Human lymphoid tissues harbor, in addition to CD56bright and CD56dim natural killer (NK) cells, a third NK cell population: CD69+CXCR6+ lymphoid tissue (lt)NK cells. The function and development of ltNK cells remain poorly understood. In this study we performed RNA sequencing on the CD56bright and CD56dim NK cells (from bone marrow and blood), and the ltNK cells (from bone marrow). In addition, the blood derived CD56dim, and bone marrow derived ltNK cells were further subdivided into a NKG2A+ and NKG2A- fraction. Paired blood and bone marrow samples of 4 healthy donors were included. When comparing the NKG2A fractions, only 3 genes (of 9382 genes included) had a significantly differential expression. Therefore, we pooled the expression data proportionally from the NKG2A+ and NKG2A- fractions in subsequent analyses. In ltNK cells, 1353 genes were differentially expressed compared to circulating NK cells. Several molecules involved in migration were downregulated in ltNK cells: S1PR1, SELPLG and CD62L. By flow cytometry we confirmed that the expression profile of adhesion molecules (CD49e-, CD29low, CD81high, CD62L-, CD11c-) and transcription factors (Eomeshigh, Tbetlow) of ltNK cells differed from their circulating counterparts. LtNK cells were characterized by enhanced expression of inhibitory receptors TIGIT and CD96 and low expression of DNAM1 and cytolytic molecules (GZMB, GZMH, GNLY). Their proliferative capacity was reduced compared to the circulating NK cells. By performing gene set enrichment analysis we identified DUSP6 and EGR2 as potential regulators of the ltNK cell transcriptome. Remarkably, comparison of the ltNK cell transcriptome to the published human spleen-resident memory CD8+ T (Trm) cell transcriptome revealed an overlapping gene signature. Moreover, the phenotypic profile of ltNK cells resembled that of CD8+ Trm cells in bone marrow. Together, we provide a comprehensive molecular framework of the conventional CD56bright and CD56dim NK cells as well as the tissue-resident ltNK cells and provide a core gene signature which might be involved in promoting tissue-residency. Overall design: mRNA sequencing of NK cell populations isolated from blood: CD56bright, NKG2A+ CD56dim and NKG2A- CD56dim, and bone marrow: CD56bright, CD56dim, NKG2A+ ltNK, and NKG2A- ltNK. Each sample has 4 biological replicates.
Human Bone Marrow-Resident Natural Killer Cells Have a Unique Transcriptional Profile and Resemble Resident Memory CD8<sup>+</sup> T Cells.
Specimen part, Subject
View SamplesCellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T-cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. In this study, we performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN- to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlation between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage)-restricted expression as potential targets for immunotherapy of hematological cancers.
Integrated Whole Genome and Transcriptome Analysis Identified a Therapeutic Minor Histocompatibility Antigen in a Splice Variant of ITGB2.
Specimen part, Cell line
View SamplesExpression levels of the RNA-binding protein Quaking (QKI) are low in monocytes of early, human atherosclerotic lesions, but abundant in macrophages of advanced plaques. Specific depletion of QKI protein impaired monocyte adhesion, migration, differentiation into macrophages, and foam cell formation in vitro and in vivo. RNA-seq and microarray analysis of human monocyte and macrophage transcriptomes, including those of a unique QKI haploinsufficient patient, revealed striking changes in QKI-dependent mRNA levels and splicing of RNA transcripts. Overall design: RNA-seq analysis of primary monocytes and macrophages from a QKI haploinsufficient patient and their (control) sibling.
Quaking promotes monocyte differentiation into pro-atherogenic macrophages by controlling pre-mRNA splicing and gene expression.
No sample metadata fields
View SamplesThe two immune cell populations Myeloid-derived suppressor cells (MDSCs), monocytes (MONO) and neutrophils (PMNs) are difficult to differentiate because of shared surface marker expression. Here we utilize the integrin receptor CD11b combined with conventional Ly6G and Ly6C expression to more accurately separate cellular populations via FACS. Then we apply high-throughput RNA Sequencing to Ly6G+Ly6C+CD11bhigh MDSC, Ly6G+Ly6C+CD11blow PMN and Ly6G-Ly6C+ monocyte populations. A total of 6,466 genes were significantly differentially expressed in MDSCs vs. monocytes, whereas only 297 genes were significantly different between MDSCs and PMNs. A number of genes implicated in cell cycle regulation were identified, and in vivo EdU labeling revealed that over 75% of MDSCs proliferated locally at the site of S. aureus biofilm infection. Overall design: RNA-Seq of myeloid-derived suppressor cells (MDSCs), neutrophils (PMNs), and monocytes during S. aureus biofilm infection in mice
Heterogeneity of Ly6G<sup>+</sup> Ly6C<sup>+</sup> Myeloid-Derived Suppressor Cell Infiltrates during Staphylococcus aureus Biofilm Infection.
Specimen part, Cell line, Subject
View SamplesS. aureus biofilms are associated with the organism's ability to cause disease. Biofilm associated bacteria must cope with the host's innate immune system.
Global transcriptome analysis of Staphylococcus aureus biofilms in response to innate immune cells.
No sample metadata fields
View SamplesGene expression profile of cancer cell lines of breast, lung, pancreatic, gasctric, ovarian, hepatocellular, prostate carcinomas and melanomas.
Gene expression profiling of 30 cancer cell lines predicts resistance towards 11 anticancer drugs at clinically achieved concentrations.
No sample metadata fields
View SamplesCurcumin is a potent anti-inflammatory compound capable of preventing chemically induced colitis in mice.
Protective effects of dietary curcumin in mouse model of chemically induced colitis are strain dependent.
Treatment
View SamplesNa+/H+ exchanger 3 (NHE3) provides a major route for intestinal Na+ absorption. It has been considered as a target of proinflammatory cytokines and enteropathogenic bacteria and impaired NHE3 expression and/or activity may be responsible for inflammation-associated diarrhea.
Colonic gene expression profile in NHE3-deficient mice: evidence for spontaneous distal colitis.
No sample metadata fields
View SamplesHepatic gene expression analysis in mice fed control diet or diets supplemented with 1% Fraction 1 (haxane) or Fraction 2 (methanol) of Boswellia Serrata
Effects of Boswellia serrata in mouse models of chemically induced colitis.
No sample metadata fields
View SamplesIn order to understand differentially regulated gene expression after the different treatments, 4 size matched tumors of each group were analyzed by microarrays.
Regulation of myeloid cells by activated T cells determines the efficacy of PD-1 blockade.
Specimen part
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