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Wang C, Pu W, Zhao D, Zhou Y, Lu T, Chen S, He Z, Feng X, Wang Y, Li C, Li S, Jin L, Guo S, Wang J, Wang M. Identification of Hyper-Methylated Tumor Suppressor Genes-Based Diagnostic Panel for Esophageal Squamous Cell Carcinoma (ESCC) in a Chinese Han Population. Front Genet 2018; 9:356. [PMID: 30233644 PMCID: PMC6133993 DOI: 10.3389/fgene.2018.00356] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 08/20/2018] [Indexed: 12/22/2022] Open
Abstract
DNA methylation-based biomarkers were suggested to be promising for early cancer diagnosis. However, DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC), especially in Chinese Han populations have not been identified and evaluated quantitatively. Candidate tumor suppressor genes (N = 65) were selected through literature searching and four public high-throughput DNA methylation microarray datasets including 136 samples totally were collected for initial confirmation. Targeted bisulfite sequencing was applied in an independent cohort of 94 pairs of ESCC and normal tissues from a Chinese Han population for eventual validation. We applied nine different classification algorithms for the prediction to evaluate to the prediction performance. ADHFE1, EOMES, SALL1 and TFPI2 were identified and validated in the ESCC samples from a Chinese Han population. All four candidate regions were validated to be significantly hyper-methylated in ESCC samples through Wilcoxon rank-sum test (ADHFE1, P = 1.7 × 10-3; EOMES, P = 2.9 × 10-9; SALL1, P = 3.9 × 10-7; TFPI2, p = 3.4 × 10-6). Logistic regression based prediction model shown a moderately ESCC classification performance (Sensitivity = 66%, Specificity = 87%, AUC = 0.81). Moreover, advanced classification method had better performances (random forest and naive Bayes). Interestingly, the diagnostic performance could be improved in non-alcohol use subgroup (AUC = 0.84). In conclusion, our data demonstrate the methylation panel of ADHFE1, EOMES, SALL1 and TFPI2 could be an effective methylation-based diagnostic assay for ESCC.
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Affiliation(s)
- Chenji Wang
- Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China
| | - Weilin Pu
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Dunmei Zhao
- Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China
| | - Yinghui Zhou
- Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China
| | - Ting Lu
- Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China
| | - Sidi Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Zhenglei He
- Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China
| | - Xulong Feng
- Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China
| | - Ying Wang
- Genesky Biotechnologies Inc., Shanghai, China
| | - Caihua Li
- Genesky Biotechnologies Inc., Shanghai, China
| | - Shilin Li
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Shicheng Guo
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, United States
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Minghua Wang
- Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China
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Kozak D, Kithva P, Bax J, Surawski PPT, Monteiro MJ, Trau M. Development of encoded particle-polymer arrays for the accelerated screening of antifouling layers. Chem Commun (Camb) 2011; 47:9687-9. [PMID: 21773613 DOI: 10.1039/c1cc13571f] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A multiplexed screening methodology for the rapid development of antifouling polymer surfaces is presented. An array of protein resistant polymer layers with high grafting (>100 mg m(-2)) were polymerized on optically encoded particles. Multiplexed analysis showed a 97% reduction in nonspecific protein adsorption for all polymer layers created.
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Affiliation(s)
- Darby Kozak
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, Australia 4072.
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