title: Identification of reproducible drug-resistance-related dysregulated genes in small-scale cancer cell line experiments.
abstract: Researchers usually measure only a few technical replicates of two types of cell line, resistant or sensitive to a drug, and use a fold-change (FC) cut-off value to detect differentially expressed (DE) genes. However, the FC cut-off lacks statistical control and is biased towards the identification of genes with low expression levels in both cell lines. Here, viewing every pair of resistant-sensitive technical replicates as an experiment, we proposed an algorithm to identify DE genes by evaluating the reproducibility of the expression difference or FC between every two independent experiments without overlapping samples. Using four small datasets of cancer cell line resistant or sensitive to a drug, we demonstrated that this algorithm could efficiently capture reproducible DE genes significantly enriched in biological pathways relevant to the corresponding drugs, whereas many of them could not be found by the FC and other commonly used methods. Therefore, the proposed algorithm is an effective complement to current approaches for analysing small cancer cell line data.
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108.
authors.forename: Lu
authors.initials: L
authors.lastname: Ao
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108.
authors.forename: Haidan
authors.initials: H
authors.lastname: Yan
authors.affiliation: Biomarker Technologies Corporation, Beijing, 101300.
authors.forename: Tingting
authors.initials: T
authors.lastname: Zheng
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150001.
authors.forename: Hongwei
authors.initials: H
authors.lastname: Wang
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108.
authors.forename: Mengsha
authors.initials: M
authors.lastname: Tong
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108.
authors.forename: Qingzhou
authors.initials: Q
authors.lastname: Guan
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108.
authors.forename: Xiangyu
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108.
authors.forename: Hao
authors.initials: H
authors.lastname: Cai
authors.affiliation: Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108.
authors.forename: Mengyao
authors.initials: M
authors.lastname: Li
authors.affiliation: 1] Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350108 [2] College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150001.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Guo
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D019008:Drug Resistance, Neoplasm; D015972:Gene Expression Regulation, Neoplastic; D045325:HCT116 Cells; D006801:Humans; D061986:MCF-7 Cells