Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0021051 (immunodeficiency)
 71,517 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

As cancer mortality is high in most regions of the world, early screening of cancer has become increasingly important. Minimally invasive screening programs that use peripheral blood mononuclear cells (PBMCs) are a new and reliable strategy that can achieve early detection of tumors by identifying marker genes. From 797 datasets, four (GSE12771, GSE24536, GSE27562, and GSE42834) including 428 samples, 236 solid tumor cases, and 192 healthy controls were chosen according to the inclusion criteria. A total of 285 genes from among 440 reported genes were selected by meta-analysis. Among them, 4 of the top significantly differentially expressed genes (ANXA1, IFI44, IFI44L, and OAS1) were identified as marker genes of PBMCs. Pathway enrichment analysis identified, two significant pathways, the 'primary immunodeficiency' pathway and the 'cytokine-cytokine receptor interaction' pathway. Protein- protein interaction (PPI) network analysis revealed the top 27 hubs with a degree centrality greater than 23 to be hub genes. We also identified 3 modules in Molecular Complex Detection (MCODE) analysis: Cluster 1 (related to ANXA1), Cluster 2 (related to IFI44 and IFI44L) and Cluster 3 (related to OAS1). Among the 4 marker genes, IFI44, IFI44L, and OAS1 are potential diagnostic biomarkers, even though their results were not as remarkable as those for ANXA1 in our study. ANXA1 is involved in the immunosuppressive mechanism in tumor-bearing hosts and may be used in a new strategy involving the use of the host's own immunity to achieve tumor suppression.
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PMID:Identification of human peripheral blood monocyte gene markers for early screening of solid tumors. 3222 26

The tumor microenvironment (TME) is a heterogeneous system that contributes to breast cancer progression. The Cancer Genome Atlas (TCGA) database provides global gene expression profiling data for further analysis of various malignancies, including breast cancer. Based on the ESTIMATE algorithm, immune and stromal scores were calculated according to immune or stromal components in the TME. We divided breast cancer cases into high- and low-score groups and identified differentially expressed genes (DEGs) that were significantly associated with overall survival. We performed enrichment analysis and constructed a protein-protein interaction network and found that the DEGs were mainly involved in primary immunodeficiency, T cell receptor signaling pathway and cytokine-cytokine receptor reaction. Furthermore, we explored the effect of aging on immune and stromal scores, which was validated by lower immune/stromal scores, lower infiltration of T cells and lower expression of immune checkpoints in the elder group. In conclusion, certain differentially expressed immune-related genes contribute to longer overall survival, and aging influences the immune microenvironment and immunotherapy efficacy by changing the tumor-infiltrating lymphocyte (TIL) abundance and checkpoint expression in breast cancer.
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PMID:Alterations in Immune-Related Genes as Potential Marker of Prognosis in Breast Cancer. 3222 76

Heart failure (HF) is a global pandemic cardiovascular disease with increasing prevalence, but the pathogenesis remains to be elucidated. The present study aimed to investigate the underlying mechanism in heart failure (HF) using bioinformatics and experimental validation. A HF-associated dataset GSE84796 was downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) were screened for using Bayes method in the Limma package. Kyoto Encyclopedia of Genes and Genomes pathway analysis was used to perform pathway enrichment analysis of these DEGs using The Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of DEG-encoded proteins was subsequently constructed using the Search tool for the Retrieval of Interacting Genes/Proteins, and a transcription factor (TF)/miRNA-target network was constructed according to the WEB-based Gene SeT AnaLysis Tookit. The expression levels of microRNA (miRNA/miR)-155, G-protein coupled receptor 18 (GRP18) and E26 transformation-specific transcription factor 2 (ETS2) were analyzed in clinical HF samples, and functional validations were performed in H9c2 (2-1) cells. A total of 419 DEGs were identified, including 366 upregulated genes and 53 downregulated genes. The upregulated DEGs were significantly enriched in the pathways of 'cytokine-cytokine receptor interaction', 'natural killer cell mediated cytotoxicity' and 'primary immunodeficiency'. A total of two functional modules were identified in the PPI network: Module A was enriched in 3 KEGG pathways and module B was enriched in 15 KEGG pathways. Furthermore, a total of three miRNAs and eight TFs were identified in the TF/miRNA-target network. Specifically, GPR18 was discovered to be targeted by both ETS2 and miR-155. Clinical validation revealed that the expression levels of miR-155 were significantly decreased in the HF samples, whereas the expression levels of ETS2 and GPR18 were significantly increased in HF samples. In conclusion, the present study suggested that GPR18 may be a target of ETS2 and miR-155, and miR-155 may regulate cell viability and apoptosis in H9c2 (2-1) cells through targeting and regulating GPR18.
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PMID:ETS2 and microRNA-155 regulate the pathogenesis of heart failure through targeting and regulating GPR18 expression. 3234 8


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