title: Differential expression analysis for individual cancer samples based on robust within-sample relative gene expression orderings across multiple profiling platforms.
abstract: The highly stable within-sample relative expression orderings (REOs) of gene pairs in a particular type of human normal tissue are widely reversed in the cancer condition. Based on this finding, we have recently proposed an algorithm named RankComp to detect differentially expressed genes (DEGs) for individual disease samples measured by a particular platform. In this paper, with 461 normal lung tissue samples separately measured by four commonly used platforms, we demonstrated that tens of millions of gene pairs with significantly stable REOs in normal lung tissue can be consistently detected in samples measured by different platforms. However, about 20% of stable REOs commonly detected by two different platforms (e.g., Affymetrix and Illumina platforms) showed inconsistent REO patterns due to the differences in probe design principles. Based on the significantly stable REOs (FDR<0.01) for normal lung tissue consistently detected by the four platforms, which tended to have large rank differences, RankComp detected averagely 1184, 1335 and 1116 DEGs per sample with averagely 96.51%, 95.95% and 94.78% precisions in three evaluation datasets with 25, 57 and 58 paired lung cancer and normal samples, respectively. Individualized pathway analysis revealed some common and subtype-specific functional mechanisms of lung cancer. Similar results were observed for colorectal cancer. In conclusion, based on the cross-platform significantly stable REOs for a particular normal tissue, differentially expressed genes and pathways in any disease sample measured by any of the platforms can be readily and accurately detected, which could be further exploited for dissecting the heterogeneity of cancer.
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Qingzhou
authors.initials: Q
authors.lastname: Guan
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Rou
authors.initials: R
authors.lastname: Chen
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Haidan
authors.initials: H
authors.lastname: Yan
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Cai
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.|Department of Preventive Medicine, School of Basic Medicine Sciences, Gannan Medical University, Ganzhou, 341000, China.
authors.forename: You
authors.initials: Y
authors.lastname: Guo
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Mengyao
authors.initials: M
authors.lastname: Li
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Xiangyu
authors.initials: X
authors.lastname: Li
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Mengsha
authors.initials: M
authors.lastname: Tong
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Lu
authors.initials: L
authors.lastname: Ao
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Hongdong
authors.initials: H
authors.lastname: Li
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Guini
authors.initials: G
authors.lastname: Hong
authors.affiliation: Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Guo
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008168:Lung / Q000378:metabolism; D008175:Lung Neoplasms / Q000235:genetics*; D015233:Models, Statistical; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D015203:Reproducibility of Results
keywords: differentially expressed genes; gene expression profiling; heterogeneity of cancer; individual level; multiple platforms