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Targeted bisulfite sequencing identified a panel of DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC)
- Source :
- Clinical Epigenetics, Vol 9, Iss 1, Pp 1-12 (2017), Clinical Epigenetics
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- Background DNA methylation has been implicated as a promising biomarker for precise cancer diagnosis. However, limited DNA methylation-based biomarkers have been described in esophageal squamous cell carcinoma (ESCC). Methods A high-throughput DNA methylation dataset (100 samples) of ESCC from The Cancer Genome Atlas (TCGA) project was analyzed and validated along with another independent dataset (12 samples) from the Gene Expression Omnibus (GEO) database. The methylation status of peripheral blood mononuclear cells and peripheral blood leukocytes from healthy controls was also utilized for biomarker selection. The candidate CpG sites as well as their adjacent regions were further validated in 94 pairs of ESCC tumor and adjacent normal tissues from the Chinese Han population using the targeted bisulfite sequencing method. Logistic regression and several machine learning methods were applied for evaluation of the diagnostic ability of our panel. Results In the discovery stage, five hyper-methylated CpG sites were selected as candidate biomarkers for further analysis as shown below: cg15830431, P = 2.20 × 10−4; cg19396867, P = 3.60 × 10−4; cg20655070, P = 3.60 × 10−4; cg26671652, P = 5.77 × 10−4; and cg27062795, P = 3.60 × 10−4. In the validation stage, the methylation status of both the five CpG sites and their adjacent genomic regions were tested. The diagnostic model based on the combination of these five genomic regions yielded a robust performance (sensitivity = 0.75, specificity = 0.88, AUC = 0.85). Eight statistical models along with five-fold cross-validation were further applied, in which the SVM model reached the best accuracy in both training and test dataset (accuracy = 0.82 and 0.80, respectively). In addition, subgroup analyses revealed a significant difference in diagnostic performance between the alcohol use and non-alcohol use subgroups. Conclusions Methylation profiles of the five genomic regions covering cg15830431 (STK3), cg19396867, cg20655070, cg26671652 (ZNF418), and cg27062795 (ZNF542) can be used for effective methylation-based testing for ESCC diagnosis. Electronic supplementary material The online version of this article (10.1186/s13148-017-0430-7) contains supplementary material, which is available to authorized users.
- Subjects :
- Male
0301 basic medicine
Oncology
Esophageal Neoplasms
Bisulfite sequencing
lcsh:Medicine
Serine-Threonine Kinase 3
Epigenesis, Genetic
Machine Learning
0302 clinical medicine
Databases, Genetic
Diagnosis
Promoter Regions, Genetic
Early Detection of Cancer
Genetics (clinical)
DNA methylation
Methylation
Middle Aged
DNA-Binding Proteins
CpG site
030220 oncology & carcinogenesis
Carcinoma, Squamous Cell
Biomarker (medicine)
Female
Targeted bisulfite sequencing
Pseudogenes
medicine.medical_specialty
lcsh:QH426-470
Pseudogene
Protein Serine-Threonine Kinases
Biology
Sensitivity and Specificity
Peripheral blood mononuclear cell
03 medical and health sciences
Esophageal squamous cell carcinoma
Internal medicine
Biomarkers, Tumor
Genetics
medicine
Humans
Molecular Biology
Aged
Research
lcsh:R
Sequence Analysis, DNA
Biomarker
Human genetics
Repressor Proteins
lcsh:Genetics
Logistic Models
030104 developmental biology
CpG Islands
Developmental Biology
Subjects
Details
- ISSN :
- 18687083 and 18687075
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Clinical Epigenetics
- Accession number :
- edsair.doi.dedup.....9b5cfde20d5c135078bfb694eeec838d