Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học 'Respiratory Research cung cấp cho các bạn kiến thức về ngành y đề tài: Genomic approaches to research in lung cancer Edward Gabrielson. | http content 1 1 036 Review Genomic approaches to research in lung cancer Edward Gabrielson The Johns Hopkins University School of Medicine Baltimore USA Received 21 April 2000 Revisions requested 11 May 2000 Revisions received 1 June 2000 Accepted 1 June 2000 Published 23 June 2000 Respir Res 2000 1 36-39 Current Science Ltd Print ISSN 1465-9921 Online ISSN 1465-993X Abstract The medical research community is experiencing a marked increase in the amount of information available on genomic sequences and genes expressed by humans and other organisms. This information offers great opportunities for improving our understanding of complex diseases such as lung cancer. In particular we should expect to witness a rapid increase in the rate of discovery of genes involved in lung cancer pathogenesis and we should be able to develop reliable molecular criteria for classifying lung cancers and predicting biological properties of individual tumors. Achieving these goals will require collaboration by scientists with specialized expertise in medicine molecular biology and decision-based statistical analysis. Keywords cDNA arrays genomics lung cancer Introduction Genomics - the discipline that characterizes the structural and functional anatomy of the genome - has attracted continuously increased interest and investment over the past decade. The complete sequencing of the human genome is expected within a few years together with the identification of expressed sequences and polymorphic sequences a vast information infrastructure will be available to medical researchers throughout the world. The rationale for this ambitious project is now well known to the medical community. The discovery of genes involved in the pathogenesis of human diseases will it is hoped lead to new targets for diagnosis and treatment of those diseases. Knowing the polymorphisms that make each of us unique individuals could be the key in the future to predicting individual risks for
