Detection of differentially expressed genes in primary tumor tissues using representational differences analysis coupled to microarray hybridization

Diagnosis and Prediction of Endometrial Carcinoma Using Machine Learning and Artificial Neural Networks Based on Public Databases

Endometrial carcinoma (EC), a common female reproductive system malignant tumor, affects thousands of people with high morbidity and mortality worldwide. This study was aimed at developing a prediction model for the diagnosis of EC in the general population. First, we obtained datasets GSE63678, GSE106191, and GSE115810 from the Gene Expression Omnibus (GEO) database, dataset GSE17025 from the GEO database, and the RNA sequence of EC from The Cancer Genome Atlas (TCGA) database to constitute the training, test, and validation groups, respectively. Subsequently, the 96 most significantly differentially expressed genes (DEGs) were identified and analyzed for function and pathway enrichment in the training group. Next, we acquired the disease-specific genes by random forest and established an artificial neural network for the diagnosis. Receiver operating characteristic (ROC) curves were utilized to identify the signature across the three groups. Finally, immune infiltration was analyzed to reveal tumor-immune microenvironment (TIME) alterations in EC. The top 96 DEGs (77 down-regulated and 19 up-regulated genes) were primarily enriched in the interleukin-17 signaling pathway, protein digestion and absorption, and transcriptional misregulation in cancer. Subsequently, 14 characterizing genes of EC were identified by random forest. In the training, test, and validation groups, the artificial neural network was constructed with high diagnostic accuracies of 0.882, 0.864, and 0.839, respectively, and areas under the ROC curve (AUCs) of 0.928, 0.921, and 0.782, respectively. Finally, resting and activated mast cells were found to have increased in TIME. We constructed an artificial diagnostic model with excellent reliability for EC and uncovered variations in the immunological ecosystem of EC through integrated bioinformatics approaches, which might be potential diagnostic targets for EC.

Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research

In recent years, the diversity of cancer cells in tumor tissues as a result of intratumor heterogeneity has attracted attention. In particular, the development of single-cell analysis technology has made a significant contribution to the field; technologies that are centered on single-cell RNA sequencing (scRNA-seq) have been reported to analyze cancer constituent cells, identify cell groups responsible for therapeutic resistance, and analyze gene signatures of resistant cell groups. However, although single-cell analysis is a powerful tool, various issues have been reported, including batch effects and transcriptional noise due to gene expression variation and mRNA degradation. To overcome these issues, machine learning techniques are currently being introduced for single-cell analysis, and promising results are being reported. In addition, machine learning has also been used in various ways for single-cell analysis, such as single-cell assay of transposase accessible chromatin sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq) analysis, and multi-omics analysis; thus, it contributes to a deeper understanding of the characteristics of human diseases, especially cancer, and supports clinical applications. In this review, we present a comprehensive introduction to the implementation of machine learning techniques in medical research for single-cell analysis, and discuss their usefulness and future potential.

Powerful quantifiers for cancer transcriptomics

Every day, investigators find a new link between a form of cancer and a particular alteration in the sequence or/and expression level of a key gene, awarding this gene the title of “biomarker”. The clinician may choose from numerous available panels to assess the type of cancer based on the mutation or expression regulation (“transcriptomic signature”) of “driver” genes. However, cancer is not a “one-gene show” and, together with the alleged biomarker, hundreds other genes are found as mutated or/and regulated in cancer samples. Regardless of the platform, a well-designed transcriptomic study produces three independent features for each gene: Average expression level, expression variability and coordination with expression of each other gene. While the average expression level is used in all studies to identify what genes were up-/down-regulated or turn on/off, the other two features are unfairly ignored. We use all three features to quantify the transcriptomic change during the progression of the disease and recovery in response to a treatment. Data from our published microarray experiments on cancer nodules and surrounding normal tissue from surgically removed tumors prove that the transcriptomic topologies are not only different in histopathologically distinct regions of a tumor but also dynamic and unique for each human being. We show also that the most influential genes in cancer nodules [the Gene Master Regulators (GMRs)] are significantly less influential in the normal tissue. As such, “smart” manipulation of the cancer GMRs expression may selectively kill cancer cells with little consequences on the normal ones. Therefore, we strongly recommend a really personalized approach of cancer medicine and present the experimental procedure and the mathematical algorithm to identify the most legitimate targets (GMRs) for gene therapy.

Identification of Biomarker for Cutaneous Squamous Cell Carcinoma Using Microarray Data Analysis

Cutaneous squamous cell carcinoma (CSCC) is one of the most malignant tumors worldwide. We aimed to explore the molecular mechanism of this CSCC and screen feature genes that can function as the biomarker of CSCC and thus provide a theoretical basis for the pathogenesis research and development of medicine. The method of microarray data analysis was used in this study to explore the differentially expressed genes between tissues of normal specimens and tissues of patients with CSCC. Besides, functional enrichment analysis and signal pathway were performed on these genes to screen the feature genes that are closely associated with CSCC can function as the potential biomarkers of CSCC.A total of 53 samples from two datasets, GSE45216 and GSE45164, were used in the differentially expressed analysis. And as a result, a total of 833 genes were screened out, including 465 up-regulated genes and 215 down-regulated genes. Candidate genes, including up-regulated genes like S100A12, MMP1, DEFB4B/DEFB4A, KRT16 and PI3, and down-regulated genes like EGR3, LRP4, C14orf132, PAMR1, CCL27, and KRT2 were screened out. All these genes were testified in the dataset of GSE66359. The result showed that only three genes, KRT16, PI3 and EGR3, were mostly differentially expressed and only EGR3 had the same expression pattern with both datasets, GSE45216 and GSE45164.Of note, EGR3 gene was found to be the most differentially expressed gene in cutaneous squamous cell carcinoma, which had the potential to function as the candidate genes and help in the diagnosis and prognostic treatments of CSCC.

Overview of DNA microarrays: types, applications, and their future

This unit provides an overview of DNA microarrays. Microarrays are a technology in which thousands of nucleic acids are bound to a surface and are used to measure the relative concentration of nucleic acid sequences in a mixture via hybridization and subsequent detection of the hybridization events. This overview first discusses the history of microarrays and the antecedent technologies that led to their development. This is followed by discussion of the methods of manufacture of microarrays and the most common biological applications. The unit ends with a brief description of the limitations of microarrays and discusses how microarrays are being rapidly replaced by DNA sequencing technologies.

INTERRELATED TWO-WAY CLUSTERING AND ITS APPLICATION ON GENE EXPRESSION DATA

Microarray technologies are capable of simultaneously measuring the signals for thousands of messenger RNAs and large numbers of proteins from single samples. Arrays are now widely used in basic biomedical research for mRNA expression profiling and are increasingly being used to explore patterns of gene expression in clinical research. Most research has focused on the interpretation of the meaning of the microarray data which are transformed into gene expression matrices where usually the rows represent genes, the columns represent various samples. Clustering samples can be done by analyzing and eliminating of irrelevant genes. However, majority methods are supervised (or assisted by domain knowledge), less attention has been paid on unsupervised approaches which are important when little domain knowledge is available. In this paper, we present a new framework for unsupervised analysis of gene expression data, which applies an interrelated two-way clustering approach on the gene expression matrices. The goal of clustering is to identify important genes and perform cluster discovery on samples. The advantage of this approach is that we can dynamically manipulate the relationship between the gene clusters and sample groups while conducting an iterative clustering through both of them. The performance of the proposed method with various gene expression data sets is also illustrated.

Gene network inference and biochemical assessment delineates GPCR pathways and CREB targets in small intestinal neuroendocrine neoplasia

Small intestinal (SI) neuroendocrine tumors (NET) are increasing in incidence, however little is known about their biology. High throughput techniques such as inference of gene regulatory networks from microarray experiments can objectively define signaling machinery in this disease. Genome-wide co-expression analysis was used to infer gene relevance network in SI-NETs. The network was confirmed to be non-random, scale-free, and highly modular. Functional analysis of gene co-expression modules revealed processes including ‘Nervous system development’, ‘Immune response’, and ‘Cell-cycle’. Importantly, gene network topology and differential expression analysis identified over-expression of the GPCR signaling regulators, the cAMP synthetase, ADCY2, and the protein kinase A, PRKAR1A. Seven CREB response element (CRE) transcripts associated with proliferation and secretion: BEX1, BICD1, CHGB, CPE, GABRB3, SCG2 and SCG3 as well as ADCY2 and PRKAR1A were measured in an independent SI dataset (n = 10 NETs; n = 8 normal preparations). All were up-regulated (p<0.035) with the exception of SCG3 which was not differently expressed. Forskolin (a direct cAMP activator, 10⁻⁵ M) significantly stimulated transcription of pCREB and 3/7 CREB targets, isoproterenol (a selective ß-adrenergic receptor agonist and cAMP activator, 10⁻⁵ M) stimulated pCREB and 4/7 targets while BIM-53061 (a dopamine D₂ and Serotonin [5-HT₂] receptor agonist, 10⁻⁶ M) stimulated 100% of targets as well as pCREB; CRE transcription correlated with the levels of cAMP accumulation and PKA activity; BIM-53061 stimulated the highest levels of cAMP and PKA (2.8-fold and 2.5-fold vs. 1.8–2-fold for isoproterenol and forskolin). Gene network inference and graph topology analysis in SI NETs suggests that SI NETs express neural GPCRs that activate different CRE targets associated with proliferation and secretion. In vitro studies, in a model NET cell system, confirmed that transcriptional effects are signaled through the cAMP/PKA/pCREB signaling pathway and that a SI NET cell line was most sensitive to a D₂ and 5-HT₂ receptor agonist BIM-53061.

ZBED4, a BED-type zinc-finger protein in the cones of the human retina

PURPOSE

To characterize the ZBED4 cDNA identified by subtractive hybridization and microarray of retinal cone degeneration (cd) adult dog mRNA from mRNA of normal dog retina.

METHODS

The cDNA library obtained from subtractive hybridization was arrayed and screened with labeled amplicons from normal and cd dog retinas. Northern blot analysis was used to verify ZBED4 mRNA expression in human retina. Flow cytometry sorted peanut agglutinin (PNA)-labeled cones from dissociated mouse retinas, and quantitative RT-PCR (QPCR) was used to measure ZBED4 mRNA levels in these cone cells. Immunohistochemistry localized ZBED4 in human retinas. Expression of ZBED4 mRNA transiently transfected into HEK293 cells was analyzed by immunofluorescence. ZBED4 subcellular localization was determined with Western blot analysis.

RESULTS

One of 80 cDNAs differentially expressed in normal and cd dog retinas corresponded to a novel gene, ZBED4, which is also expressed in human and mouse retinas. ZBED4 mRNA was found to be present in cone photoreceptors. When ZBED4 cDNA was transfected into HEK293 cells, the expressed protein showed nuclear localization. However, in human retinas, ZBED4 was localized to cone nuclei, inner segments, and pedicles, as well as to Müller cell endfeet. Confirming these immunohistochemical results, the 135-kDa ZBED4 was found in both the nuclear and cytosolic extracts of human retinas. ZBED4 has four predicted DNA-binding domains, a dimerization domain, and two LXXLL motifs characteristic of coactivators/corepressors of nuclear hormone receptors.

CONCLUSIONS

ZBED4 cellular/subcellular localization and domains suggest a regulatory role for this protein, which may exert its effects in cones and Müller cells through multiple ways of action.

Gene expression analysis of neural cells and tissues using DNA microarrays

DNA microarrays pose specific challenges to those studying the central and peripheral nervous systems. Probably the most important involve difficulty in obtaining appropriate tissue for study, as well as the problems posed by cellular heterogeneity. This unit describes advances in the available technologies and provides protocols for cDNA microarray hybridization, including the use of PCR amplicons. Protocols are also provided for the two major methods for limiting cellular heterogeneity by study of RNA from single cell populations in high-throughput microarray studies, laser capture microdissection (LCM), and automated fluorescent cell sorting (FACS-array).

Kamchatka crab duplex-specific nuclease-mediated transcriptome subtraction method for identifying long cDNAs of differentially expressed genes

The subtraction method is a quick and economical technique to scan differential gene expression. However, most subtraction methods are limited by the complexity and length of cDNA samples. To overcome this problem, we developed a novel method to identify the unique full-length cDNAs in two complicated tissue or cell types. This method, duplex-specific nuclease (DSN)-mediated transcriptome subtraction (DTS), is based on the normalization strategy of the crab duplex-specific nuclease and the subtraction method of suppression subtractive hybridization. DSN eliminates nearly all of the common sequences in the tester and driver cDNA samples after the first hybridization step, ensures accurate discrimination between the tester and the driver cDNA samples, and enriches the full-length differential cDNAs from the tester. Using the DTS method, we have successfully identified an 1812-bp additional GUS gene from the complicated Arabidopsis seedling cDNA library. We also employed DTS to detect the differences in mRNA expression of salt-treated Arabidopsis seedlings to illustrate further the efficiency of the subtraction method.

Gene expression profiling by DNA microarray technology

Methods in molecular and genetic biology have provided important clues to elucidate the complex mechanisms of oral and craniofacial development and pathogenesis of diseases. It has become increasingly clear that a biological phenotype is a result of multiple factors involving a large number of regulatory genes, while a single nucleotide mutation can cause various degrees of oral and craniofacial abnormalities. These oral and craniofacial problems often present a challenge to the molecular screening process. Recent advances in microarray-based technologies allow for large-scale gene expression analysis in a single experiment, which have been applied to genome-wide assays, mutational analysis, drug discovery, developmental biology, and molecular analysis of various diseases. This review introduces the basic principle and some modifications of techniques and materials used in microarray technology, as well as currently available microarray data analysis strategies. Microarray technology can be applied to the soon-to-be-available human genome database and will be a powerful research tool for those inquiring into specific problems associated with oral and craniofacial biology.

Microarray analysis of sarcomas

Microarrays began to be used to study gene expression profiles in the mid-1990s, but it was only after 2000 that serious attempts have been made to apply this technology to investigate sarcomas. Microarray technologies provide a comprehensive survey of active molecular pathways and potential molecular targets for diagnosis and treatment, but are challenging to use because of issues of specimen collection, cost, and complexities in experimental design and data analysis. As a discovery-based technique, microarray analyses are most valuable when framed around specific gaps in our knowledge of tumor etiology and progression, challenges in differential diagnosis, and pressing therapeutic needs. To date, microarray analyses of sarcomas support their division into molecularly defined and molecularly heterogeneous categories, and have provided useful diagnostic markers for entities such as gastrointestinal stromal tumors, synovial sarcoma, and dermatofibrosarcoma protuberans. Signatures predicting outcome and response to therapy have been published for Ewing sarcoma and osteosarcoma, and receptor tyrosine kinase expression patterns have suggested novel therapeutic approaches which may be applied to several types of sarcoma. Nevertheless, results need to be interpreted in the context of histopathology and validated by complementary technologies and/or other research groups.

Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach

BACKGROUND

The main limitation in performing genome-wide gene-expression profiling is the assay of low-expression genes. Approaches with high throughput and high sensitivity for assaying low-expression transcripts are urgently needed for functional genomic studies. Combination of the suppressive subtractive hybridization (SSH) and cDNA microarray techniques using the subtracted cDNA clones as probes printed on chips has greatly improved the efficiency for fishing out the differentially expressed clones and has been used before. However, it remains tedious and inefficient sequencing works for identifying genes including the great number of redundancy in the subtracted amplicons, and sacrifices the original advantages of high sensitivity of SSH in profiling low-expression transcriptomes.

RESULTS

We modified the previous combination of SSH and microarray methods by directly using the subtracted amplicons as targets to hybridize the pre-made cDNA microarrays (named as "SSH/microarray"). mRNA prepared from three pairs of hepatoma and non-hepatoma liver tissues was subjected to the SSH/microarray assays, as well as directly to regular cDNA microarray assays for comparison. As compared to the original SSH and microarray combination assays, the modified SSH/microarray assays allowed for much easier inspection of the subtraction efficiency and identification of genes in the subtracted amplicons without tedious and inefficient sequencing work. On the other hand, 5015 of the 9376 genes originally filtered out by the regular cDNA microarray assays because of low expression became analyzable by the SSH/microarray assays. Moreover, the SSH/microarray assays detected about ten times more (701 vs. 69) HCC differentially expressed genes (at least a two-fold difference and P < 0.01), particularly for those with rare transcripts, than did the regular cDNA microarray assays. The differential expression was validated in 9 randomly selected genes in 18 pairs of hepatoma/non-hepatoma liver tissues using quantitative RT-PCR. The SSH/microarray approaches resulted in identifying many differentially expressed genes implicated in the regulation of cell cycle, cell death, signal transduction and cell morphogenesis, suggesting the involvement of multi-biological processes in hepato-carcinogenesis.

CONCLUSION

The modified SSH/microarray approach is a simple but high-sensitive and high-efficient tool for differentially profiling the low-expression transcriptomes. It is most adequate for applying to functional genomic studies.

EWS–ETS oncoproteins: The linchpins of Ewing tumors

Ewing tumors, which comprise Ewing's sarcoma and peripheral primitive neuroectodermal tumors, are highly aggressive and mostly affect children and adolescents. Their molecular signature is a chromosomal translocation leading to the generation of EWS-ETS (or very rarely FUS-ETS) fusion proteins that are capable of transforming cells. These oncoproteins act as aberrant transcription factors due to the fusion of an ETS DNA binding domain to a highly potent EWS (or FUS) transactivation domain. Accordingly, many EWS-ETS target genes have been identified whose dysregulation could contribute to the development of tumor formation. Furthermore, EWS-ETS oncoproteins may impact on RNA splicing or affect other proteins through disturbing their ability to form functional complexes. The molecular knowledge gained so far from studying EWS-ETS oncoproteins has not only broadened our understanding of Ewing tumors but also improved the diagnosis of these highly undifferentiated tumors. In addition, several potential prognostic markers have been uncovered and novel therapies are suggested that may improve the still dismal survival rate of Ewing tumor patients.

A modified cDNA subtraction to identify differentially expressed genes from plants with universal application to other eukaryotes

We have designed a simple and efficient polymerase chain reaction (PCR)-based cDNA subtraction protocol for high-throughput cloning of differentially expressed genes from plants that can be applied to any experimental system and as an alternative to DNA chip technology. Sequence-independent PCR-amplifiable first-strand cDNA population was synthesized by priming oligo-dT primer with a defined 5' heel sequence and ligating another specified single-stranded oligonucleotide primer on the 3' ends of first-strand cDNAs by T4 RNA ligase. A biotin label was introduced into the sense strands of cDNA that must be subtracted by using 5' biotinylated forward primer during PCR amplification to immobilize the sense strand onto the streptavidin-linked paramagnetic beads. The unamplified first strand (antisense) of the interrogating cDNA population was hybridized with a large excess of amplified sense strands of control cDNA. We used magnetic bead technology for the efficient removal of common cDNA population after hybridization to reduce the complexity of the cDNA prior to PCR amplification for the enrichment and sequence abundance normalization of differentially expressed genes. Construction of a subtracted and normalized cDNA library efficiently eliminates common abundant cDNA messages and also increases the probability of identifying clones differentially expressed in low-abundance cDNA messages. We used this method to successfully isolate differentially expressed genes from Pennisetum seedlings in response to salinity stress. Sequence analysis of the selected clones showed homologies to genes that were reported previously and shown to be involved in plant stress adaptation.

Construction and screening of subtracted cDNA libraries from limited populations of plant cells: a comparative analysis of gene expression between maize egg cells and central cells

The analysis of cell type-specific gene expression is an essential step in understanding certain biological processes during plant development, such as differentiation. Although methods for isolating specific cell types have been established, the application of cDNA subtraction to small populations of isolated cell types for direct identification of specific or differentially expressed transcripts has not yet been reported. As a first step in the identification of genes expressed differentially between maize egg cells and central cells, we have manually isolated these types of cell, and applied a suppression-subtractive hybridization (SSH) strategy. After microarray screening of 1030 cDNAs obtained from the subtracted libraries, we identified 340 differentially expressed clones. Of these, 142 were sequenced, which resulted in the identification of 62 individual cDNAs. The expression patterns of 20 cDNAs were validated by quantitative RT-PCR, through which we identified five transcripts with cell type-specific expression. The specific localization of some of these transcripts was also confirmed by in situ hybridization on embryo sac sections. Taken together, our data demonstrate the effectiveness of our approach in identifying differentially expressed and cell type-specific transcripts of relatively low abundance. This was also confirmed by the identification of previously reported egg cell- and central cell-specific genes in our screen. Importantly, from our analysis we identified a significant number of novel sequences not present in other embryo sac or, indeed, in other plant expressed sequence tag (EST) databases. Thus, in combination with standard EST sequencing and microarray hybridization strategies, our approach of differentially screening subtracted cDNAs will add substantially to the expression information in spatially highly resolved transcriptome analyses.

Gliomas: advances in molecular analysis and characterization

BACKGROUND

Gliomas represent the most common primary brain tumor. Despite recent advances in diagnostic imaging, neurosurgical technique, radiation therapy, and chemotherapy, significant advances in accurate prognosis and improved survival have not been achieved. Nevertheless, new developments in molecular biology could have potential impact on the clinical management of patients with these brain tumors. This review will describe the technological advances being used to enrich the classification of gliomas, present specific studies that have successfully used the new technologies to identify molecular subtypes of glioblastoma, and discuss the implications of such enhanced classification and molecular characterizations for the prediction of therapeutic response and the design of future brain tumor therapies.

RESULTS

Innovative techniques using complementary DNA and oligonucleotide microarrays (gene chips), tissue microarrays (tissue chips), and differential immunoabsorption have provided high throughput and potentially comprehensive approaches for the molecular characterization of human gliomas. Alterations of several tumor suppressor genes and oncogenes have already been identified as being critical to glioma transformation and progression. These approaches have led to the subclassification of glioblastoma multiforme into distinct subtypes based on the molecular signatures of the tumors.

CONCLUSIONS

Classifications of gliomas can now be enhanced with new techniques for comprehensive molecular characterization. Improved and efficient molecular profiling of brain tumors is advancing diagnosis/prognosis and identifying targets for novel and rational therapeutic approaches. Neurosurgeons and neuro-oncologists should be aware of these new developments so they can better advise and treat their patients.

Modified representational difference analysis: isolation of differentially expressed mRNAs from rare cell populations

Representational difference analysis of cDNAs (cDNA-RDA) is a sensitive subtractive hybridization technique capable of isolating rare mRNAs differentially expressed in two cell populations. cDNA-RDA can detect sequences represented at 0.0001% in the starting mRNA. By using reverse transcriptase polymerase chain reaction (PCR), cDNA-RDA also lends itself to studies in which samples are derived from limited numbers of cells. Standard cDNA-RDA protocols depend upon the presence of specific restriction enzyme sites in each cDNA, typically enzymes with four base recognition sequences. These sites are used to reduce the cDNA size range and provide primer sites for subsequent PCR amplification. Consequently, transcripts containing fewer than two of the chosen restriction sites are undetectable by cDNA-RDA. We have developed a restriction enzyme site-independent cDNA-RDA protocol called modified RDA (MRDA). We constructed MRDA test sequences from random hexamer-primed cDNA, thereby increasing the representation of mRNAs which are excluded by cDNA-RDA protocols. MRDA is also more efficient than cDNA-RDA at removing highly expressed housekeeping genes during the subtractive hybridization process, thereby allowing more efficient isolation of preferentially expressed mRNAs. Using MRDA, we isolated cDNAs differentially expressed between limited numbers of human CD4(+) naive and memory T lymphocyte subsets and skin- and gut-homing memory T cell subsets.

Validation of RNA Arbitrarily Primed PCR Probes Hybridized to Glass cDNA Microarrays: Application to the Analysis of Limited Samples

Background: The applicability of microarray-based transcriptome massive analysis is often limited by the need for large amounts of high-quality RNA. RNA arbitrarily primed PCR (RAP-PCR) is an unbiased fingerprinting PCR technique that reduces both the amount of initial material needed and the complexity of the transcriptome. The aim of this study was to evaluate the feasibility of using hybridization of RAP-PCR products as transcriptome representations to analyze differential gene expression in a microarray platform.

Methods: RAP-PCR products obtained from samples with limited availability of biological material, such as experimental metastases, were hybridized to conventional cDNA microarrays. We performed replicates of self-self hybridizations of RAP-PCR products and mathematical modeling to assess reproducibility and sources of variation.

Results: Gene/slide interaction (47.3%) and the PCR reaction (33.8%) accounted for the majority of the variability. From these observations, we designed a protocol using two pools of three independent RAP-PCR reactions coming from two independent reverse transcription reactions hybridized in duplicate and evaluated them in the analyses of paired xenograft-metastases samples. Using this approach, we found that HER2 and MMP7 may be down-regulated during distal dissemination of colorectal tumors.

Conclusion: RAP-PCR glass array hybridization can be used for transcriptome analysis of small samples.

Panel of genes transcriptionally up-regulated in squamous cell carcinoma of the cervix identified by representational difference analysis, confirmed by macroarray, and validated by real-time quantitative reverse transcription-PCR

BACKGROUND

The Pap smear is currently the most widely used method of screening for squamous cell carcinoma of the cervix (SCCC). Because it is based on cell morphology, it is subject to variability in interpretation. Sensitive molecular markers capable of differentiating cancerous samples from noncancerous ones would be beneficial in this regard.

METHODS

We performed representational difference analysis (RDA) using paired, noncancerous (normal) and cancerous (disease) tissues taken from the same specimen obtained from a single patient with a confirmed diagnosis of SCCC. Linearly amplified cDNA from normal and diseased tissues of the original patient and seven others were hybridized to DNA macroarrays containing the candidate gene transcript fragments. Real-time quantitative reverse transcription-PCR was used to validate the macroarray results.

RESULTS

RDA identified a candidate pool of 65 transcript fragments up-regulated in diseased tissue compared with normal tissue. Forty-one transcripts were found to be up-regulated in diseased compared with normal tissue in at least one half the patients by macroarray hybridization. Eleven of those genes were selected for real-time quantitative reverse transcription-PCR analysis, and all were confirmed as transcriptionally up-regulated in cancer compared with normal tissue in at least one half the patients.

CONCLUSIONS

RDA using tissues from a single patient identified gene fragments confirmed to be transcriptionally up-regulated in SCCC both in the original patient and in seven others. The confirmed genes have a variety of functions and also have the potential to serve as diagnostic or prognostic markers.

Tests for finding complex patterns of differential expression in cancers: towards individualized medicine

Background

Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g., comparison of sample means) to identify differentially expressed genes. This leads to the discovery of 'population-level' markers, i.e., genes with the expression patterns A > B and B > A. We introduce the PPST test that identifies genes where a significantly large subset of cases exhibit expression values beyond upper and lower thresholds observed in the control samples.

Results

Interestingly, the test identifies A > B and B < A pattern genes that are missed by population-level approaches, such as the t-test, and many genes that exhibit both significant overexpression and significant underexpression in statistically significantly large subsets of cancer patients (ABA pattern genes). These patterns tend to show distributions that are unique to individual genes, and are aptly visualized in a 'gene expression pattern grid'. The low degree of among-gene correlations in these genes suggests unique underlying genomic pathologies and high degree of unique tumor-specific differential expression. We compare the PPST and the ABA test to the parametric and non-parametric t-test by analyzing two independently published data sets from studies of progression in astrocytoma.

Conclusions

The PPST test resulted findings similar to the nonparametric t-test with higher self-consistency. These tests and the gene expression pattern grid may be useful for the identification of therapeutic targets and diagnostic or prognostic markers that are present only in subsets of cancer patients, and provide a more complete portrait of differential expression in cancer.

Tissue-wide expression profiling using cDNA subtraction and microarrays to identify tumor-specific genes

With the objective of discovering novel putative intervention sites for anticancer therapy, we compared transcriptional profiles of breast cancer, lung squamous cell cancer (LSCC), lung adenocarcinoma (LAC), and renal cell cancer (RCC). Each of these tumor types still needs improvement in medical treatment. Our intention was to search for genes not only highly expressed in the majority of patient samples but which also exhibit very low or even absence of expression in a comprehensive panel of 16 critical (vital) normal tissues. To achieve this goal, we combined two powerful technologies, PCR-based cDNA subtraction and cDNA microarrays. Seven subtractive libraries consisting of approximately 9250 clones were established and enriched for tumor-specific transcripts. These clones, together with approximately 1750 additional tumor-relevant genes, were used for cDNA microarray preparation. Hybridizations were performed using a pool of 16 critical normal tissues as a reference in all experiments. In total, we analyzed 20 samples of breast cancer, 11 of LSCC, 11 of LAC, and 8 of RCC. To select for genes with low or even no expression in normal tissues, expression profiles of 22 different normal tissues were additionally analyzed. Importantly, this tissue-wide expression profiling allowed us to eliminate genes, which exhibit also high expression in normal tissues. Similarly, expression signatures of genes, which are derived from infiltrating cells of the immune system, were eliminated as well. Cluster analysis resulted in the identification of 527 expressed sequence tags specifically up-regulated in these tumors. Gene-wise hierarchical clustering of these clones clearly separated the different tumor types with RCC exhibiting the most homogeneous and LAC the most diverse expression profile. In addition to already known tumor-associated genes, the majority of identified genes have not yet been brought into context with tumorigenesis such as genes involved in bone matrix mineralization (OSN, OPN, and OSF-2) in lung, breast, and kidney cancer or genes controlling Ca(2+) homeostasis (RCN1,CALCA, S100 protein family). EGLN3, which recently has been shown to be involved in regulation of hypoxia-inducible factor, was found to be highly up-regulated in all RCCs and in half of the LSCCs analyzed. Furthermore, 42 genes, the expression level of which correlated with the overall survival of breast cancer patients, were identified. The gene dendogram clearly separates two groups of genes, those up-regulated such as cyclin B1, TGF-beta 3, B-Myb, Erg2, VCAM-1, and CD44 and those down-regulated such as MIG-6, Esp15, and CAK in patients with short survival time.

Negative subtraction hybridization: an efficient method to isolate large numbers of condition-specific cDNAs

Background

The construction of cDNA libraries is a useful tool to understand gene expression in organisms under different conditions, but random sequencing of unbiased cDNA collections is laborious and can give rise to redundant EST collections.

We aimed to isolate cDNAs of messages induced by switching Aspergillus nidulans from growth on glucose to growth on selected polysaccharides. Approximately 4,700 contigs from 12,320 ESTs were already available from a cDNA library representing transcripts isolated from glucose-grown A. nidulans during asexual development. Our goals were to expand the cDNA collection without repeated sequencing of previously identified ESTs and to find as many transcripts as possible that are specifically induced in complex polysaccharide metabolism.

Results

We have devised a Negative Subtraction Hybridization (NSH) method and tested it in A. nidulans. NSH entails screening a plasmid library made from cDNAs prepared from cells grown under a selected physiological condition with labeled cDNA probes prepared from another physiological condition. Plasmids with inserts that failed to hybridize to cDNA probes through two rounds of screening (i.e. negatives) indicate that they are transcripts present at low concentration in the labeled probe pool. Thus, these transcripts will be predominantly condition-specific, along with some rare transcripts.

In a screen for transcripts induced by switching the carbon source from glucose to 12 selected polysaccharides, 3,532 negatives were isolated from approximately 100,000 surveyed colonies using this method. Negative clones were end-sequenced and assembled into 2,039 contigs, of which 1,722 were not present in the previously characterized glucose-grown cDNA library. Single-channel microarray hybridization experiments confirmed that the majority of the negatives represented genes that were differentially induced by a switch from growth in glucose to one or more of the polysaccharides.

Conclusions

The Negative Subtraction Hybridization method described here has several practical benefits. This method can be used to screen any existing cDNA library, including full-length and pooled libraries, and does not rely on PCR or sequence information. In addition, NSH is a cost-effective method for the isolation of novel, full-length cDNAs for differentially expressed transcripts or enrichment of rare transcripts.

Molecular analysis of metastasis in a polyomavirus middle T mouse model: the role of osteopontin

INTRODUCTION

In order to study metastatic disease, we employed the use of two related polyomavirus middle T transgenic mouse tumor transplant models of mammary carcinoma (termed Met and Db) that display significant differences in metastatic potential.

METHODS

Through suppression subtractive hybridization coupled to the microarray, we found osteopontin (OPN) to be a highly expressed gene in the tumors of the metastatic mouse model, and a lowly expressed gene in the tumors of the lowly metastatic mouse model. We further analyzed the role of OPN in this model by examining sense and antisense constructs using in vitro and in vivo methods.

RESULTS

With in vivo metastasis assays, the antisense Met cells showed no metastatic tumor formation to the lungs of recipient mice, while wild-type Met cells, with higher levels of OPN, showed significant amounts of metastasis. The Db cells showed a significantly reduced metastasis rate in the in vivo metastasis assay as compared with the Met cells. Db cells with enforced overexpression of OPN showed elevated levels of OPN but did not demonstrate an increase in the rate of metastasis compared with the wild-type Db cells.

CONCLUSIONS

We conclude that OPN is an essential regulator of the metastatic phenotype seen in polyomavirus middle T-induced mammary tumors. Yet OPN expression alone is not sufficient to cause metastasis. These data suggest a link between metastasis and phosphatidylinositol-3-kinase-mediated transcriptional upregulation of OPN, but additional phosphatidylinositol-3-kinase-regulated genes may be essential in precipitating the metastasis phenotype in the polyomavirus middle T model.

Transcriptional profiling of epidermal keratinocytes: comparison of genes expressed in skin, cultured keratinocytes, and reconstituted epidermis, using large DNA microarrays

Epidermal keratinocytes are complex cells that create a unique three-dimensional (3-D) structure, differentiate through a multistage process, and respond to extracellular stimuli from nearby cells. Consequently, keratinocytes express many genes, i.e., have a relatively large "transcriptome." To determine which of the expressed genes are innate to keratinocytes, which are specific for the differentiation and 3-D architecture, and which are induced by other cell types, we compared the transcriptomes of skin from human subjects, differentiating 3-D reconstituted epidermis, cultured keratinocytes, and nonkeratinocyte cell types. Using large oligonucleotide microarrays, we analyzed five or more replicates of each, which yielded statistically consistent data and allowed identification of the differentially expressed genes. Epidermal keratinocytes, unlike other cells, express many proteases and protease inhibitors and genes that protect from UV light. Skin specifically expresses a higher number of receptors, secreted proteins, and transcription factors, perhaps influenced by the presence of nonkeratinocyte cell types. Surprisingly, mitochondrial proteins were significantly suppressed in skin, suggesting a low metabolic rate. Three-dimensional samples, skin and reconstituted epidermis, are similar to each other, expressing epidermal differentiation markers. Cultured keratinocytes express many cell-cycle and DNA replication genes, as well as integrins and extracellular matrix proteins. These results define innate, architecture-specific, and cell-type-regulated genes in epidermis.

Customized cDNA microarray for expression profiling of environmentally important genes of Pseudomonas stutzeri strain KC

DNA microarray is a powerful tool for parallel detection of multiple target genes in biological systems. In this study, a low-density DNA microarray has been custom designed by using Pseudomonas stutzeri strain KC ORFs that are implicated in carbon tetrachloride degradation. PCR amplified strain KC probes of varying lengths were obtained using ORF-specific primers. Purified short probes (80-120 bp) and full-length amplicons were directly immobilized on gamma-aminosilane coated and superaldehyde trade mark glass substrates without any chemical modification. The full-length amplicons exhibited a much higher signal compared to the shorter probes upon hybridization with the Cy5/Cy3-labeled unfragmented cDNA targets. The meager signal with the shorter probes limits the advantage of using the multiple probes of the same genes for enhancing the specificity of hybridization with environmental samples. Nevertheless, expression analysis of strain KC genome, under controlled laboratory conditions, revealed the constitutive expression of at least 11 putative ORFs of the pdt operon. Comparatively weaker hybridization signals with the cDNA from mutant cells suggested a low abundance of mRNA transcripts in the KC 1896 mutant. Similar expression levels of the pdt ORFs I, J, K, M, N, O, P, and fur gene both under iron-limiting conditions and in presence of iron (20 micro M Fe(3+)) suggested metal ion-independent regulation of the pdt operon. The tailor-made array with strain KC gene-specific probes served as a model for demonstrating the utility of cDNA microarray technology in monitoring the expression of environmentally important genes in bacteria.

Gene expression changes in an in vitro model of chondroinduction: a comparison of two methods

There are many useful technologies to describe patterns of gene expression that occur during tissue repair and regeneration. Results from different methods used in one experimental setting are not often compared. In this case study of chondrogenesis, we compare two methods to identify differentially expressed genes, representational difference analysis and targeted macroarray analysis, as a model for investigating genes that may be relevant to tissue repair. We sought to identify genes whose expression was altered when human dermal fibroblasts were cultured in a three-dimensional, porous collagen sponge with the chondroinductive agent, demineralized bone. Both representational difference analysis and macroarray experiments revealed several functional families of genes as up-regulated or down-regulated in chondroinduced fibroblasts. An advantage of representational difference analysis is that altered expression of specific mRNA transcripts can be revealed. In this example, representational difference analysis uncovered the up-regulation of a specific transcript of Wnt5a in fibroblasts cultured with demineralized bone. Representational difference analysis is limited, however, as there can be false negatives for genes not readily amplified by polymerase chain reaction. We conclude that small arrays containing functional classes of genes can be used to ask specific, hypothesis-driven questions at minimal cost. It may be prudent, however, to use more than one method to survey differences in gene expression in order to validate and expand findings.

Shotgun sequencing and microarray analysis of RDA transcripts

Monitoring of differential gene expression is an important step towards understanding of gene function. We describe a comparison of the representational difference analysis (RDA) subtraction process with corresponding microarray analysis. The subtraction steps are followed in a quantitative manner using a shotgun cloning and sequencing procedure that includes over 1900 gene sequences. In parallel, the enriched transcripts are spotted onto microarrays facilitating large scale hybridization analysis of the representations and the difference products. We show by the shotgun procedure that there is a high diversity of gene fragments represented in the iterative RDA products (92-67% singletons) with a low number of shared sequences (<9%) between subsequent subtraction cycles. A non redundant set of 1141 RDA clones were immobilized on glass slides and the majority of these clones (97%) gave repeated good fluorescent signals in a subsequent hybridization of the labelled and amplified original cDNA. We observed only a low number of false positives (<2%) and a more than twofold differential expression for 32% (363) of the immobilized RDA clones. In conclusion, we show that by random sequencing of the difference products we obtained an accurate transcript profile of the individual steps and that large-scale confirmation of the obtained transcripts can be achieved by microarray analysis.

Modulation of GdCl3 and Angelica Sinensis polysaccharides on differentially expressed genes in liver of hepatic immunological injury mice by cDNA microarray

AIM: To study the modulating effect of GdCl₃ and Angelica Sinensis polysaccharides (ASP) on differentially expressed genes in liver of hepatic immunological mice by cDNA microarray.

METHODS: Hepatic immunological injury was induced by lipopolysaccharide (LPS ip, 0.2 mg·kg^-1) in bacillus calmetteguerin (BCG ip, 1 mg·kg^-1) primed mice; A single dose of 20 mg·kg^-1 GdCl₃ was simultaneously pretreated and 30 mg·kg^-1 ASP (ig, qd × 7 d) was administrated when the BCG+LPS was primed. The mice were sacrificed at the end of the 7^th day after ip LPS for 6 h and the liver was removed quickly. The PCR products of 512 genes were spotted onto a chemical material-coated glass plate in array. The DNAs were fixed to the glass plate after series of treatments. The total RNAs were isolated from the liver tissue, and were purified to mRNAs by Oligotex. Both mRNAs from the normal liver tissue and the liver tissue from the mice with hepatic immunological injury or that pretreated with GdCl₃ or ASP were reversely transcribed to cDNAs with the incorporation of fluorescent dUTP to prepare the hybridization probes. The mixed probes were hybridized to the cDNA microarray. After high-stringent washing, the cDNA microarray was scanned for fluorescent signals and showed differences between the two tissues.

RESULTS: Among the 512 target genes, 18 differed in liver tissue of hepatic immunological injury mice, and 6 differed in those pretreated by ASP, 7 differed in those pretreated by GdCl₃.

CONCLUSION: cDNA microarray technique is effective in screening the differentially expressed genes between two different kinds of tissue. Further analysis of those obtained genes will be helpful to understand the molecular mechanism of hepatic immunological injury and to study the intervention of drug. Both ASP and GdCl₃ can decrease the number of the differentially expressed genes in liver tissue of mice with hepatic immunological injury.

Subgenome-specific markers in allopolyploid cotton Gossypium hirsutum: implications for evolutionary analysis of polyploids

We developed a set of genetic markers specific to the A and D genome types of cotton using representational difference analysis (RDA). These markers produce amplification products with genomic DNA from allotetraploid cotton Gossypium hirsutum. One of the markers is a polymorphic amplified restriction fragment (PARF) - a sequence found in both A and D genomes but differently flanked by restriction sites. Results of phylogenetic analysis of the PARF sequences from diploid cottons and from allotetraploid G. hirsutum agree with a previous observation of the interlocus concerted evolution (sequences corresponding to A and D genomes are homogenized to a D genome-type sequence). Our study shows how RDA can be used to develop genome-specific markers that can be used to study molecular evolution of allopolyploids.

Evaluation of techniques using amplified nucleic acid probes for gene expression profiling

Gene expression analyses using spotted cDNA microarrays typically require relatively large quantities of total RNA (up to 100 microg) or polyA+RNA (1-5 microg). However, samples obtained by microdissection, patient biopsies, or embryonic samples often are small and yield an insufficient amount of RNA. Methods such as linear RNA amplification by in vitro transcription (IVT) or cDNA amplification by PCR are currently being used to circumvent these limitations. In the present study, labeled probes from mouse liver and kidney were generated with two amplification methods and were analyzed in terms of reproducibility of intensity values from repeated experiments. In addition, the reliability of differential gene expression detection among the different types of amplified and non-amplified probes was assessed. Data derived from IVT-amplified RNA, as well as from PCR-amplified cDNA probes were reproducible with correlation coefficients of 0.89 and 0.91, respectively. 88-92% of the strongly differentially expressed genes detected with non-amplified probes were also detected as being at least two-folds differentially expressed with the amplified probes. Both the PCR-amplified probe and the IVT-amplified probe were comparable in reproducibility and reliability.

Application of genomics and proteomics for study of the integrated response to zinc exposure in a non-model fish species, the rainbow trout

The advent of DNA array technology and proteomics has revolutionised biology by allowing global analysis of cellular events. So far, the benefits from these new techniques have primarily been realised for well-characterised species. These organisms are rarely the most relevant for environmental biology and ecotoxicology. Thus, there is a need to explore new ways to exploit transcriptomics and proteomics for non-model species. In the present study, rainbow trout (Oncorhynchus mykiss) were exposed to a sublethal concentration of waterborne zinc for up to 6 days. The response in gill tissue was investigated by differential screening of a heterologous cDNA array and by protein profiling using Surface Enhanced Laser Desorption/Ionisation (SELDI). The cDNA array, which was a high-density spotted library of cDNA from Fugu rubripes gill, revealed differentially expressed genes related to energy production, protein synthesis, paracellular integrity, and inflammatory response. SELDI analysis yielded seven proteins that were consistently present only in zinc-exposed gills, and four proteins unique to gills from control fish. A further 11 proteins were differentially regulated. Identification of these proteins by bioinformatics proved difficult in spite of detailed information on molecular mass, charge and zinc-binding affinity. It is concluded that these approaches are viable to non-model species although both have clear limitations.

Novel candidate tumor marker genes for lung adenocarcinoma

Using the representational difference analysis (RDA) technique on pooled mRNA of five primary lung adenocarcinomas and their corresponding non-neoplastic lung tissues, we identified six genes that were putatively overexpressed in this type of lung cancer. Five corresponded to previously isolated genes, while one (Lc19) matched with the sequence of an unannotated EST. Real-time RT-PCR analyses of expression levels in a panel of 34 paired primary non-small cell lung cancer (NSCLC) and corresponding grossly normal appearing lung tissues confirmed the common overexpression of these genes in non-small cell lung cancer. Among these genes, overexpression of Lc19, hyaluronan binding protein 2 (HABP2) and crystalline-mu appeared more specific to adenocarcinoma, whereas ceruloplasmin, integrin alpha-11 and collagen type XI alpha 1 were overexpressed at high frequency among both adenocarcinoma and squamous cell carcinoma. These genes represent novel candidate tumor biomarker genes for NSCLC and its histological subtypes.

cDNA microarray analysis of vestibular schwannomas

BACKGROUND

Vestibular schwannomas are known to harbor mutations in the neurofibromatosis type 2 tumor suppressor gene, but the mechanism of the neurofibromatosis type 2 tumor suppressor gene action is not well understood. Identification of genes differentially expressed in normal and diseased tissues through the use of a large-scale, cDNA microarray approach may lead to increased understanding of pathways that lead to tumor formation.

OBJECTIVE

The objectives of this study were to evaluate the gene expression profiles in vestibular schwannomas in comparison with normal vestibular nerve tissues and to identify pathways that may be altered in schwannomas.

METHODS

Total RNA was extracted from one normal vestibular nerve and seven vestibular schwannomas. The normal vestibular nerve was from one of the seven patients with small vestibular schwannomas. Radiolabeled cDNA was synthesized and hybridized to cDNA microarray filters that contained 25,920 known genes or expressed sequence tags. Expression profiles were imaged and analyzed. Selected genes that showed three-fold or greater difference in the intensity between the normal nerve and the schwannomas were further examined by real-time polymerase chain reaction and by immunohistochemical staining.

RESULTS

Forty-two genes (0.2%) were upregulated 3-fold or more in at least 5 of the 7 tumors when the filter images were compared with a normal adjacent vestibular nerve. Among them, osteonectin, an angiogenesis mediator, and RhoB GTPase, which is important in cell signaling, were significantly upregulated in 5 of 7 tumors. Among genes that were downregulated, an apoptosis-related LUCA-15 gene was highly underexpressed in 6 of 7 schwannomas when compared with the normal nerve. Also, ezrin, a relative of the NF2 protein, was significantly downregulated in 5 of 7 tumors. Real-time PCR and immunohistochemistry data support the cDNA microarray findings.

CONCLUSION

Our cDNA microarray analysis of schwannomas suggested several interesting and potentially important tumorigenesis pathways associated with vestibular schwannoma formation. Further in vivo study is necessary to define the roles of these identified genes and their potential relationships with the neurofibromatosis type 2 tumor suppressor gene.

Monitoring gene expression profile changes in bladder transitional cell carcinoma using cDNA microarray

PURPOSE

Differential gene expression profiles between normal bladder mucosas and bladder transitional cell carcinomas TCC were detected.

MATERIALS AND METHODS

cDNA microarrays were prepared by spotting PCR products of 12,800 human genes onto specially treated glass slides. The cDNA probes were prepared by labeling normal bladder mucosa mRNA and TCC tissue mRNA with Cy3-dUTP and Cy5-dUTP respectively through reverse transcription. The arrays were then hybridized against the cDNA probe mixture and the fluorescent signals were scanned. The ratios of Cy5/Cy3 were computed. Northern analysis was used to confirm the results of microarray hybridization.

RESULTS

Eighty-three genes (0.65%), whose ratios of Cy5/Cy3 were greater than 4.0 or less than 0.25, were screened out after 10 groups of hybridization. In the cancerous tissues 28 of them showed higher expression and 55 lower. Twenty-three genes are unregistered in GenBank. These differentially expressed genes are always involved in the physiological processes such as signal transduction, apoptosis and cell cycle, etc.

CONCLUSIONS

This technique provides a powerful method for quantitative analysis of the expression levels of thousands of genes in parallel, and is used to identify genes involved in TCC carcinogenesis. The data obtained by this means are comparable to those obtained by other methods. Using cDNA microarrays to define alterations in gene expression associated with a specific cancer may be an efficient way to uncover the clues to specific molecular derangements that account for its pathogenesis and thus identify potential targets for therapeutic intervention.

Manufacturing DNA microarrays from unpurified PCR products

For the production of DNA microarrays from PCR products, purification of the the DNA fragments prior to spotting is a major expense in cost and time. Also, a considerable amount of material is lost during this process and contamination might occur. Here, a protocol is presented that permits the manufacture of microarrays from unpurified PCR products on aminated surfaces such as glass slides coated with the widely used poly(L-lysine) or aminosilane. The presence of primer molecules in the PCR sample does not increase the non-specific signal upon hybridisation. Overall, signal intensity on arrays made of unpurified PCR products is 94% of the intensity obtained with the respective purified molecules. This slight loss in signal, however, is offset by a reduced variation in the amount of DNA present at the individual spot positions across an array, apart from the considerable savings in time and cost. In addition, a larger number of arrays can be made from one batch of amplification products.

Nuclei and subnuclei gene expression profiling in mammalian brain

Information on the neuroanatomical expression of a given gene is critical to understanding its function in the central nervous system. The integration of laser capture microdissection (LCM), T7-based RNA amplification and cDNA microarrays allows for this information to be simultaneously generated for thousands of genes. To validate this integrative approach, we catalogued the gene expression profiles of seven rat brain nuclei or subnuclei. A hundred cells from the following seven brain nuclei were analyzed: locus coeruleus (LC), dorsal raphe nucleus (DR), parvocellular division (PA) and magnocellular division (MG) of the hypothalamic paraventricular nucleus (PVN) and CA1, CA3 and dentate gyrus (DG) divisions of the hippocampal formation. Of the 2145 genes investigated, 1402 genes (65%) gave a hybridization signal statistically different from the background level that was defined by non-specific hybridizations to 15 different plant genes. Validation of our microarray data on four arbitrarily selected genes was confirmed by Real-Time PCR. Previous research showing expression patterns of 'signature' genes (n=17) for specific brain nuclei are consistent with our findings. For example, as previously shown, enriched mRNA expression encoding the serotonin transporter or tyrosine hydroxylase was found in DR and LC cells, respectively. Interestingly, expression of the serotonin 5-HT(2B) receptor mRNA was also found in DR cells. We confirmed this new finding by in-situ hybridization. The hierarchical clustering analysis of gene expression shows that the two divisions of the PVN (PA and MG) are closely related to each other, as well as the three regions of the hippocampal formation (CA1, CA3 and DG), which also showed similar gene expression profiles. This study demonstrates the importance, feasibility and utility of cellular brain nuclei profiling.

The implications of microarray technology for animal use in scientific research

Microarray technology has the potential to affect the number of laboratory animals used, the severity of animal experiments, and the development of non-animal alternatives in several areas scientific research. Microarrays can contain hundreds or thousands of microscopic spots of DNA, immobilised on a solid support, and their use enables global patterns of gene expression to be determined in a single experiment. This technology is being used to improve our understanding of the operation of biological systems during health and disease, and their responses to chemical insults. Although it is impossible to predict with certainty any future trends regarding animal use, microarray technology might not initially reduce animal use, as is often claimed to be the case. The accelerated pace of research as a result of the use of microarrays could increase overall animal use in basic and applied biological research, by increasing the numbers of interesting genes identified for further analysis, and the number of potential targets for drug development. Each new lead will require further evaluation i n studies that could involve animals. In toxicity testing, microarray studies could lead to increases in animal studies, if further confirmatory and other studies are performed. However, before such technology can be used more extensively, several technical problems need to be overcome, and the relevance of the data to biological processes needs to be assessed. Were microarray technology to be used in the manner envisaged by its protagonists, there need to be efforts to increase the likelihood that its application will create new opportunities for reducing, refining and replacing animal use. This comment is a critical assessment of the possible implications of the application of microarray technology on animal experimentation in various research areas, and makes some recommendations for maximising the application of the Three Rs.

Molecular characterization of prostate hyperplasia in prolactin-transgenic mice by using cDNA representational difference analysis

BACKGROUND

Transgenic mice overexpressing the rat prolactin (PRL) gene develop a dramatic enlargement of the prostate gland. The objective of this study was to characterize the molecular mechanisms in the prostate of importance for the prostate hyperplasia seen in these transgenic mice.

METHODS

cDNA representational difference analysis (cDNA RDA) was used to isolate differentially expressed transcripts in the prostate hyperplasia of the transgenic mice compared with wildtype littermates. Furthermore, cDNA microarray analysis was used to verify the RDA output.

RESULTS

Here we report 10 transcripts, some of them described to be involved in proliferation and apoptosis, which are differentially expressed in the enlarged transgenic prostates compared with controls.

CONCLUSION

The identified differentially expressed transcripts presented herein supports molecular similarities between the prostate hyperplasia of PRL-transgenic mice and human BPH that may contribute to explain the molecular basis of prostate hyperplasia.

Differential display in the time of microarrays

A brief overview of major methods used for genome-wide expression profiling is presented. Special attention is devoted to ordered differential display, subtractive hybridization and DNA microarrays. Future prospects of comparative gene expression studies using combinations of differential display methods and microarray technology are outlined.

Adhesive mechanisms regulating invasion and metastasis in oral cancer

It is the relentless invasion and growth into surrounding tissue that characterize oral squamous cell carcinoma. Metastasis is perhaps the most challenging and important aspect of cancer progression, in that it generally signifies limited survival and ineffective therapy. Inherent in metastasis is invasion, the process by which cells infiltrate into adjacent tissues, degrading basement membranes and extracellular matrix and disrupting tissue architecture and sometimes organ function. The factors that regulate these processes are complex and likely involve loss of the controls that are normally in place in physiologic tissue modeling. Adhesion receptors and their ligands are important in modulating not only invasion of oral squamous cell carcinoma cells but also their survival and proliferation. Normal oral mucosal epithelial cells use integrins to maintain their anchorage to the basement membrane, whereas the formation of stratifying cell layers depends on the formation of intercellular adhesions mediated by cadherins. The process of squamous cell carcinoma invasion and dissemination requires active cell migration through the extracellular matrix with the simultaneous remodeling of intercellular adhesions. Integrins are clearly important in the invasive process, whereas intercellular adhesion receptors restrain invasion and promote a more differentiated phenotype.

Comprehensive gene expression analysis by transcript profiling

After the completion of the genomic sequence of Arabidopsis thaliana, it is now a priority to identify all the genes, their patterns of expression and functions. Transcript profiling is playing a substantial role in annotating and determining gene functions, having advanced from one-gene-at-a-time methods to technologies that provide a holistic view of the genome. In this review, comprehensive transcript profiling methodologies are described, including two that are used extensively by the authors, cDNA-AFLP and cDNA microarraying. Both these technologies illustrate the requirement to integrate molecular biology, automation, LIMS and data analysis. With so much uncharted territory in the Arabidopsis genome, and the desire to tackle complex biological traits, such integrated systems will provide a rich source of data for the correlative, functional annotation of genes.

DNA microarrays for functional plant genomics

DNA microarray technology is a key element in today's functional genomics toolbox. The power of the method lies in miniaturization, automation and parallelism permitting large-scale and genome-wide acquisition of quantitative biological information from multiple samples. DNA microarrays are currently fabricated and assayed by two main approaches involving either in situ synthesis of oligonucleotides ('oligonucleotide microarrays') or deposition of pre-synthesized DNA fragments ('cDNA microarrays') on solid surfaces. To date, the main applications of microarrays are in comprehensive, simultaneous gene expression monitoring and in DNA variation analyses for the identification and genotyping of mutations and polymorphisms. Already at a relatively early stage of its application in plant science, microarrays are being utilized to examine a range of biological issues including the circadian clock, plant defence, environmental stress responses, fruit ripening, phytochrome A signalling, seed development and nitrate assimilation. Novel insights are obtained into the molecular mechanisms co-ordinating metabolic pathways, regulatory and signalling networks. Exciting new information will be gained in the years to come not only from genome-wide expression analyses on a few model plant species, but also from extensive studies of less thoroughly studied species on a more limited scale. The value of microarray technology to our understanding of living processes will depend both on the amount of data to be generated and on its clever exploration and integration with other biological knowledge arising from complementary functional genomics tools for 'profiling' the genome, proteome, metabolome and phenome.