Targeted gene therapies: tools, applications, optimization

Many devastating human diseases are caused by mutations in a single gene that prevent a somatic cell from carrying out its essential functions, or by genetic changes acquired as a result of infectious disease or in the course of cell transformation. Targeted gene therapies have emerged as potential strategies for treatment of such diseases. These therapies depend upon rare-cutting endonucleases to cleave at specific sites in or near disease genes. Targeted gene correction provides a template for homology-directed repair, enabling the cell's own repair pathways to erase the mutation and replace it with the correct sequence. Targeted gene disruption ablates the disease gene, disabling its function. Gene targeting can also promote other kinds of genome engineering, including mutation, insertion, or gene deletion. Targeted gene therapies present significant advantages compared to approaches to gene therapy that depend upon delivery of stably expressing transgenes. Recent progress has been fueled by advances in nuclease discovery and design, and by new strategies that maximize efficiency of targeting and minimize off-target damage. Future progress will build on deeper mechanistic understanding of critical factors and pathways.     

抗真菌植物基因工程的策略和进展

所有高等植物都受多种真菌的侵害,水稻的240多种病害中真菌性痫害占90％。,可见真菌病害是世界范围内危害作物产蘑的主要因素之一,是长期以来作物育种学家一直在努力攻克的难题。目前国     

Advanced therapies for the treatment of hemophilia: future perspectives

Monogenic diseases are ideal candidates for treatment by the emerging advanced therapies, which are capable of correcting alterations in protein expression that result from genetic mutation. In hemophilia A and B such alterations affect the activity of coagulation factors VIII and IX, respectively, and are responsible for the development of the disease. Advanced therapies may involve the replacement of a deficient gene by a healthy gene so that it generates a certain functional, structural or transport protein (gene therapy); the incorporation of a full array of healthy genes and proteins through perfusion or transplantation of healthy cells (cell therapy); or tissue transplantation and formation of healthy organs (tissue engineering). For their part, induced pluripotent stem cells have recently been shown to also play a significant role in the fields of cell therapy and tissue engineering. Hemophilia is optimally suited for advanced therapies owing to the fact that, as a monogenic condition, it does not require very high expression levels of a coagulation factor to reach moderate disease status. As a result, significant progress has been possible with respect to these kinds of strategies, especially in the fields of gene therapy (by using viral and non-viral vectors) and cell therapy (by means of several types of target cells). Thus, although still considered a rare disorder, hemophilia is now recognized as a condition amenable to gene therapy, which can be administered in the form of lentiviral and adeno-associated vectors applied to adult stem cells, autologous fibroblasts, platelets and hematopoietic stem cells; by means of non-viral vectors; or through the repair of mutations by chimeric oligonucleotides. In hemophilia, cell therapy approaches have been based mainly on transplantation of healthy cells (adult stem cells or induced pluripotent cell-derived progenitor cells) in order to restore alterations in coagulation factor expression.     

Targeted gene therapies: tools,applications, optimization

Many devastating human diseases are caused by mutations in a single gene that prevent a somatic cell from carrying out its essential functions, or by genetic changes acquired as a result of infectious disease or in the course of cell transformation. Targeted gene therapies have emerged as potential strategies for treatment of such diseases. These therapies depend upon rare-cutting endonucleases to cleave at specific sites in or near disease genes. Targeted gene correction provides a template for homology-directed repair, enabling the cell’s own repair pathways to erase the mutation and replace it with the correct sequence. Targeted gene disruption ablates the disease gene, disabling its function. Gene targeting can also promote other kinds of genome engineering, including mutation, insertion, or gene deletion. Targeted gene therapies present significant advantages compared to approaches to gene therapy that depend upon delivery of stably expressing transgenes. Recent progress has been fueled by advances in nuclease discovery and design, and by new strategies that maximize efficiency of targeting and minimize off-target damage. Future progress will build on deeper mechanistic understanding of critical factors and pathways.     

Recent advances in gene therapy and future prospects

Gene therapy, which is treatment of diseases by introducing normal genes into the body, is becoming feasible as the result of advances in genetic engineering. The hematopoietic stem cells have been considered as the appropriate target for gene transfer in many genetic diseases for which allogeneic bone marrow transplantation has been employed successfully. However, there are still many problems to be solved. In particular, expression from retrovirally transduced genes in bone marrow cells has been transient and unstable. On the other hand, an alternative approach to somatic cell gene therapy using nonhematopoietic cells, including skin fibroblasts, endothelial cells, keratinocytes, and lymphocytes, has been shown to possess several advantages. This kind of approach is usually applied to supplementation therapy in not only hereditary disorders but also various acquired diseases, such as cancer or infectious diseases. Recently, clinical application of gene transfer into lymphocytes to treat cancer and immunodeficiency have been approved at NIH (USA). The trial could represent the start of a new era in molecular medicine.     

CRISPR/Cas system: An emerging technology in stem cell research

The identification of new and even more precise technologies for modifying and manipulating the genome has been a challenge since the discovery of the DNA double helix. The ability to modify selectively specific genes provides a powerful tool for characterizing gene functions, performing gene therapy, correcting specific genetic mutations, eradicating diseases, engineering cells and organisms to achieve new and different functions and obtaining transgenic animals as models for studying specific diseases. Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology has recently revolutionized genome engineering. The application of this new technology to stem cell research allows disease models to be developed to explore new therapeutic tools. The possibility of translating new systems of molecular knowledge to clinical research is particularly appealing for addressing degenerative diseases. In this review, we describe several applications of CRISPR/Cas9 to stem cells related to degenerative diseases. In addition, we address the challenges and future perspectives regarding the use of CRISPR/Cas9 as an important technology in the medical sciences.     

基因治疗与人类健康

随着分子生物学及基因工程技术的迅猛发展 ,基因治疗已经成为治疗人类疾病的重要方法之一 ,同时也是维护人类健康最有发展前景的手段之一。诸如遗传病、肿瘤、和传染病与心血管病的基因治疗。遗传免疫方面 ,病毒性疾病和肿瘤的基因治疗 ,如将病毒抗原基因 (HBsAg)及一些肿瘤抗原基因 (CEA)直接注入人体内而产生抗体 ;人类亚健康状态 ,如肥胖、秃顶、疲劳、衰老等的基因治疗。然而基因治疗目前仍面临着许多困扰 ,如基因治疗的有效性、安全性、及社会伦理等诸多问题 ,因此在临床实际应用中要慎之又慎。只有对基因治疗合理规范和正确引导并遵循伦理原则 ,才能最终推动现代医学的发展。     

Co-clustering phenome�Cgenome for phenotype classification and disease gene discovery

Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways.     

Therapeutic targets in cardiovascular disorders

The feasibility of gene therapy for cardiovascular diseases related to atherosclerosis is a topic that needs to be addressed. Most recent papers have dealt with technical aspects and feasibility and most of the genes transferred were reporter genes like those for β-galactosidase or luciferase. This may mean that the ideal vector, one that is not pathogenic or immunotolerant but is still efficient, is still not available. The results of these studies are ambiguous and it has been doubted whether the genes targeted really affect the disease. Further efforts are therefore needed to elucidate the underlying pathophysiology.     

转录因子在植物抗病基因工程中的研究进展

转录因子与顺式作用元件结合,可调控下游一系列基因的表达。通过基因工程手段使一个抗病转录因子基因在植物中超表达就相当于转入了多个抗病基因,从而提高综合抗病能力,因此,转录因子已成为近年来的研究热点。综述了乙烯应答元件结合因子(Ethylene-responsive element binding factors,AP2/EREBP)、MYB、WRKY、碱性亮氨酸拉链家族和homeodomain蛋白5种植物抗病相关转录因子的结构、功能特性、调控机制以及它们在植物抗病基因工程方面的研究成果,并展望了其应用前景。     

Computational gene knockout reveals transdisease-transgene association structure

Genome-wide association studies for a variety of diseases are identifying increasing numbers of candidate genes. Now we are confronted with the fact that some genes are common candidates across diseases. Thus there is a strong need to develop a hypothesis formulation methodology to comprehend multifaceted associations between genes and diseases. We have developed a computational method for building transdisease-transgene association structure. By introducing the basic rationale underlying the gene knockout approach as an information processing procedure to a network constructed on the basis of hyperlinks between disease and gene pages listed in the Online Mendelian Inheritance in Man (OMIM) database, relations of genes with diseases are computationally quantified. We did successively eliminate gene pages (called "computational gene knockout" in this paper) expected to contribute to metabolic syndrome, and catalogued each association with various disease pages. We thereby apply a co-clustering method to the gene-disease relations to obtain an association structure by classifying diseases and genes simultaneously. Observing an association structure between over 100 diseases and their related genes, we then found that the structure revealed gene classes that were commonly associated with diseases as well as gene classes that were selectively associated with a specific disease class.     

Dawn of ocular gene therapy: implications for molecular diagnosis in retinal disease

Personalized medicine aims to utilize genomic information about patients to tailor treatment. Gene replacement therapy for rare genetic disorders is perhaps the most extreme form of personalized medicine, in that the patients’ genome wholly determines their treatment regimen. Gene therapy for retinal disorders is poised to become a clinical reality. The eye is an optimal site for gene therapy due to the relative ease of precise vector delivery, immune system isolation, and availability for monitoring of any potential damage or side effects. Due to these advantages, clinical trials for gene therapy of retinal diseases are currently underway. A necessary precursor to such gene therapies is accurate molecular diagnosis of the mutation(s) underlying disease. In this review, we discuss the application of Next Generation Sequencing (NGS) to obtain such a diagnosis and identify disease causing genes, using retinal disorders as a case study. After reviewing ocular gene therapy, we discuss the application of NGS to the identification of novel Mendelian disease genes. We then compare current, array based mutation detection methods against next NGS-based methods in three retinal diseases: Leber’s Congenital Amaurosis, Retinitis Pigmentosa, and Stargardt’s disease. We conclude that next-generation sequencing based diagnosis offers several advantages over array based methods, including a higher rate of successful diagnosis and the ability to more deeply and efficiently assay a broad spectrum of mutations. However, the relative difficulty of interpreting sequence results and the development of standardized, reliable bioinformatic tools remain outstanding concerns. In this review, recent advances NGS based molecular diagnoses are discussed, as well as their implications for the development of personalized medicine.     

Construction and phenotypic analysis of mice carrying a duplication of the major histocompatibility class I (MHC-I) locus

Copy number variation (CNV) has been associated increasingly with altered susceptibility to human disease. Large CNVs are likely to incur disease risk or resilience via predictable changes in gene dosage that are relatively straightforward to model using chromosomal engineering in mice. The classical class I major histocompatibility locus (MHC-I) contains a dense set of genes essential for innate immune system function in vertebrates. MHC-I genes are highly polymorphic and genetic variation in the region is associated with altered susceptibility to a wide variety of common diseases. Here we investigated the role of gene dosage within MHC-I on susceptibility to disease by engineering a mouse line carrying a 1.9-Mb duplication of this region [called Dp(MHC-I)]. Extensive phenotypic analysis of heterozygous (3N) Dp(MHC-I) animals did not reveal altered blood and stem cell parameters, susceptibility to high-fat diet, death by cancer, or contact dermatitis. However, several measures of disease severity in a model of atherosclerosis were improved, suggesting dosage-sensitive modulators of cardiovascular disease. Homozygous Dp(MHC-I)/Dp(MHC-I) mice demonstrated embryonic lethality. These mice serve as a model for studying the consequences of targeted gene dosage alteration in MHC-I with functional and evolutionary implications.     

Integration of text- and data-mining using ontologies successfully selects disease gene candidates

Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause diseases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant challenge. Additionally, identifying the genes that cause complex diseases is problematic due to low penetrance of multiple contributing genes. Here, we describe a novel bioinformatic approach that selects candidate disease genes according to their expression profiles. We use the eVOC anatomical ontology to integrate text-mining of biomedical literature and data-mining of available human gene expression data. To demonstrate that our method is successful and widely applicable, we apply it to a database of 417 candidate genes containing 17 known disease genes. We successfully select the known disease gene for 15 out of 17 diseases and reduce the candidate gene set to 63.3% (±18.8%) of its original size. This approach facilitates direct association between genomic data describing gene expression and information from biomedical texts describing disease phenotype, and successfully prioritizes candidate genes according to their expression in disease-affected tissues.     

Molecular genetic approaches to understanding disease.

Molecular genetics has greatly increased the understanding of diseases in which there is a single gene defect such as cystic fibrosis. Discovering the gene responsible and its function not only helps determine the pathogenesis of the disease but also offers a possible treatment-gene therapy. Polygenic disorders such as diabetes may soon yield their secrets to the same approach. Animal models of genetic diseases are proving useful research tools, and transgenesis has made xenografting possible. Furthermore, antisense technology allows specific inhibition of undesirably overexpressed genes such as those driving unwanted vascular cell proliferation and restenosis after angioplasty. The completion of the human genome project should make the search for "disease" gene much quicker and will increase still further the importance of these gene based approaches toward diseases.     

A Pathway-Based View of Human Diseases and Disease Relationships

It is increasingly evident that human diseases are not isolated from each other. Understanding how different diseases are related to each other based on the underlying biology could provide new insights into disease etiology, classification, and shared biological mechanisms. We have taken a computational approach to studying disease relationships through 1) systematic identification of disease associated genes by literature mining, 2) associating diseases to biological pathways where disease genes are enriched, and 3) linking diseases together based on shared pathways. We identified 4,195 candidate disease associated genes for 1028 diseases. On average, about 50% of disease associated genes of a disease are statistically mapped to pathways. We generated a disease network which consists of 591 diseases and 6,931 disease relationships. We examined properties of this network and provided examples of novel disease relationships which cannot be readily captured through simple literature search or gene overlap analysis. Our results could potentially provide insights into the design of novel, pathway-guided therapeutic interventions for diseases.     

Prostate cancer gene therapy-what have we learned and where are we going?

With recent advances in genetic engineering, tumor biology, and immunology, gene therapy has been recognized as a promising new treatment option for various cancers, including prostate cancer. Several clinical trials of prostate cancer gene therapy, using therapeutic genes which include suicide genes, immunomodulatory genes, tumor suppressor genes, and anti-oncogenes, are under way and preliminary reports have emerged. Although gene therapy for prostate cancer is still at an early stage and requires additional technological breakthroughs, new insights obtained from recent clinical trials indicate a promising potential for prostate cancer gene therapy. In this report, general concepts, current progress, and future prospects in prostate cancer gene therapy are summarized.     

Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms

Background

Complex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.

Results

We identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.

Conclusions

Modules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.