title: Multivariate classification of urine metabolome profiles for breast cancer diagnosis.
abstract: 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 multivariate classification techniques and developed an analysis procedure for classification studies using metabolome data. Through this strategy, we identified five potential urinary biomarkers for breast cancer with high accuracy, among which the four biomarker candidates were not identifiable by only univariate methods. We also proposed potential diagnosis rules to help in clinical decision making. Besides, we showed that combinatorial effects among multiple biomarkers can enhance discriminative power for breast cancer.
  
  
  CONCLUSIONS
  In this study, we successfully showed that multivariate classifications are needed to precisely diagnose breast cancer. After further validation with independent cohorts and experimental confirmation, these marker candidates will likely lead to clinically applicable assays for earlier diagnoses of breast cancer.
authors.affiliation: Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.
authors.forename: Younghoon
authors.initials: Y
authors.lastname: Kim
authors.forename: Imhoi
authors.initials: I
authors.lastname: Koo
authors.forename: Byung Hwa
authors.initials: BH
authors.lastname: Jung
authors.forename: Bong Chul
authors.initials: BC
authors.lastname: Chung
authors.forename: Doheon
authors.initials: D
authors.lastname: Lee
mesh_terms: D000328:Adult; D001185:Artificial Intelligence; D014408:Biomarkers, Tumor / Q000652:urine*; D001943:Breast Neoplasms / Q000378:metabolism / Q000652:urine*; D016022:Case-Control Studies; D003663:Decision Trees; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D008875:Middle Aged; D015999:Multivariate Analysis
chemical_list: D014408:Biomarkers, Tumor
references.citation: Toxicol Pathol. 2005;33(4):425-33
references.pmid: 16036859
references.citation: Lancet Oncol. 2006 Mar;7(3):230-40
references.pmid: 16510332
references.citation: Mol Cell Proteomics. 2009 Mar;8(3):558-70
references.pmid: 19008263
references.citation: Cancer Res. 2006 Nov 15;66(22):10795-804
references.pmid: 17108116
references.citation: Am J Clin Nutr. 2007 Dec;86(6):1687-93
references.pmid: 18065587
references.citation: BMC Bioinformatics. 2007 Nov 01;8 Suppl 7:S3
references.pmid: 18047726
references.citation: J Proteome Res. 2008 Aug;7(8):3597-601
references.pmid: 18620448
references.citation: Proc Natl Acad Sci U S A. 2007 Jan 23;104(4):1307-12
references.pmid: 17220270
references.citation: Lancet. 2006 Sep 16;368(9540):1012-21
references.pmid: 16980117
references.citation: Chem Res Toxicol. 2009 Jan;22(1):118-28
references.pmid: 19099400
references.citation: Bioinformatics. 2006 Mar 1;22(5):634-6
references.pmid: 16403790
references.citation: Anal Biochem. 2007 Apr 15;363(2):185-95
references.pmid: 17316536
references.citation: Transplant Proc. 1995 Oct;27(5):2571-2
references.pmid: 7482830
references.citation: Nat Biotechnol. 2004 Nov;22(11):1459-66
references.pmid: 15529173
references.citation: BMC Bioinformatics. 2005 Jul 18;6:179
references.pmid: 16026613
references.citation: Plant Mol Biol. 2002 Jan;48(1-2):155-71
references.pmid: 11860207