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Wang Y, Zhang M, Hu X, Qin W, Wu H, Wei M. Colon cancer-specific diagnostic and prognostic biomarkers based on genome-wide abnormal DNA methylation. Aging (Albany NY) 2020; 12:22626-22655. [PMID: 33202377 PMCID: PMC7746390 DOI: 10.18632/aging.103874] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 07/25/2020] [Indexed: 12/11/2022]
Abstract
Abnormal DNA methylation is a major early contributor to colon cancer (COAD) development. We conducted a cohort-based systematic investigation of genome-wide DNA methylation using 299 COAD and 38 normal tissue samples from TCGA. Through conditional screening and machine learning with a training cohort, we identified one hypomethylated and nine hypermethylated differentially methylated CpG sites as potential diagnostic biomarkers, and used them to construct a COAD-specific diagnostic model. Unlike previous models, our model precisely distinguished COAD from nine other cancer types (e.g., breast cancer and liver cancer; error rate ≤ 0.05) and from normal tissues in the training cohort (AUC = 1). The diagnostic model was verified using a validation cohort from The Cancer Genome Atlas (AUC = 1) and five independent cohorts from the Gene Expression Omnibus (AUC ≥ 0.951). Using Cox regression analyses, we established a prognostic model based on six CpG sites in the training cohort, and verified the model in the validation cohort. The prognostic model sensitively predicted patients’ survival (p ≤ 0.00011, AUC ≥ 0.792) independently of important clinicopathological characteristics of COAD (e.g., gender and age). Thus, our DNA methylation analysis provided precise biomarkers and models for the early diagnosis and prognostic evaluation of COAD.
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Affiliation(s)
- Yilin Wang
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Ming Zhang
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Xiaoyun Hu
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Wenyan Qin
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Huizhe Wu
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Minjie Wei
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
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AlShibli A, Mathkour H. Fuzzy methods for the detection of copy number variations in comparative genomic hybridization arrays. Saudi J Biol Sci 2020; 27:3647-3654. [PMID: 33304176 PMCID: PMC7714972 DOI: 10.1016/j.sjbs.2020.08.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 08/02/2020] [Accepted: 08/03/2020] [Indexed: 11/19/2022] Open
Abstract
Genomic copy number variations (CNVs) are considered as a significant source of genetic diversity and widely involved in gene expression and regulatory mechanism, genetic disorders and disease risk, susceptibility to certain diseases and conditions, and resistance to medical drugs. Many studies have targeted the identification, profiling, analysis, and associations of genetic CNVs. We propose herein two new fuzzy methods, taht is, one based on the fuzzy inference from the pre-processed input, and another based on fuzzy C-means clustering. Our solutions present a higher true positive rate and a lower false negative with no false positive, efficient performance and consumption of least resources.
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Affiliation(s)
- Ahmad AlShibli
- Department of computer science, College of computer and information sciences, King Saud University, Riyadh, Saudi Arabia
- Corresponding author at: P.O. Box 230734, Riyadh, Saudi Arabia.
| | - Hassan Mathkour
- Department of computer science, College of computer and information sciences, King Saud University, Riyadh, Saudi Arabia
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