Clinical Implementation of Pharmacogenetic Testing in a Hospital of the Spanish National Health System: Strategy and Experience Over 3 Years.

In 2014, we established a pharmacogenetics unit with the intention of facilitating the integration of pharmacogenetic testing into clinical practice. This unit was centered around two main ideas: i) individualization of clinical recommendations, and ii) preemptive genotyping in risk populations. Our unit is based on the design and validation of a single nucleotide polymorphism (SNP) microarray, which has allowed testing of 180 SNPs associated with drug response (PharmArray), and clinical consultation regarding the results. Herein, we report our experience in integrating pharmacogenetic testing into our hospital and we present the results of the 2,539 pharmacogenetic consultation requests received over the past 3 years in our unit. The results demonstrate the feasibility of implementing pharmacogenetic testing in clinical practice within a national health system.

Recent advances in molecular diagnostics of hepatitis B virus.

Hepatitis B virus (HBV) is one of the important global health problems today. Infection with HBV can lead to a variety of clinical manifestations including severe hepatic complications like liver cirrhosis and hepatocellular carcinoma. Presently, routine HBV screening and diagnosis is primarily based on the immuno-detection of HBV surface antigen (HBsAg). However, identification of HBV DNA positive cases, who do not have detectable HBsAg has greatly encouraged the use of nucleic acid amplification based assays, that are highly sensitive, specific and are to some extent tolerant to sequence variation. In the last few years, the field of HBV molecular diagnostics has evolved rapidly with advancements in the molecular biology tools, such as polymerase chain reaction (PCR) and real-time PCR. Recently, apart of PCR based amplification methods, a number of isothermal amplification assays, such as loop mediated isothermal amplification, transcription mediated amplification, ligase chain reaction, and rolling circle amplification have been utilized for HBV diagnosis. These assays also offer options for real time detection and integration into biosensing devices. In this manuscript, we review the molecular technologies that are presently available for HBV diagnostics, with special emphasis on isothermal amplification based technologies. We have also included the recent trends in the development of biosensors and use of next generation sequencing technologies for HBV.

Microarray analysis in cardiac arrhythmias: a new perspective?

The opportunity to distinguish an accurate set of genes associated with multigenic diseases such as cardiomyopathies or cardiac arrhythmias was very limited before the genomic era. Numerous methods of measuring RNA abundance exist, including northern blotting, multiplex polymerase chain reaction (PCR), and quantitative real-time reverse transcriptase-PCR. However, these techniques might be used to assess the expression levels of only 10-50 genes at time. Today, DNA microarrays provide us with opportunity to simultaneously analyze tens of thousands of genes, giving a remarkable possibility to investigate the genomic contribution to cardiovascular diseases. A particular tissue at any stage of health or disease may be used to generate a genomic profile. Microarray techniques are already used in infectious diseases, oncology, and pharmacology to facilitate clinicians, risk-stratify patients, as well as to predict and assess therapeutic responses to drugs. In this paper, we describe recent advances in the use of various types of microarray technique in the diagnosis of arrhythmogenic heart disease. We also highlight other strategies and methods of differential gene typing comparing with pros and cons of microarray analysis.

Scenario drafting to anticipate future developments in technology assessment.

BACKGROUND: Health Technology Assessment (HTA) information, and in particular cost-effectiveness data is needed to guide decisions, preferably already in early stages of technological development. However, at that moment there is usually a high degree of uncertainty, because evidence is limited and different development paths are still possible. We developed a multi-parameter framework to assess dynamic aspects of a technology -still in development-, by means of scenario drafting to determine the effects, costs and cost-effectiveness of possible future diffusion patterns. Secondly, we explored the value of this method on the case of the clinical implementation of the 70-gene signature for breast cancer, a gene expression profile for selecting patients who will benefit most from chemotherapy. METHODS: To incorporate process-uncertainty, ten possible scenarios regarding the introduction of the 70-gene signature were drafted with European experts. Out of 5 most likely scenarios, 3 drivers of diffusion (non-compliance, technical failure, and uptake) were quantitatively integrated in a decision-analytical model. For these scenarios, the cost-effectiveness of the 70-gene signature expressed in Incremental Cost-Effectiveness Ratios (ICERs) was compared to clinical guidelines, calculated from the past (2005) until the future (2020). RESULTS: In 2005 the ICER was €1,9 million/quality-adjusted-life-year (QALY), meaning that the 70-gene signature was not yet cost-effective compared to the current clinical guideline. The ICER for the 70-gene signature improved over time with a range of €1,9 million to €26,145 in 2010 and €1,9 million to €11,123/QALY in 2020 depending on the separate scenario used. From 2010, the 70-gene signature should be cost-effective, based on the combined scenario. The uptake-scenario had strongest influence on the cost-effectiveness. CONCLUSIONS: When optimal diffusion of a technology is sought, incorporating process-uncertainty by means of scenario drafting into a decision model may reveal unanticipated developments and can demonstrate a range of possible cost-effectiveness outcomes. The effect of scenarios give additional information on the speed with cost effectiveness might be reached and thus provide a more realistic picture for policy makers, opinion leaders and manufacturers.

Application of personalized medicine to solid tumors: opportunities and challenges.

Personalised medicine is an emerging model that will revolutionise our current healthcare system. In the last decade, several genomic aberrations were discovered that are now used as predictive markers for treatment with targeted therapeutics. The technological advances in the last few years, such as the development of high resolution DNA microarrays or second generation sequencers, have led to a dramatic increase in the number of ongoing genomic profiling studies. These studies, in turn, are leading to an enormous number of detected genomic aberrations whose biological interpretation is still pending. This review will provide an overview on the current state of personalised medicine in cancer. Discussion of the use and development of the various technologies will help us to understand the opportunities and challenges that arise when novel technologies are implemented.

[Personalized medicine]. / Individualisierte Medizin 2011.

Molecular and cell biology have revolutionized not only diagnosis, therapy and prevention of human diseases but have also greatly contributed to the understanding of their pathogenesis. Based on modern molecular and biochemical methods it is possible to identify on the one hand point mutations and single nucleotide polymorphisms. On the other hand, using high throughput array technologies, it is possible to analyze thousands of genes simultaneously, resulting in an individual gene or gene expression profile (signature). These data increasingly allow to define the individual risk for a given disease and to predict the individual prognosis of a disease as well as the efficacy of therapeutic strategies (personalized medicine). In this review recent advances of predictive medicine and its clinical relevance will be addressed.

Recent advances in molecular diagnostics of colorectal cancer by genomic arrays: proposal for a procedural shift in biological sampling and pathological report.

Two forms of genetic instability have been described in colorectal cancer: chromosomal instability, characterized by structural and numerical chromosomal abnormalities and associated to aneuploidy; and microsatellite instability, characterized by a deficiency in the mismatch repair system that leads to slippage in microsatellites and is associated to euploidy. Thirteen colorectal cancer sample DNAs were analyzed after colectomy. High-resolution genome-wide DNA copy number and Single Nucleotide Polimorphism genotyping analysis was performed by Affymetrix SNP 6.0 arrays that interrogates 906,600 single nucleotide polymorphisms and 945,826 copy number probes. We implemented this analysis as part of a routine procedure that includes the sampling of fresh tissue from the tumor mass without affecting the subsequent standard histopathological procedure. The novel molecular technology allows the determination of a genome-wide molecular karyotype using only 500 ng of high-quality tumor DNA; it distinguishes the two main types of genomic instability, discriminating between chromosomal instability positive and negative tumors. It also detects loss of heterozygosity (LOH) regions, called copy neutral-LOH. Tumor-associated copy neutral-LOH regions may play a pivotal role in oncogenesis when they determine duplications of either activating or loss of function gene mutation. We observed recurrent gains of chromosomes 2, 7, 8q, 9, 12, 13, 20 and losses of chromosomes 4, 5, 8p, 15, 17p, 18, 22, and Y, in agreement with previous cytogenetic studies. The use of such sampling procedure could stimulate the routine detection of point mutations in specific genes, thus avoiding subsequent sectioning of formalin-fixed and paraffin-embedded samples.

Microarray: an instrument for cancer surgeons of the future?

Microarray enables the study of thousands of genes simultaneously. While still in its infancy as a technique and with a number of barriers to be overcome, microarray is allowing scientists to thoroughly examine the molecular pathways of cancer pathogenesis. However, the adoption of microarray as a clinically applicable technique has been slow coming. Current literature suggests roles in the diagnosis of tumours of unknown origin, in the evaluation of prognostic markers, and in guiding treatment for recurrent and resistant malignancy. This review outlines the science of microarray and draws on clinical examples, including osteosarcoma, breast, prostate and pancreatic carcinomas, to highlight the potential of microarray as a technique of surgical importance.

Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances.

Array manufacturers originally designed single nucleotide polymorphism (SNP) arrays to genotype human DNA at thousands of SNPs across the genome simultaneously. In the decade since their initial development, the platform's applications have expanded to include the detection and characterization of copy number variation--whether somatic, inherited, or de novo--as well as loss-of-heterozygosity in cancer cells. The technology's impressive contributions to insights in population and molecular genetics have been fueled by advances in computational methodology, and indeed these insights and methodologies have spurred developments in the arrays themselves. This review describes the most commonly used SNP array platforms, surveys the computational methodologies used to convert the raw data into inferences at the DNA level, and details the broad range of applications. Although the long-term future of SNP arrays is unclear, cost considerations ensure their relevance for at least the next several years. Even as emerging technologies seem poised to take over for at least some applications, researchers working with these new sources of data are adopting the computational approaches originally developed for SNP arrays.

Discussion of the applicability of microarrays: profiling of leukemias.

Leukemias are classified according to clinical, morphologic, and immunologic phenotypes, caused by specific genetic aberrations in association to distinct prognostic profiles. Usually the subtypes are defined using complementary laboratory methods, such as multiparameter flow cytometry, cytogenetics in combination with fluorescence in situ hybridization, and molecular methods such as the polymerase chain reaction. The genetic variations of the different subtypes lead to distinct changes also in gene expression, which is comprehensively analysed by DNA microarrays. Thus, first gene expression profiling studies showed that analysis with whole-genome DNA microarrays leads to a prediction accuracy of 95.6% with respect to the classical methods, and even allowed a further distinction of subtypes. It is expected that diagnostic strategies can be optimized with this new technology and that the understanding of the molecular pathogenesis of leukemias will be significantly improved. This could also lead to the identification of new targets for future drugs.

A decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects.

The past decade has shown a marked increase in the use of high-throughput assays in clinical research into human cancer, including acute myeloid leukemia (AML). In particular, genome-wide gene expression profiling (GEP) using DNA microarrays has been extensively used for improved understanding of the diagnosis, prognosis, and pathobiology of this heterogeneous disease. This review discusses the progress that has been made, places the technologic limitations in perspective, and highlights promising future avenues.

Do DNA microarrays have their future behind them?

The first report on DNA microarray technology appeared in Science in 1995. Starting from gene expression profiling, its application fields have considerably evolved and extend from microbiology to cancer study. DNA microarrays are now routinely used for the detection of single nucleotide polymorphisms, microRNAs analysis, study of copy number variation, CpG methylations detection.... Furthermore, the approval of DNA microarray technology by US Food and Drug Administration has opened the door to new applications in clinical diagnostics. At the same time, DNA arrays have to face the concurrence of the latest generation of very high throughput sequencing devices which are predicted to make the microarray technology obsolete. This review will discuss on this paradoxical situation.

Advances in gene chip technique in Barrett's metaplasia and adenocarcinoma.

Gene chip methods are applied to the study of gene expression. The differentially expressed genes in different specimens may be detected with parallel analysis by gene chip, which has greatly improved the traditional experiments in that only a single or several gene expressions need to be observed for each test, thereby speeding up the identification of differentially expressed genes and the construction of differential expression profiles. Many studies have applied this technology for Barrett's metaplasia and adenocarcinoma, and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence, prognosis and treatment selection. This review described the gene expression profile and molecular changes related to Barrett's metaplasia and adenocarcinoma of the esophagus, with emphasis on its prognostic value and possibilities for targeted therapy in a clinical setting.

Tissue microarrays in clinical oncology.

Tissue microarray (TMA) is a recently implemented, high-throughput technology for the analysis of molecular markers in oncology. This research tool permits the rapid assessment of a biomarker in thousands of tumor samples, using commonly available laboratory assays such as immunohistochemistry and in situ hybridization. Although introduced less than a decade ago, TMA has proven to be invaluable in the study of tumor biology, the development of diagnostic tests, and the investigation of oncologic biomarkers. This review describes the impact of TMA-based research in clinical oncology and its potential future applications. Technical aspects of TMA construction and the advantages and disadvantages inherent to this technology are also discussed.

Microarray analysis of gene expression of cancer to guide the use of chemotherapeutics.

The beauty of microarray analysis of gene expression (MAGE) is that it can be used to discover some genes that were previously thought to be unrelated to a physiologic or pathologic event. During the period from 1999 to 2007, applications of MAGE in cancer investigation have shifted from molecular profiling, identifying previously undiscovered cancer types, predicting outcomes of cancer patients, revealing metastasis signatures of solid tumors, to guiding the use of therapeutics. The roles of cancer genomic signatures have evolved through three phases. In the first phase, genomic signatures were described in stored cancer specimens and dubbed as molecular portraits of cancer. When gene expression profiles were carefully correlated with sufficient clinical information of cancer patients, new subgroups of cancers with distinct outcomes were revealed. In studies of the second phase, validation of cancer signatures was emphasized and commonly performed with independent groups of cancer specimens or independent data set. In the third phase, cancer genomic signatures have been further expanded beyond depicting the molecular portrait of cancer to predicting patient outcomes and guiding the use of cancer therapeutics. Cancer genomic signatures have become an essential part of a new generation of cancer clinical trials. It is advocated that, in future clinical trials of cancer therapy, the cancer specimens of each participant should be tested for currently available predictor genomic signatures, so that the most effective treatment with the least adverse effects for each patient can be identified. Then, participants can be triaged to an appropriate study group.

Innovative proteomic approaches for cancer biomarker discovery.

Substantial technological advances in proteomics and related computational science have been made in the past few years. These advances overcome in part the complexity and heterogeneity of the human proteome, permitting quantitative analysis and identification of protein changes associated with tumor development. Here, we discuss some of these advances that are uncovering new cancer biomarkers that have potential to detect cancer at early and curable stages and address remaining challenges.

Application of array-based genomic and epigenomic technologies to unraveling the heterogeneous nature of breast tumors: on the road to individualized treatment.

The recent application of genomic microarray technology to the molecular profiling of breast tumors has clearly demonstrated their heterogeneous nature. Targeted treatment strategies are having a clear impact on patient survival. It has also become apparent that accumulated mutations, genomic instability, epigenetic phenomena, genetic variability and environmental factors all contribute to the uniqueness of a patient's tumor. Novel genomic and epigenetic-based technologies have been or are being developed in order to greatly enhance the analysis of tumor samples including those samples previously thought unusable due to the fixation process, such as archival formalin-fixed paraffin-embedded (FFPE) samples. Patients and their tumors can now be studied with regard to genetic variation, genomic instability, gene expression, gene mutations, and methylation patterns. These areas of research are being made more accessible through genome-wide screening technologies and will, in the near future, rapidly expand our understanding of what contributes to the unique properties of each tumor and lead to the identification of genes that could be potential therapeutic targets for specific tumor subtypes. Application of these technologies to our understanding of breast cancer will undoubtedly have an impact on the individualization of treatment for breast cancer patients in the not to distant future.

Development of reverse phase protein microarrays for clinical applications and patient-tailored therapy.

While genomics provide important information about the somatic genetic changes, and RNA transcript profiling can reveal important expression changes that correlate with outcome and response to therapy, it is the proteins that do the work in the cell. At a functional level, derangements within the proteome, driven by post-translational and epigenetic modifications, such as phosphorylation, is the cause of a vast majority of human diseases. Cancer, for instance, is a manifestation of deranged cellular protein molecular networks and cell signaling pathways that are based on genetic changes at the DNA level. Importantly, the protein pathways contain the drug targets in signaling networks that govern overall cellular survival, proliferation, invasion and cell death. Consequently, the promise of proteomics resides in the ability to extend analysis beyond correlation to causality. A critical gap in the information knowledge base of molecular profiling is an understanding of the ongoing activity of protein signaling in human tissue: what is activated and "in use" within the human body at any given point in time. To address this gap, we have invented a new technology, called reverse phase protein microarrays, that can generate a functional read-out of cell signaling networks or pathways for an individual patient obtained directly from a biopsy specimen. This "wiring diagram" can serve as the basis for both, selection of a therapy and patient stratification.