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.

Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

Breast cancer is a global public health issue as it is the most frequently diagnosed malignancy in women in the Western world with over a million new cases every year worldwide. Previous epigenetic analyses have identified aberrant DNA methylation signatures associated with breast cancer. Methylation alterations resulting in aberrant gene expression are key contributors to breast tumorigenesis. There are more than 100 candidate genes reported throughout the literatures as promoter hypermethylated in breast cancers (Pubmeth web resource). More recently, with the application of genome wide array-based methylation profile analysis and next generation sequencing, hundreds of new methylation candidate genes have been reported to be associated with breast cancer. It is crucial to develop an approach for targeted methylaton resequencing to validate these candidate genes in hundreds of patient samples and develop a breast cancer detection panel for early diagnostics. We have developed a targeted gene bisulfite-sequencing approach using a nanofluidic platform, the Access Array™ system, which enables simultaneous amplification of 48 genetic regions (amplicon) from 48 samples in parallel. We have selected 48 breast cancer associated methylation candidate genes, each commonly reported by multiple literatures. Bisulfite-specific-sequencing (BSP) primers were designed for the promoter regions of these genes. In addition, we have applied a primer design strategy that incorporates sample-specific barcodes and Illumina (Miseq) sequencing adaptors into each amplicon, removing the need for additional library preparation before sequencing. We will present methylation sequencing data collected from amplicon libraries generated using the Access Array system. The 48 promoter regions have been amplified in paired tumor/normal tissues and plasma DNA from 48 breast cancer patients. Our results indicate the excellent utilization of this approach in the validation of methylation biomarkers and selection of detection panel for breast cancer. Citation Format: Jun Wang, Zibo Li, Yepeng Wu, Xinwu Guo, Shengyun Li, Zhi Xiao, Feiyu Chen, Zhongping Deng, Lizhong Dai, Wenjun Yi, Lili Tang. High-throughput methylation sequencing of targeted genes in breast cancer specimens using nanofluidic PCR prepared libraries. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 293. doi:10.1158/1538-7445.AM2014-293