How the Electronic Health Record Will Change the Future of Health Care

Genetic testing is expected to play a critical role in patient care in the near future. Advances in genomic research have the potential to impact medicine in very tangible and direct ways, from carrier screening to disease diagnosis and prognosis to targeted treatments and personalized medicine. However, numerous barriers to widespread adoption of genetic testing continue to exist, and health information technology will be a critical means of addressing these challenges. Electronic health records (EHRs) are a digital replacement for the traditional paper-based patient chart designed to improve the quality of patient care. EHRs have become increasingly essential to managing the wealth of existing clinical information that now includes genetic information extracted from the patient genome. The EHR is capable of changing health care in the future by transforming the way physicians use genomic information in the practice of medicine.     

On being “actionable”: clinical sequencing and the emerging contours of a regime of genomic medicine in oncology

This article explores commercial, academic, and national initiatives aimed at using sequencing technologies to generate “actionable” genomic results that can be applied to the clinical management of oncology patients. We argue that the term “actionable” is not merely a buzzword, but signals the emergence of a distinctive sociotechnical regime of genomic medicine in oncology. Unlike other regimes of genomic medicine that are organized around assessing and managing inherited risk for developing cancer (e.g. BRCA testing), actionable regimes aim to generate predictive relationships between genetic information and drug therapies, thereby generating new kinds of clinical actions. We explore how these genomic results are made actionable by articulating them with existing clinical routines, clinical trials, regulatory regimes, and health care systems; and in turn, how clinical sequencing programs have begun to reconfigure knowledge and practices in oncology. Actionability regimes confirm the emergence of bio-clinical decision-making in oncology, whereby the articulation of molecular hypotheses and experimental therapeutics become central to patient care.     

Heterogeneity of lipidomic profiles among lung cancer subtypes of patients

Lung cancer is a leading cause of cancer‐related deaths with an increasing incidence and poor prognoses. To further understand the regulatory mechanisms of lipidomic profiles in lung cancer subtypes, we measure the profiles of plasma lipidome between health and patients with lung cancer or among patients with squamous cell carcinomas, adenocarcinoma or small cell lung cancer and to correct lipidomic and genomic profiles of lipid‐associated enzymes and proteins by integrating the data of large‐scale genome screening. Our studies demonstrated that circulating levels of PS and lysoPS significantly increased, while lysoPE and PE decreased in patients with lung cancer. Our data indicate that lung cancer‐specific and subtype‐specific lipidomics in the circulation are important to understand mechanisms of systemic metabolisms and identify diagnostic biomarkers and therapeutic targets. The carbon atoms, dual bonds or isomerism in the lipid molecule may play important roles in lung cancer cell differentiations and development. This is the first try to integrate lipidomic data with lipid protein‐associated genomic expression among lung cancer subtypes as the part of clinical trans‐omics. We found that a large number of lipid protein‐associated genes significantly change among cancer subtypes, with correlations with altered species and spatial structures of lipid metabolites.     

A 17-marker panel for global genomic instability in breast cancer

Genomic instability is a hallmark of cancer that plays a pivotal role in breast cancer development and evolution. A number of existing prognostic gene expression signatures for breast cancer are based on proliferation-related genes. Here, we identified a 17-marker panel associated with genome stability. A total of 136 primary breast carcinomas were stratified by genome stability. Matched gene expression profiles showed an innate segregation based on genome stability. We identified a 17-marker panel stratifying the training and validation cohorts into high- and low-risk patients. The 17 genes associated with genomic instability strongly impacted clinical outcome in breast cancer. Pathway analyses determined chromosome organisation, cell cycle regulation, and RNA processing as the underlying biological processes, thereby offering options for drug development and treatment tailoring. Our work supports the applicability of the 17-marker panel to improve clinical outcome prediction for breast cancer patients based on a signature accounting for genomic instability.     

Implementation of Genetics to Personalize Medicine

Background: We stand on the verge of integrating individual genetic and genomic information into health care provision and maintenance to improve health, increase efficiency, and decrease costs. We are beginning to integrate information on inherited susceptibility, gene expression, and predicted pharmacogenomic response to refine our medical management.Objective: This article reviews the current utility of genetics and genomics in a wide array of clinical circumstances, considers the future applications, and defines some of the obstacles and potential solutions to clinical integration of genomic medicine.Methods: Using the search terms genetics, genomics, pharmacogenomics, newborn screening, long QT syndrome, BRCA1/BRCA2, maturity onset diabetes of youth, diabetes, hemochromatosis, coronary artery disease, copy number changes, genetic discrimination, and genetic education, the PubMed database was searched from January 2000 to March 2007 to identify pertinent articles. Search results were restricted to English-language and human studies.Results: Several areas of medicine have begun to incorporate genetics into clinical practice, including newborn screening and breast cancer risk stratification and treatment. Molecular genetic tests are, and will increasingly become, available for inherited arrhythmias, diabetes, cancer, coronary artery disease, and pharmacogenomics. However, there are many barriers to implementation, including the cost of testing, the genetic literacy of patients and health care providers, and concerns about genetic discrimination.Conclusion: Genetics and genomics will be increasingly utilized in every field of medicine; however, health care providers and patients must have realistic expectations about its predictive power and current limitations.     

二代基因测序数据管理和大数据平台在精准医学中的应用

精准医学集合了多种数据,包括组学、临床、环境和行为等,是对疾病进行个性化治疗、预防和管理的科学。随着基因测序费用的大幅下降,人们对肿瘤等疾病的认识从传统病理到分子水平的飞跃等,相关科学的发展和普及推动了精准医学的诞生和发展,将更加深远地影响着人类的健康。本文介绍了精准医学的概念、目的及应用,介绍了二代DNA测序技术在精准医学中的应用,认为基因组学数据、样本管理、数据质量控制标准以及数据管理平台等是实现精准医学的基础,智能化精准医疗将是来的发展方向。进行展望的同时,也认为基因组学海量数据的规模特点、各种健康应用在推动数据管理平台的发展的同时,也对其演进提出了挑战。     

Genomic medicine and neurological disease

“Genomic medicine” refers to the diagnosis, optimized management, and treatment of disease—as well as screening, counseling, and disease gene identification—in the context of information provided by an individual patient’s personal genome. Genomic medicine, to some extent synonymous with “personalized medicine,” has been made possible by recent advances in genome technologies. Genomic medicine represents a new approach to health care and disease management that attempts to optimize the care of a patient based upon information gleaned from his or her personal genome sequence. In this review, we describe recent progress in genomic medicine as it relates to neurological disease. Many neurological disorders either segregate as Mendelian phenotypes or occur sporadically in association with a new mutation in a single gene. Heritability also contributes to other neurological conditions that appear to exhibit more complex genetics. In addition to discussing current knowledge in this field, we offer suggestions for maximizing the utility of genomic information in clinical practice as the field of genomic medicine unfolds.     

Electronic health records: the European scene.

Caring for patients'' health problems relies increasingly on sharing information between clinical departments and disciplines and with managers. The medical record of the future will need to provide a flexible and shareable framework for recording and analysing the consultation process. The advanced informatics in medicine (AIM) programme seeks to encourage research and development in telemedicine in areas that are beyond the scope of any one country. It includes many European projects attempting to define the best storage and transmission formats for such diverse data types as laboratory results, biosignals, x ray images, and photographs, and in clinical specialties varying from intensive care to medicine for elderly people. One example, the good European health record project, is developing a model architecture for computerised health records across Europe that is capable of operating on a wide variety of computer hardwares and will also be able to communicate with many different information systems. The ultimate European health record will be comprehensive and medicolegally acceptable across clinical domains, hold all data types, and be automatically translated between languages.     

Coupled analysis of gene expression and chromosomal location

Microarray technology can be used to assess simultaneously global changes in expression of mRNA or genomic DNA copy number among thousands of genes in different biological states. In many cases, it is desirable to determine if altered patterns of gene expression correlate with chromosomal abnormalities or assess expression of genes that are contiguous in the genome. We describe a method, differential gene locus mapping (DIGMAP), which aligns the known chromosomal location of a gene to its expression value deduced by microarray analysis. The method partitions microarray data into subsets by chromosomal location for each gene interrogated by an array. Microarray data in an individual subset can then be clustered by physical location of genes at a subchromosomal level based upon ordered alignment in genome sequence. A graphical display is generated by representing each genomic locus with a colored cell that quantitatively reflects its differential expression value. The clustered patterns can be viewed and compared based on their expression signatures as defined by differential values between control and experimental samples. In this study, DIGMAP was tested using previously published studies of breast cancer analyzed by comparative genomic hybridization (CGH) and prostate cancer gene expression profiles assessed by cDNA microarray experiments. Analysis of the breast cancer CGH data demonstrated the ability of DIGMAP to deduce gene amplifications and deletions. Application of the DIGMAP method to the prostate data revealed several carcinoma-related loci, including one at 16q13 with marked differential expression encompassing 19 known genes including 9 encoding metallothionein proteins. We conclude that DIGMAP is a powerful computational tool enabling the coupled analysis of microarray data with genome location.     

An economic perspective on personalized medicine

The concept of personalized medicine not only promises to enhance the life of patients and increase the quality of clinical practice and targeted care pathways, but also to lower overall healthcare costs through early-detection, prevention, accurate risk assessments and efficiencies in care delivery. Current inefficiencies are widely regarded as substantial enough to have a significant impact on the economies of major nations like the US and China, and, therefore the world economy. A recent OECD report estimates healthcare expenditure for some of the developed western and eastern nations to be anywhere from 10% to 18%, and growing (with the US at the highest). Personalized medicine aims to use state-of-the-art genomic technologies, rich medical record data, tissue and blood banks and clinical knowledge that will allow clinicians and payors to tailor treatments to individuals, thereby greatly reducing the costs of ineffective therapies incurred through the current trial and error clinical paradigm. Pivotal to the field are drugs that have been designed to target a specific molecular pathway that has gone wrong and results in a diseased condition and the diagnostic tests that allow clinicians to separate responders from non-responders. However, the truly personalized approach in medicine faces two major problems: complex biology and complex economics; the pathways involved in diseases are quite often not well understood, and most targeted drugs are very expensive. As a result of all current efforts to translate the concepts of personalized healthcare into the clinic, personalized medicine becomes participatory and this implies patient decisions about their own health. Such a new paradigm requires powerful tools to handle significant amounts of personal information with the approach to be known as “P4 medicine”, that is predictive, preventive, personalized and participatory. P4 medicine promises to increase the quality of clinical care and treatments and will ultimately save costs. The greatest challenges are economic, not scientific.     

An interventional magnetic resonance imaging technique for the molecular characterization of intraprostatic dynamic contrast enhancement

The biological characterization of an individual patient's tumor by noninvasive imaging will have an important role in cancer care and clinical research if the molecular processes that underlie the image data are known. Spatial heterogeneity in the dynamics of magnetic resonance imaging contrast enhancement (DCE-MRI) is hypothesized to reflect variations in tumor angiogenesis. Here we demonstrate the feasibility of precisely colocalizing DCE-MRI data with the genomic and proteomic profiles of underlying biopsy tissue using a novel MRI-guided biopsy technique in a patients with prostate cancer.     

Genomic medicine: bringing biomarkers to clinical medicine

An important by-product of sequencing the human genome has been the development of a novel 'toolbox' for biomarker discovery and development. Genomic medicine is an emerging discipline in the genome sciences that integrates these tools to interrogate genomic variation in well-defined populations in order to develop predictors of disease susceptibility, progression and drug response. Several important classes of biomarkers result from these analyses which, when translated to clinical medicine and drug development, will have an important impact on human health and disease. This review highlights both the opportunities and challenges in bringing biomarkers into clinical medicine.     

Cancer genomics: from discovery science to personalized medicine

Recent advances in genome technologies and the ensuing outpouring of genomic information related to cancer have accelerated the convergence of discovery science and clinical medicine. Successful examples of translating cancer genomics into therapeutics and diagnostics reinforce its potential to make possible personalized cancer medicine. However, the bottlenecks along the path of converting a genome discovery into a tangible clinical endpoint are numerous and formidable. In this Perspective, we emphasize the importance of establishing the biological relevance of a cancer genomic discovery in realizing its clinical potential and discuss some of the major obstacles to moving from the bench to the bedside.     

Mining the cancer genome uncovers therapeutic activity of EphA7 against lymphoma

The functional annotation of the cancer genome can reveal new opportunities for cancer therapies. The wealth of genomic data on various cancers has not yet been mined for clinically and therapeutically useful information. We use cross-comparisons of genomic data with the results of unbiased genetic screens to prioritize genomic changes for further study. In this manner, we have identified a soluble variant of the ephrin receptor A7 (EPHA7^TR) as a tumor suppressor that is lost in lymphoma. We also developed antibody-based delivery to restore this tumor suppressor to the cancer cells in situ. We will discuss our strategy of screening genomic data, specific findings concerning EPHA7 and the potential for future discoveries.     

The Impact of Genomic Prof ling for Novel Cancer Therapy–Recent Progress in Non-Small Cell Lung Cancer

There is high expectation for significant improvements in cancer patient care after completion of the human genome project in 2003.Through pains-taking analyses of genomic profiles in cancer patients,a number of targetable gene alterations have been discovered,with some leading to novel therapies,such as activating mutations of EGFR,BRAF and ALK gene fusions.As a result,clinical management of cancer through targeted therapy has finally become a reality for a subset of cancers,such as lung adenocarcinomas and melanomas.In this review,we summarize how gene mutation discovery leads to new treatment strategies using non-small cell lung cancer(NSCLC)as an example.We also discuss possible future implications of cancer genome analyses.     

Multigene delivery in mammalian cells: Recent advances and applications

Systems for multigene delivery in mammalian cells, particularly in the context of genome engineering, have gained a lot of attention in biomolecular research and medicine. Initially these methods were based on RNA polymerase II promoters and were used for the production of protein complexes and for applications in cell biology such as reprogramming of somatic cells to stem cells. Emerging technologies such as CRISPR/Cas9-based genome engineering, which enable any alteration at the genomic level of an organism, require additional elements including U6-driven expression cassettes for RNA expression and homology constructs for designed genome modifications. For these applications, systems with high DNA capacity, flexibility and transfer rates are needed. In this article, we briefly give an update on some of recent strategies that facilitate multigene assembly and delivery into mammalian cells. Also, we review applications in various fields of biology that rely on multigene delivery systems.