Dataset Information

Interferon-gamma-induced gene expression in CD34 cells: identification of pathologic cytokine-specific signature profiles.

ABSTRACT: Hematopoietic effects of interferon-gamma (IFN-gamma) may be responsible for certain aspects of the pathology seen in bone marrow failure syndromes, including aplastic anemia (AA), paroxysmal nocturnal hemoglobinuria (PNH), and some forms of myelodysplasia (MDS). Overexpression of and hematopoietic inhibition by IFN-gamma has been observed in all of these conditions. In vitro, IFN-gamma exhibits strong inhibitory effects on hematopoietic progenitor and stem cells. Previously, we have studied the transcriptome of CD34 cells derived from patients with bone marrow failure syndromes and identified characteristic molecular signatures common to some of these conditions. In this report, we have investigated genome-wide expression patterns after exposure of CD34 and bone marrow stroma cells derived from normal bone marrow to IFN-gamma in vitro and have detected profound changes in the transcription profile. Some of these changes were concordant in both stroma and CD34 cells, whereas others were specific to CD34 cells. In general, our results were in agreement with the previously described function of IFN-gamma in CD34 cells involving activation of apoptotic pathways and immune response genes. Comparison between the IFN-gamma transcriptome in normal CD34 cells and changes previously detected in CD34 cells from AA and PNH patients reveals the presence of many similarities that may reflect molecular signature of in vivo IFN-gamma exposure.

SUBMITTER: Zeng W

PROVIDER: S-EPMC1895358 | biostudies-literature | 2006 Jan

REPOSITORIES: biostudies-literature

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Interferon-gamma-induced gene expression in CD34 cells: identification of pathologic cytokine-specific signature profiles.

Zeng Weihua W Miyazato Akira A Chen Guibin G Kajigaya Sachiko S Young Neal S NS Maciejewski Jaroslaw P JP

Blood 20050830 1

Hematopoietic effects of interferon-gamma (IFN-gamma) may be responsible for certain aspects of the pathology seen in bone marrow failure syndromes, including aplastic anemia (AA), paroxysmal nocturnal hemoglobinuria (PNH), and some forms of myelodysplasia (MDS). Overexpression of and hematopoietic inhibition by IFN-gamma has been observed in all of these conditions. In vitro, IFN-gamma exhibits strong inhibitory effects on hematopoietic progenitor and stem cells. Previously, we have studied the ...[more]

PMID: 16131564

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Project description:Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases.

Dataset Information

Interferon-gamma-induced gene expression in CD34 cells: identification of pathologic cytokine-specific signature profiles.

Publications

Interferon-gamma-induced gene expression in CD34 cells: identification of pathologic cytokine-specific signature profiles.

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