, cytokines, and cell surface were prominent in our analyses. The activation markers identified by this study could be used to better characterize tumor-associated macrophages from biopsies as well as other macrophage populations collected from human clinical samples. 36 samples total from primary human monocyte-derived macrophages (3 technical replicates for untreated controls and 33 individual samples of uniquely activated macrophage types)

ORGANISM(S): Homo sapiens

SUBMITTER: Joel Graff

PROVIDER: E-GEOD-68854 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Macrophage activation is associated with profound transcriptional reprogramming. Although much progress has been made in the understanding of macrophage activation, polarization and function, the transcriptional programs regulating these processes remain poorly characterized. We stimulated human macrophages with diverse activation signals, acquiring a dataset of 299 macrophage transcriptomes. Analysis of this dataset revealed a spectrum of macrophage activation states extending the current M1 versus M2-polarization model. Network analyses identified central transcriptional regulators associated with all macrophage activation complemented by regulators related to stimulus-specific programs. Applying these transcriptional programs to human alveolar macrophages from smokers and patients with chronic obstructive pulmonary disease (COPD) revealed an unexpected loss of inflammatory signatures in COPD patients. Finally, by integrating murine data from the ImmGen project we propose a refined, activation-independent core signature for human and murine macrophages. This resource serves as a framework for future research into regulation of macrophage activation in health and disease. Illumina: To better understand the transcriptional program of human macrophages a set of different stimuli were used to activate and differentiate human macrophages in vitro. These macrophages were then assessed by transcriptomics and analyzed by different approaches using gene co-regulation analysis, SOM-clustering, hierarchical clustering, reverse network engineering and statistical models such as ANOVA. Affymetrix: To understand the relationship of in vivo macrophages with in vitro stimulations, two alveaolar macrophage datasets GSE13896 (COPD patients, smokers and non-smokers) and GSE2125 (asthmatic patients, smokers and non-smokers) were downloaded and processed together. In total, the combined dataset consists of 12 COPD samples, 15 asthmatic, 49 smoker samples and 39 non-smokers as control. Clustering of the samples (such as correlation network, principal component analysis and hierarchical clustering) and Gene Set Enrichment Analysis was performed on differentially expressed genes from 28 in vitro conditions.

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A Systematic Approach to Identify Markers of Distinctly Activated Human Macrophages

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