Differences in gene expression between B-cell chronic lymphocytic leukemia and normal B cells: a meta-analysis of three microarray studies

MOTIVATION: A major focus of current cancer research is to identify genes that can be used as markers for prognosis and diagnosis, and as targets for therapy. Microarray technology has been applied extensively for this purpose, even though it has been reported that the agreement between microarray platforms is poor. A critical question is: how can we best combine the measurements of matched genes across microarray platforms to develop diagnostic and prognostic tools related to the underlying biology? RESULTS: We introduce a statistical approach within a Bayesian framework to combine the microarray data on matched genes from three investigations of gene expression profiling of B-cell chronic lymphocytic leukemia (CLL) and normal B cells (NBC) using three different microarray platforms, oligonucleotide arrays, cDNA arrays printed on glass slides and cDNA arrays printed on nylon membranes. Using this approach, we identified a number of genes that were consistently differentially expressed between CLL and NBC samples.     

cDNA microarray analysis of altered gene expression in Ara-C-treated leukemia cells

The acute lymphoblastic leukemia cell line CCRF-CEM is sensitive to Ara-C and undergoes apoptosis. In contrast, the chronic myelogenous leukemia (CML) cell line K562 is highly resistant to Ara-C, which causes the cells to differentiate into erythrocytes before undergoing apoptosis. We used cDNA microarrays to monitor the alterations in gene expression in these two cell lines under conditions leading to apoptosis or differentiation. Ara-C-treated CCRF-CEM cells were characterized by a cluster of down-regulated chaperone genes, whereas Ara-C-treated K562 cells were characterized by a cluster of up-regulated hemoglobin genes. In K562 cells, Ara-C treatment induced significant down-regulation of the asparagine synthetase gene, which is involved in resistance to L-asparaginase. Sequential treatment with Ara-C and L-asparaginase had a synergistic effect on the inhibition of K562 cell growth, and combination therapy with these two anticancer agents may prove effective in the treatment of CML, which cannot be cured by either drug alone.     

Monitoring the gene expression profiles of doxorubicin-resistant acute myelocytic leukemia cells by DNA microarray analysis

Acquired drug-resistance phenotype is a key factor in the relapse of patients suffering hematological malignancies. In order to investigate the genes involved in drug resistance, a human leukemia cell line that is resistant to doxorubicin, an anthracycline anticancer agent (AML-2/DX100), was selected and its gene expression profile was analyzed using a cDNA microarray. A number of genes were differentially expressed in the AML-2/DX100 cells, compared with the wild type (AML-2/WT). Pro-apoptotic genes such as TNFSF7 and p21 (Cip1/Waf1) were significantly down-regulated, whereas the IKBKB, PCNA, stathmin 1, MCM5, MMP-2 and MRP1 genes, which are involved in anti-apoptotic or cell cycle progression, were over-expressed. The AML-2/DX100 cells were also resistant to other anticancer drugs, including daunorubicin and camptothecin, and the expression levels of the differentially regulated genes such as STMN1, MMP-2 and CTSG, were constantly maintained. This suggests that the deregulated genes obtained from the DNA microarray analysis in a cell line model of drug resistance might contribute to the acquired drug resistance after chronic exposure.     

Detection of px gene product of bovine leukemia virus in infected cells

Bovine leukemia virus (BLV), like its closest relatives human T-cell leukemia virus-I and II, contain a 'px' gene, between the 'env' gene and the 3' long terminal repeat in its genome. A monoclonal antibody prepared against a synthetic oligopeptide whose sequence was deduced from highly conserved region of 'px' gene of BLV, was used to detect the presence of 'px' gene product in chronically BLV infected synchronised cells. By immunoperoxidase staining the 'px' gene product was detected maximum after 6-9 hr after synchronization in the nucleus of the cells which demonstrated the close interaction of it with viral DNA which is integrated with host cell genome.     

cDNA microarray analysis of bovine embryo gene expression profiles during the pre-implantation period

Background

After fertilization, embryo development involves differentiation, as well as development of the fetal body and extra-embryonic tissues until the moment of implantation. During this period various cellular and molecular changes take place with a genetic origin, e.g. the elongation of embryonic tissues, cell-cell contact between the mother and the embryo and placentation. To identify genetic profiles and search for new candidate molecules involved during this period, embryonic gene expression was analyzed with a custom designed utero-placental complementary DNA (cDNA) microarray.

Methods

Bovine embryos on days 7, 14 and 21, extra-embryonic membranes on day 28 and fetuses on days 28 were collected to represent early embryo, elongating embryo, pre-implantation embryo, post-implantation extra-embryonic membrane and fetus, respectively. Gene expression at these different time points was analyzed using our cDNA microarray. Two clustering algorithms such as k-means and hierarchical clustering methods identified the expression patterns of differentially expressed genes across pre-implantation period. Novel candidate genes were confirmed by real-time RT-PCR.

Results

In total, 1,773 individual genes were analyzed by complete k-means clustering. Comparison of day 7 and day 14 revealed most genes increased during this period, and a small number of genes exhibiting altered expression decreased as gestation progressed. Clustering analysis demonstrated that trophoblast-cell-specific molecules such as placental lactogens (PLs), prolactin-related proteins (PRPs), interferon-tau, and adhesion molecules apparently all play pivotal roles in the preparation needed for implantation, since their expression was remarkably enhanced during the pre-implantation period. The hierarchical clustering analysis and RT-PCR data revealed new functional roles for certain known genes (dickkopf-1, NPM, etc) as well as novel candidate genes (AW464053, AW465434, AW462349, AW485575) related to already established trophoblast-specific genes such as PLs and PRPs.

Conclusions

A large number of genes in extra-embryonic membrane increased up to implantation and these profiles provide information fundamental to an understanding of extra-embryonic membrane differentiation and development. Genes in significant expression suggest novel molecules in trophoblast differentiation.     

Viral expression directs the fate of B cells in bovine leukemia virus-infected sheep

The host immune response is believed to tightly control viral replication of deltaretroviruses such as human T-lymphotropic virus type 1 (HTLV-1) and bovine leukemia virus (BLV). However, this assumption has not been definitely proven in vivo. In order to further evaluate the importance of the immune response in the BLV model, we studied the fate of cells in which viral expression was transiently induced. Using a dual fluorochrome labeling approach, we showed that ex vivo induction of viral expression induces higher death rates of B cells in vivo. Furthermore, cyclosporine treatment of these animals indicated that an efficient immune response is required to control virus-expressing cells.     

Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data

MOTIVATION: Because co-expressed genes are likely to share the same biological function, cluster analysis of gene expression profiles has been applied for gene function discovery. Most existing clustering methods ignore known gene functions in the process of clustering. RESULTS: To take advantage of accumulating gene functional annotations, we propose incorporating known gene functions into a new distance metric, which shrinks a gene expression-based distance towards 0 if and only if the two genes share a common gene function. A two-step procedure is used. First, the shrinkage distance metric is used in any distance-based clustering method, e.g. K-medoids or hierarchical clustering, to cluster the genes with known functions. Second, while keeping the clustering results from the first step for the genes with known functions, the expression-based distance metric is used to cluster the remaining genes of unknown function, assigning each of them to either one of the clusters obtained in the first step or some new clusters. A simulation study and an application to gene function prediction for the yeast demonstrate the advantage of our proposal over the standard method.     

Identification of significant periodic genes in microarray gene expression data

Background  

One frequent application of microarray experiments is in the study of monitoring gene activities in a cell during cell cycle or cell division. A new challenge for analyzing the microarray experiments is to identify genes that are statistically significantly periodically expressed during the cell cycle. Such a challenge occurs due to the large number of genes that are simultaneously measured, a moderate to small number of measurements per gene taken at different time points, and high levels of non-normal random noises inherited in the data.     

B cells under influence: transformation of B cells by Epstein-Barr virus

Epstein-Barr virus (EBV) is an extremely successful virus, infecting more than 90% of the human population worldwide. After primary infection, the virus persists for the life of the host, usually as a harmless passenger residing in B cells. However, EBV can transform B cells, which can result in the development of malignant lymphomas. Intriguingly, the three main types of EBV-associated B-cell lymphoma - that is, Burkitt lymphoma, Hodgkin lymphoma and post-transplant lymphomas - seem to derive from germinal-centre B cells or atypical survivors of the germinal-centre reaction in most, if not all, cases, indicating that EBV-infected germinal-centre B cells are at particular risk for malignant transformation.     

Comparison of bovine leukemia virus (BLV) and CMV promoter-driven reporter gene expression in BLV-infected and non-infected cells

Background  

Viral promoters are used in mammalian expression vectors because they generally have strong activity in a wide variety of cells of differing tissues and species.     

AVA: visual analysis of gene expression microarray data

SUMMARY: AVA (Array Visual Analyzer) is a Java program that provides a graphical environment for visualization and analysis of gene expression microarray data. Together with its interactive visualization tools and a variety of built-in data analysis and filtration methods, AVA effectively integrates microarray data normalization, quality assessment, and data mining into one application. AVAILABILITY: The software is freely available for academic users on request from the authors.