Please use this identifier to cite or link to this item: https://doi.org/10.1016/S1470-2045(10)70005-X
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dc.titleMolecular epidemiology and its current clinical use in cancer management
dc.contributor.authorHartman, M.
dc.contributor.authorLoy, E.Y.
dc.contributor.authorKu, C.S.
dc.contributor.authorChia, K.S.
dc.date.accessioned2011-07-26T03:02:19Z
dc.date.available2011-07-26T03:02:19Z
dc.date.issued2010
dc.identifier.citationHartman, M., Loy, E.Y., Ku, C.S., Chia, K.S. (2010). Molecular epidemiology and its current clinical use in cancer management. The Lancet Oncology 11 (4) : 383-390. ScholarBank@NUS Repository. https://doi.org/10.1016/S1470-2045(10)70005-X
dc.identifier.issn14702045
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/24647
dc.description.abstractThe revelation of the entire human DNA sequence in 2001, and the launching of the international haplotype map (HapMap) project, made the identification of common markers of disease possible, dramatically transforming molecular epidemiology. In recent years, the development of, and discoveries within, human genome research have been rapid, highlighted by the current explosion of genome-wide association studies (GWAS). GWAS aim at finding germline changes that increase cancer risk. An equally important and rapid development had been seen in cancer genomics, with great strides being made in our understanding of somatic mutations that allow and accompany cancer development. In this review we discuss whether it is currently possible to use these new discoveries to aid the reduction of cancer mortality by reducing risk of disease, improving prognosis, and keeping complications due to treatment to a minimum. Findings from GWAS have mostly been used to predict risk, but there is the potential to use them for prognostication and even treatment prediction. Expression arrays have identified prognostic patterns for breast cancer, but few reliable patterns are available for treatment prediction. More importantly, virtually no genetic signatures are available to predict morbidity from treatment. Thus, there is a need to bring different biological techniques together and integrate them with existing clinical oncological care for a simultaneous risk and outcome assessment. © 2010 Elsevier Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S1470-2045(10)70005-X
dc.sourceScopus
dc.typeReview
dc.contributor.departmentEPIDEMIOLOGY & PUBLIC HEALTH
dc.contributor.departmentCENTRE FOR MOLECULAR EPIDEMIOLOGY
dc.description.doi10.1016/S1470-2045(10)70005-X
dc.description.sourcetitleThe Lancet Oncology
dc.description.volume11
dc.description.issue4
dc.description.page383-390
dc.identifier.isiut000276765100025
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