Multivariate classification of urine metabolome profiles for breast cancer diagnosis

Background: Diagnosis techniques using urine are non-invasive, inexpensive, and easy to perform in clinical settings. The metabolites in urine, as the end products of cellular processes, are closely linked to phenotypes. Therefore, urine metabolome is very useful in marker discoveries and clinical applications. However, only univariate methods have been used in classification studies using urine metabolome. Since multiple genes or proteins would be involved in developments of complex diseases such as breast cancer, multiple compounds including metabolites would be related with the complex diseases, and multivariate methods would be needed to identify those multiple metabolite markers. Moreover, because combinatorial effects among the markers can seriously affect disease developments and there also exist individual differences in genetic makeup or heterogeneity in cancer progressions, single marker is not enough to identify cancers. Results: We proposed classification models using mult...

• Type: Conference
• Year: 2009
• Where: CIKM
• Authors: Younghoon Kim, Imhoi Koo, Byung Hwa Jung, Bong Chul Chung, Doheon Lee
• Keywords: Breast Cancer, CIKM 2009, Database, Univariate Methods, Urine Metabolome