Dataset Information

Identification of Hyper-Methylated Tumor Suppressor Genes-Based Diagnostic Panel for Esophageal Squamous Cell Carcinoma (ESCC) in a Chinese Han Population.

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.

SUBMITTER: Wang C

PROVIDER: S-EPMC6133993 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Identification of Hyper-Methylated Tumor Suppressor Genes-Based Diagnostic Panel for Esophageal Squamous Cell Carcinoma (ESCC) in a Chinese Han Population.

Wang Chenji C Pu Weilin W Zhao Dunmei D Zhou Yinghui Y Lu Ting T Chen Sidi S He Zhenglei Z Feng Xulong X Wang Ying Y Li Caihua C Li Shilin S Jin Li L Guo Shicheng S Wang Jiucun J Wang Minghua M

Frontiers in genetics 20180905

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 (<i>N</i> = 65) were selected through literature searching and four public high-throughput DNA methylation microarray datasets including 136 samples totally were collected for initial confirmat ...[more]

PMID: 30233644

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Project description: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.

Project description:MicroRNAs (miRNAs) are an endogenous conserved class of non-coding 20–22 nt small RNAs that regulate gene expression at post-transcriptional level by mostly binding to 3′-UTR of target mRNAs, leading to mRNA degradation or translation inhibition. Recent reports demonstrate a role for miRNA expression in the disease progression and outcome. By now, many researcher focusing on miRNA expression profiles in Barrett's esophagus and esophageal adenocarcinoma have been reported. Nevertheless, there is still a little information available about specific miRNA expression pattern and their roles in ESCC. To develop novel diagnostic and therapeutic targets for esophageal squamous cancer, we first investigated the expression profile of miRNA in three pairs of ESCC clinical samples. Tissues of ESCC and the matched normal counterparts were obtained from surgical specimens immediately after resection from patients undergoing primary surgical treatment of esophageal carcinoma from the Department of Tumor Surgery of Shantou Central Hospital, China. RNA labeling and hybridization were completed by KangChen Bio-tech Inc. (Shanghai, China) according to the manufacturer's instructions. Briefly, total RNA from three pairs of esophageal carcinoma and matched normal tissues were isolated by Trizol (Invitrogen, USA) and purified by RNeasy mini kit (QIAGEN, German). The concentration and quality of total RNA were measured by NanoDrop ND-1000 at 260 and 280 nm (A260/280) and checked by gel electrophoresis. Each RNA sample from three pairs of ESCC was separately labeled either using the miRCURY Hy3/Hy5 labeling kit and hybridized on the six miRCURYTM locked nucleic acid (LNA) array version 11.0 (Exiqon, Denmark), which contains probes for 1700 mature miRNA. Scans were quantified by using GenePix software (Molecular Devices). The data were exported to Microsoft Excel worksheets, log2 transformed, normalized using global Lowess (Locally Weighted Scatter plot Smoothing) regression algorithm (MIDAS, TIGR Microarray Data Analysis System).

Dataset Information

Identification of Hyper-Methylated Tumor Suppressor Genes-Based Diagnostic Panel for Esophageal Squamous Cell Carcinoma (ESCC) in a Chinese Han Population.

Publications

Identification of Hyper-Methylated Tumor Suppressor Genes-Based Diagnostic Panel for Esophageal Squamous Cell Carcinoma (ESCC) in a Chinese Han Population.

Similar Datasets

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