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.     

Yeast as a model organism for studying the evolution of non-standard genetic codes.

During the last 30 years, a number of alterations to the standard genetic code have been uncovered both in prokaryotes and eukaryotic nuclear and mitochondrial genomes. But, the study of the evolutionary pathways and molecular mechanisms of codon identity redefinition has been largely ignored due to the assumption that non-standard genetic codes can only evolve through neutral evolutionary mechanisms and that they have no functional significance. The recent discovery of a genetic code change in the genus Candida that evolved through an ambiguous messenger RNA decoding mechanism is bringing that naive assumption to an abrupt end by showing, in a rather dramatic way, that genetic code changes have profound physiological and evolutionary consequences for the species that redefine codon identity. In this paper, the recent data on the evolution of the Candida genetic code are reviewed and an experimental framework based on forced evolution, molecular genetics and comparative and functional genomics methodologies is put forward for the study of non-standard genetic codes and genetic code ambiguity in general. Additionally, the importance of using Saccharomyces cerevisiae as a model organism for elucidating the evolutionary pathway of the Candida and other genetic code changes is emphasised.     

Drugging the R-loop interactome: RNA-DNA hybrid binding proteins as targets for cancer therapy

Unravelling the origin of genetic alterations from point mutations to chromosomal rearrangements was greatly enhanced by the discovery of RNA-DNA hybrids (R-loops) that behave as hotspots of genomic instability in a variety of organisms. Current models suggest that uncontrolled R-loops are a hazard to genome integrity, therefore, identifying proteins that are involved in recognising and signalling R-loop structures are of key importance. Herein we analysed key RNA-DNA hybrid binding proteins in humans taking advantage of large-scale gene expression, survival rate, and drug-sensitivity data from cancer genomics databases. We show that expression of RNA-DNA hybrid binding proteins in various cancer types is associated with survival and may have contrasting outcomes in responding to therapeutic treatments. Based on the revealed pharmacogenomic landscape of human RNA-DNA hybrid binding proteins, we propose that R-loops and R-loop binding proteins are potentially relevant new epigenetic markers and therapeutic targets in multiple cancers.     

Genome-wide approaches for cancer gene discovery

One of the central aims of cancer research is to identify and characterize cancer-causing alterations in cancer genomes. In recent years, unprecedented advances in genome-wide sequencing, functional genomics technologies for RNA interference screens and methods for evaluating three-dimensional chromatin organization in vivo have resulted in important discoveries regarding human cancer. The cancer-causing genes identified from these new genome-wide technologies have also provided opportunities for effective and personalized cancer therapy. In this review, we describe some of the most recent technologies for cancer gene discovery. We also provide specific examples in which these technologies have proven remarkably successful in uncovering important cancer-causing alterations.     

Genomic signatures associated with the development, progression, and outcome of prostate cancer

Prostate cancer remains a common cause of cancer death in men. Applications of new genomic technologies to the recent development of high-quality prostate cancer models in multiple contexts have added great molecular insight into the development of and progression to metastasis. Genomic analysis of DNA, RNA, and protein alterations allows for the global assessment of this disease and provides the molecular framework to improve risk classification, outcome prediction, and development of targeted therapies. The creation of expression profiles and signatures will allow the evaluation of cancer phenotypes and give insight into determining those with increased risk of cancer, identification of critical pathways involved in the development of cancer, prediction of disease outcome, and assessment of the response of cancer to established and novel therapies.This review focuses on highlighting recent work in genomics and on its role in evaluating potential genetic modifiers of prostate cancer and novel biomarkers that may help with prostate cancer diagnosis, its potential to provide a better understanding of prostate cancer behavior and transition to metastatic disease, and its role in current and new therapies in prostate cancer. This framework has the exciting potential to be predictive and provide personalized and individual treatment to the large number of men diagnosed with prostate cancer each year.     

Phenocopy--a strategy to qualify chemical compounds during hit-to-lead and/or lead optimization

A phenocopy is defined as an environmentally induced phenotype of one individual which is identical to the genotype-determined phenotype of another individual. The phenocopy phenomenon has been translated to the drug discovery process as phenotypes produced by the treatment of biological systems with new chemical entities (NCE) may resemble environmentally induced phenotypic modifications. Various new chemical entities exerting inhibition of the kinase activity of Transforming Growth Factor β Receptor I (TGF-βR1) were qualified by high-throughput RNA expression profiling. This chemical genomics approach resulted in a precise time-dependent insight to the TGF-β biology and allowed furthermore a comprehensive analysis of each NCE's off-target effects. The evaluation of off-target effects by the phenocopy approach allows a more accurate and integrated view on optimized compounds, supplementing classical biological evaluation parameters such as potency and selectivity. It has therefore the potential to become a novel method for ranking compounds during various drug discovery phases.     

Genomic expression discovery predicts pathways and opposing functions behind phenotypes

Discovering states of genetic expression that are true to a high degree of certainty is likely to predict gene function behind biological phenotypes. The states of expression (up- or down-regulated) of 19200 cDNAs in 10 meningiomas are compared with normal brain by an algorithm that detects only 1 false measurement per 192000; 364 genes are discovered. The expression data accurately predict activation of signaling pathways and link gene function to specific phenotypes. Meningiomas appear to acquire aberrant phenotypes by disturbing the balanced expression of molecules that promote opposing functions. The findings expose interconnected genes and propose a role of genomic expression discovery in functional genomics of living systems.     

Functional genomics of soybean for improvement of productivity in adverse conditions

Global soybean production is frequently impacted by various stresses, including both abiotic and biotic stresses. To develop soybean plants with enhanced tolerance to different stressors, functional genomics of soybean and a comprehensive understanding of available biotechnological resources and approaches are essential. In this review, we will discuss recent advances in soybean functional genomics which provide unprecedented opportunities to understand global patterns of gene expression, gene regulatory networks, various physiological, biochemical, and metabolic pathways as well as their association with the development of specific phenotypes. Soybean functional genomics, therefore, will ultimately enable us to develop new soybean varieties with improved productivity under adverse conditions by genetic engineering.     

NutriTRAILomics in prostate cancer: time to have two strings to one’s bow

The astonishing development of broad genomics and proteomics tools have catalyzed a new era in both therapeutic interventions and nutrition in prostate cancer. The terms pharmacogenomics and nutrigenomics have been derived out of their genetic forbears as large-scale genomics technologies have been established in the last decade. It is unquestionable that rationale of both disciplines is to individualize or personalize medicine and food and nutrition, and eventually health, by tailoring the drug or the food to the individual genotype. The purpose of this review is to significantly inspect results from current research concerning the mechanisms of action of phytonutrients and potential effects on prostate cancer. Substantial emerging data supports the synergistic adiministration of nutraceuticals with TRAIL in prostate cancer progression to circumvent TRAIL refractoriness. Nonetheless, developing novel scientific methods for discovery, validation, characterization and standardization of these multicomponent phyto-therapeutics is vital to their recognition into mainstream medicine. The key to interpret a personalized response is a greater comprehension of nutrigenomics, proteomics and metabolomics.     

Comparative RNAi Screens in C. elegans and C. briggsae Reveal the Impact of Developmental System Drift on Gene Function

Although two related species may have extremely similar phenotypes, the genetic networks underpinning this conserved biology may have diverged substantially since they last shared a common ancestor. This is termed Developmental System Drift (DSD) and reflects the plasticity of genetic networks. One consequence of DSD is that some orthologous genes will have evolved different in vivo functions in two such phenotypically similar, related species and will therefore have different loss of function phenotypes. Here we report an RNAi screen in C. elegans and C. briggsae to identify such cases. We screened 1333 genes in both species and identified 91 orthologues that have different RNAi phenotypes. Intriguingly, we find that recently evolved genes of unknown function have the fastest evolving in vivo functions and, in several cases, we identify the molecular events driving these changes. We thus find that DSD has a major impact on the evolution of gene function and we anticipate that the C. briggsae RNAi library reported here will drive future studies on comparative functional genomics screens in these nematodes.     

Dissecting complex phenotypes using the genomics of twins

Genetics in the post-genomic period is shifting from structural to functional genetics or genomics. Meanwhile, the use of twins is largely expanding from traditional heritability estimation for disease phenotypes to the study of both diseases and various molecular phenotypes, such as the regulatory phenotypes in functional genomics concerning gene expression and regulation, by engaging both classical twin design and marker-based gene mapping techniques in genetic epidemiology. New research designs have been proposed for making novel uses of twins in studying the molecular basis in the epigenetics of human diseases. Besides, twins not only serve as ideal samples for disease gene mapping using conventional genetic markers but also represent an excellent model for associating DNA copy number variations, a structural genetic marker, with human diseases. It is believed that, with the rapid development in biotechniques and new advances in bioinformatics, the unique samples of twins will make new contributions to our understanding of the nature and nurture in complex disease development and in human health. This paper aims at summarizing the new uses of twins in current genetic studies and suggesting novel proposes together with useful design and analytical strategies.