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PubMed2004

Gene expression profiling in breast cancer research.

The gene expression profiles of breast cancers can now be determined with microarray technologies which measure the expression of tens of thousands of genes. By applying statistical and bioinformatics tools to gene expression data, tumors can be classified into biologically and clinically relevant categories. In addition to improving tumor classification, gene expression signatures have been identified which are related to BRCA1 and BRCA2 mutation status, ER status, and patient prognosis. Beyond its impact on research into the basic mechanisms of breast tumor progression, continued progress in tumor gene expression profiling appears likely to lead to clinically useful gene expression tests.

Journal Article↗

PubMed2002

Identifying good diagnostic gene groups from gene expression profiles using the concept of emerging patterns.

MOTIVATIONS AND RESULTS: Gene groups that are significantly related to a disease can be detected by conducting a series of gene expression experiments. This work is aimed at discovering special types of gene groups that satisfy the following property. In each group, its member genes are found to be one-to-one contained in pre-determined intervals of gene expression level with a large frequency in one class of cells but are never found unanimously in these intervals in the other class of cells. We call these gene groups emerging patterns, to emphasize the patterns' frequency changes between two classes of cells. We use effective discretization and gene selection methods to obtain the most discriminatory genes. We also use efficient algorithms to derive the patterns from these genes. According to our studies on the ALL/AML dataset and the colon tumor dataset, some patterns, which consist of one or more genes, can reach a high frequency of 90%, or even 100%. In other words, they nearly or fully dominate one class of cells, even though they rarely occur in the other class. The discovered patterns are used to classify new cells with a higher accuracy than other reported methods. Based on these patterns, we also conjecture the possibility of a personalized treatment plan which converts colon tumor cells into normal cells by modulating the expression levels of a few genes.

Algorithms↗

PubMed2003

Unveiling the gene-expression profile of pollen.

Four recent papers have characterized the transcription profile of pollen grains, showing striking differences between gene expression in pollen and other plant tissues. These studies increase the number of known pollen-expressed genes by as much as 50-fold and have identified many novel genes that are potentially pollen-specific.

Gene Expression Profiling↗

PubMed2005

New insights into MLL gene rearranged acute leukemias using gene expression profiling: shared pathways, lineage commitment, and partner genes.

Rearrangements of the MLL gene occur in both acute lymphoblastic and acute myeloid leukemias (ALL, AML). This study addressed the global gene expression pattern of these two leukemia subtypes with respect to common deregulated pathways and lineage-associated differences. We analyzed 73 t(11q23)/MLL leukemias in comparison to 290 other acute leukemias and demonstrate that 11q23 leukemias combined are characterized by a common specific gene expression signature. Additionally, in unsupervised and supervised data analysis algorithms, ALL and AML cases with t(11q23) segregate according to the lineage they are derived from, that is, myeloid or lymphoid, respectively. This segregation can be explained by a highly differing transcriptional program. Through the use of novel biological network analyses, essential regulators of early B cell development, PAX5 and EBF, were shown to be associated with a clear B-lineage commitment in lymphoblastic t(11q23)/MLL leukemias. Also, the influence of the different MLL translocation partners on the transcriptional program was directly assessed. Interestingly, gene expression profiling did not reveal a clear distinct pattern associated with one of the analyzed partner genes. Taken together, the identified molecular expression pattern of MLL fusion gene samples and biological networks revealed new insights into the aberrant transcriptional program in 11q23/MLL leukemias.

Acute Disease↗

PubMed2004

Gene expression profile of human chondrocyte HCS-2/8 cell line by EST sequencing analysis.

Large-scale single-pass sequencing of randomly selected cDNA clones from cell type specific libraries has proven to be a powerful approach for the discovery of novel gene functions, identification of novel gene family members, and definition of gene expression profiles. HCS-2/8 chondrocyte has been used as a cell culture model to study chondrocyte differentiation. Here we performed 3350 single-pass sequencing reactions obtained from the 5' ends of cDNAs from HCS-2/8 cells. To define the expression profiles of HCS-2/8 chondrocytes, we analyzed the identity of these representative cDNA sequences using database searches (BLAST). The sequences represent 1927 unique genes with known function (i.e., unigene clusters), 38 transcripts that are similar to genes with known function, 739 expressed genes with unknown function (i.e., expressed sequence tags), and 18 cDNAs which have not previously been sequenced. Interestingly, many transcripts were expressed from chromosome 12 compared with total genes, while the fewer numbers of cDNAs were derived from genes on chromosomes 14, 18 and Y. The chondrocytic phenotype of HCS-2/8 cells is reflected by abundant expression of genes related to cell structure and motility and the 20 most frequently expressed unigenes reflect a chondrocyte-related gene expression signature. Thus, our data establish a representative set of more than 2000 genes expressed in a chondrocytic cell line. This finding provides a framework for understanding cell growth and differentiation of chondrocytes and their metabolic function in the formation and remodeling of cartilage.

Cell Line, Tumor↗

PubMed2003

Comparison of the gene expression profiles of monocytic versus granulocytic lineages of HL-60 leukemia cell differentiation by DNA microarray analysis.

It is now recognized that precise patterns of differentially expressed genes ultimately direct a particular cell toward a given lineage. In this study, we compared the expression profiles of cancer-related genes by cDNA microarray analysis during the differentiation of human promyelocytic leukemia HL-60 cells into either monocytes or granulocytes. RNA was isolated at times 0, 6, 12, 24, 36, 48, and 72 h following stimulation of differentiation with all-trans retinoic acid (all-trans RA) or 1,25-dihydroxyvitamin D(3) [1,25-(OH)(2)D(3)], and hybridized to the microarray gene chips containing 872 genes related to cell-cycles, oncogenes and leukemias. Several genes were commonly or differentially regulated during cell differentiation into either lineage, as demonstrated by both hierarchical and self-organizing map clustering analysis. At 72 h the expression levels of 45 genes were commonly up- or down-regulated at least a twofold in both lineages. Most importantly, 32 genes including alpha-L-fucosidase gene and adducin gamma subunit gene were up- or down-regulated only in all-trans RA-treated HL-60 cells, while 12 genes including interleukin 1beta and hypoxia-inducible factor 1alpha were up- or down-regulated only in 1,25-(OH)(2)D(3)-treated HL-60 cells. The expression of selected genes was confirmed by Northern blot analysis. As expected, some genes identified have not been examined during HL-60 cell differentiation into either lineage. The identification of genes associated with a specific differentiation lineage may give important insights into functional and phenotypic differences between two lineages of HL-60 cell differentiation.

Calcitriol↗

PubMed2006

Gene expression profiling in insulinomas of Men1 beta-cell mutant mice reveals early genetic and epigenetic events involved in pancreatic beta-cell tumorigenesis.

Mutations of the MEN1 gene lead to the occurrence of multiple endocrine neoplasia type 1 (MEN1). To gain insights into the mechanisms of the tumorigenesis related to MEN1 inactivation, we have used mice in which the Men1 gene was specifically disrupted in pancreatic beta-cells. In these mice, we observed full penetrance of insulinoma with defined histological characteristics of tumorigenesis. To identify the genetic factors taking part in the tumour development, we performed gene expression profiling analysis of these insulinomas at different stages. Here, we show that in late stage insulinomas, 56 genes are up-regulated and 194 are down-regulated more than fourfold compared with normal pancreatic islets. Clustering analysis reveals the deregulation of Hox gene family and the genes involved in cell proliferation and cell cycle control. The altered expression of Igf2, Igfbp3 and Igfbp6 as well as cyclin A2, B2 and D2 are confirmed by quantitative RT-PCR, with the overexpression of all the three cyclins found in early stage insulinomas. Moreover, an increased proportion of cyclin A2- and D2-expressing cells and the overexpression of insulin-like growth factor 2 (IGF2) protein are detected in mouse Men1 insulinomas by immunostaining. Interestingly, the analysis of DNA methylation patterns by quantitative serial pyrosequencing reveals that four specific CpGs in the intragenic differentially methylated region 2 (DMR2) region of the Igf2 gene known to augment transcription through methylation are significantly hypermethylated in insulinomas of Men1 beta-cell mutant mice at 6 and 10 months of age, even before IGF2 overexpression can be detected. Thus, our data indicate the involvement of both genetic and epigenetic mechanisms in early tumorigenesis of beta-cells related to MEN1 inactivation.

Animals↗

PubMed2005

Peripheral blood gene expression profiling in rheumatoid arthritis.

We carried out gene expression profiling of peripheral blood mononuclear cells (PBMCs) in 29 patients with active rheumatoid arthritis (RA) and 21 control subjects using Affymetrix U95Av2 arrays. Using cluster analysis, we observed a significant alteration in the expression pattern of 81 genes (P<0.001) in the PBMCs of RA patients compared with controls. Many of these genes correlated with differences in monocyte counts between the two study populations, and we show that a large fraction of these genes are specifically expressed at high levels in monocytes. In addition, a logistic regression analysis was performed to identify genes that performed best in the categorization of RA and control samples. Glutaminyl cyclase, IL1RA, S100A12 (also known as calgranulin or EN-RAGE) and Grb2-associated binding protein (GAB2) were among the top discriminators. Along with previous data, the overexpression of S100A12 in RA patients emphasizes the likely importance of RAGE pathways in disease pathogenesis. The altered expression of GAB2, an intracellular adaptor molecule involved in regulating phosphatase function, is of particular interest given the recent identification of the intracellular phosphatase PTPN22 as a risk gene for RA. These data suggest that a detailed study of gene expression patterns in peripheral blood can provide insight into disease pathogenesis. However, it is also clear that substantially larger sample sizes will be required in order to evaluate fully gene expression profiling as a means of identifying disease subsets, or defining biomarkers of outcome and response to therapy in RA.

Adult↗

PubMed2005

A microarray-based comparative analysis of gene expression profiles during grain development in transgenic and wild type wheat.

Global, comparative gene expression analysis is potentially a very powerful tool in the safety assessment of transgenic plants since it allows for the detection of differences in gene expression patterns between a transgenic line and the mother variety. In the present study, we compared the gene expression profile in developing seeds of wild type wheat and wheat transformed for endosperm-specific expression of an Aspergillus fumigatus phytase. High-level expression of the phytase gene was ensured by codon modification towards the prevalent codon usage of wheat genes and by using the wheat 1DX5HMW glutenin promoter for driving transgene expression. A 9K wheat unigene cDNA microarray was produced from cDNA libraries prepared mainly from developing wheat seed. The arrays were hybridised to flourescently labelled cDNA prepared from developing seeds of the transgenic wheat line and the mother variety, Bobwhite, at three developmental stages. Comparisons and statistical analyses of the gene expression profiles of the transgenic line vs. that of the mother line revealed only slight differences at the three developmental stages. In the few cases where differential expression was indicated by the statistical analysis it was primarily genes that were strongly expressed over a shorter interval of seed development such as genes encoding storage proteins. Accordingly, we interpret these differences in gene expression levels to result from minor asynchrony in seed development between the transgenic line and the mother line. In support of this, real time PCR validation of results from selected genes at the late developmental stage could not confirm differential expression of these genes. We conclude that the expression of the codon-modified A. fumigatus phytase gene in the wheat seed had no significant effects on the overall gene expression patterns in the developing seed.

6-Phytase↗

PubMed2002

Gene expression profile of native human retinal pigment epithelium.

PURPOSE: To generate a profile of genes expressed in the native human retinal pigment epithelium and identify candidate genes for retinal and macular diseases. METHODS: Two cDNA libraries (one amplified, the other unamplified) were constructed using RNA isolated from native human RPE sheets. The sequence from the 5' end was obtained for randomly selected clones from the two libraries. Of these, more than 2000 expressed sequence tags (ESTs) were analyzed for similarity to sequences and gene clusters in public databases. RESULTS: EST analysis revealed several known RPE-expressed genes and more than 500 genes that have been characterized previously but were not known to be expressed in the RPE. Transthyretin and 90-kDa heat shock protein represent the most abundant transcripts identified in these RPE libraries. More than 200 novel ESTs and putative proteins were identified. An additional 344 sequences matched only the human genomic sequence. CONCLUSIONS: High-complexity cDNA libraries were generated from native human RPE. Analysis of ESTs generated from these libraries has yielded a profile of genes expressed in the native RPE. Several of the identified genes are known to play a significant role in the RPE. Novel ESTs, putative proteins, and genomic hits may represent as yet unidentified RPE-expressed genes and many of these, mapping in the region of retinal disease loci, may serve as candidate genes. In addition, the nonredundant set of more than 1100 genes and ESTs described herein will be a valuable resource for generating gene microarrays, which can assist in delineating RPE expression profiles during human disease pathogenesis.

Child↗

PubMed2002

cDNA arrays: gene expression profiles of Hodgkin's disease and anaplastic large cell lymphoma cell lines.

cDNA arrays are a powerful tool for the identification of differentially expressed genes in malignant tumors. We used this technique to study the gene expression profiles of anaplastic large cell lymphoma (ALCL) and Hodgkin's disease (HD). Gene expression of 11 lymphoma cell lines was analyzed covering 1176 cDNA sequences. Comparing these data to the expression profiles of B- and T-lymphocytes, we identified 27 genes that were deregulated in all cell lines or in a particular entity. For the establishment of gene expression profiles the 27 genes were assigned to four groups composed of genes deregulated in (i) all lymphoma cell lines, (ii) ALCL and HD, (iii) only HD, and (iv) ALCL exclusively. Our results indicate that ALCL and HD share the differential expression of at least five genes. In addition, both entities are characterized by the differentially deregulated expression of four genes in HD and seven genes in ALCL. Because the expression profiling was performed on cell lines, further studies are needed to clarify the biological significance of the differentially expressed genes.

B-Lymphocytes↗

PubMed2004

Microarray analysis of gene expression profiles in wing discs of Bombyx mori during pupal ecdysis.

Wing discs of holometabolous insects undergo dramatic morphological changes during metamorphosis, a process that is controlled by the actions of hundreds of gene products. Using cDNA microarrays constructed from 5086 ESTs, we monitored the gene expression profiles in wing discs of Bombyx mori at 13 time points during pupal ecdysis (day-4 fifth instar larvae to day-0 pupae). Of the 5086 ESTs on the microarrays, 2998 ESTs had significant signals in more than half of the experiments. Of the 2998 ESTs, genes represented by 683 ESTs showed significant perturbations during pupal ecdysis. Genes previously known to be induced during metamorphosis were identified, including E75, Urbain, Chitinases, and cuticle proteins. The expressions of genes represented by 59 ESTs induced at the beginning of wandering contained genes predicted to be involved in protein degradation, amino acid metabolism, and amino acid transport. The expressions of genes represented by 147 ESTs induced after the ecdysteroid peak had a role in cuticle synthesis, pigmentation, ion transport, protein transport, and transcription regulation. The expressions of genes represented by 85 ESTs repressed after the ecdysteroid peak were predicted to be involved in nucleotide and nucleic acid metabolism and cell cycle. This indicates the involvement of several biological processes in wing disc development during metamorphosis.

Animals↗

PubMed2006

Gene expression profiling of human endothelial cells exposed to 50-Hz magnetic fields fails to produce regulated candidate genes.

To address the question of a possible effect of magnetic fields (MF) at 50 Hz on living systems, gene expression analyses were performed on human primary vascular endothelial cells exposed to MF of various intensities compared to control cells. Exposure protocols included continuous exposure at a single intensity (10 and 700 microT), intermittent exposure at a single intensity (700 microT), and continuous exposure to a variable-intensity field (10-30 microT). The transcriptional response of the cells was investigated using oligonucleotide microarrays containing up to 30 000 unique features. Although in individual experiments genes were identified where the expression appeared to be affected by exposure to MF, none of these genes were regulated in the same manner in subsequent repetition experiments. This is the first report of a transcriptome-wide analysis of the effects of MF exposure on human cells. The lack of a reproducible effect of MF on the expression of any genes in our investigation adds further weight to the evidence that 50-Hz MF are not capable of interacting with biological systems and thus do not represent an endothelial stress factor.

Cell Culture Techniques↗

PubMed2005

Survival trees for analyzing clinical outcome in lung adenocarcinomas based on gene expression profiles: identification of neogenin and diacylglycerol kinase alpha expression as critical factors.

We present survival trees as an exploratory tool for revealing new insights into gene expression profiles in combination with clinical patient data. Survival trees partition the patient data studied into groups with similar survival outcomes and identify characteristic genetic profiles within these groups. We demonstrate the application of survival trees in a study involving the expression profiles of 3,588 genes in 211 lung adenocarcinoma patients. The survival tree identified a group of early-stage cancer patients with relatively low survival rates and another group of advanced-stage patients with remarkably good survival outcome. For both groups, the tree identified characteristic expression profiles of genes that might play a role in cancerogenesis and disease progression, notably the genes for the netrin receptor neogenin and the Ras/Rho kinase modulator diacylglycerol kinase alpha.

Adenocarcinoma↗

PubMedDate not supplied

Gene expression profiling of ductal carcinomas in situ and invasive breast tumors.

UNLABELLED: Comparative and functional genomics are powerful tools to advance the understanding of the molecular basis of cancer. It is believed that genes are epigenetically regulated and, thus, each tumor type and stage will be characterized by a gene expression fingerprint. In this study we identified genes that are differentially expressed in ductal carcinoma in situ and invasive ductal carcinoma of the breast. To isolate genes that are associated with progression of breast cancer we performed differential display and subtractive cloning procedures using matched RNA from normal and tumor tissue. cDNA microarray analysis generated gene expression profiles typical of the transition from in situ to invasive breast cancer when we used mRNA extracted from a case of low- to intermediate-grade DCIS and a case of high-grade DCIS/IDC. cDNAs from these samples were the probes in a cDNA microarray hybridization to 9183 unique cDNAs representing 8507 genes. Signals from both transcriptomes were obtained for 8083 genes, and the balanced differential expression values between pure DCIS and DCIS/invasive tumors revealed 303 distinct cDNAs with a ratio of > 2. Interferon inducible genes were found to be expressed at the highest level in the pure DCIS sample. Genes most abundantly expressed in the invasive tumor were immunoglobulin heavy constant gamma 3 and calgranulin B. Further analysis of RNA and protein expression in breast tumor cell lines and patient tissue samples revealed that: IGFBP-rP1 is down-regulated in invasive tumors whereas cyclin I protein is regulated by ubiquitination and is associated with ER-negative breast cancers. CONCLUSION: The known and novel genes discussed here represent targets for molecular characterization during breast cancer development as well as for designing novel strategies for diagnosis and treatment.

Biomarkers, Tumor↗

PubMed2004

Gene expression profiles and molecular markers to predict recurrence of Dukes' B colon cancer.

PURPOSE: The 5-year survival rate of patients with Dukes' B colon cancer is approximately 75%. Identification of the patients at high risk of recurrence in this group would allow better staging and more informed use of adjuvant chemotherapy. In this study, we used DNA chip technology to systematically identify new prognostic markers for tumor relapse in Dukes' B patients. PATIENTS AND METHODS: Using Affymetrix U133a GeneChip containing approximately 22,000 transcripts (Affymetrix, Santa Clara, CA), RNA samples from 74 patients with Dukes' B colon cancer were analyzed. Thirty-one patients developed tumor relapse in less than 3 years, whereas 43 patients remained disease-free for more than 3 years after surgery. Two supervised class prediction approaches were used to identify gene markers that can best discriminate between patients who would experience relapse and patients who would remain disease-free. A multivariate Cox model was built to predict recurrence. RESULTS: Gene expression profiling identified a 23-gene signature that predicts recurrence in Dukes' B patients. This signature was validated in 36 independent patients. The overall performance accuracy was 78%. Thirteen of 18 relapse patients and 15 of 18 disease-free patients were predicted correctly, giving an odds ratio of 13 (95% CI, 2.6 to 65; P =.003). The log-rank test indicated a significant difference in disease-free time between the predicted relapse and disease-free patients (P =.0001). CONCLUSION: The clinical value of these markers is that the patients at a high predicted risk of relapse (13-fold risk) could be upstaged to receive adjuvant therapy, similar to Dukes' C patients. Our data highlight the feasibility of a prognostic assay that could focus more intensive treatment for localized colon cancer.

Algorithms↗

PubMed2003

Gene expression profiles in different stages of mouse spermatogenic cells during spermatogenesis.

During spermatogenesis, diploid stem cells differentiate, undergo meiosis and spermiogenesis, and transform into haploid spermatozoa. Various factors have been demonstrated to regulate this marvelous process of differentiation, but the expression of only a few genes specifically involved in spermatogenesis has been studied. In the present study, different types of spermatogenic cells were isolated from Balb/c mice testes of different ages using the velocity sedimentation method, and we determined the expression profiles of 1176 known mouse genes in six different types of mouse spermatogenic cells (primitive type A spermatogonia, type B spermatogonia, preleptotene spermatocytes, pachytene spermatocytes, round spermatids, and elongating spermatids) using Atlas cDNA arrays. Of the 1176 genes on the Atlas Mouse 1.2 cDNA Expression Arrays, we detected 181 genes in primitive type A spermatogonia, 256 in type B spermatogonia, 221 in preleptotene spermatocytes, 160 in pachytene spermatocytes, 141 in round spermatids, and 126 in elongating spermatids. A number of genes were detected as differential expression (up-regulation or down-regulation). Fourteen of the differentially expressed genes have been further confirmed by reverse transcription-polymerase chain reaction for their expression characterizations in different types of spermatogenic cells. These results provide more information for further studies into spermatogenesis-related genes and may lead to the identification of genes with potential relevance to spermatogenesis.

Animals↗

PubMedDate not supplied

Gene expression profiling of human diseases by serial analysis of gene expression.

Until recently, the approach to understanding the molecular basis of complex syndromes such as cancer, coronary artery disease, and diabetes was to study the behavior of individual genes. However, it is generally recognized that expression of a number of genes is coordinated both spatially and temporally and that this coordination changes during the development and progression of diseases. Newly developed functional genomic approaches, such as serial analysis of gene expression (SAGE) and DNA microarrays have enabled researchers to determine the expression pattern of thousands of genes simultaneously. One attractive feature of SAGE compared to microarrays is its ability to quantify gene expression without prior sequence information or information about genes that are thought to be expressed. SAGE has been successfully applied to the gene expression profiling of a number of human diseases. In this review, we will first discuss SAGE technique and contrast it to microarray. We will then highlight new biological insights that have emerged from its application to the study of human diseases.

Gene Expression↗