Moving towards personalized medicine in rheumatoid arthritis

To develop personalized medicine strategies for improvement of patient management in rheumatoid arthritis, the clinical and molecular properties of the individual patients need to be well characterized. A crucial step in this approach is to discover subgroups of patients that are characterized by a good or poor treatment outcome. Dennis and colleagues have identified distinct pretreatment gene expression profiles in affected synovial tissue specimens and a tissue type-related systemic protein pattern which are associated with a positive or negative clinical outcome to monotherapy with adalumimab (anti-TNFα) and tocilizumab (anti-IL-6 receptor). These observations assign biological pathways associated with response outcome and provide evidence for the existence of systemic, easy-to-measure predictive biomarkers for clinical benefit of these biologics.     

Mammalian synthetic biology in the age of genome editing and personalized medicine

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Enhanced microarray performance using low complexity representations of the transcriptome

Low abundance mRNAs are more difficult to examine using microarrays than high abundance mRNAs due to the effect of concentration on hybridization kinetics and signal-to-noise ratios. This report describes the use of low complexity representations (LCRs) of mRNA as the targets for cDNA microarrays. Individual sequences in LCRs are more highly represented than in the mRNA populations from which they are derived, leading to favorable hybridization kinetics. LCR targets permit the measurement of abundance changes that are difficult to measure using oligo(dT) priming for target synthesis. An oligo(dT)-primed target and three LCRs detect twice as many differentially regulated genes as could be detected by the oligo(dT)-primed target alone, in an experiment in which serum-starved fibroblasts responded to the reintroduction of serum. Thus, this target preparation strategy considerably increases the sensitivity of cDNA microarrays.     

Next generation sequencing in cardiomyopathy: towards personalized genomics and medicine

Next generation sequencing (NGS) is perhaps one of the most exciting advances in the field of life sciences and biomedical research in the last decade. With the availability of massive parallel sequencing, human DNA blueprint can be decoded to explore the hidden information with reduced time and cost. This technology has been used to understand the genetic aspects of various diseases including cardiomyopathies. Mutations for different cardiomyopathies have been identified and cataloging mutations on phenotypic basis are underway and are expected to lead to new discoveries that may translate to novel diagnostic, prognostic and therapeutic targets. With ease in handling NGS, cost effectiveness and fast data output, NGS is now considered as a diagnostic tool for cardiomyopathy by providing targeted gene sequencing. In addition to the number of genetic variants that are identified in cardiomyopathies, there is a need of quicker and easy way to screen multiple genes associated with the disease. In this review, an attempt has been made to explain the NGS technology, methods and applications in cardiomyopathies and their perspective in clinical practice and challenges which are to be addressed.     

Moving beyond genome sequencing into personalized genomic medicine: biological and computing challenges

A report of the second annual Beyond the Genome conference held on the 19-22 September 2011 at The Universities at Shady Grove, Rockville, Maryland, USA, where increases in computing that may help make personal genomics a reality were a major focus.     

iPSC-derived organ-on-a-chip models for personalized human genetics and pharmacogenomics studies

Genome-wide association studies (GWAS) have now correlated hundreds of genetic variants with complex genetic diseases and drug efficacy. Functional characterization of these factors remains challenging, particularly because of the lack of human model systems. Molecular and nanotechnological advances, in particular the ability to generate patient-specific PSC lines, differentiate them into diverse cell types, and seed and combine them on microfluidic chips, have led to the establishment of organ-on-a-chip (OoC) platforms that recapitulate organ biology. OoC technology thus provides unique personalized platforms for studying the effects of host genetics and environmental factors on organ physiology. In this review we describe the technology and provide examples of how OoCs may be used for disease modeling and pharmacogenetic research.     

Screens, maps & networks: from genome sequences to personalized medicine

Genome sequencing of tumors provides a wealth of information on mutations and structural variations, instilling hope that this data can be used to predict individual tumor progression and response to treatment. Yet currently, our ability to predict the functional consequences of these aberrations remains poor. How do cancer-associated mutations give rise to the hallmark phenotypes of cancer? Recently, information about the genetic makeup of cancer cells has been combined with novel functional genomics approaches to identify novel targets, exploit synthetic lethality and explore the rewiring of cellular pathways. Here, we highlight recent developments revealing the hidden landscape of genetic interactions in model organisms and cancer cells, a key step toward personalized cancer diagnostics and therapy.     

Metagenomics and personalized medicine

The microbiome is a complex community of Bacteria, Archaea, Eukarya, and viruses that infect humans and live in our tissues. It contributes the majority of genetic information to our metagenome and, consequently, influences our resistance and susceptibility to diseases, especially common inflammatory diseases, such as type 1 diabetes, ulcerative colitis, and Crohn's disease. Here we discuss how host-gene-microbial interactions are major determinants for the development of these multifactorial chronic disorders and, thus, for the relationship between genotype and phenotype. We also explore how genome-wide association studies (GWAS) on autoimmune and inflammatory diseases are uncovering mechanism-based subtypes for these disorders. Applying these emerging concepts will permit a more complete understanding of the etiologies of complex diseases and underpin the development of both next-generation animal models and new therapeutic strategies for targeting personalized disease phenotypes.     

Human genome project: pharmacogenomics and drug development

Now that all 30,000 or so genes that make up the human genome have been deciphered, pharmaceutical industries are emerging to capitalize the custom based drug treatment. Understanding human genetic variation promises to have a great impact on our ability to uncover the cause of individual variation in response to therapeutics. The study of association between genetics and drug response is called pharmacogenomics. The potential implication of genomics and pharmacogenomics in clinical research and clinical medicine is that disease could be treated according to the interindividual differences in drug disposition and effects, thereby enhancing the drug discovery and providing a stronger scientific basis of each patient's genetic constitution. Sequence information derived from the genomes of many individuals is leading to the rapid discovery of single nucleotide polymorphisms or SNPs. Detection of these human polymorphisms will fuel the discipline of pharmacogenomics by developing more personalized drug therapies. A greater understanding of the way in which individuals with a particular genotype respond to a drug allows manufacturers to identify population subgroups that will benefit most from a particular drug. The increasing emphasis on pharmacogenomics is likely to raise ethical and legal questions regarding, among other things, the design of research studies, the construction of clinical trials and the pricing of drugs.     

Breaking the 1000-gene barrier for Mimivirus using ultra-deep genome and transcriptome sequencing

The Filoviridae family comprises of Ebola and Marburg viruses, which are known to cause lethal hemorrhagic fever. However, there is no effective anti-viral therapy or licensed vaccines currently available for these human pathogens. The envelope glycoprotein (GP) of Ebola virus, which mediates entry into target cells, is cytotoxic and this effect maps to a highly glycosylated mucin-like region in the surface subunit of GP (GP1). However, the mechanism underlying this cytotoxic property of GP is unknown. To gain insight into the basis of this GP-induced cytotoxicity, HEK293T cells were transiently transfected with full-length and mucin-deleted (Δmucin) Ebola GP plasmids and GP localization was examined relative to the nucleus, endoplasmic reticulum (ER), Golgi, early and late endosomes using deconvolution fluorescent microscopy. Full-length Ebola GP was observed to accumulate in the ER. In contrast, GPΔmucin was uniformly expressed throughout the cell and did not localize in the ER. The Ebola major matrix protein VP40 was also co-expressed with GP to investigate its influence on GP localization. GP and VP40 co-expression did not alter GP localization to the ER. Also, when VP40 was co-expressed with the nucleoprotein (NP), it localized to the plasma membrane while NP accumulated in distinct cytoplasmic structures lined with vimentin. These latter structures are consistent with aggresomes and may serve as assembly sites for filoviral nucleocapsids. Collectively, these data suggest that full-length GP, but not GPΔmucin, accumulates in the ER in close proximity to the nuclear membrane, which may underscore its cytotoxic property.     

Exploiting the complete yeast genome sequence

The completion of the genome sequence of the budding yeast Saccharomyces cerevisiae marks the dawn of an exciting new era in eukaryotic biology that will bring with it a new understanding of yeast, other model organisms, and human beings. This body of sequence data benefits yeast researchers by obviating the need for piecemeal sequencing of genes, and allows researchers working with other organisms to tap into experimental advantages inherent in the yeast system and learn from functionally characterized yeast gene products which are their proteins of interest. In addition, the yeast post-genome sequence era is serving as a testing ground for powerful new technologies, and proven experimental approaches are being applied for the first time in a comprehensive fashion on a complete eukaryotic gene repertoire.