title: Application of the rank-based method to DNA methylation for cancer diagnosis.
abstract: Detecting aberrant DNA methylation as diagnostic or prognostic biomarkers for cancer has been a topic of considerable interest recently. However, current classifiers based on absolute methylation values detected from a cohort of samples are typically difficult to be transferable to other cohorts of samples. Here, focusing on relative methylation levels, we employed a modified rank-based method to extract reversal pairs of CpG sites whose relative methylation level orderings differ between disease samples and normal controls for cancer diagnosis. The reversal pairs identified for five cancer types respectively show excellent prediction performance with the accuracy above 95%. Furthermore, when evaluating the reversal pairs identified for one cancer type in an independent cohorts of samples, we found that they could distinguish different subtypes of this cancer or different malignant stages including early stage of this cancer from normal controls. The identified reversal pairs also appear to be specific to cancer type. In conclusion, the reversal pairs detected by the rank-based method could be used for accurate cancer diagnosis, which are transferable to independent cohorts of samples.
authors.affiliation: Bioinformatics Centre, School of Life Science, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Hongdong
authors.initials: H
authors.lastname: Li
authors.affiliation: Bioinformatics Centre, School of Life Science, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Guini
authors.initials: G
authors.lastname: Hong
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Xu
authors.affiliation: Bioinformatics Centre, School of Life Science, University of Electronic Science and Technology of China, Chengdu, China; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China; Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China. Electronic address: guoz@ems.hrbmu.edu.cn.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Guo
mesh_terms: D014408:Biomarkers, Tumor; D019295:Computational Biology / Q000379:methods*; D018899:CpG Islands; D019175:DNA Methylation; D006801:Humans; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000378:metabolism; D011379:Prognosis; D011401:Promoter Regions, Genetic; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D060388:Support Vector Machine
chemical_list: D014408:Biomarkers, Tumor
keywords: Cancer diagnosis; DNA methylation; Rank-based