A concise guide to cDNA microarray analysis

Transcription patterning of uncoupled proliferation and differentiation in myelodysplastic bone marrow with erythroid-focused arrays

Because abnormal erythroid differentiation is the most common manifestation of the myelodysplastic syndromes (MDS), it was hypothesized that erythroid gene expression may be used to illustrate myelodysplastic transcription patterns. Ten normal bone marrow aspirates (NBM) were first analyzed using an erythroid-focused cDNA array to define steady-state transcription levels. Proliferation and differentiation gene subsets were identified by statistically significant differences between NBM and erythroleukemia gene expression. Next, cDNAs from 5 separate MDS aspirates were studied: refractory anemia, refractory anemia with ringed sideroblasts, refractory anemia with excess blasts, refractory anemia with excess blasts in transformation (RAEB-T), and RAEB-T/secondary MDS. A distinct pattern of significantly increased proliferation-associated and reduced differentiation-associated gene activity was established for MDS.

Expression microarray hybridization kinetics depend on length of the immobilized DNA but are independent of immobilization substrate

Expression microarrays are often constructed by the immobilization of PCR products on two-dimensional modified glass slides or on three-dimensional microporous substrates. In this study we investigate whether the length of the immobilized species and the substrate choice influence hybridization dynamics. Using a simple bimolecular mass action controlled model to describe hybridization, we observed that the extent of hybridization and the initial velocities were directly dependent on the length of the immobilized species. An inflection point was noted at a length of 712 bases, above which the influence of length on hybridization rate decreased. Interestingly, we observed no differences in these parameters whether hybridization occurred on a two- or three-dimensional surface. Furthermore, the affinity of the solution phase labeled species for the immobilized species was identical for all arrayed lengths on both surfaces. These data indicate a similar interaction of the noncovalently immobilized species with either surface. Finally, we have determined that competitive hybridization on expression microarrays is nonlinear with respect to time and concentration of competitor. This observation is critical for analysis of expression array data.

Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification

To better understand the molecular mechanisms that underlie the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC), we studied the gene expression profiles of 29 ccRCC tumors obtained from patients with diverse clinical outcomes by using 21,632 cDNA microarrays. We identified gene expression alterations that were both common to most of the ccRCC studied and unique to clinical subsets. There was a significant distinction in gene expression profile between patients with a relatively nonaggressive form of the disease [100% survival after 5 years with the majority (15/17 or 88%) having no clinical evidence of metastasis] versus patients with a relatively aggressive form of the disease (average survival time 25.4 months with a 0% 5-year survival rate). Approximately 40 genes most accurately make this distinction, some of which have previously been implicated in tumorigenesis and metastasis. To test the robustness and potential clinical usefulness of this molecular distinction, we simulated its use as a prognostic tool in the clinical setting. In 96% of the ccRCC cases tested, the prediction was compatible with the clinical outcome, exceeding the accuracy of prediction by staging. These results suggest that two molecularly distinct forms of ccRCC exist and that the integration of expression profile data with clinical parameters could serve to enhance the diagnosis and prognosis of ccRCC. Moreover, the identified genes provide insight into the molecular mechanisms of aggressive ccRCC and suggest intervention strategies.

Analysis of complex brain disorders with gene expression microarrays: schizophrenia as a disease of the synapse

The level of cellular and molecular complexity of the nervous system creates unique problems for the neuroscientist in the design and implementation of functional genomic studies. Microarray technologies can be powerful, with limitations, when applied to the analysis of human brain disorders. Recently, using cDNA microarrays, altered gene expression patterns between subjects with schizophrenia and controls were shown. Functional data mining led to two novel discoveries: a consistent decrease in the group of transcripts encoding proteins that regulate presynaptic function; and the most changed gene, which has never been previously associated with schizophrenia, regulator of G-protein signaling 4. From these and other findings, a hypothesis has been formulated to suggest that schizophrenia is a disease of the synapse. In the context of a neurodevelopmental model, it is proposed that impaired mechanics of synaptic transmission in specific neural circuits during childhood and adolescence ultimately results in altered synapse formation or pruning, or both, which manifest in the clinical onset of the disease.

DNA microarrays in neuropsychopharmacology

Recent advances in experimental genomics, coupled with the wealth of sequence information available for a variety of organisms, have the potential to transform the way pharmacological research is performed. At present, high-density DNA microarrays allow researchers to quickly and accurately quantify gene-expression changes in a massively parallel manner. Although now well established in other biomedical fields, such as cancer and genetics research, DNA microarrays have only recently begun to make significant inroads into pharmacology. To date, the major focus in this field has been on the general application of DNA microarrays to toxicology and drug discovery and design. This review summarizes the major microarray findings of relevance to neuropsychopharmacology, as a prelude to the design and analysis of future basic and clinical microarray experiments. The ability of DNA microarrays to monitor gene expression simultaneously in a large-scale format is helping to usher in a post-genomic age, where simple constructs about the role of nature versus nurture are being replaced by a functional understanding of gene expression in living organisms.

Array-based gene expression profiling to study aging

With recent sequencing of the genome and development of high-density array technology, it is now possible to assess global gene expression in cells/tissues by a technique that is sensitive, quantitative, and rapid. Gene expression array technology is extremely useful in studying a complex, multigenetic process, such as aging, where one needs to understand the interaction of a large number of genes. Although the technology holds great promise, it is novel and not yet well-established and there are no widely-accepted standards to guide investigators in the analysis and interpretation of the data obtained. Gene expression array analysis requires strong biostatistical support to minimize false-positives and maximize true-positives in candidate gene identification. It also requires independent validation of the array measurements using other detection methods. Confirmation that differentially expressed (transcribed) genes are reflected by differential expression at the protein level will ultimately be an important measurement. In this review, we focus on the three steps necessary for aging studies when using the gene expression array technology: (1) array hybridization; (2) biostatistical analysis; and (3) array result confirmation. Genes identified by several investigators for their age-associated change using the gene expression array systems are also discussed.

Impact of laminin 5 beta3 gene versus protein replacement on gene expression patterns in junctional epidermolysis bullosa

Molecular therapy studies to date have examined only a limited number of corrective parameters. To assess more global impacts on cellular gene expression for two major molecular therapeutic approaches, we compared gene versus protein delivery in the human genetic disease junctional epidermolysis bullosa (JEB). Both gene and protein replacement of the laminin 5 beta3 (beta3) adhesion molecule restored normal growth and adhesion to poorly viable JEB cells. Gene expression profiling was then performed using cDNA microarrays. The expression of more genes was normalized after beta3 gene transfer than after protein transfer. As anticipated for beta3 delivery, many of the genes whose expression was restored to the normal range were those encoding adhesion molecules and hemidesmosome components. Although gene transfer normalized the expression of a higher percentage of genes than did protein transfer, neither approach fully normalized expression of all genes examined. In addition, both approaches disrupted the expression of some genes, but protein transfer altered expression of a larger proportion of the genes studied. Our findings suggest that therapeutic gene and protein delivery may exert different effects on gene expression and thus may have implications for the development and analysis of molecular therapies for the treatment of genetic disorders.

Computational analysis of microarray data

Microarray experiments are providing unprecedented quantities of genome-wide data on gene-expression patterns. Although this technique has been enthusiastically developed and applied in many biological contexts, the management and analysis of the millions of data points that result from these experiments has received less attention. Sophisticated computational tools are available, but the methods that are used to analyse the data can have a profound influence on the interpretation of the results. A basic understanding of these computational tools is therefore required for optimal experimental design and meaningful data analysis.

Construction of a human cardiovascular cDNA microarray: portrait of the failing heart

Identifying key genes that regulate the complex diseases of the cardiovascular system can be greatly facilitated with the use of microarrays. In an effort to obtain a global portrait of gene expression in the failing heart, we have constructed in-house a glass microscope slide cDNA microarray (termed "CardioChip") containing 10,368 redundant and randomly-selected sequenced expressed sequence tags (representing known genes, other matched ESTs, and novel, unmatched ESTs) derived from several human heart and artery cDNA libraries. From our preliminary data with Cy3- and Cy5-labeled probes, we have identified 38 transcripts showing a minimum twofold differential expression, among which are several novel or previously-uncharacterized genes. This array-representing what we believe to be the largest cardiovascular-based cDNA array to date-establishes a practical and invaluable platform for obtaining a global genetic portrait of complex cardiovascular diseases, particularly in the failing heart.

The human genome project: a historical perspective

Efforts in genomics over the last decade have created a stream of opportunities for drug discovery. High-throughput DNA sequencing has forced a re-definition of the paradigm for identification and validation of targets for drug development. One purpose of this review is to delineate the different approaches to sequence data generation and to establish their various uses for the definition of gene function. There still remain crucial dilemmas for the pharmaceutical industry. The multitude of potential targets can each absorb enormous validation costs and the vast majority are likely to prove academically interesting but useless for drug development. An additional dimension arises from the importance of sequence variation between different individuals. These differences can determine response to therapy and must inform both the drug development process and healthcare delivery. This presents great challenges and opportunities for drug companies, their customers and society as a whole. I will review the technological aspects in some detail and give my view of the legal and social aspects. The field of bioinformatics is at the core of functional and pharmacogenomics and advances will depend on the continuing evolution of tools to interpret data. For the most part this evolution is reviewed in the context of specific application areas rather than as a discrete field, in recognition of its all-pervasive effects.

DNA microarrays: raising the profile

Expression profiling using DNA microarrays is starting to come of age. The past year has seen significant advances in the number, scope and quality of studies that incorporate expression profiling experiments. Attention is starting to move on from making DNA microarrays to appropriate experimental design and sophisticated data analysis techniques.

Protein microarrays: prospects and problems

Protein microarrays are potentially powerful tools in biochemistry and molecular biology. Two types of protein microarrays are defined. One, termed a protein function array, will consist of thousands of native proteins immobilized in a defined pattern. Such arrays can be utilized for massively parallel testing of protein function, hence the name. The other type is termed a protein-detecting array. This will consist of large numbers of arrayed protein-binding agents. These arrays will allow for expression profiling to be done at the protein level. In this article, some of the major technological challenges to the development of protein arrays are discussed, along with potential solutions.

Development of a 950-gene DNA array for examining gene expression patterns in mouse testis

BACKGROUND

Over the past five years, interest in and use of DNA array technology has increased dramatically, and there has been a surge in demand for different types of arrays. Although manufacturers offer a number of pre-made arrays, these are generally of utilitarian design and often cannot accommodate the specific requirements of focused research, such as a particular set of genes from a particular tissue. We found that suppliers did not provide an array to suit our particular interest in testicular toxicology, and therefore elected to design and produce our own.

RESULTS

We describe the procedures used by members of the US Environmental Protection Agency MicroArray Consortium (EPAMAC) to produce a mouse testis expression array on both filter and glass-slide formats. The approaches used in the selection and assembly of a pertinent, nonredundant list of testis-expressed genes are detailed. Hybridization of the filter arrays with normal and bromochloroacetic acid-treated mouse testicular RNAs demonstrated that all the selected genes on the array were expressed in mouse testes.

CONCLUSION

We have assembled two lists of mouse (950) and human (960) genes expressed in the mouse and/or human adult testis, essentially all of which are available as sequence-verified clones from public sources. Of these, 764 are homologous and will therefore enable close comparison of gene expression between murine models and human clinical testicular samples.

Comprehensive genetic analysis of cancer cells

Human cancer is viewed as a disorder of genes originating from the progeny of a single cell that has accumulated multiple genetic alterations. The genetic alterations include point mutation, chromosomal rearrangements and imbalances. Amplifications primarily involve oncogenes whose overexpression leads to growth deregulation, while deletions commonly target tumor suppressor genes that control cell cycle checkpoints and DNA repair mechanisms. With the advent of molecular cytogenetics procedures for global detection of genomic imbalances and for multicolor visualization of structural chromosome changes, as well as the completion of human genome mapping and the development of microarray technology for serial gene expression analysis of the entire genomes, a significant progress has been made in uncovering the molecular basis of cancer. The major challenge in cancer biology is to decipher the molecular anatomy of various cancers and to identify cancer-related genes that now comprise only a fraction of human genes. The complete genetic anatomy of specific cancers would allow a better understanding of the role of genetic alterations in carcinogenesis, provide diagnostic and prognostic markers and discriminate between cells at different stages of progression toward malignancy. This review highlights current technologies that are available to explore cancer cells and outlines their application to investigations in human hepatocellular carcinoma.