title: Methylation profiling of 48 candidate genes in tumor and matched normal tissues from breast cancer patients.
abstract: Gene-specific methylation alterations in breast cancer have been suggested to occur early in tumorigenesis and have the potential to be used for early detection and prevention. The continuous increase in worldwide breast cancer incidences emphasizes the urgent need for identification of methylation biomarkers for early cancer detection and patient stratification. Using microfluidic PCR-based target enrichment and next-generation bisulfite sequencing technology, we analyzed methylation status of 48 candidate genes in paired tumor and normal tissues from 180 Chinese breast cancer patients. Analysis of the sequencing results showed 37 genes differentially methylated between tumor and matched normal tissues. Breast cancer samples with different clinicopathologic characteristics demonstrated distinct profiles of gene methylation. The methylation levels were significantly different between breast cancer subtypes, with basal-like and luminal B tumors having the lowest and the highest methylation levels, respectively. Six genes (ACADL, ADAMTSL1, CAV1, NPY, PTGS2, and RUNX3) showed significant differential methylation among the 4 breast cancer subtypes and also between the ER +/ER- tumors. Using unsupervised hierarchical clustering analysis, we identified a panel of 13 hypermethylated genes as candidate biomarkers that performed a high level of efficiency for cancer prediction. These 13 genes included CST6, DBC1, EGFR, GREM1, GSTP1, IGFBP3, PDGFRB, PPM1E, SFRP1, SFRP2, SOX17, TNFRSF10D, and WRN. Our results provide evidence that well-defined DNA methylation profiles enable breast cancer prediction and patient stratification. The novel gene panel might be a valuable biomarker for early detection of breast cancer.
authors: The State Key Laboratory of Medical Genetics & School of Life Sciences, Central South University, 172 Tongzipo Road, Changsha, 410013, Hunan, People's Republic of China.
authors: Zibo
authors: Z
authors: Li
authors: Xinwu
authors: X
authors: Guo
authors: Yepeng
authors: Y
authors: Wu
authors: Shengyun
authors: S
authors: Li
authors: Jinhua
authors: J
authors: Yan
authors: Limin
authors: L
authors: Peng
authors: Zhi
authors: Z
authors: Xiao
authors: Shouman
authors: S
authors: Wang
authors: Zhongping
authors: Z
authors: Deng
authors: Lizhong
authors: L
authors: Dai
authors: Wenjun
authors: W
authors: Yi
authors: Kun
authors: K
authors: Xia
authors: Lili
authors: L
authors: Tang
authors: Jun
authors: J
authors: Wang
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000473:pathology; D019175:DNA Methylation / Q000235:genetics*; D055088:Early Detection of Cancer; D005260:Female; D020869:Gene Expression Profiling; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000235:genetics*; D011401:Promoter Regions, Genetic
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins