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Methylation profiling of 48 candidate genes in tumor and matched normal tissues from breast cancer patients

  • Epidemiology
  • Published:
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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.

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Abbreviations

BSP:

Bisulfite sequencing primer

ER:

Estrogen receptor

PR:

Progesterone receptor

HER2:

Human epidermal growth factor receptor-2

IFCs:

Integrated fluidic circuits

TP:

True positive

FP:

False positive

TN:

True negative

FN:

False negative

ROC:

Receiver operating characteristics

AUC:

Area under the ROC curve

MLR:

Multivariate logistics regression

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Acknowledgments

This work was supported in part by grants from the Natural Science Foundation of China (No. 81272296), the Scientific Project of China Hunan Provincial Science and Technology Department (No. 2012SK2013), and the Major Special Projects of the Science and Technology Bureau of Changsha, China (Nos. K1204017-31 and K1306011-31). Zibo Li was supported by the Hunan Province Postgraduate Student Scientific Innovation Project, China (No. CX2013B087).

Ethical standards

We declare that the experiments performed in this study comply with the current laws of the People’s Republic of China.

Conflict of interest

Xingwu Guo, Limin Peng, Zhongping Deng, and Lizhong Dai are employees of Sanway Gene Technology Inc.

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    Authors and Affiliations

    1. 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

      Zibo Li, Yepeng Wu, Jinhua Yan, Kun Xia & Jun Wang

    2. Sanway Gene Technology Inc., Changsha, 410205, Hunan, People’s Republic of China

      Xinwu Guo, Limin Peng, Zhongping Deng & Lizhong Dai

    3. Department of Breast Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, People’s Republic of China

      Shengyun Li, Zhi Xiao, Shouman Wang & Lili Tang

    4. Department of Breast and Thyroid Surgery, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, People’s Republic of China

      Wenjun Yi

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    1. Zibo Li
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    2. Xinwu Guo
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    Correspondence to Lili Tang or Jun Wang.

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    Zibo Li, Xinwu Guo and Yepeng Wu have contributed equally.

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    Li, Z., Guo, X., Wu, Y. et al. Methylation profiling of 48 candidate genes in tumor and matched normal tissues from breast cancer patients. Breast Cancer Res Treat 149, 767–779 (2015). https://doi.org/10.1007/s10549-015-3276-8

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