Developing a cell line standard for HER2/neu

Advancements in medical genetics are resulting in the identification of key molecules in the pathways that lead to carcinogenesis. With these discoveries, drugs are developed that target a protein or block a particular molecular pathway with the potential to bring about disease regression. The HER2/neu tyrosine kinase receptor is one such target. Therapy based on the humanised monoclonal antibody, trastuzumab, targets HER-2/neu and inhibits the growth of HER2/neu-overexpressing breast cancer cells. Assays for markers to HER2/neu are forerunners of many more predictive assays that are likely to enter the clinical arena in the near future, many of which will require quantitative analysis. In the field of tissue based assay systems controversies are well documented on the lack of reproducibility in the immunohistochemical analysis HER2/neu. The problems encountered to date lye with the difficulty in reliably standardising the immunohistochemical assay. One of the first steps in addressing this issue is to develop a standard reference material against which the 'variable' of assay sensitivity for HER2/neu can be accurately gauged. Work in the United States and Europe aimed at providing a standard reference material for HER2/neu has already commenced. Preliminary work conducted in Europe shows that development of a standard comprised of cell lines is feasible and when employed as part of an external quality assurance programme, results in significant improvement in the numbers of clinical laboratories achieving appropriate results. In the United States it has been proposed that two standards consisting of well characterized cell lines will be produced, one a National Institute of Standards and Technology (NIST)--certifiable standard, and the other a commercially developed standard for use in all HER2/neu testing. The aim is that this approach will act as a template for other important predictive markers of the future.

Breast cancer prognostication and prediction in the postgenomic era

Expanding knowledge, together with implementation of new techniques, has fuelled the area of translational medical research aiming at improving prognostication as well as prediction in cancer therapy. At the same time, new discoveries have revealed a biological complexity we were unaware of only a decade ago. Thus, we are faced with novel challenges with respect to how we may explore issues such as prognostication and predict drug resistance in vivo. While microarray analysis exploring expression of thousands of genes in concert represents a major methodological advancement, discoveries such as the finding of different mechanisms of epigenetic silencing, intronic mutations, that most gene transcripts in the human genome are subject to alternative splicing and that hypersplicing seems to be a tumour-related phenomenon, exemplifies a complex pathology that may not be explored with use of single analytical methods only. This paper discusses clinical settings for studying drug resistance in vivo together with a discussion of contemporary biology in this field. Notably, each individual parameter which has been found correlated to drug resistance in vivo so far represents either a direct drug target or a factor involved in DNA repair or apoptosis. On the basis of these findings, we suggest drug resistance may be explored on the basis of upfront biological hypotheses.

Moving cancer diagnostics from bench to bedside

To improve treatment and reduce the mortality from cancer, a key task is to detect the disease as early as possible. To achieve this, many new technologies have been developed for biomarker discovery and validation. This review provides an overview of omics technologies in biomarker discovery and cancer detection, and highlights recent applications and future trends in cancer diagnostics. Although the present omic methods are not ready for immediate clinical use as diagnostic tools, it can be envisaged that simple, fast, robust, portable and cost-effective clinical diagnosis systems could be available in near future, for home and bedside use.

From genome to proteome in tumor profiling: molecular events in colorectal cancer genesis

Biomedical research has advanced rapidly in recent years with the sequencing of the human genome and the availability of technologies such as global gene and protein expression profiling using different chip platforms. However, this progress has not yet been transferred to the bedside. While detection of cancer at early stages is critical for curative treatment interventions, efficient diagnostic and therapeutic markers for the majority of malignancies still seem to be lacking. Comprehensive tumor profiling has therefore become a field of intensive research aiming at identifying biomarkers relevant for improved diagnostics and therapeutics. This chapter will demonstrate a genomic and proteomic approach while focusing on tumor profiling during colorectal cancer development.

The Glomerular Transcriptome and Proteome

Histopathology provides the current basis for classification and diagnosis of glomerular disorders. Molecular profiling methods, such as microarray analysis of mRNA expression, have rapidly emerged over the past years and are now applicable to minute amounts of tissue material, such as glomeruli from embryos or adult experimental animals, or from human renal needle biopsies. This review summarizes current efforts aiming at the determination of the glomerular transcriptome and proteome during development, in the healthy adult, and in disease. These studies are encouraging and show that comprehensive molecular profiling of the kidney glomerulus will most likely provide significant new insights into the normal structure and function of the glomerular filter, the molecular mechanisms of glomerular development, the diagnosis and classification of glomerular disease, and the pathogenic mechanisms underlying the stepwise breakdown of glomerular filter function that accompanies several common systemic disorders.

Development of computations in bioscience and bioinformatics and its application: review of the Symposium of Computations in Bioinformatics and Bioscience (SCBB06)

The first symposium of computations in bioinformatics and bioscience (SCBB06) was held in Hangzhou, China on June 21–22, 2006. Twenty-six peer-reviewed papers were selected for publication in this special issue of BMC Bioinformatics. These papers cover a broad range of topics including bioinformatics theories, algorithms, applications and tool development. The main technical topics contain gene expression analysis, sequence analysis, genome analysis, phylogenetic analysis, gene function prediction, molecular interaction and system biology, genetics and population study, immune strategy, protein structure prediction and proteomics.

Microbial metabolomics: past, present and future methodologies

Microbial metabolomics has received much attention in recent years mainly because it supports and complements a wide range of microbial research areas from new drug discovery efforts to metabolic engineering. Broadly, the term metabolomics refers to the comprehensive (qualitative and quantitative) analysis of the complete set of all low molecular weight metabolites present in and around growing cells at a given time during their growth or production cycle. This review focuses on the past, current and future development of various experimental protocols in the rapid developing area of metabolomics in the ongoing quest to reliably quantify microbial metabolites formed under defined physiological conditions. These developments range from rapid sample collection, instant quenching of microbial metabolic activity, extraction of the relevant intracellular metabolites as well as quantification of these metabolites using enzyme based and or modern high tech hyphenated analytical protocols, mainly chromatographic techniques coupled to mass spectrometry (LC-MS(n), GC-MS(n), CE-MS(n)), where n indicates the number of tandem mass spectrometry, and nuclear magnetic resonance spectroscopy (NMR).

Yeast as a tool to uncover the cellular targets of drugs

Knowledge of the spectrum of cellular proteins targeted by experimental therapeutic agents would greatly facilitate drug development. However, identifying the targets of drugs is a daunting challenge. The yeast Saccharomyces cerevisiae is a valuable model organism for human diseases and pathways because it is genetically tractable and shares many functional homolog with humans. In yeast, it is possible to increase or decrease the expression level of essentially every gene and measure changes in drug sensitivity to uncover potential targets. It is also possible to infer mechanism of action from comparing the changes in mRNA expression elicited by drug treatment with those induced by gene deletions or by other drugs. Proteins that bind drugs directly can be identified using yeast protein chips. This review of the use of yeast for discovering targets of drugs discusses the advantages and drawbacks of each approach and how combining methods may reveal targets more efficiently.

Gene expression during terminal erythroid differentiation

PURPOSE OF REVIEW

Expression profiling is a powerful technique to sample cell state. This review shows how expression profiling is being applied to the study of erythroid differentiation.

RECENT FINDINGS

Expression-based studies of multipotential hematopoietic progenitor cells has shown that these cells express lineage-restricted genes from multiple lineages at low levels, and that they are in effect 'primed' to develop into all hematopoietic cell types. Expression profiling of oligopotent and committed progenitor cells has further shown that commitment to the erythroid lineage is associated with a progressive decline in the number of expressed genes. Lineage commitment is regulated by lineage-restricted transcription factors, and studies show that the erythroid transcription factor GATA1, in addition to activating a subset of genes, has global repressive effects on gene expression. Terminal erythroid differentiation is associated with further reduction in the number of expressed genes. The erythroid program is defined by those genes that are still expressed, and their high-level expression depends on specific epigenetic modifications, recruitment of transcription factors, and posttranscriptional effects.

SUMMARY

Expression profiling provides the means to identify novel targets for the therapy of erythrocytes disorders, and to obtain insights into the mechanisms of cellular differentiation.

Global genetic regulatory networks controlling hematopoietic cell fates

PURPOSE OF REVIEW

The gene expression profile of a cell is a consequence of transcription factor activities, which, in turn, are controlled by extra-cellular signals. The relationships between all these regulators constitute a genetic regulatory network, which can be used to predict the behavior of the cell in changing environments. We outline the progress being made to identify Genetic Regulatory Networks for hematopoiesis, using gene-by-gene approaches or emerging genomic technologies.

RECENT FINDINGS

The construction of genetic regulatory networks for single and multicellular organisms has inspired the building of genetic regulatory networks for erythropoiesis and B-cell differentiation. genetic regulatory networks are 'scale-free', whereby some genes have many connections while others have very few. The well connected genes, or hubs, correspond to master regulators of the networks, acting to integrate signals and control the sequential passage of the cells through the differentiation process. Lineage decisions are governed by cross-antagonism between two hubs. Large datasets from genome-wide analyses support the concept of multilineage priming and will increasingly refine the network topologies.

SUMMARY

As the underlying genetic regulatory networks for hematopoiesis continue to emerge, the program for lineage choice and differentiation will be revealed. More large-scale datasets identifying network components are needed alongside continued gene-by-gene analyses.

Modern genome-wide genetic approaches to reveal intrinsic properties of stem cells

PURPOSE OF REVIEW

The clinical use of hematopoietic stem cells, which produce all mature blood cell lineages in the circulation, is continuously increasing. Identification of genes and gene networks specifying either stemness or commitment will not only be of major relevance for a fundamental understanding of developmental biology, but also for the emerging fields of tissue engineering and regenerative medicine. Our appreciation of the transcriptional machinery that distinguishes stem cells from their nonstem cell progeny is, however, rudimentary. State-of-the art genome-wide tools are now becoming available to elucidate intrinsic properties of stem cells. Here, we review recent progress that has been made in this field.

RECENT FINDINGS

Approaches to study stem cell-specific genes and gene networks include genetical genomics, mRNA and microRNA expression profiling of carefully selected cells, proteomics, chromatin studies using 'CHIP-on-chip' tools, genome-wide binding site analyses for transcription factors and chromatin-remodeling proteins, and tools to study the three-dimensional organization of gene loci. It is promising to see that the combined application of these tools has resulted in the identification of multiple novel genes that regulate stem cell self-renewal.

SUMMARY

Exploitation of the available technology and integrating the data by translation into a dynamic model of networks, operating in all four dimensions, will be essential to fully comprehend the elusive concept of 'stemness'. It is time to harvest.

A Genomic Approach to Investigate Neuronal Apoptosis

Apoptosis has been postulated to play a possible causal role in the onset of Alzheimer's disease due to shortage of trophic supply, deafferentation and excessive production of free radicals. Many experiments in the past have demonstrated the requirement of de novo gene expression during neuronal apoptosis. In view of the possible involvement of apoptotic processes in Alzheimer's disease and to begin a comprehensive survey of the gene-based molecular mechanisms that underlie these events we have used genome scale screening by DNA microarray technology in cerebellar granule neurons following serum and potassium deprivation. From the 8740 genes interrogated by the microarrays, 423 genes were found regulated both at the transcriptional and post-transcriptional level and segregated into distinct clusters. Functional clustering based on gene ontologies showed coordinated expression of genes with common biological functions and metabolic pathways. Among the genes implicated in apoptotic cerebellar granule neurons, 70 were in common with those differentially expressed in cortical neurons exposed to amyloid beta-protein, indicating the existence of common mechanisms responsible of neuronal cell death. This new approach offer a genomic view of the changes that accompany neuronal apoptosis and yield new insights into the molecular basis underlying it.

Alternative splicing: new insights from global analyses

Recent analyses of sequence and microarray data have suggested that alternative splicing plays a major role in the generation of proteomic and functional diversity in metazoan organisms. Efforts are now being directed at establishing the full repertoire of functionally relevant transcript variants generated by alternative splicing, the specific roles of such variants in normal and disease physiology, and how alternative splicing is coordinated on a global level to achieve cell- and tissue-specific functions. Recent progress in these areas is summarized in this review.

Comparative and integrative functional genomics of HCC

Global gene expression profiling of hepatocellular carcinoma (HCC) is a promising new technology that has already refined the diagnosis and prognostic predictions of HCC patients. This has been accomplished by identifying genes whose expression pattern is associated with clinicopathological features of HCC tumors. Molecular characterization of HCC from gene expression profiling studies will undoubtedly improve the prediction of treatment responses, selection of treatments for specific molecular subtypes of HCC and ultimately the clinical outcome of HCC patients. The research focus is now shifting toward the identification of genetic determinants that are components of the specific regulatory pathways altered in cancers, and that may constitute novel therapeutic targets. Here we review the recent advances in gene expression profiling of HCC and discuss the future strategies for analysing large and complicated data sets from microarray studies and how to integrate these with diverse genomic data.

Evolution of microarray analysis

Reddy's very thorough review of the history of gene expression analysis of neurodegenerative disease made me think about the early days of microarrays, so I want to reminisce a little before commenting on the evolution of the technology and some issues that I think still continue to plague us.

Merging microfluidics with microarray-based bioassays

Microarray technologies provide powerful tools for biomedical researchers and medicine, since arrays can be configured to monitor the presence of molecular signatures in a highly parallel fashion and can be configured to search either for nucleic acids (DNA microarrays) or proteins (antibody-based microarrays) as well as different types of cells. Microfluidics on the other hand, provides the ability to analyze small volumes (micro-, nano- or even pico-liters) of sample and minimize costly reagent consumption as well as automate sample preparation and reduce sample processing time. The marriage of microarray technologies with the emerging field of microfluidics provides a number of advantages such as, reduction in reagent cost, reductions in hybridization assay times, high-throughput sample processing, and integration and automation capabilities of the front-end sample processing steps. However, this potential marriage is also fraught with some challenges as well, such as developing low-cost manufacturing methods of the fluidic chips, providing good interfaces to the macro-world, minimizing non-specific analyte/wall interactions due to the high surface-to-volume ratio associated with microfluidics, the development of materials that accommodate the optical readout phases of the assay and complete integration of peripheral components (optical and electrical) to the microfluidic to produce autonomous systems appropriate for point-of-care testing. In this review, we provide an overview and recent advances on the coupling of DNA, protein and cell microarrays to microfluidics and discuss potential improvements required for the implementation of these technologies into biomedical and clinical applications.

Cellular transcriptomics -- the next phase of endocrine expression profiling

Transcriptome analysis, or global gene expression profiling, has become a commonly used and valuable tool in both basic and clinical endocrine research. Novel endocrine regulators have 'surfaced' and greater consideration is now given to understanding function at the level of gene networks. Recent developments have shown that the transcriptome is considerably larger and more divergently expressed than was previously thought. Endocrine cells express a great variety of coding and noncoding RNAs in a highly cell-specific manner. If further value is to be taken from this research area, then steps towards defined cellular transcriptomics must be taken. New sampling techniques that utilize novel genetic models are a key first step.

Gene expression profile analysis: an emerging approach to investigate mechanisms of genotoxicity

The response to stress triggers transcriptional activation of genes involved in cell survival and/or cell death. Thus, the monitoring of gene expression levels in large gene sets or whole genomes in response to various agents (toxicogenomics) has been proposed as a tool for investigating mechanisms of toxicity. Although standard in vitro genetic toxicity testing provides relatively simple and accurate hazard detection, interpretation of positive findings, i.e., in vitro chromosome aberrations, in terms of relevant risk to humans is difficult, due to the limited insight into the underlying mechanisms. Therefore, the development of experimental approaches capable of differentiating a wide range of genotoxic mechanisms is expected to significantly improve risk assessment. The goal of this review is to summarize current developments in toxicogenomic analysis of genotoxic stress, and to provide a perspective on the application of gene expression profile analysis in genetic toxicology.

Pharmacogenomics in lung cancer: an analysis of DNA repair gene expression in patients treated with platinum-based chemotherapy

Lung cancer is a worldwide epidemic and despite platinum-based chemotherapy being the cornerstone of non-small cell lung cancer treatment, patient response rates to these regimens remain very low. Although resistance to cisplatin is multifactorial, DNA repair plays a critical role in cisplatin resistance. One of the most important goals in translational research is to investigate the clinical use of DNA repair pathways that may influence cisplatin chemosensitivity. Trying to understand the role of genes involved in DNA repair and response to treatment has become one of the main objectives of individualised chemotherapy. It is well known that chemosensitivity is individually predetermined, and the upregulation of mRNA transcripts has been linked to differential response to cytotoxic drugs. In this article, the authors try to highlight the more relevant aspects regarding these issues, primarily focused on the potential role of ERCC1, RRM1, XPD and BRCA1 expression profiling as predictors of anticancer drug efficacy.