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. 2011 Jan 24;6(1):e16080.
doi: 10.1371/journal.pone.0016080.

Hypermethylation of tumor suppressor genes involved in critical regulatory pathways for developing a blood-based test in breast cancer

Ramin Radpour  1 , Zeinab Barekati, Corina Kohler, Qing Lv, Nicole Bürki, Claude Diesch, Johannes Bitzer, Hong Zheng, Seraina Schmid, Xiao Yan Zhong
Affiliations

Hypermethylation of tumor suppressor genes involved in critical regulatory pathways for developing a blood-based test in breast cancer

Ramin Radpour et al. PLoS One. .

Abstract

Background: Aberrant DNA methylation patterns might be used as a biomarker for diagnosis and management of cancer patients.

Methods and findings: To achieve a gene panel for developing a breast cancer blood-based test we quantitatively assessed the DNA methylation proportion of 248 CpG sites per sample (total of 31,248 sites in all analyzed samples) on 10 candidate genes (APC, BIN1, BMP6, BRCA1, CST6, ESR-b, GSTP1, P16, P21 and TIMP3). The number of 126 samples consisting of two different cohorts was used (first cohort: plasma samples from breast cancer patients and normal controls; second cohort: triple matched samples including cancerous tissue, matched normal tissue and serum samples). In the first cohort, circulating cell free methylated DNA of the 8 tumor suppressor genes (TSGs) was significantly higher in patients with breast cancer compared to normal controls (P<0.01). In the second cohort containing triple matched samples, seven genes showed concordant hypermethylated profile in tumor tissue and serum samples compared to normal tissue (P<0.05). Using eight genes as a panel to develop a blood-based test for breast cancer, a sensitivity and specificity of more than 90% could be achieved in distinguishing between tumor and normal samples.

Conclusions: Our study suggests that the selected TSG panel combined with the high-throughput technology might be a useful tool to develop epigenetic based predictive and prognostic biomarker for breast cancer relying on pathologic methylation changes in tumor tissue, as well as in circulation.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Methylation profiling of 10 candidate genes in two studied cohorts.
A) An example of high-throughput methylation analysis of CpG sites for the BRCA1 gene for the 60 triple samples (cancerous tissue, matched normal tissue and serum samples). The complete data for the other genes is summarized in Dataset S1. B) Peaks show percentage of methylation extent obtained from an informative CpG site of BRCA1 gene with a significant difference between serum and tumor with normal tissue in a triple case. C) Double dendrogram profiles the mean methylation proportion of all 10 studied genes in plasma samples from breast cancer patients and normal subjects. D) Double dendrogram profiles the mean methylation proportion of all 10 studied genes in triple matched samples. E) PCA mapping of the mean methylation proportion of analyzed genes in plasma samples. F) PCA mapping of the mean methylation proportion of analyzed genes in triple matched samples.
Figure 2
Figure 2. Comparison between quantitative methylation analyses of 10 candidate genes.
A) Thirty six plasma samples of breast cancer patients and 30 plasma samples of normal subjects as control. B) Triple matched samples from 20 breast cancer patients. (* significant difference; Mann-Whitney U Test).
Figure 3
Figure 3. ROC curve analysis using cfDNA for discriminating between cancerous and normal samples based on methylation patterns of 10 candidate genes.
A) ROC curves of cfDNA to discriminate between plasma sample of breast cancer patients and plasma samples of normal subjects. B) ROC curves of cfDNA to discriminate between serum with and matched normal tissue samples.
Figure 4
Figure 4. Comparison of the mean methylation proportion and approximate position of informative CpG sites in the range of −400 to +200 according to the recognition sites of the transcription factors in the 10 candidate genes.
A) Comparison of methylation proportion in 36 plasma samples of breast cancer patients and 30 plasma samples of normal subjects. B) Comparison of methylation proportion in 60 triple samples (cancerous breast tissue, matched normal tissue and serum samples) from 20 breast cancer patients. (Dots in the map are corresponding to the mean methylation quantity of each CpG site in all analyzed cases).
See this image and copyright information in PMC

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