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http://dx.doi.org/10.5808/GI.2013.11.4.174

Application of Cancer Genomics to Solve Unmet Clinical Needs  

Lee, Se-Hoon (Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine)
Sim, Sung Hoon (Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine)
Kim, Ji-Yeon (Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine)
Cha, SooJin (Cancer Research Institute, Seoul National University College of Medicine)
Song, Ahnah (Cancer Research Institute, Seoul National University College of Medicine)
Publication Information
Genomics & Informatics / v.11, no.4, 2013 , pp. 174-179 More about this Journal
Abstract
The large amount of data on cancer genome research has contributed to our understanding of cancer biology. Indeed, the genomics approach has a strong advantage for analyzing multi-factorial and complicated problems, such as cancer. It is time to think about the actual usage of cancer genomics in the clinical field. The clinical cancer field has lots of unmet needs in the management of cancer patients, which has been defined in the pre-genomic era. Unmet clinical needs are not well known to bioinformaticians and even non-clinician cancer scientists. A personalized approach in the clinical field will bring potential additional challenges to cancer genomics, because most data to now have been population-based rather than individualbased. We can maximize the use of cancer genomics in the clinical field if cancer scientists, bioinformaticians, and clinicians think and work together in solving unmet clinical needs. In this review, we present one imaginary case of a cancer patient, with which we can think about unmet clinical needs to solve with cancer genomics in the diagnosis, prediction of prognosis, monitoring the status of cancer, and personalized treatment decision.
Keywords
drug therapy; early detection of cancer; genomics; health services needs and demand; high-throughput nucleotide sequencing;
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