OBJECTIVE: To identify biological pathways that contribute to risk for bipolar disorder (BP) using genes with consistent evidence for association in multiple genome-wide association studies (GWAS).
DATA SOURCES: Four independent data sets with individual genome-wide data available in July 2011 along with all data sets contributed to the Psychiatric Genomics Consortium Bipolar Group by May 2012. A prior meta-analysis was used as a source for brain gene expression data.
STUDY SELECTION: The 4 published GWAS were included in the initial sample. All independent BP data sets providing genome-wide data in the Psychiatric Genomics Consortium were included as a replication sample.
DATA EXTRACTION AND SYNTHESIS: We identified 966 genes that contained 2 or more variants associated with BP at P gene size and allowed the calculation of an empirical P value for each gene; empirically significant genes were entered into a pathway analysis. Each of these pathways was then tested in the replication sample (n = 8396 [3507 cases, 4889 controls]) using gene set enrichment analysis for single-nucleotide polymorphisms. The 226 genes were also compared with results from a meta-analysis of gene expression in the dorsolateral prefrontal cortex.
MAIN OUTCOMES AND MEASURES: Empirically significant genes and biological pathways. RESULTS Among 966 genes, 226 were empirically significant (P genes, 9 differed in expression in the dorsolateral prefrontal cortex in patients with BP: CACNA1C, DTNA, FOXP1, GNG2, ITPR2, LSAMP, NPAS3, NCOA2, and NTRK3.
CONCLUSIONS AND RELEVANCE: Pathways involved in the genetic predisposition to BP include hormonal regulation, calcium channels, second messenger systems, and glutamate signaling. Gene expression studies implicate neuronal development pathways as well. These results tend to reinforce specific hypotheses regarding BP neurobiology and may provide clues for new approaches to treatment and prevention.
MATERIALS AND METHODS: From a PSA screening initiative, 161 men were shown to have elevated PSA levels in their blood and underwent prostatic tissue biopsy. DNA was extracted from the blood, and exon 1 of the AR gene amplified by PCR and sequenced. The number of CAG repeat sequences were counted and compared to the immunohistochemical expression of ERG and AR in the matched tumour biopsies.
RESULTS: Of men with elevated PSA, 89 were diagnosed with prostate cancer, and 72 with benign prostatic hyperplasia (BPH). There was no significant difference in the length of the CAG repeat in men with prostate cancer and BPH. The CAG repeat length was not associated with; age, PSA or tumour grade, though a longer CAG repeat was associated with tumour stage. ERG and AR were expressed in 36% and 86% of the cancers, respectively. There was no significant association between CAG repeat length and ERG or AR expression. However, there was a significant inverse relationship between ERG and AR expression. In addition, a significantly great proportion of Indian men had ERG positive tumours, compared to men of Malay or Chinese descent.
CONCLUSIONS: CAG repeat length is not associated with prostate cancer or expression of ERG or AR. However, ERG appears to be more common in the prostate cancers of Malaysian Indian men than in the prostate cancers of other Malaysian ethnicities and its expression in this study was inversely related to AR expression.
MATERIALS AND METHODS: We evaluated simple statistics and published model-based approaches. Multiplex-qPCR was conducted to determine the expression of 24 candidate RG in AMLs (N=9). Singleplex-qPCR was carried out on selected RG (SRP14, B2M and ATP5B) and genes of interest in AML (N=15) and healthy controls, HC (N=12).
RESULTS: RG expression levels in AML samples were highly variable and coefficient of variance (CV) ranged from 0.37% to 10.17%. Analysis using GeNorm and Normfinder listed different orders of most stable genes but the top seven (ACTB, UBE2D2, B2M, NF45, RPL37A, GK, QARS) were the same. In singleplex-qPCR, SRP14 maintained the lowest CV in AML samples. B2M, one of most stable reference genes in AML, was expressed near significantly different in AML and HC. GeNorm selected ATP5B+SRP14 while Normfinder chose SRP14+B2M as the best two RG in combination. The median expressions of combined RG genes in AML compared to HC were less significantly different than individually implying smaller expression variation after combination. Genes of interest normalised with RG in combination or individually, displayed significantly different expression patterns.
CONCLUSIONS: The selection of best reference gene in qPCR must consider all sample sets. Model-based approaches are important in large candidate gene analysis. This study showed combination of RG SRP14+B2M was the most suitable normalisation factor for qPCR analysis of AML and healthy individuals.
METHODS: The main aim was to determine the stemness properties of serial-passaged human chorion-derived stem cells (hCDSC). Quantitative polymerase chain reaction (PCR) was performed to reveal the following stemness gene expression in serial-passaged hCDSC: Oct-4, Sox-2, FGF-4, Rex-1, TERT, Nanog (3), Nestin, FZD-9, ABCG-2 and BST-1. Cell growth rate was evaluated from passage (P) 1 until P5. The colony-forming unit-fibroblast (CFU-F) frequency of P3 and P5 cells and multilineage differentiation potential of P5 cells were determined. The immunophenotype of hCDSC was compared using the surface markers CD9, CD31, CD34, CD44, CD45, CD73, CD90, CD117, HLA-ABC and HLA-DR, -DP and -DQ. Immunostaining for trophoblast markers was done on P0, P1, P3 and P5 cells to detect the contamination of trophoblasts in culture, while chromosomal abnormality was screened by cytogenetic analysis of P5 cells.
RESULTS: The surface markers for mesenchymal lineage in hCDSC were more highly expressed at P5 compared with P3 and P0, indicating the increased purity of these stem cells after serial passage. Indeed, all the stemness genes except TERT were expressed at P1, P3 and P5 hCDSC. Furthermore, human chorion contained high clonogenic precursors with a 1:30 CFU-F frequency. Successful adipogenic, chondrogenic and osteogenic differentiation demonstrated the multilineage potential of hCDSC. The karyotyping analysis showed hCDSC maintained chromosomal stability after serial passage.
CONCLUSIONS: hCDSC retain multipotent potential even at later passages, hence are a promising source for cell therapy in the future.
MATERIALS AND METHODS: BCR-ABL positive CML cells resistant to imatinib (K562-R) were developed by overexposure of K562 cell lines to the drug. Cytotoxicity was determined by MTS assays and IC50 values calculated. Apoptosis assays were performed using annexin V-FITC binding assays and analyzed by flow cytometry. Methylation profiles were investigated using methylation specific PCR and sequencing analysis of SOCS-1 and SOCS-3 genes. Gene expression was assessed by quantitative real-time PCR, and protein expression and phosphorylation of STAT1, 2 and 3 were examined by Western blotting.
RESULTS: The IC50 for imatinib on K562 was 362 nM compared to 3,952 nM for K562-R (p=0.001). Percentage of apoptotic cells in K562 increased upto 50% by increasing the concentration of imatinib, in contrast to only 20% in K562-R (p<0.001). A change from non-methylation of the SOCS-3 gene in K562 to complete methylation in K562-R was observed. Gene expression revealed down- regulation of both SOCS-1 and SOCS-3 genes in resistant cells. STAT3 was phosphorylated in K562-R but not K562.
CONCLUSIONS: Development of cells resistant to imatinib is feasible by overexposure of the drug to the cells. Activation of STAT3 protein leads to uncontrolled cell proliferation in imatinib resistant BCR-ABL due to DNA methylation of the SOCS-3 gene. Thus SOCS-3 provides a suitable candidate for mechanisms underlying the development of imatinib resistant in CML patients.
MATERIALS AND METHODS: ER+ MCF7 and ER- MDA-MB-231 cell lines were subjected to two-dimensional electrophoresis (2-DE) and spots of interest were identified by matrix-assisted laser desorption/ionization time of- flight/time- of-flight (MALDI-TOF/TOF) mass spectrometry (MS) analysis after downregulation of RhoGDIα using short interfering RNA (siRNA) and upregulated using GFP-tagged ORF clone of RhoGDIα.
RESULTS: The results showed a total of 35 proteins that were either up- or down-regulated in these cells. Here we identifed 9 and 15 proteins differentially expressed with silencing of RhoGDIα in MCF-7 and the MDA-MB-231 cells, respectively. In addition, 10 proteins were differentially expressed in the upregulation of RhoGDIα in MCF7, while only one protein was identified in the upregulation of RhoGDIα in MDA-MB-231. Based on the biological functions of these proteins, the results revealed that proteins involved in cell migration are more strongly altered with RhoGDI-α activity. Although several of these proteins have been previously indicated in tumorigenesis and invasiveness of breast cancer cells, some ohave not been previously reported to be involved in breast cancer migration. Hence, these proteins may serve as useful candidate biomarkers for tumorigenesis and invasiveness of breast cancer cells.
CONCLUSIONS: Future studies are needed to determine the mechanisms by which these proteins regulate cell migration. The combination of RhoGDIα with other potential biomarkers may be a more promising approach in the inhibition of breast cancer cell migration.