Unknown,Transcriptomics,Genomics,Proteomics

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Human lymphedema tissues exhibit an inflammatory gene expression profile

ABSTRACT: Lymphedema (LD) is characterized by the accumulation of protein-rich interstitial fluid, lipids and a significant inflammatory cell infiltrate in the limb. It causes a significant morbidity and is a common disabling disease affecting more than 150 million people worldwide, however there is no yet curative treatment. In this study, we found that LD tissues from patients exhibit inflamed gene expression profile compared to their normal arm. This was next confirmed by a lipidomic analysis that revealed severe decrease in arachidonic acid-derived lipid mediators generated by the 15-lipoxygenase (15-LO) in lymphedematous arms. Using a mouse model of lymphedema, we reproduced the etiology of the human pathology including the loss of specialized pro-resolving lipid mediators that play essential role in resolution of inflammation. This was associated with a lack of nonlymphoid PPAR-positive regulatory T cells (Treg) recruitment in the injured limb adipose tissue. Importantly, we identified the lymphatic endothelial 15-LO as responsible for the chemoattraction and survival of this Treg subpopulation. These results were confirmed by an aggravation of LD and degradation of the lymphatic network in an original transgenic mouse model in which ALOX15 gene has been selectively deleted in the lymphatic system (ALOX15lecKO). Importantly, this phenotype was rescued by the injection of ALOX15-expressing lentivectors. These results provide evidence that lymphatic 15-LO may represent a novel therapeutic target for LD by serving as a mediator of nonlymphoid Treg cell population invasion into lymphedematous adipose tissue to resolve inflammation. Experimental workflow: To broadly identify gene expression signatures associated to secondary LD, we performed bulk-RNA sequencing on dermolipectomy tissue samples from women who developed LD after breast cancer. Four patient biopsies (normal arm and LD arm in each patient) were studied and the differential expression analysis (DEseq) followed by a protein-coding RNA profiling.

INSTRUMENT(S): Illumina HiSeq 3000

ORGANISM(S): Homo sapiens

SUBMITTER: Tangra Draia-Nicolau

PROVIDER: E-MTAB-13019 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:The pathogenesis of rheumatoid arthritis (RA) is complicated and involves both innate and adaptive immunity [5]. The innate immunity such as macrophages or fibroblast-like synoviocytes (FLS) in the synovium can generate inflammatory mediators, including TNF-α, IL-1, IL-6, IL-17, IFN-γ, and chemo kines that lead to synovial inflammation, bone erosion, and cartilage damage [6-8]. The IL-17 signaling mediates the autoantibody production in collagen-induced arthritis (CIA) model [9]. However, the treatment response with an anti-IL17 monoclonal antibody in RA patients shows a high degree of heterogeneity [10]. The inhibitors of the Janus kinase (JAK) pathway are approved for RA patients [11]. These data suggest that the targeted multiple cytokines through the JAK pathway are useful for RA treatment. Disturbance of type I IFNs (IFNs-I) signaling and production drive autoimmune development [12]. The presymptomatic RA patients display an increase of IFNs-I before the onset of symptoms [13]. The RA patients also show the elevation of IFN- α in the synovial fluid and high expression of IFNs-I regulated gene in peripheral blood mononuclear cells (PBMC) [14]. However, the role of IFNs-I in arthritis and bone homeostasis has suggested the accelerating effect of arthritis and bone damage. The interferon-alpha receptor knockout mice develop arthritis severity higher than wild-type mice in the model of antigen-induced arthritis [15]. IFNs-I also affects the bone homeostasis by inhibiting osteoclastogenesis via receptor activator of nuclear factor-kappa B (RANK) pathway, and reduction of c-FOS expression [16-18]. Therefore, the goal of RA treatment with antagonizing the IFNs-I pathway has to be optimized between efficacy and potentially adverse effect. STING is a cytosolic DNA sensor that initiates the production of IFNs-I. STING functions have been reported as both pro-inflammatory signaling and negative regulator against inflammation [19-21]. The mutation in exon 5 of the STING gene results in gain function leading to initiate inflammation and cause the Sting associated vasculopathy with onset in infancy (SAVI) [22]. Loss of STING function rescues DNaseII-deficient mice from lethality and polyarthritis [23]. However, Sting-deficient lupus mice (MRL/Lpr mice) show higher and earlier mortality than Sting-sufficient MRL/Lpr mice [24]. The pathology also shows lymphoid hypertrophy with a higher amount of macrophages and granulocytes infiltration, autoantibodies, and cytokine [24]. The objective of this study was to identify the role of STING in the pathogenesis of rheumatoid arthritis using collagen-induced arthritis (CIA) model as a representative model of the human RA.

Project description:LncRNA expression profiling for liver tissues of mice fed for a normal diet (NFD, 3mice) and a high-fat diet (HFD, 3mice) Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.

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Human lymphedema tissues exhibit an inflammatory gene expression profile

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