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Cancer Genome Sequencing and Its Implications for Personalized Cancer Vaccines  [PDF]
Lijin Li,Peter Goedegebuure,Elaine R. Mardis,Matthew J.C. Ellis,Xiuli Zhang,John M. Herndon,Timothy P. Fleming,Beatriz M. Carreno,Ted H. Hansen,William E. Gillanders
Cancers , 2011, DOI: 10.3390/cancers3044191
Abstract: New DNA sequencing platforms have revolutionized human genome sequencing. The dramatic advances in genome sequencing technologies predict that the $1,000 genome will become a reality within the next few years. Applied to cancer, the availability of cancer genome sequences permits real-time decision-making with the potential to affect diagnosis, prognosis, and treatment, and has opened the door towards personalized medicine. A promising strategy is the identification of mutated tumor antigens, and the design of personalized cancer vaccines. Supporting this notion are preliminary analyses of the epitope landscape in breast cancer suggesting that individual tumors express significant numbers of novel antigens to the immune system that can be specifically targeted through cancer vaccines.
Personalized Targeted Therapy for Lung Cancer  [PDF]
Kehua Wu,Larry House,Wanqing Liu,William C.S. Cho
International Journal of Molecular Sciences , 2012, DOI: 10.3390/ijms130911471
Abstract: Lung cancer has long been recognized as an extremely heterogeneous disease, since its development is unique in every patient in terms of clinical characterizations, prognosis, response and tolerance to treatment. Personalized medicine refers to the use of markers to predict which patient will most likely benefit from a treatment. In lung cancer, the well-developed epidermal growth factor receptor (EGFR) and the newly emerging EML4-anaplastic lymphoma kinase (ALK) are important therapeutic targets. This review covers the basic mechanism of EGFR and EML4-ALK activation, the predictive biomarkers, the mechanism of resistance, and the current targeted tyrosine kinase inhibitors. The efficacy of EGFR and ALK targeted therapies will be discussed in this review by summarizing the prospective clinical trials, which were performed in biomarker-based selected patients. In addition, the revolutionary sequencing and systems strategies will also be included in this review since these technologies will provide a comprehensive understanding in the molecular characterization of cancer, allow better stratification of patients for the most appropriate targeted therapies, eventually resulting in a more promising personalized treatment. The relatively low incidence of EGFR and ALK in non-Asian patients and the lack of response in mutant patients limit the application of the therapies targeting EGFR or ALK. Nevertheless, it is foreseeable that the sequencing and systems strategies may offer a solution for those patients.
Next-Generation Sequencing: From Understanding Biology to Personalized Medicine  [PDF]
Karen S. Frese,Hugo A. Katus,Benjamin Meder
Biology , 2013, DOI: 10.3390/biology2010378
Abstract: Within just a few years, the new methods for high-throughput next-generation sequencing have generated completely novel insights into the heritability and pathophysiology of human disease. In this review, we wish to highlight the benefits of the current state-of-the-art sequencing technologies for genetic and epigenetic research. We illustrate how these technologies help to constantly improve our understanding of genetic mechanisms in biological systems and summarize the progress made so far. This can be exemplified by the case of heritable heart muscle diseases, so-called cardiomyopathies. Here, next-generation sequencing is able to identify novel disease genes, and first clinical applications demonstrate the successful translation of this technology into personalized patient care.
Critical role of bioinformatics in translating huge amounts of next-generation sequencing data into personalized medicine
HuiXiao Hong,WenQian Zhang,Jie Shen,ZhenQiang Su,BaiTang Ning,Tao Han,Roger Perkins,LeMing Shi,WeiDa Tong
Science China Life Sciences , 2013, DOI: 10.1007/s11427-013-4439-7
Abstract: Realizing personalized medicine requires integrating diverse data types with bioinformatics. The most vital data are genomic information for individuals that are from advanced next-generation sequencing (NGS) technologies at present. The technologies continue to advance in terms of both decreasing cost and sequencing speed with concomitant increase in the amount and complexity of the data. The prodigious data together with the requisite computational pipelines for data analysis and interpretation are stressors to IT infrastructure and the scientists conducting the work alike. Bioinformatics is increasingly becoming the rate-limiting step with numerous challenges to be overcome for translating NGS data for personalized medicine. We review some key bioinformatics tasks, issues, and challenges in contexts of IT requirements, data quality, analysis tools and pipelines, and validation of biomarkers.
Pharmacogenomics and personalized medicine: the plunge into next-generation sequencing
Mia Wadelius, Ana Alfirevic
Genome Medicine , 2011, DOI: 10.1186/gm294
Abstract: In recent years, pharmacogenomics has moved beyond candidate gene and genome-wide association studies (GWASs) towards truly personalized genomics. The use of new biotechnological, mathematical and computational tools has enabled an exponential increase in the number of biomarkers for drug safety and efficacy; however, their clinical utility in achieving personalized therapy remains to be determined. Here we cover current expert opinions concerning emerging pharmacogenomic technologies, international consortia and collaborations including underrepresented populations, development of personalized medicine and clinical relevance of pharmacogenetic testing. In addition, future directives presented at the meeting are discussed.Since the first Wellcome Trust/Cold Spring Harbor Laboratory meeting on pharmacogenetics in 2003, the field has evolved into pharmacogenomics through a shift from candidate gene studies to GWASs. Such large-scale studies enable simultaneous detection of > 1 million SNPs that can be tested for association with drug-related outcomes, and verified by replication in separate cohorts. The development of next-generation sequencing (NGS) technology has led to a drastic drop in the cost (> 10,000-fold) and time (from 10 years to 1 week) needed to sequence a genome. NGS is now being introduced as a method to personalize medicine.Yingrui Li (Beijing Genomics Institute, China) described the sequencing revolution that has made personal genomes affordable, while it remains difficult and costly to interpret the results. Recent whole genome sequencing of individuals at the Beijing Genomics Institute has shown an excess of rare deleterious SNPs together with extensive structural variations and novel individual specific sequences with potential functional impact. These new genetic variants are likely to explain part of the missing heritability seen with previous GWASs. Interestingly, Li reported that more ethnic-specific haplotypes exist than previously thought and
Perspectives of DNA microarray and next-generation DNA sequencing technologies
XiaoKun Teng,HuaSheng Xiao
Science China Life Sciences , 2009, DOI: 10.1007/s11427-009-0012-9
Abstract: DNA microarray and next-generation DNA sequencing technologies are important tools for high-throughput genome research, in revealing both the structural and functional characteristics of genomes. In the past decade the DNA microarray technologies have been widely applied in the studies of functional genomics, systems biology and pharmacogenomics. The next-generation DNA sequencing method was first introduced by the 454 Company in 2003, immediately followed by the establishment of the Solexa and Solid techniques by other biotech companies. Though it has not been long since the first emergence of this technology, with the fast and impressive improvement, the application of this technology has extended to almost all fields of genomics research, as a rival challenging the existing DNA microarray technology. This paper briefly reviews the working principles of these two technologies as well as their application and perspectives in genome research.
Promising Communication Technologies for Emergency and Safety Systems
Anwar M. Mousa
International Journal of Engineering and Advanced Technology , 2013,
Abstract: this article discusses the uses of promising modern communication technologies for emergency and safety systems focusing on cognitive radio technologies and their roles in effective spectrum use. Given that only 10% to 30% of licensed spectrum is occupied in a specific time and locations, the remaining unused spectrum constitutes a huge room for increasing bandwidth and hence the number of served users in emergency events. Based on cognitive radio and sensed spectrum holes, the paper developed new approximated linear relations between the total number of served users in emergency situations as a function of total available bandwidth. Results show that increasing the number of channels per cell, as a result of sensed spectrum holes, yields a significant increase in cell capacity and the number of served users. The paper begins with highlighting the impact of current andpromising communications technologies on strengthening disaster awareness and mitigation.
Perspectives of DNA microarray and next-generation DNA sequencing technologies

TENG XiaoKun &,XIAO HuaSheng,

中国科学C辑(英文版) , 2009,
Abstract: DNA microarray and next-generation DNA sequencing technologies are important tools for high-throughput genome research, in revealing both the structural and functional characteristics of genomes. In the past decade the DNA microarray technologies have been widely applied in the studies of functional genomics, systems biology and pharmacogenomics. The next-generation DNA sequencing method was first introduced by the 454 Company in 2003, immediately followed by the establishment of the Solexa and Solid techniques by other biotech companies. Though it has not been long since the first emergence of this technology, with the fast and impressive improvement, the application of this technology has extended to almost all fields of genomics research, as a rival challenging the existing DNA microarray technology. This paper briefly reviews the working principles of these two technologies as well as their application and perspectives in genome research. Supported by the National High-Tech Research Program of China (Grant No.2006AA020704) and Shanghai Science and Technology Commission (Grant No. 05DZ22201)
Next Generation Digital Commerce Technologies
Muzhir Shaban Al-Ani
International Journal of Interactive Mobile Technologies (iJIM) , 2009, DOI: 10.3991/ijim.v3i2.655
Abstract: This paper deals with the demonstration of commerce technologies and concentration on the next generation technologies. The development of high advance technologies in telecommunications such as internet and mobile telephony leads to massive support for digital commerce. The main feature of the third generation mobile internet protocol addressing introduced an access to the internet through mobile. The trends of next generation digital commerce try to overcome all the commercial problems and to develop a fast secure and intelligent commerce depending on the high performance next generation technologies.
TANGRAM for Personalized Learning Using the Semantic Web Technologies
Jelena Jovanovic,Dragan Ga?evi?,Vladan Deved?i?
Journal of Emerging Technologies in Web Intelligence , 2009, DOI: 10.4304/jetwi.1.1.6-21
Abstract: Motivated with the goal to provide dynamic assembly and personalization of learning content parts, we propose an ontology-based solution implemented as an integrated learning environment called TANGRAM. TANGRAM relies on two ontologies for representing learning object (LO) content structure and LO content type (i.e. pedagogical role). LO content described by those two ontologies is further annotated with concepts of a domain ontology, while a learning paths ontology is used to specify pedagogical relations (e.g. prerequisites) among domain concepts. A user model ontology is defined to represent relevant information about TANGRAM’s users. The paper presents the employed ontologies, in the context of user modeling and personalization. Furthermore, it describes the algorithm we defined to dynamically assemble content units into learning content personalized to the user’s domain knowledge, preferences, and learning styles. We also discuss our experiences with dynamic content generation and summarize results of the conducted evaluation study. Although TAGRAM is a general-purpose learning environment, in this paper, we analyze it in the domain of intelligent information systems.
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