Skin biopsies for the measurement of clinical pharmacodynamic biomarkers

The integration of biomarkers reporting on drug pharmacodynamics or on a disease state is becoming necessary in the cost-effective design of clinical trials. Transcriptional changes in skin measured using whole-genome arrays have been useful in assessing the disease state in dermatology. Not only are skin biopsies well-tolerated and easy to obtain, but they sample a system in which many complex signaling and developmental networks are active and in which a wide variety of drug targets may be expected to play a role, either directly or indirectly. Recent advances have led to the use of transcriptional profiling of skin for making pharmacodynamic measurements in clinical trials, even for non-dermatological conditions.

Exploiting naturally occurring DNA variation and molecular profiling data to dissect disease and drug response traits

Identifying the key drivers of common human diseases and associated signaling pathways remains one of the primary objectives in the biomedical and life sciences. In this respect, common inbred strains of mice have played a crucial role, and recent advances in the development of genomics and bioinformatics tools have significantly enhanced their utility for this purpose. These advances have enabled a more holistic, network-oriented view of biological systems that facilitates elucidation of the underlying causes of disease and the best ways to target them. Success in reconstructing gene networks underlying disease traits (or other complex traits like drug response) and identifying the key drivers of these traits now largely rests on integrative approaches that combine data from multiple different sources. Such integrative genomics approaches that take into account genotypic, molecular profiling and clinical data in segregating mouse populations have recently been developed. Key to this integration has been the development and application of sophisticated algorithms to mine the diversity of data.

Emerging concepts in glioma biology: implications for clinical protocols and rational treatment strategies

Glioblastoma multiforme (GBM), the most common primary central nervous system neoplasm, is a complex, heterogeneous disease. The recent identification of stem cells in murine tumor xenografts that were capable of recapitulating the tumor phenotype adds a new dimension of complexity to the already challenging treatment of patients with GBMs. Although specific cellular and genetic changes are commonly associated with GBM, the mechanism by which those changes occur may have a significant impact on treatment outcome. Of the many bioinformatics techniques developed in recent years, gene expression profiling has become a commonly used research tool for investigating tumor characteristics, and the development of rationally targeted molecular therapies has also accelerated following the initial success of specifically designed inhibitors in the treatment of malignancies. Despite these advances in research techniques and targeted molecular therapies, however, limited clinical impact has been achieved in the treatment of infiltrative malignancies such as GBMs. Thus, further extension in survival of patients with GBMs may require use of multiple analyses of tumors to develop tailored therapies that reflect the inter- and intratumoral heterogeneity of this disease. In this review, the authors briefly consider the potential use of expression profiling combined with mutation analysis in the development of treatment modalities to address the heterogeneity of this complex tumor phenotype.

Cell-based therapies and imaging in cardiology

Cell therapy for cardiac repair has emerged as one of the most exciting and promising developments in cardiovascular medicine. Evidence from experimental and clinical studies is increasing that this innovative treatment will influence clinical practice in the future. But open questions and controversies with regard to the basic mechanisms of this therapy continue to exist and emphasise the need for specific techniques to visualise the mechanisms and success of therapy in vivo. Several non-invasive imaging approaches which aim at tracking of transplanted cells in the heart have been introduced. Among these are direct labelling of cells with radionuclides or paramagnetic agents, and the use of reporter genes for imaging of cell transplantation and differentiation. Initial studies have suggested that these molecular imaging techniques have great potential. Integration of cell imaging into studies of cardiac cell therapy holds promise to facilitate further growth of the field towards a broadly clinically useful application.

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.

Functional genomics may allow accurate categorization of the benzimidazole fungicide benomyl: lack of ability to act via steroid-receptor-mediated mechanisms

Although benomyl and its metabolite carbendazim have been shown to adversely affect male reproduction, the mechanisms of action do not appear to involve the endocrine system. However, few studies have been conducted using currently proposed tests specifically focused on endocrine disruption. Here, potential estrogen- and androgen-mediated activity of benomyl was therefore investigated in vitro and in vivo. Benomyl and carbendazim proved negative for agonistic and antagonistic activity in reporter gene assays for the human estrogen receptor alpha and androgen receptor. In uterotrophic and Hershberger assays using Crj:CD(SD)IGS rats, benomyl (100, 300 or 1000 mg/kg/day, p.o., N = 6) did not exert agonistic effects. However, the highest dose decreased uterine weights in the uterotrophic assay, and decreased weights of some androgen-related tissues of castrated rats receiving a testosterone propionate (TP, 0.2 mg/kg) injection in the Hershberger assay; the effects were less severe than those with p,p'-DDE (100 mg/kg/day). When 4 mg/kg/day of TP was injected, decrease of organ weights due to benomyl was attenuated but still observed. Thus, its influence in some tissues was more potent than that of p,p'-DDE. Benomyl had no apparent effects on serum androgen levels. Microarray analysis of the gene expression profile in the ventral prostate of TP-injected castrated rats treated with benomyl indicated clear differences from the patterns observed with p,p'-DDE and flutamide. Taken together, these findings suggest the decreased organ weights observed in vivo to be caused by mechanisms that are not steroid-receptor-mediated, such as interfering with assembly of microtubules by benomyl. The study furthermore suggests that functional genomics may provide a reliable evidence for accurate categorization of test chemicals.

Proteomics and the analysis of proteomic data: an overview of current protein-profiling technologies

In recent years, several proteomic methodologies have been developed that now make it possible to identify, characterize, and comparatively quantify the relative level of expression of hundreds of proteins that are coexpressed in a given cell type or tissue, or that are found in biological fluids such as serum. These advances have resulted from the integration of diverse scientific disciplines including molecular and cellular biology, protein/peptide chemistry, bioinformatics, analytical and bioanalytical chemistry, and the use of instrumental and software tools such as multidimensional electrophoretic and chromatographic separations and mass spectrometry. In this unit, some of the common protein-profiling technologies are reviewed, along with the accompanying data-analysis tools.

Bacterial proteomics and its role in antibacterial drug discovery

Gene-expression profiling technologies in general, and proteomic technologies in particular have proven extremely useful to study the physiological response of bacterial cells to various environmental stress conditions. Complex protein toolkits coordinated by sophisticated regulatory networks have evolved to accommodate bacterial survival under ever-present stress conditions such as varying temperatures, nutrient availability, or antibiotics produced by other microorganisms that compete for habitat. In the last decades, application of man-made antibacterial agents resulted in additional bacterial exposure to antibiotic stress. Whereas the targeted use of antibiotics has remarkably reduced human suffering from infectious diseases, the ever-increasing emergence of bacteria that are resistant to antibiotics has led to an urgent need for novel antibiotic strategies. The intent of this review is to present an overview of the major achievements of proteomic approaches to study adaptation networks that are crucial for bacterial survival with a special emphasis on the stress induced by antibiotic treatment. A further focus will be the review of the, so far few, published efforts to exploit the knowledge derived from bacterial proteomic studies directly for the antibacterial drug-discovery process.

Proteome analysis in the study of lymphoma cells

This review provides an overview on recent studies in the field of proteome analysis of lymphoma cells, and highlights the potentials of such studies for a better knowledge of drug effects at the molecular level. After giving general information on the field of proteome analysis of lymphoma cells, some characteristics of the strategies used during this analysis are pointed out, such as cell extraction strategies and affinity captures. Therefore, the issue of proteome analysis of lymphoma cells content will be covered with respect to those protein extracts that can be prepared in saline solutions, such as cytoplasm proteins, or that are associated with the cell membranes. The question of which kinds of information have been retrieved from lymphoma-cell proteomics is discussed on the basis of several examples-lymphoma cell-mapping studies and constitution of protein databases, and comparative proteome analysis studies of the modifications that result from a drug treatment.

Applications of DNA tiling arrays for whole-genome analysis

DNA microarrays are a well-established technology for measuring gene expression levels. Microarrays designed for this purpose use relatively few probes for each gene and are biased toward known and predicted gene structures. Recently, high-density oligonucleotide-based whole-genome microarrays have emerged as a preferred platform for genomic analysis beyond simple gene expression profiling. Potential uses for such whole-genome arrays include empirical annotation of the transcriptome, chromatin-immunoprecipitation-chip studies, analysis of alternative splicing, characterization of the methylome (the methylation state of the genome), polymorphism discovery and genotyping, comparative genome hybridization, and genome resequencing. Here we review different whole-genome microarray designs and applications of this technology to obtain a wide variety of genomic scale information.

Functional Genomics meets neurodegenerative disorders

Transcriptomics and proteomics are increasingly applied to gain a mechanistic insight into neurodegenerative disorders. These techniques not only identify distinct, differentially expressed mRNAs and proteins but are also employed to dissect signaling pathways and reveal networks by using an integrated approach. In part I of this back-to-back review, technical aspects are discussed: in the transcriptomics section, which includes enrichment by laser microcapture dissection, we comment on qRT-PCR, SAGE, subtractive hybridization, differential display and microarrays, including software packages. In the proteomics section we discuss two-dimensional (2D) gel electrophoresis, liquid chromatography, methods to label and enrich specific proteins or peptides, and different types of mass spectrometers. These tools have been applied to a range of neurodegenerative disorders and are discussed and integrated in part II (Functional Genomics meets neurodegenerative disorders. Part II: application and data integration).

Functional Genomics meets neurodegenerative disorders

The transcriptomic and proteomic techniques presented in part I (Functional Genomics meets neurodegenerative disorders. Part I: transcriptomic and proteomic technology) of this back-to-back review have been applied to a range of neurodegenerative disorders, including Huntington's disease (HD), Prion diseases (PrD), Creutzfeldt-Jakob disease, amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), frontotemporal dementia (FTD) and Parkinson's disease (PD). Samples have been derived either from human brain and cerebrospinal fluid, tissue culture cells or brains and spinal cord of experimental animal models. With the availability of huge data sets it will firstly be a major challenge to extract meaningful information and secondly, not to obtain contradicting results when data are collected in parallel from the same source of biological specimen using different techniques. Reliability of the data highly depends on proper normalization and validation both of which are discussed together with an outlook on developments that can be anticipated in the future and are expected to fuel the field. The new insight undoubtedly will lead to a redefinition and subdivision of disease entities based on biochemical criteria rather than the clinical presentation. This will have important implications for treatment strategies.

Gene expression-driven diagnostics and pharmacogenomics in cancer

The advancement of microarray technologies for characterizing tumors at the gene expression level has made a significant impact on the field of oncology. Profiling gene expression of various human tumors has led to the identification of gene expression patterns or signatures related to tumor classification, disease outcome and response to therapy. This technology can also be used to study the mechanism of action of specific therapeutics. Routine application of microarrays in clinical practice will require significant efforts to standardize the array manufacturing techniques, assay protocols and analytical methods used to interpret the data. Extensive, independent validation using large, statistically sound datasets will also be necessary. Studies on gene expression profiling of clinically relevant tissue samples with the aim of finding gene markers to support disease prognosis and therapy decisions are reviewed.

Where are we in genomics?

Genomic studies provide scientists with methods to quickly analyse genes and their products en masse. The first high-throughput techniques to be developed were sequencing methods. A great number of genomes from different organisms have thus been sequenced. Genomics is now shifting to the study of gene expression and function. In the past 5-10 years genomics, proteomics and high-throughput microarray technologies have fundamentally changed our ability to study the molecular basis of cells and tissues in health and diseases, giving a new comprehensive view. For example, in cancer research we have seen new diagnostic opportunities for tumour classification, and prognostication. A new exciting development is metabolomics and lab-on-a-chip techniques (which combine miniaturization and automation) for metabolic studies. However, to interpret the large amount of data, extensive computational development is required. In the coming years, we will see the study of biological networks dominating the scene in Physiology. The great accumulation of genomics information will be used in computer programs to simulate biologic processes. Originally developed for genome analysis, bioinformatics now encompasses a wide range of fields in biology from gene studies to integrated biology (i.e. combination of different data sets from genes to metabolites). This is systems biology which aims to study biological organisms as a whole. In medicine, scientific results and applied biotechnologies arising from genomics will be used for effective prediction of diseases and risk associated with drugs. Preventive medicine and medical therapy will be personalized. Widespread applications of genomics for personalized medicine will require associations of gene expression pattern with diagnoses, treatment and clinical data. This will help in the discovery and development of drugs. In agriculture and animal science, the outcomes of genomics will include improvement in food safety, in crop yield, in traceability and in quality of animal products (dairy products and meat) through increased efficiency in breeding and better knowledge of animal physiology. Genomics and integrated biology are huge tasks and no single lab can pursue this alone. We are probably at the end of the beginning rather than at the beginning of the end because Genomics will probably change Biology to a greater extent than previously forecasted. In addition, there is a great need for more information and better understanding of genomics before complete public acceptance.

Current efforts in the analysis of RNAi and RNAi target genes

RNAi is RNA interference by short RNAs. It influences gene-expression by down-regulation of mRNAs, typically by complementarity to the 3' UTR (untranslated region) of the mRNA. microRNAs (miRNAs) are short RNAs acting as natural RNAi. miRNAs mediate down-regulation of many mRNAs from developmental genes and transcription factor genes. Natural examples for this additional level of post-transcriptional control are increasing. Suitable computer-based search strategies for new miRNA candidates include precursor folding as well as different compositional search strategies. Example programs for this are presented. New own and other data are provided for an overview on such strategies. A strategy feasible in plants for miRNA target identification is direct base pairing of miRNAs to potential mRNA target 3' UTRs. Correct identification in animals usually requires comparative genomics and conserved UTR regions pairing to conserved miRNA substructures. A number of example programs and target examples for these tasks are examined. Finally, strategies and programs for artificial gene silencing by designed RNAi are explained.

DNA microarrays: from structural genomics to functional genomics. The applications of gene chips in dermatology and dermatopathology

The human genome project was successful in sequencing the entire human genome and ended earlier than expected. The vast genetic information now available will have far-reaching consequences for medicine in the twenty-first century. The knowledge gained from the mapping and sequencing of human genes on a genome-wide scale--commonly referred to as structural genomics--is prerequisite for studies that focus on the functional aspects of genes. A recently invented technique, known as gene chip, or DNA microarray, technology, allows the study of the function of thousands of genes at once, thereby opening the door to the new field of functional genomics. At its core, the DNA microarray utilizes a unique feature of DNA known as complementary hybridization. As such, it is not different from Southern (DNA) blot or northern (RNA) blot hybridizations, or the polymerase chain reaction, with the exception that it allows expression profiling of the entire human genome in a single hybridization experiment. The article highlights the principles, technology, and applications of DNA microarrays as they pertain to the field of dermatology and dermatopathology. The most important applications are the gene expression profiling of skin cancer, especially of melanoma. Other potential applications include gene expression profiling of inflammatory skin diseases, the mutational analysis of genodermatoses, and polymorphism screening, as well as drug development and chemosensitivity prediction. cDNA microarrays will shape the diagnostic approach of the dermatology and the dermatopathology of the future and may lead to new therapeutic options.

Potential of DNA microarrays for developing parallel detection tools (PDTs) for microorganisms relevant to biodefense and related research needs

Development of parallel detection tools using microarrays is critically reviewed in view of the need for screening multiple microorganisms in a single test. Potential research needs with respect to probe design and specificity, validation, sample concentration, selective target enrichment and amplification, and data analysis are discussed. Data illustrating selected probe design issues for detecting multiple targets in mixed microbial systems is presented. Challenges with respect to cost, time, and ease of use compared to other methods are also summarized.