This study was aimed to detect the expression of Musashi-2 (Msi2) in acute myeloid leukemia (AML) and investigate the relationship between Msi2 and other clinical parameters, especially CD34. A total RNA was extracted from bone marrow of newly diagnosed AML patietns. The Msi2 mRNA expression in newly diagnosed AML patients was detected with real-time fluorescence quantitative RT-PCR. The expression level of CD34 in above-menthioned patients was detected by flow cytometry (FCM). The relationship between the expression of Msi2 mRNA and clinical outcome in AML patients was analysed. The results showed that (1)the expression of Msi2 mRNA in newly diagnosed AML patients was much higher than that in healthy volunteers (P < 0.05) , especially in M1, M4 and M5 patients; (2)the expression level of Msi2 did not correlate with age, sex, white blood cell count of peripheral blood, AML1/ETO and PML/RARa fusion gene (P > 0.05); (3) Msi2 expression level in patients with CD34(+) cells was significantly higher than that in patients with CD34(-) cells (P < 0.05). It is concluded that the Msi2 mRNA expresses in leukamia stem cells, the high expression of Msi2 mRNA has been found in newly diagnosed AML patients, especially in M1, M4 and M5 patients, the high expression also has been observed in patients with CD34(+).
Flow Cytometry ; Gene Expression Regulation, Leukemic ; Humans ; Leukemia, Myeloid, Acute ; genetics ; Neoplastic Stem Cells ; metabolism ; RNA, Messenger ; RNA-Binding Proteins ; genetics

Objective: To analyze the expression levels of the F9 gene and F9 protein in hepatocellular carcinoma by combining multiple gene chip data, real-time fluorescence quantitative PCR (RT qPCR), and immunohistochemistry. Additionally, explore their correlation with the occurrence and development of hepatocellular carcinoma, as well as with various clinical indicators and prognosis. Methods: The mRNA microarray dataset from the GEO database was analyzed to identify the F9 gene with significant expression differences associated with hepatocellular carcinoma. Liver cancer and adjacent tissues were collected from 18 cases of hepatocellular carcinoma. RT-qPCR method was used to detect the F9 gene expression level. Immunohistochemistry was used to detect the F9 protein level. Combined with the TCGA database information, the correlation between F9 gene expression level and prognostic and clinicopathological parameters was analyzed. The biological function of F9 co-expressed genes associated with hepatocellular carcinoma was analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Statistical analysis was performed using Graphpad Prism software. Results: Meta-analysis results showed that the expression of the F9 gene was lower in HCC tissues than in non-cancerous tissues. Immunohistochemistry results were basically consistent with those of RT-qPCR. The data obtained from TCGA showed that the F9 gene had lower expression values in stages III-IV, T3-T4, and patients with vascular invasion. A total of 127 genes were selected for bioinformatics analysis as co-expressed genes of F9, which were highly enriched in redox processes and metabolic pathways. Conclusion: This study validates that the F9 gene and F9 protein are lower in HCC. The down-regulation of the F9 gene predicts adverse outcomes, which may provide a new therapeutic target for HCC.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Down-Regulation ; Prognosis ; Gene Expression ; Gene Expression Regulation, Neoplastic

Cancer gene expression data have the characteristics of high dimensionalities and small samples so it is necessary to perform dimensionality reduction of the data. Traditional linear dimensionality reduction approaches can not find the nonlinear relationship between the data points. In addition, they have bad dimensionality reduction results. Therefore a multiple weights locally linear embedding (LLE) algorithm with improved distance is introduced to perform dimensionality reduction in this study. We adopted an improved distance to calculate the neighbor of each data point in this algorithm, and then we introduced multiple sets of linearly independent local weight vectors for each neighbor, and obtained the embedding results in the low-dimensional space of the high-dimensional data by minimizing the reconstruction error. Experimental result showed that the multiple weights LLE algorithm with improved distance had good dimensionality reduction functions of the cancer gene expression data.
Algorithms ; Gene Expression Regulation, Neoplastic ; Genes, Neoplasm ; Humans ; Neoplasms ; genetics

OBJECTIVE: To screen differentially expressed gene (DEG) related to myelodysplastic syndrome (MDS) based on Gene Expression Omnibus (GEO) database, and explore the core genes and pathogenesis of MDS by analyzing the biological functions and related signaling pathways of DEG. METHODS: The expression profiles of GSE4619, GSE19429, GSE58831 including MDS patients and normal controls were downloaded from GEO database. The gene expression analysis tool (GEO2R) of GEO database was used to screen DEG according to | log FC (fold change) |≥1 and P<0.01. David online database was used to annotate gene ontology function (GO). Metascape online database was used to enrich and analyze differential genes in Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction network (PPI) was constructed by using STRING database. CytoHubba and Mcode plug-ins of Cytoscape were used to analyze the key gene clusters and hub genes. R language was used to diagnose hub genes and draw the ROC curve. GSEA enrichment analysis was performed on GSE19429 according to the expression of LEF1. RESULTS: A total of 74 co-DEG were identified, including 14 up-regulated genes and 60 down regulated genes. GO enrichment analysis indicated that BP of down regulated genes was mainly enriched in the transcription and regulation of RNA polymerase II promoter, negative regulation of cell proliferation, and immune response. CC of down regulated genes was mainly enriched in the nucleus, transcription factor complexes, and adhesion spots. MF was mainly enriched in protein binding, DNA binding, and β-catenin binding. KEGG pathway was enriched in primary immunodeficiency, Hippo signaling pathway, cAMP signaling pathway, transcriptional mis-regulation in cancer and hematopoietic cell lineage. BP of up-regulated genes was mainly enriched in type I interferon signaling pathway and viral response. CC was mainly enriched in cytoplasm. MF was mainly enriched in RNA binding. Ten hub genes and three important gene clusters were screened by STRING database and Cytoscape software. The functions of the three key gene clusters were closely related to immune regulation. ROC analysis showed that the hub genes had a good diagnostic significance for MDS. GSEA analysis indicated that LEF1 may affect the normal function of hematopoietic stem cells by regulating inflammatory reaction, which further revealed the pathogenesis of MDS. CONCLUSION Bioinformatics can effectively screen the core genes and key signaling pathways of MDS, which provides a new strategy for the diagnosis and treatment of MDS.
Computational Biology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Gene Ontology ; Humans ; Myelodysplastic Syndromes/genetics*

OBJECTIVETo study the expression of CXCR4 in acute leukemic cells and its clinical significance.

METHODBone marrow samples from 73 acute leukemia patients and leukemic cell lines were investigated by flow cytometry (FCM), the expression of SDF-1 in human marrow stromal cells and meninges were studied by using reverse transcription polymerase chain reaction (RT-PCR). Adhesion, migration and invasion of U937, NB4 and K562 cells were studied in vitro.

RESULTSThe expression rates of CXCR4 in ALL and AML patients was 65.6% and 17.1%, respectively. And it was 0.2%, 41.0% and 52.0% in K562, U937 and NB4 cells, respectively. The extramedullary infiltration rates were 61.9% and 18.2% for CXCR4 positive and negative groups of ALL, respectively (P < 0.05); while in AML, the number of peripheral white blood cells in CXCR4 positive group was lower than that in CXCR4 negative group (P < 0.05). SDF-1alpha could enhance the adhesion, migration and invasion capacity of leukemic cells in vitro.

CONCLUSIONOverexpression of CXCR4 in AL cells might be the molecular mechanism of extramedullary infiltration in leukemia.

Acute Disease ; Adolescent ; Adult ; Aged ; Bone Marrow Cells ; metabolism ; pathology ; Cell Adhesion ; Cell Line, Tumor ; Cell Movement ; Chemokine CXCL12 ; genetics ; Female ; Fibroblasts ; metabolism ; pathology ; Flow Cytometry ; Gene Expression Regulation, Neoplastic ; Humans ; K562 Cells ; Leukemia ; genetics ; metabolism ; pathology ; Leukemic Infiltration ; metabolism ; pathology ; Male ; Meninges ; metabolism ; pathology ; Middle Aged ; Receptors, CXCR4 ; biosynthesis ; Reverse Transcriptase Polymerase Chain Reaction ; U937 Cells

OBJECTIVETo explore the biological mechanisms underlying Angelica sindsis polysaccharide (ASP) -induced aging of human-derived leukemia stem cells (LSCs) in vitro.

METHODAcute myelogenous leukemia stem cells were isolated by magnetic activated cell sorting (MACS). The ability of LSC proliferation treated by various concentration of ASP(20-80 mg · L(-1)) in vitro for 48 hours were tested using cell counting Kit-8 ( CCK8) , colony forming were evaluated by methylcellulose CFU assay. The ultra structure changes of AML CD34+ CD38- cells were analyzed by transmission electron microscopy. The aging cells were detected with senescence-β-galactosidase Kit staining. Expression of aging-related p53, p21, p16, Rb mRNA and P16, Rb, CDK4 and Cyclin E protein were detected by quantitative reverse transcription polymerase chain reaction( qRT-PCR) and Western blotting, respectively.

RESULTThe purity of the CD34 + CD38 - cells is (91.15 ± 2.41)% after sorted and showed good morphology. The proliferation of LSC was exhibited significantly concentration-dependent inhibited after exposure to various concentration of ASP. Treated by 40 mg · L(-1) ASP for 48 hours, the percentage of positive cells stained by SA-β-Gal was dramatically increased (P < 0.01) and the colony-formed ability has been weakened (P < 0.01). The observation of ultrastructure showed that cell heterochromatin condensation and fragmentation, mitochondrial swelling, lysosomes increased in number. Aging-related p53, p21, p16, Rb and P16, Rb were up-regulated, protein regulatory cell-cycle CDK4 and Cyclin E were down-regulated. ASP may induce the senescence of LSCs effectively in vitro, P16-Rb cell signaling pathway play a significant role in this process.

CONCLUSIONASP can induce human leukemia stem cell senescence in vitro, the mechanism involved may be related to ASP regulation P16-Rb signaling pathways.

Angelica sinensis ; chemistry ; Cell Cycle ; drug effects ; Cell Cycle Proteins ; genetics ; metabolism ; Cells, Cultured ; Cellular Senescence ; drug effects ; Drugs, Chinese Herbal ; pharmacology ; Gene Expression Regulation, Leukemic ; drug effects ; Humans ; Leukemia ; drug therapy ; genetics ; metabolism ; physiopathology ; Neoplastic Stem Cells ; cytology ; drug effects ; Polysaccharides ; pharmacology ; Signal Transduction ; drug effects

MicroRNA (miRNA) is a class of RNA which has been discovered in recent years and relates with genesis and development of tumors. MiRNA affects the genesis and development of tumors and carries out the function similar to oncogene and antioncogene through regulation of signaling pathway in which target genes involved, thereby the miRNA disregulation plays an important role in oncogenesis. More studies revealed that the miR-17-19 cluster closely correlates with tumorigenesis and has bifunctional effects of oncogene and antioncogene. In this review, the mechanism and function of the miR-17-19 cluster in tumorigenesis are summarized.
Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Genes, Tumor Suppressor ; Humans ; MicroRNAs ; Neoplasms ; genetics ; Oncogenes ; genetics

Hepatocellular carcinoma (HCC) is highly heterogeneous in nature and has been one of the most common cancer types worldwide. To ensure repeatability of identified gene expression patterns and comprehensively annotate the transcriptomes of HCC, we carefully curated 15 public HCC expression datasets that cover around 4000 clinical samples and developed the database HCCDB to serve as a one-stop online resource for exploring HCC gene expression with user-friendly interfaces. The global differential gene expression landscape of HCC was established by analyzing the consistently differentially expressed genes across multiple datasets. Moreover, a 4D metric was proposed to fully characterize the expression pattern of each gene by integrating data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). To facilitate a comprehensive understanding of gene expression patterns in HCC, HCCDB also provides links to third-party databases on drug, proteomics, and literatures, and graphically displays the results from computational analyses, including differential expression analysis, tissue-specific and tumor-specific expression analysis, survival analysis, and co-expression analysis. HCCDB is freely accessible at http://lifeome.net/database/hccdb.
Carcinoma, Hepatocellular ; genetics ; Databases, Genetic ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Liver Neoplasms ; genetics

OBJECTIVE: To analyze the molecular markers associated with occurrence, development and poor prognosis of acute myeloid leukemia (AML) by using the data of GEO and TCGA database, as well as multiomics analysis. METHODS: The transcriptome data meeting requirements were down-loaded from GEO database, the differentially expressed genes were screened by using the R language limma package, and the GO function enrichment analysis and KEGG pathway analysis were performed for differentially expressed genes, at the same time, the protein interaction network was contracted by using STRING database and cytoscape software to screen out the hub gene, then the prognosis analysis was carried out for hub gene by combination with the clinical information affected in TCGA database. RESULTS: 620 differentially expressed genes were screened out, among which 162 differentially expressed genes were up-regulated, and 458 differentially expressed genes were down-regulated. Based on the results of GO functional enrichment, the KEGG pathway enrichment and protein interaction network, CXCL4, CXCR4, CXCR1, CXCR2, CCL5 and JUN were selected as hub genes. The survival analysis showed that the high expression of CXCL4, CXCR1, and CCL5 was a risk factor for poor prognosis of patiants. CONCLUSION CXCL4, CXCR1 and CCL5 can be used as biomarkers for the occurrence and development of AML, which relateds with the unfavorable prognosis and can provide a basis for further study.
Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Leukemia, Myeloid, Acute ; Prognosis ; Transcriptome

OBJECTIVETo study the differently expressed genes of oral squamous cell carcinoma (OSCC) tissue.

METHODSGene expression datasets related to oral squamous cell carcinoma in the gene expression omnibus (gene expression omnibus, GEO) repository were retrieved. Datasets were merged by normalization.Significantly expressed genes were obtained by statistical methods, and genes' functions, interactions, signaling pathways were analyzed accordingly.

RESULTSIn GEO, there were 1 125 records related to OSCC, and four of them were selected and merged to a super array data, within the super array data, 233 genes were significantly expressed (P < 0.05) , and the top 100 significantly expressed genes were selected as signature genes.Signature genes were more related to cell surface or cell-cell interactive activities. Clusters of interactive signature genes and the related signaling pathways were related with mitosis process.

CONCLUSIONSOSCC signature genes and the corresponding signaling pathways will provide not only an important clue for further research of the disease, but also reference for diagnosis and treatment.

Carcinoma, Squamous Cell ; genetics ; Gene Expression ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Mouth Neoplasms ; genetics ; Signal Transduction